diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_animer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_animer.json new file mode 100644 index 0000000000000000000000000000000000000000..fc39597afae3a4f4bf22410b3bea52bee30f3722 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_animer.json @@ -0,0 +1,63 @@ +{ + "tool_name":"Face Animer", + "tool_description":"Introducing Face Animer API - the cutting-edge facial animation tool that brings your digital avatars and characters to life with 21 dynamic and expressive animation effects. With just a few lines of code, easily integrate our API to add a new level of realism and emotion to your projects.", + "title":"Face Animer", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":100, + "avgLatency":535, + "avgSuccessRate":99, + "popularityScore":9.7, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/firdavscoder1/api/face-animer/", + "host":"face-animer.p.rapidapi.com", + "api_list":[ + { + "name":"Get Result", + "url":"https://face-animer.p.rapidapi.com/webFaceDriven/getTaskInfo", + "description":"Enter taskId and get result. Note: you have to wait about 5 seconds after you created the job id. Otherwise response will be Null data.", + "method":"GET", + "required_parameters":[ + { + "name":"taskId", + "type":"STRING", + "description":"Enter taskId and get result. Note: you have to wait about 5 seconds after you created the job id. Otherwise response will be Null data. ", + "default":"" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://face-animer.p.rapidapi.com/webFaceDriven/getTaskInfo\"\nquerystring = {\"taskId\": taskid}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-animer.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"Create Job ID", + "url":"https://face-animer.p.rapidapi.com/webFaceDriven/submitTaskByUrl", + "description":"Create Job ID", + "method":"GET", + "required_parameters":[ + { + "name":"templateId", + "type":"STRING", + "description":"templateId could be from 0 to 21 (0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21)", + "default":"" + }, + { + "name":"imageUrl", + "type":"STRING", + "description":"Enter valid image url", + "default":"" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://face-animer.p.rapidapi.com/webFaceDriven/submitTaskByUrl\"\nquerystring = {\"templateId\": templateid, \"imageUrl\": imageurl}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-animer.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_anti_spoofing.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_anti_spoofing.json new file mode 100644 index 0000000000000000000000000000000000000000..8cd4c2b2418867b035671bc523e0556928dd4922 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_anti_spoofing.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_4869cd92-6bac-42a6-b40a-e29beda684cd", + "tool_description": "Make sure a face is taken legitimately. Can tell if the face in the image is on a phone/picture. Can also detect if the face is an augmented 3d image.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/face-anti-spoofing2/", + "name": "Face Anti Spoofing", + "title": "Face Anti Spoofing", + "pricing": "FREEMIUM", + "tool_name": "Face Anti Spoofing", + "score": null, + "host": "face-anti-spoofing2.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://face-anti-spoofing2.p.rapidapi.com/", + "description": "Make sure a face is taken legitimately. Can tell if the face in the image is on a phone/picture.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/anti-spoof-polaroid-man.jpg?v=thumb" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-anti-spoofing2.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/anti-spoof-polaroid-man.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-anti-spoofing2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-anti-spoofing2.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/anti-spoof-polaroid-man.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-anti-spoofing2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_detection_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_detection_api.json new file mode 100644 index 0000000000000000000000000000000000000000..ecab1b091bebc13e0abea870a92ed6c84f4b79cf --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_detection_api.json @@ -0,0 +1,55 @@ +{ + "product_id": "api_e1a04de2-7238-472a-86cf-56521c8ca97a", + "tool_description": "This API allows you to detect faces in images and retrieve information about the detected faces.", + "home_url": "https://rapidapi.com/manassrivastava567/api/face-detection-api3/", + "name": "Face Detection Api", + "title": "Face Detection Api", + "pricing": "FREE", + "tool_name": "Face Detection Api", + "score": { + "avgServiceLevel": 64, + "avgLatency": 4484, + "avgSuccessRate": 29, + "popularityScore": 2, + "__typename": "Score" + }, + "host": "face-detection-api3.p.rapidapi.com", + "api_list": [ + { + "name": "detect-face-info", + "url": "https://face-detection-api3.p.rapidapi.com/detect-face-info", + "description": "Detect faces in an image and retrieve information.", + "method": "POST", + "required_parameters": [ + { + "name": "Image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-detection-api3.p.rapidapi.com/detect-face-info\"\nquerystring = {\"Image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-detection-api3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-detection-api3.p.rapidapi.com/detect-face-info\"\nquerystring = {\"Image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-detection-api3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "detect-faces-image", + "url": "https://face-detection-api3.p.rapidapi.com/detect-faces-image", + "description": "Detect faces in an image and receive an image(base64) with bounding boxes.", + "method": "POST", + "required_parameters": [ + { + "name": "Image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-detection-api3.p.rapidapi.com/detect-faces-image\"\nquerystring = {\"Image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-detection-api3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-detection-api3.p.rapidapi.com/detect-faces-image\"\nquerystring = {\"Image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-detection-api3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_emotionsentiment_detector.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_emotionsentiment_detector.json new file mode 100644 index 0000000000000000000000000000000000000000..49278f2c14720a7041a520d822aa93a7f7d6ed4e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_emotionsentiment_detector.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_748ccc68-f341-459c-952e-166a8e38d22a", + "tool_description": "Detects the emotion of a person in an image. Based on many charectoristics such as sadness, anger, happiness, etc.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/face-emotion-sentiment-detector/", + "name": "Face Emotion/Sentiment Detector", + "title": "Face Emotion/Sentiment Detector", + "pricing": "FREEMIUM", + "tool_name": "Face Emotion/Sentiment Detector", + "score": null, + "host": "face-emotion-sentiment-detector.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://face-emotion-sentiment-detector.p.rapidapi.com/", + "description": "Analyze the face in the image and return a face sentiment.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://thumbs.dreamstime.com/b/angry-woman-10224901.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-emotion-sentiment-detector.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://thumbs.dreamstime.com/b/angry-woman-10224901.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-emotion-sentiment-detector.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-emotion-sentiment-detector.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://thumbs.dreamstime.com/b/angry-woman-10224901.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-emotion-sentiment-detector.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check.json new file mode 100644 index 0000000000000000000000000000000000000000..b1982c107e962e87f97802c0cb5032844b2587cb --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check.json @@ -0,0 +1,61 @@ +{ + "tool_name": "Face liveness check", + "tool_description": "Check if the selfie your users take is indeed live, optimally clicked to save in your records, if there are multiple faces detected in the image, and what percentage of the image does the face actually cover. Face liveness detection helps you uncover frauds by ensuring that the image you have been provided isn\u2019t a picture of a picture, a passport sized image, or an image of another individual on a cell phone / laptop screen. Pair it to the Face Compare API to have complete confidence that t...", + "title": "Face liveness check", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1068, + "avgSuccessRate": 100, + "popularityScore": 9.7, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/idfy-idfy-default/api/face-liveness-check/", + "host": "face-liveness-check.p.rapidapi.com", + "api_list": [ + { + "name": "Face liveness check", + "url": "https://face-liveness-check.p.rapidapi.com/v3/tasks/async/check_photo_liveness/face", + "description": "This API compares two face images and provides a match score.\n\nUse get call on the left and pass the request id to fetch api call results.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-liveness-check.p.rapidapi.com/v3/tasks/async/check_photo_liveness/face\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-check.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "GET Call", + "url": "https://face-liveness-check.p.rapidapi.com/v3/tasks", + "description": "Used to fetch api result using the request id received in responses.", + "method": "GET", + "required_parameters": [ + { + "name": "request_id", + "type": "STRING", + "description": "", + "default": "68bbb910-da9b-4d8a-9a1d-4bd878b19846" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-liveness-check.p.rapidapi.com/v3/tasks\"\nquerystring = {\"request_id\": request_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-check.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Face liveness check", + "url": "https://face-liveness-check.p.rapidapi.com/v3/tasks/async/check_photo_liveness/face", + "description": "This API compares two face images and provides a match score.\n\nUse get call on the left and pass the request id to fetch api call results.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-liveness-check.p.rapidapi.com/v3/tasks/async/check_photo_liveness/face\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-check.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-liveness-check.p.rapidapi.com/v3/tasks/async/check_photo_liveness/face\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-check.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check/api.py new file mode 100644 index 0000000000000000000000000000000000000000..2a61ef6371604ff3fcedcbea425178fa6e89e957 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_check/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_call(request_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Used to fetch api result using the request id received in responses." + + """ + url = f"https://face-liveness-check.p.rapidapi.com/v3/tasks" + querystring = {'request_id': request_id, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "face-liveness-check.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..bee8552e4eb1e7eae043a0537eba3e28d81c6b82 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_liveness_detection.json @@ -0,0 +1,48 @@ +{ + "product_id": "api_68eb1d1e-5c4c-46b6-a2d8-199cabb01426", + "tool_description": "Face Liveness Detection", + "home_url": "https://rapidapi.com/faceonlive-inc-faceonlive-inc-default/api/face-liveness-detection3/", + "name": "Face Liveness Detection", + "title": "Face Liveness Detection", + "pricing": "FREE", + "tool_name": "Face Liveness Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1152, + "avgSuccessRate": 100, + "popularityScore": 8, + "__typename": "Score" + }, + "host": "face-liveness-detection3.p.rapidapi.com", + "api_list": [ + { + "name": "From Base64", + "url": "https://face-liveness-detection3.p.rapidapi.com/api/liveness_base64", + "description": "Liveness Detection From Base64", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-liveness-detection3.p.rapidapi.com/api/liveness_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-detection3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-liveness-detection3.p.rapidapi.com/api/liveness_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-detection3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "From Image", + "url": "https://face-liveness-detection3.p.rapidapi.com/api/liveness", + "description": "Liveness Detection From Image", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-liveness-detection3.p.rapidapi.com/api/liveness\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-detection3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-liveness-detection3.p.rapidapi.com/api/liveness\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-liveness-detection3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_mask_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_mask_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..dac224b52591f435a8f4a8d4b8499eb24eb2c8c7 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_mask_detection.json @@ -0,0 +1,181 @@ +{ + "product_id": "api_47efa1c3-c46a-4d84-8504-f1ffa1f0cf12", + "tool_description": "PresentID face mask detection API can detect that the person wears a mask or not.", + "home_url": "https://rapidapi.com/PresentID/api/face-mask-detection/", + "name": "Face Mask Detection", + "title": "Face Mask Detection", + "pricing": "FREEMIUM", + "tool_name": "Face Mask Detection", + "score": null, + "host": "face-mask-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Send image with image URL", + "url": "https://face-mask-detection.p.rapidapi.com/FaceMaskDetection", + "description": "- Send Data via Base64 or an image Url or an image file\n- Image size should not exceed 8 MB\n- Also, the images should not be larger than 5000 pixels and smaller than 50 pixels", + "method": "POST", + "required_parameters": [ + { + "name": "linkFile", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "type": "object", + "properties": { + "x0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "y1": { + "type": "integer" + }, + "masked": { + "type": "integer" + } + } + } + } + } + } + }, + { + "name": "Sending image with image file", + "url": "https://face-mask-detection.p.rapidapi.com/FaceMaskDetection", + "description": "- Send Data via Base64 or an image Url or an image file\n- Image size should not exceed 8 MB\n- Also, the images should not be larger than 5000 pixels and smaller than 50 pixels", + "method": "POST", + "required_parameters": [ + { + "name": "photo", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"photo\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"photo\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "data": { + "items": { + "properties": { + "masked": { + "type": "integer" + }, + "x0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "y1": { + "type": "integer" + } + }, + "type": "object" + }, + "type": "array" + }, + "hasError": { + "type": "boolean" + }, + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Send image with Base64", + "url": "https://face-mask-detection.p.rapidapi.com/FaceMaskDetection", + "description": "- Send Data via Base64 or an image Url or an image file\n- Image size should not exceed 8 MB\n- Also, the images should not be larger than 5000 pixels and smaller than 50 pixels", + "method": "POST", + "required_parameters": [ + { + "name": "imageBase64", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-mask-detection.p.rapidapi.com/FaceMaskDetection\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "data": { + "items": { + "properties": { + "masked": { + "type": "integer" + }, + "x0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "y1": { + "type": "integer" + } + }, + "type": "object" + }, + "type": "array" + }, + "hasError": { + "type": "boolean" + }, + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + } + }, + "type": "object" + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio.json new file mode 100644 index 0000000000000000000000000000000000000000..efc5e39b823cc0a1584265e75d0cd2526aaa07a0 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio.json @@ -0,0 +1,71 @@ +{ + "tool_name":"Face Studio", + "tool_description":"Face Generation: use AI to dynamically generate high-resolution, photo-realistic pictures of faces based on demographic input including gender, age, and ethnicity. Test the interactive version here: https://facestudio.app", + "title":"Face Studio", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":100, + "avgLatency":2207, + "avgSuccessRate":85, + "popularityScore":9.7, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/blue-reach-ai-blue-reach-ai-default/api/face-studio/", + "host":"face-studio.p.rapidapi.com", + "api_list":[ + { + "name":"/generate", + "url":"https://face-studio.p.rapidapi.com/generate", + "description":"Generate a face given optional parameters: **gender**, **age**, and **ethnicity**. Ethnicity is an approximation of the corresponding ethnic/racial phenotype for a given option.", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"ethnicity", + "type":"STRING", + "description":"For ethnicity, the following options are available: *european*, *african*, *west_asian*, *south_asian*, *east_asian*, *southeast_asian*, and *latin_american*. If not specified, the ethnic phenotype of the face will be random.", + "default":"european" + }, + { + "name":"gender", + "type":"STRING", + "description":"For gender, the following options are available: *male* and *female*. If not specified, the gender of the face can be either male or female.", + "default":"female" + }, + { + "name":"age", + "type":"STRING", + "description":"For age, the following options are available: *10s*, *20s*, *30s*, *40s*, *50s*, and *60s*. For more fine-grained control, it is also possible to input a specific *numeric* value for age. If age is not specified, then the age of the face will be random.", + "default":"20s" + } + ], + "code":"import requests\n\nurl = \"https://face-studio.p.rapidapi.com/generate\"\nquerystring = {\"ethnicity\": ethnicity, \"gender\": gender, \"age\": age}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-studio.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{}, + "headers":{}, + "schema":{ + "type":"object", + "properties":{ + "get":{ + "type":"string" + }, + "parameters":{ + "type":"array" + }, + "errors":{ + "type":"array" + }, + "results":{ + "type":"integer" + }, + "response":{ + "type":"array", + "items":{ + "type":"object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio/api.py new file mode 100644 index 0000000000000000000000000000000000000000..fbf16437258d9d0a26fde802d3b78cdf119e547f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_studio/api.py @@ -0,0 +1,38 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generate(ethnicity: str='european', gender: str='female', age: str='20s', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generate a face given optional parameters: **gender**, **age**, and **ethnicity**. Ethnicity is an approximation of the corresponding ethnic/racial phenotype for a given option." + ethnicity: For ethnicity, the following options are available: *european*, *african*, *west_asian*, *south_asian*, *east_asian*, *southeast_asian*, and *latin_american*. If not specified, the ethnic phenotype of the face will be random. + gender: For gender, the following options are available: *male* and *female*. If not specified, the gender of the face can be either male or female. + age: For age, the following options are available: *10s*, *20s*, *30s*, *40s*, *50s*, and *60s*. For more fine-grained control, it is also possible to input a specific *numeric* value for age. If age is not specified, then the age of the face will be random. + + """ + url = f"https://face-studio.p.rapidapi.com/generate" + querystring = {} + if ethnicity: + querystring['ethnicity'] = ethnicity + if gender: + querystring['gender'] = gender + if age: + querystring['age'] = age + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "face-studio.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swap.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swap.json new file mode 100644 index 0000000000000000000000000000000000000000..cba1861f19fa2bddecddd259bc884ab766338f99 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swap.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_79de23b4-1074-4c63-971e-87ff55132bae", + "tool_description": "Easy Face Swap:\n\nImagine a tool that lets faces switch places effortlessly. That's what the Face Swap API does!\n\nUsing smart technology, it smoothly swaps faces between two pictures. It's like a fun game of mix-and-match for faces.\n\nThis tool figures out the different parts of a face in one picture and puts them into another, creating a cool face swap. But remember, it works best with just one face on each image, and the quality of the pictures matters.\n\nYou can use this easy Face Swap for th...", + "home_url": "https://rapidapi.com/Ideahub/api/face-swap3/", + "name": "Face Swap", + "title": "Face Swap", + "pricing": "FREEMIUM", + "tool_name": "Face Swap", + "score": { + "avgServiceLevel": 100, + "avgLatency": 12157, + "avgSuccessRate": 100, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "face-swap3.p.rapidapi.com", + "api_list": [ + { + "name": "swap", + "url": "https://face-swap3.p.rapidapi.com/swap", + "description": "provide image url or base64 in source and target image", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-swap3.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-swap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-swap3.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-swap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swapper.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swapper.json new file mode 100644 index 0000000000000000000000000000000000000000..17612ed290f6fdfe128c9c7261f844c5d8caa0b5 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/face_swapper.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_1f5998db-4e5a-43eb-9d08-69904a55c1ca", + "tool_description": "Introducing Face Swapper API:\n\n- Face Swapper: The Advanced FaceSwap API, redefines the face swapping landscape with its potent capabilities.\n- Employing cutting-edge algorithms, Face Swapper: AI FaceSwap effortlessly transposes faces between two images.\n- Through intelligent recognition of facial attributes within the source image, it seamlessly substitutes faces in the target image.\n- While Face Swapper: AI FaceSwap produces outstanding results, the accuracy of the swap may be affected by f...", + "home_url": "https://rapidapi.com/FutureWave/api/face-swapper/", + "name": "Face Swapper", + "title": "Face Swapper", + "pricing": "FREEMIUM", + "tool_name": "Face Swapper", + "score": { + "avgServiceLevel": 100, + "avgLatency": 13394, + "avgSuccessRate": 100, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "face-swapper.p.rapidapi.com", + "api_list": [ + { + "name": "swap", + "url": "https://face-swapper.p.rapidapi.com/swap", + "description": "provide image url or base64 in source and target image", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://face-swapper.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-swapper.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://face-swapper.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"face-swapper.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facehub_ai_face_swap.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facehub_ai_face_swap.json new file mode 100644 index 0000000000000000000000000000000000000000..0924264f10da14d8d73fd538f544da56d616bb8a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facehub_ai_face_swap.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_ad1c8cb2-35fb-4c64-ad7d-523c219ffd3b", + "tool_description": "FaceHub - Smart Face Swap:\n\nIntroducing FaceHub, your go-to for easy face swapping with AI magic!\n\nThis clever technology takes faces from one picture and smoothly puts them into another. It's like a cool face switcher with superpowers.\n\nFaceHub knows all about faces and swaps them effortlessly. Just remember, it works best with one face in each image, and the pictures should be clear.\n\nYou can use FaceHub to have fun with social media filters, add excitement to entertainment apps, or create ...", + "home_url": "https://rapidapi.com/futurize/api/facehub-ai-face-swap/", + "name": "FaceHub - AI Face Swap", + "title": "FaceHub - AI Face Swap", + "pricing": "FREEMIUM", + "tool_name": "FaceHub - AI Face Swap", + "score": null, + "host": "facehub-ai-face-swap.p.rapidapi.com", + "api_list": [ + { + "name": "swap", + "url": "https://facehub-ai-face-swap.p.rapidapi.com/swap", + "description": "provide image url or base64 in source and target image", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://facehub-ai-face-swap.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"facehub-ai-face-swap.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://facehub-ai-face-swap.p.rapidapi.com/swap\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"facehub-ai-face-swap.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facial_landmark_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facial_landmark_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..9e1cbdb9811b35f1624bb65e9bf493761980e4fc --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/facial_landmark_detection.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_1f98478a-3c95-480e-917c-4cadb435ba90", + "tool_description": "Use the Facial Landmark Detection API to detect facial features in an image. With this API, you can find 64 points on the face in an image. ", + "home_url": "https://rapidapi.com/smartclick-smartclick-default/api/facial-landmark-detection/", + "name": "Facial Landmark Detection", + "title": "Facial Landmark Detection", + "pricing": "FREEMIUM", + "tool_name": "Facial Landmark Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2425, + "avgSuccessRate": 75, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "facial-landmark-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Landmark detection in an image", + "url": "https://facial-landmark-detection.p.rapidapi.com/landmark-detection", + "description": "![](https://cdn.smclk.net/rapidmarket/Facial-Landmark-Detection.png)\nFor more details [contact us](https://smartclick.ai/contact/)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://facial-landmark-detection.p.rapidapi.com/landmark-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"facial-landmark-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://facial-landmark-detection.p.rapidapi.com/landmark-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"facial-landmark-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_nsfw_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_nsfw_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..b924552d78ae9d640cd1d7b2e050e7f9f5af4524 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_nsfw_detection.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_91c21581-b502-4c73-8558-b1363f4d6289", + "tool_description": "Detects NSFW percentages in image with class names Neutral,Drawing,Hentai,Sexy etc.", + "home_url": "https://rapidapi.com/engagehitsmail/api/fast-nsfw-detection/", + "name": "Fast NSFW Detection", + "title": "Fast NSFW Detection", + "pricing": "FREEMIUM", + "tool_name": "Fast NSFW Detection", + "score": null, + "host": "fast-nsfw-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Get NSFW Prediction", + "url": "https://fast-nsfw-detection.p.rapidapi.com/nsfw", + "description": "Get NSFW Prediction based on base64 input image", + "method": "POST", + "required_parameters": [ + { + "name": "base64image", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://fast-nsfw-detection.p.rapidapi.com/nsfw\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-nsfw-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-nsfw-detection.p.rapidapi.com/nsfw\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-nsfw-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_object_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_object_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..4ace5b5674d488e2930e14b6b69ec1d9ad3bebed --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_object_detection.json @@ -0,0 +1,55 @@ +{ + "product_id": "api_70540a89-4490-4c4a-aaaa-539ba221f662", + "tool_description": "Object Detection or Image Classification using pretrained models of mobilenet and coco ssd.\nReturns Classnames and bounding box coordinates. ", + "home_url": "https://rapidapi.com/engagehitsmail/api/fast-object-detection/", + "name": "Fast Object Detection", + "title": "Fast Object Detection", + "pricing": "FREEMIUM", + "tool_name": "Fast Object Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 71263, + "avgSuccessRate": 100, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "fast-object-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Get Coco Predictions", + "url": "https://fast-object-detection.p.rapidapi.com/coco", + "description": "Uses coco ssd model to display predictions along with bounding box coordinates", + "method": "POST", + "required_parameters": [ + { + "name": "base64image", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://fast-object-detection.p.rapidapi.com/coco\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-object-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-object-detection.p.rapidapi.com/coco\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-object-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Get MobileNet Predictions", + "url": "https://fast-object-detection.p.rapidapi.com/mobilenet", + "description": "Uses MobileNet V2 model to display predictions", + "method": "POST", + "required_parameters": [ + { + "name": "base64image", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://fast-object-detection.p.rapidapi.com/mobilenet\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-object-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-object-detection.p.rapidapi.com/mobilenet\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-object-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_ocr_for_image_captcha.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_ocr_for_image_captcha.json new file mode 100644 index 0000000000000000000000000000000000000000..8dfc8a0d982c6b6ac3e36093bdf7a553ee47475e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_ocr_for_image_captcha.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_e4ff757e-27f7-4510-97c0-1c3e38c31de4", + "tool_description": "Solves Image Captcha Using Service. Accuracy depends on the captcha type and level of difficulty. \nUse the Basic version and check if this suits your requirements. ", + "home_url": "https://rapidapi.com/engagehitsmail/api/fast-ocr-for-image-captcha/", + "name": "Fast OCR for Image Captcha ", + "title": "Fast OCR for Image Captcha ", + "pricing": "FREEMIUM", + "tool_name": "Fast OCR for Image Captcha ", + "score": { + "avgServiceLevel": 100, + "avgLatency": 417, + "avgSuccessRate": 100, + "popularityScore": 9.2, + "__typename": "Score" + }, + "host": "fast-ocr-for-image-captcha.p.rapidapi.com", + "api_list": [ + { + "name": "Create Image Captcha Request", + "url": "https://fast-ocr-for-image-captcha.p.rapidapi.com/in.php", + "description": "Creates a request to solve Image Captcha. Takes base64 image as input", + "method": "POST", + "required_parameters": [ + { + "name": "base64image", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://fast-ocr-for-image-captcha.p.rapidapi.com/in.php\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-ocr-for-image-captcha.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-ocr-for-image-captcha.p.rapidapi.com/in.php\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-ocr-for-image-captcha.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_pose_detection_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_pose_detection_api.json new file mode 100644 index 0000000000000000000000000000000000000000..25360fc8a9cd93b0addf097a21d0f9bcf14c0d34 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_pose_detection_api.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_54f35523-c834-4304-999e-7feab60d1c36", + "tool_description": "Detects 17 keypoints of a body.\n\nThe following are the keypoints. \n0: nose\n1: left_eye\n2: right_eye\n3: left_ear\n4: right_ear\n5: left_shoulder\n6: right_shoulder\n7: left_elbow\n8: right_elbow\n9: left_wrist\n10: right_wrist\n11: left_hip\n12: right_hip\n13: left_knee\n14: right_knee\n15: left_ankle\n16: right_ankle", + "home_url": "https://rapidapi.com/engagehitsmail/api/fast-pose-detection-api/", + "name": "Fast Pose Detection API", + "title": "Fast Pose Detection API", + "pricing": "FREEMIUM", + "tool_name": "Fast Pose Detection API", + "score": null, + "host": "fast-pose-detection-api.p.rapidapi.com", + "api_list": [ + { + "name": "Get PoseNet Predictions", + "url": "https://fast-pose-detection-api.p.rapidapi.com/posemovenet", + "description": "Get PoseNet Prediction based on base64 input image", + "method": "POST", + "required_parameters": [ + { + "name": "base64image", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://fast-pose-detection-api.p.rapidapi.com/posemovenet\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-pose-detection-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-pose-detection-api.p.rapidapi.com/posemovenet\"\nquerystring = {\"base64image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-pose-detection-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_text_toxicity_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_text_toxicity_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..4f9bbf0c71f3c54b41f329bdb97832f738d68a8c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/fast_text_toxicity_detection.json @@ -0,0 +1,44 @@ +{ + "product_id": "api_e8eebfc0-1b9a-458e-9119-30f3148b5e93", + "tool_description": "The text toxicity detects whether text contains toxic content such as threatening language, insults, obscenities, identity-based hate, or sexually explicit language.", + "home_url": "https://rapidapi.com/engagehitsmail/api/fast-text-toxicity-detection/", + "name": "Fast Text Toxicity Detection", + "title": "Fast Text Toxicity Detection", + "pricing": "FREEMIUM", + "tool_name": "Fast Text Toxicity Detection", + "score": { + "avgServiceLevel": 88, + "avgLatency": 25318, + "avgSuccessRate": 88, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "fast-text-toxicity-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Get Text Toxicity", + "url": "https://fast-text-toxicity-detection.p.rapidapi.com/toxicity", + "description": "Get Text Toxicity based on the sentences . Input is an array of sentences and threshold is an optional parameter. The default threshold is 0.9. It can be set between 0.1 and 0.9.\n\nThe response is an array of objects, one for each prediction head, that contains the raw probabilities for each input along with the final prediction in `match` (either `true` or `false`). If neither prediction exceeds the threshold, `match` is `null`.", + "method": "POST", + "required_parameters": [ + { + "name": "sentences", + "type": "ARRAY", + "description": "", + "default": "" + } + ], + "optional_parameters": [ + { + "name": "threshold", + "type": "NUMBER", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://fast-text-toxicity-detection.p.rapidapi.com/toxicity\"\nquerystring = {\"threshold\": \"\", \"sentences\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-text-toxicity-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://fast-text-toxicity-detection.p.rapidapi.com/toxicity\"\nquerystring = {\"threshold\": \"\", \"sentences\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"fast-text-toxicity-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/financial_summarization_advanced.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/financial_summarization_advanced.json new file mode 100644 index 0000000000000000000000000000000000000000..f5ae8bfed339597f8b03da6af3a8ac5ee426dc0c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/financial_summarization_advanced.json @@ -0,0 +1,39 @@ +{ + "product_id": "api_f9118437-f94d-43c9-9a71-050f930fa9e7", + "tool_description": "From the team that built the original financial summarization model on Hugging Face (>45K downloads on April 2023) here comes the advanced version with even greater performance! Use it and build your personal or commercial apps quickly summarizing thousands of articles!", + "home_url": "https://rapidapi.com/medoid-ai-medoid-ai-default/api/financial-summarization-advanced/", + "name": "Financial Summarization Advanced", + "title": "Financial Summarization Advanced", + "pricing": "FREEMIUM", + "tool_name": "Financial Summarization Advanced", + "score": { + "avgServiceLevel": 100, + "avgLatency": 950, + "avgSuccessRate": 100, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "financial-summarization-advanced.p.rapidapi.com", + "api_list": [ + { + "name": "summarize", + "url": "https://financial-summarization-advanced.p.rapidapi.com/summarize", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://financial-summarization-advanced.p.rapidapi.com/summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"financial-summarization-advanced.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://financial-summarization-advanced.p.rapidapi.com/summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"financial-summarization-advanced.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "summary": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/flexible_ocr_detects_text_in_image.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/flexible_ocr_detects_text_in_image.json new file mode 100644 index 0000000000000000000000000000000000000000..fec04627f1caf579285d817813996f25cbab0eef --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/flexible_ocr_detects_text_in_image.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_9b26d16b-cb7b-4383-9525-63bfd67b52c6", + "tool_description": "Detects and recognizes English text in images that are more complex than scans of a page.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/flexible-ocr-detects-text-in-image/", + "name": "Flexible OCR Detects Text in Image", + "title": "Flexible OCR Detects Text in Image", + "pricing": "FREEMIUM", + "tool_name": "Flexible OCR Detects Text in Image", + "score": null, + "host": "flexible-ocr-detects-text-in-image.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://flexible-ocr-detects-text-in-image.p.rapidapi.com/", + "description": "Returns the text found in the image, as-well as where in the image the text was found.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://previews.123rf.com/images/lprising/lprising1603/lprising160300001/54239265-many-signs-at-a-street-corner-in-new-york-city.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://flexible-ocr-detects-text-in-image.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://previews.123rf.com/images/lprising/lprising1603/lprising160300001/54239265-many-signs-at-a-street-corner-in-new-york-city.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"flexible-ocr-detects-text-in-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://flexible-ocr-detects-text-in-image.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://previews.123rf.com/images/lprising/lprising1603/lprising160300001/54239265-many-signs-at-a-street-corner-in-new-york-city.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"flexible-ocr-detects-text-in-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/framefusion.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/framefusion.json new file mode 100644 index 0000000000000000000000000000000000000000..f33343d0d3d4db33a416f56255b5a73e5b976848 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/framefusion.json @@ -0,0 +1,89 @@ +{ + "product_id": "api_b165ec2d-302b-43c0-af17-600e02e6d74f", + "tool_description": "Discover the Premier API for Crafting Stunning Images and Animations Using State-of-the-Art Models.", + "home_url": "https://rapidapi.com/serhaterfidan/api/framefusion/", + "name": "FrameFusion", + "title": "FrameFusion", + "pricing": "FREEMIUM", + "tool_name": "FrameFusion", + "score": { + "avgServiceLevel": 100, + "avgLatency": 985, + "avgSuccessRate": 81, + "popularityScore": 9.4, + "__typename": "Score" + }, + "host": "framefusion.p.rapidapi.com", + "api_list": [ + { + "name": "3D Render Style", + "url": "https://framefusion.p.rapidapi.com/generateimage", + "description": "Generate image with 3D render style with high quality", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://framefusion.p.rapidapi.com/generateimage\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"framefusion.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://framefusion.p.rapidapi.com/generateimage\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"framefusion.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "Prompt Generate", + "url": "https://framefusion.p.rapidapi.com/promptgenerate", + "description": "Generate prompt with your texts", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://framefusion.p.rapidapi.com/promptgenerate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"framefusion.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://framefusion.p.rapidapi.com/promptgenerate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"framefusion.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_cartoonized.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_cartoonized.json new file mode 100644 index 0000000000000000000000000000000000000000..66d592434f48c7f7d078c11779ee547d4bb35704 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_cartoonized.json @@ -0,0 +1,58 @@ +{ + "product_id": "api_033b0050-2f7d-42e4-ac50-976a9f77dbca", + "tool_description": "Free AI Image Cartoonized", + "home_url": "https://rapidapi.com/y393162333/api/free-ai-image-cartoonized/", + "name": "Free AI Image Cartoonized", + "title": "Free AI Image Cartoonized", + "pricing": "PAID", + "tool_name": "Free AI Image Cartoonized", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3103, + "avgSuccessRate": 67, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "free-ai-image-cartoonized.p.rapidapi.com", + "api_list": [ + { + "name": "/cartoon", + "url": "https://free-ai-image-cartoonized.p.rapidapi.com/cartoon", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/temp3.webp" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-ai-image-cartoonized.p.rapidapi.com/cartoon\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/temp3.webp\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-cartoonized.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-ai-image-cartoonized.p.rapidapi.com/cartoon\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/temp3.webp\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-cartoonized.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_generator_midjourney.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_generator_midjourney.json new file mode 100644 index 0000000000000000000000000000000000000000..fba7a6d157dbca42e6024d215b7ece76088232f2 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_generator_midjourney.json @@ -0,0 +1,36 @@ +{ + "product_id": "api_109e2323-6d74-4825-9ee5-7fd45471dc5e", + "tool_description": "Free AI Image Generator Midjourney", + "home_url": "https://rapidapi.com/y393162333/api/free-ai-image-generator-midjourney/", + "name": "Free AI Image Generator Midjourney", + "title": "Free AI Image Generator Midjourney", + "pricing": "PAID", + "tool_name": "Free AI Image Generator Midjourney", + "score": { + "avgServiceLevel": 91, + "avgLatency": 993, + "avgSuccessRate": 91, + "popularityScore": 8.9, + "__typename": "Score" + }, + "host": "free-ai-image-generator-midjourney.p.rapidapi.com", + "api_list": [ + { + "name": "/stablediffusionai/api/v1/generate/startGenerate", + "url": "https://free-ai-image-generator-midjourney.p.rapidapi.com/stablediffusionai/api/v1/generate/startGenerate", + "description": "start generate", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-ai-image-generator-midjourney.p.rapidapi.com/stablediffusionai/api/v1/generate/startGenerate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-generator-midjourney.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-ai-image-generator-midjourney.p.rapidapi.com/stablediffusionai/api/v1/generate/startGenerate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-generator-midjourney.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "x-apifox-ignore-properties": [], + "x-apifox-orders": [] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_scale.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_scale.json new file mode 100644 index 0000000000000000000000000000000000000000..6fe466abe430c86eca426ac35007f9b3f2fdedee --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_image_scale.json @@ -0,0 +1,58 @@ +{ + "product_id": "api_33054384-9385-4e77-8c63-358b6def1b70", + "tool_description": "Free Image Scale lossless enlargement BY AI", + "home_url": "https://rapidapi.com/y393162333/api/free-ai-image-scale/", + "name": "Free AI Image Scale", + "title": "Free AI Image Scale", + "pricing": "PAID", + "tool_name": "Free AI Image Scale", + "score": { + "avgServiceLevel": 100, + "avgLatency": 125, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "free-ai-image-scale.p.rapidapi.com", + "api_list": [ + { + "name": "/scale", + "url": "https://free-ai-image-scale.p.rapidapi.com/scale", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/temp3.webp" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-ai-image-scale.p.rapidapi.com/scale\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/temp3.webp\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-scale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-ai-image-scale.p.rapidapi.com/scale\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/temp3.webp\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-image-scale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_enhance_image_color.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_enhance_image_color.json new file mode 100644 index 0000000000000000000000000000000000000000..d629b0467bfe5a84930278b361b8d8243a56f6d8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_enhance_image_color.json @@ -0,0 +1,52 @@ +{ + "product_id": "api_eb0974e7-d8df-43be-af2e-6fd546cc8148", + "tool_description": "Free AI Smart Enhance Image Color", + "home_url": "https://rapidapi.com/y393162333/api/free-ai-smart-enhance-image-color/", + "name": "Free AI Smart Enhance Image Color", + "title": "Free AI Smart Enhance Image Color", + "pricing": "PAID", + "tool_name": "Free AI Smart Enhance Image Color", + "score": null, + "host": "free-ai-smart-enhance-image-color.p.rapidapi.com", + "api_list": [ + { + "name": "/enhance-image-color", + "url": "https://free-ai-smart-enhance-image-color.p.rapidapi.com/enhance-image-color", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/RemoveImageWatermark1.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-ai-smart-enhance-image-color.p.rapidapi.com/enhance-image-color\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-smart-enhance-image-color.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-ai-smart-enhance-image-color.p.rapidapi.com/enhance-image-color\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-smart-enhance-image-color.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_image_cropping.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_image_cropping.json new file mode 100644 index 0000000000000000000000000000000000000000..ed3c26dd1c626c4371595ca5f73c8d3b5b44426a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_ai_smart_image_cropping.json @@ -0,0 +1,65 @@ +{ + "product_id": "api_84673992-3f65-4181-95fb-98bd07c78d14", + "tool_description": "Free AI Smart Image cropping", + "home_url": "https://rapidapi.com/y393162333/api/free-ai-smart-image-cropping/", + "name": "Free AI Smart Image cropping", + "title": "Free AI Smart Image cropping", + "pricing": "PAID", + "tool_name": "Free AI Smart Image cropping", + "score": null, + "host": "free-ai-smart-image-cropping.p.rapidapi.com", + "api_list": [ + { + "name": "/change-image-size", + "url": "https://free-ai-smart-image-cropping.p.rapidapi.com/change-image-size", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/RemoveImageWatermark1.jpg" + } + ], + "optional_parameters": [ + { + "name": "width", + "type": "NUMBER", + "description": "", + "default": "200" + }, + { + "name": "height", + "type": "NUMBER", + "description": "", + "default": "200" + } + ], + "code": "import requests\n\nurl = \"https://free-ai-smart-image-cropping.p.rapidapi.com/change-image-size\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\", \"width\": \"200\", \"height\": \"200\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-smart-image-cropping.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-ai-smart-image-cropping.p.rapidapi.com/change-image-size\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\", \"width\": \"200\", \"height\": \"200\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-ai-smart-image-cropping.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_color.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_color.json new file mode 100644 index 0000000000000000000000000000000000000000..ada931cd79eca596b90c604bc0fc78decd6675e7 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_color.json @@ -0,0 +1,52 @@ +{ + "product_id": "api_bc6c0717-23eb-412a-a930-19af3b329bd5", + "tool_description": "Free Auto Change Image Color By AI", + "home_url": "https://rapidapi.com/y393162333/api/free-image-color/", + "name": "Free Image Color", + "title": "Free Image Color", + "pricing": "PAID", + "tool_name": "Free Image Color", + "score": null, + "host": "free-image-color.p.rapidapi.com", + "api_list": [ + { + "name": "/colorize-image", + "url": "https://free-image-color.p.rapidapi.com/colorize-image", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/RemoveImageWatermark1.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-image-color.p.rapidapi.com/colorize-image\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-image-color.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-image-color.p.rapidapi.com/colorize-image\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-image-color.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_style_transfer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_style_transfer.json new file mode 100644 index 0000000000000000000000000000000000000000..6c05c31f18bb1b88fad4cad59fb631a5224d020d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_image_style_transfer.json @@ -0,0 +1,65 @@ +{ + "product_id": "api_0476ea43-bb12-4677-b027-b24235818d13", + "tool_description": "Free Image Style Transfer by AI", + "home_url": "https://rapidapi.com/y393162333/api/free-image-style-transfer/", + "name": "Free Image Style Transfer", + "title": "Free Image Style Transfer", + "pricing": "PAID", + "tool_name": "Free Image Style Transfer", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2260, + "avgSuccessRate": 50, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "free-image-style-transfer.p.rapidapi.com", + "api_list": [ + { + "name": "/extend-image-style", + "url": "https://free-image-style-transfer.p.rapidapi.com/extend-image-style", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "style_file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/QQ20231002-193737@2x.png" + } + ], + "optional_parameters": [ + { + "name": "major_file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/5.png" + } + ], + "code": "import requests\n\nurl = \"https://free-image-style-transfer.p.rapidapi.com/extend-image-style\"\nquerystring = {\"style_file\": \"file:///Users/ben/Desktop/QQ20231002-193737@2x.png\", \"major_file\": \"file:///Users/ben/Desktop/5.png\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-image-style-transfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-image-style-transfer.p.rapidapi.com/extend-image-style\"\nquerystring = {\"style_file\": \"file:///Users/ben/Desktop/QQ20231002-193737@2x.png\", \"major_file\": \"file:///Users/ben/Desktop/5.png\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-image-style-transfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_subtitles.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_subtitles.json new file mode 100644 index 0000000000000000000000000000000000000000..6fd75f81e14343c905b1756500b6436fe11bef0d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_subtitles.json @@ -0,0 +1,52 @@ +{ + "product_id": "api_667d73fc-b0d9-4616-936c-1f823cdd9321", + "tool_description": "Free Remove Image Subtitles", + "home_url": "https://rapidapi.com/y393162333/api/free-remove-image-subtitles/", + "name": "Free Remove Image Subtitles", + "title": "Free Remove Image Subtitles", + "pricing": "PAID", + "tool_name": "Free Remove Image Subtitles", + "score": null, + "host": "free-remove-image-subtitles.p.rapidapi.com", + "api_list": [ + { + "name": "/remove-image-watermark", + "url": "https://free-remove-image-subtitles.p.rapidapi.com/remove-image-watermark", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/RemoveImageWatermark1.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-remove-image-subtitles.p.rapidapi.com/remove-image-watermark\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-remove-image-subtitles.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-remove-image-subtitles.p.rapidapi.com/remove-image-watermark\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-remove-image-subtitles.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_watermark.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_watermark.json new file mode 100644 index 0000000000000000000000000000000000000000..b65cb179f4db225dcebeb3d90e4263aa87cc0d68 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/free_remove_image_watermark.json @@ -0,0 +1,58 @@ +{ + "product_id": "api_c7ef1efb-e44a-42ea-95d0-f8a26a528dc6", + "tool_description": "Free Remove Image Watermark", + "home_url": "https://rapidapi.com/y393162333/api/free-remove-image-watermark/", + "name": "Free Remove Image Watermark", + "title": "Free Remove Image Watermark", + "pricing": "PAID", + "tool_name": "Free Remove Image Watermark", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2430, + "avgSuccessRate": 100, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "free-remove-image-watermark.p.rapidapi.com", + "api_list": [ + { + "name": "/remove-image-watermark", + "url": "https://free-remove-image-watermark.p.rapidapi.com/remove-image-watermark", + "description": "", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "file:///Users/ben/Desktop/RemoveImageWatermark1.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://free-remove-image-watermark.p.rapidapi.com/remove-image-watermark\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-remove-image-watermark.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://free-remove-image-watermark.p.rapidapi.com/remove-image-watermark\"\nquerystring = {\"file\": \"file:///Users/ben/Desktop/RemoveImageWatermark1.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"free-remove-image-watermark.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "integer" + }, + "url": { + "type": "string" + } + }, + "required": [ + "status", + "url" + ], + "x-apifox-ignore-properties": [], + "x-apifox-orders": [ + "status", + "url" + ] + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gender_detection_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gender_detection_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..ace95aecedb587f326ced3ffa0639a3f1a6fd54f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gender_detection_ai.json @@ -0,0 +1,33 @@ +{ + "product_id": "api_b9fb2680-b6d1-440e-938d-ba0774afc91e", + "tool_description": "Detects the gender of a person in an image.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/gender-detection-ai/", + "name": "Gender Detection AI", + "title": "Gender Detection AI", + "pricing": "FREEMIUM", + "tool_name": "Gender Detection AI", + "score": null, + "host": "gender-detection-ai.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://gender-detection-ai.p.rapidapi.com/", + "description": "Return the detected gender of the people in the image.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://media.npr.org/assets/img/2022/11/08/ap22312071681283-0d9c328f69a7c7f15320e8750d6ea447532dff66.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gender-detection-ai.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://media.npr.org/assets/img/2022/11/08/ap22312071681283-0d9c328f69a7c7f15320e8750d6ea447532dff66.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gender-detection-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gender-detection-ai.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://media.npr.org/assets/img/2022/11/08/ap22312071681283-0d9c328f69a7c7f15320e8750d6ea447532dff66.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gender-detection-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/general_image_captioning.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/general_image_captioning.json new file mode 100644 index 0000000000000000000000000000000000000000..707b170ee72d0c16a2995cc4022c90acde76c031 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/general_image_captioning.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_d7a46c8c-5a90-4faa-97b2-3831956ce3a9", + "tool_description": "Generates English captions from images. Ideal for auto-generating captions and creating metadata at scale.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/general-image-captioning/", + "name": "General Image Captioning", + "title": "General Image Captioning", + "pricing": "FREEMIUM", + "tool_name": "General Image Captioning", + "score": { + "avgServiceLevel": 100, + "avgLatency": 19044, + "avgSuccessRate": 83, + "popularityScore": 8.8, + "__typename": "Score" + }, + "host": "general-image-captioning.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://general-image-captioning.p.rapidapi.com/", + "description": "Return a caption/description given an image.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/image-caption-002.jpg?v=thumb" + } + ], + "code": "import requests\n\nurl = \"https://general-image-captioning.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/image-caption-002.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"general-image-captioning.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://general-image-captioning.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/model-gallery/images/image-caption-002.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"general-image-captioning.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt3_5.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt3_5.json new file mode 100644 index 0000000000000000000000000000000000000000..9c7908e49017a42fc5cf5335b499d2e7c1a74cf4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt3_5.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_12fbdff9-4fc1-4179-9840-06d63f450dbd", + "tool_description": "gpt3.5 interface model\nChatGPT is a large language model developed by OpenAI that can generate human-like text based on input given to it. It uses deep learning algorithms to predict the next word in a sequence, allowing it to respond to a wide range of prompts from users. Its primary purpose is to assist with writing tasks such as essays and reports by generating coherent and relevant content. Additionally, ChatGPT can also function as a personal assistant, answering questions and providing ...", + "home_url": "https://rapidapi.com/KingBes/api/gpt3-5/", + "name": "GPT3.5", + "title": "GPT3.5", + "pricing": "FREEMIUM", + "tool_name": "GPT3.5", + "score": { + "avgServiceLevel": 100, + "avgLatency": 4349, + "avgSuccessRate": 100, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "gpt3-5.p.rapidapi.com", + "api_list": [ + { + "name": "GPT", + "url": "https://gpt3-5.p.rapidapi.com/", + "description": "[\n\t\t{\n\t\t\t\"id\": \"LEMUR_AI_SYSTEM_SETTING\", // required\n\t\t\t\"isSensitive\": false,\n\t\t\t\"needCheck\": false,\n\t\t\t\"role\": \"system\", //system \u3001 assistant or user\n\t\t\t\"content\": \"\"\n\t\t},\n\t\t{\n\t\t\t\"role\": \"user\",\n\t\t\t\"needCheck\": true,\n\t\t\t\"isSensitive\": false,\n\t\t\t\"content\": \"hello\"\n\t\t}\n\t]", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt3-5.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt3-5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt3-5.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt3-5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_3_encoder_tokenizer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_3_encoder_tokenizer.json new file mode 100644 index 0000000000000000000000000000000000000000..5023347186c9d016d35dfc558d1fa9557e6900c1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_3_encoder_tokenizer.json @@ -0,0 +1,45 @@ +{ + "product_id": "api_695a91a5-e5ae-4e30-b99d-b48d12b1e640", + "tool_description": "This is the official GPT-3 tokenizer, the same tokenizer is being used by OpenAI here https://platform.openai.com/tokenizer.\ncontact : um3r.it@gmail.com", + "home_url": "https://rapidapi.com/um3rit/api/gpt-3-encoder-tokenizer/", + "name": "GPT-3 Encoder & Tokenizer", + "title": "GPT-3 Encoder & Tokenizer", + "pricing": "FREEMIUM", + "tool_name": "GPT-3 Encoder & Tokenizer", + "score": { + "avgServiceLevel": 0, + "avgLatency": 585, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "gpt-3-encoder-tokenizer.p.rapidapi.com", + "api_list": [ + { + "name": "Decode Tokens [from tokens to text]", + "url": "https://gpt-3-encoder-tokenizer.p.rapidapi.com/decode", + "description": "This endpoint is designed to convert a sequence of tokens back into their corresponding text format.\nThis endpoint accepts a list of token IDs as input and returns the original text representation of the tokens.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-3-encoder-tokenizer.p.rapidapi.com/decode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-3-encoder-tokenizer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-3-encoder-tokenizer.p.rapidapi.com/decode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-3-encoder-tokenizer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Encode & Get Number Tokens [from text to tokens]", + "url": "https://gpt-3-encoder-tokenizer.p.rapidapi.com/encode", + "description": "The following endpoint is highly useful as it provides the count of tokens. Additionally, it can also return the token IDs upon request. \nHowever, it is advisable to ***request token IDs only when required***, as it may increase the response time.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-3-encoder-tokenizer.p.rapidapi.com/encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-3-encoder-tokenizer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-3-encoder-tokenizer.p.rapidapi.com/encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-3-encoder-tokenizer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_claude_google_palm_and_other_ais.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_claude_google_palm_and_other_ais.json new file mode 100644 index 0000000000000000000000000000000000000000..5ac6290dc078175ab5d085d4bf112faf634a0bf5 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_claude_google_palm_and_other_ais.json @@ -0,0 +1,63 @@ +{ + "product_id": "api_8d1ad112-4eea-4da9-800c-c9cb2ccaad82", + "tool_description": "Claude-Instant, Google-PaLM, Code-Llama, ChatGPT, Solar and other AIs", + "home_url": "https://rapidapi.com/darkpydoor-darkpydoor-default/api/gpt-claude-google-palm-and-other-ais/", + "name": "GPT, Claude, Google-PaLM and other AIs", + "title": "GPT, Claude, Google-PaLM and other AIs", + "pricing": "FREEMIUM", + "tool_name": "GPT, Claude, Google-PaLM and other AIs", + "score": { + "avgServiceLevel": 100, + "avgLatency": 581, + "avgSuccessRate": 100, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "gpt-claude-google-palm-and-other-ais.p.rapidapi.com", + "api_list": [ + { + "name": "Chat with AI that has already been created", + "url": "https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat", + "description": "Chat with AI that has already been created", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Retrieving previous messages", + "url": "https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/previous_messages", + "description": "Retrieving previous messages", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/previous_messages\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/previous_messages\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Cleaning up the context of the conversation", + "url": "https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat_break", + "description": "Cleaning up the context of the conversation", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat_break\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/chat_break\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Create Chat AI", + "url": "https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/createchat", + "description": "Create Chat AI", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/createchat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://gpt-claude-google-palm-and-other-ais.p.rapidapi.com/api/v1/createchat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-claude-google-palm-and-other-ais.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api.json new file mode 100644 index 0000000000000000000000000000000000000000..83f1138f29617cc1e8f1d35c1f6fe7937624a5f7 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api.json @@ -0,0 +1,73 @@ +{ + "tool_name":"GPT-Generated Kenyan News API", + "tool_description":"The GPT-Generated Kenyan News API generates original news articles tailored specifically for the Kenyan context. ", + "title":"GPT-Generated Kenyan News API", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/zamaonlinenews/api/gpt-generated-kenyan-news-api/", + "host":"gpt-generated-kenyan-news-api.p.rapidapi.com", + "api_list":[ + { + "name":"getArticleById", + "url":"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{id}", + "description":"Get specific articles by their IDs", + "method":"GET", + "required_parameters":[ + { + "name":"id", + "type":"NUMBER", + "description":"", + "default":"354" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{id}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-generated-kenyan-news-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{} + }, + { + "name":"getArticleByCategory", + "url":"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{category}", + "description":"Get articles of different categories Politics, Entertainment, Exclusive, News, Lifestyle", + "method":"GET", + "required_parameters":[ + { + "name":"category", + "type":"string", + "description":"", + "default":"Politics" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{category}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-generated-kenyan-news-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{} + }, + { + "name":"getAllArticles", + "url":"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles", + "description":"Retrieves all articles for all categories", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"gpt-generated-kenyan-news-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..9f2eb30b9dbc930d06f67bb14e3862e50e86a88c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/gpt_generated_kenyan_news_api/api.py @@ -0,0 +1,71 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def getarticlebyid(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get specific articles by their IDs" + + """ + url = f"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "gpt-generated-kenyan-news-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def getarticlebycategory(category: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get articles of different categories Politics, Entertainment, Exclusive, News, Lifestyle" + + """ + url = f"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles/{category}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "gpt-generated-kenyan-news-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def getallarticles(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Retrieves all articles for all categories" + + """ + url = f"https://gpt-generated-kenyan-news-api.p.rapidapi.com/articles" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "gpt-generated-kenyan-news-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hate_symbol_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hate_symbol_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..c3cfc2b85446562f6ec26bb7a0b315ff5b488e6f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hate_symbol_detection.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_5186e9f0-a443-43dc-8d72-b332d64fbba9", + "tool_description": "AI for detecting regions of images or videos that contain hate symbols.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/hate-symbol-detection/", + "name": "Hate Symbol Detection", + "title": "Hate Symbol Detection", + "pricing": "FREEMIUM", + "tool_name": "Hate Symbol Detection", + "score": null, + "host": "hate-symbol-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://hate-symbol-detection.p.rapidapi.com/", + "description": "Return the hate symbol type, as-well as the location of the symbol.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://assets1.cbsnewsstatic.com/hub/i/r/2019/12/04/dcb29b12-2ad5-4325-a320-d132f822b12a/thumbnail/1200x630/05e1e2e2f11d0b178e084c104f202af1/Vandalism.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://hate-symbol-detection.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://assets1.cbsnewsstatic.com/hub/i/r/2019/12/04/dcb29b12-2ad5-4325-a320-d132f822b12a/thumbnail/1200x630/05e1e2e2f11d0b178e084c104f202af1/Vandalism.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hate-symbol-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://hate-symbol-detection.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://assets1.cbsnewsstatic.com/hub/i/r/2019/12/04/dcb29b12-2ad5-4325-a320-d132f822b12a/thumbnail/1200x630/05e1e2e2f11d0b178e084c104f202af1/Vandalism.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hate-symbol-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/head_pose_estimation.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/head_pose_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..6bc0f5df863b3a0ca13a19c19a44ca0f16974b09 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/head_pose_estimation.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_be3894b2-ea91-400f-a373-87e75ea3fde5", + "tool_description": "The model predicts the pose of a human head in an image. In cases when you want to find out what direction the head is facing, this model will give you all the information. More specifically, it concerns the prediction of the Euler angles of a human head. The Euler angles consist of the following three values: yaw, pitch, and roll.", + "home_url": "https://rapidapi.com/smartclick-smartclick-default/api/head-pose-estimation1/", + "name": "Head Pose Estimation", + "title": "Head Pose Estimation", + "pricing": "FREEMIUM", + "tool_name": "Head Pose Estimation", + "score": { + "avgServiceLevel": 88, + "avgLatency": 5740, + "avgSuccessRate": 65, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "head-pose-estimation1.p.rapidapi.com", + "api_list": [ + { + "name": "Head Pose Estimation for image", + "url": "https://head-pose-estimation1.p.rapidapi.com/direction-detection", + "description": "![](https://cdn.smclk.net/img/Head-Pose-Estimation.png)\nFor more details [contact us](https://smartclick.ai/contact/)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://head-pose-estimation1.p.rapidapi.com/direction-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"head-pose-estimation1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://head-pose-estimation1.p.rapidapi.com/direction-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"head-pose-estimation1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/human_level_speech_to_text.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/human_level_speech_to_text.json new file mode 100644 index 0000000000000000000000000000000000000000..392bd18cc0b49c73fc01c2374b58fed4cfc3b67e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/human_level_speech_to_text.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_478a0a9f-9b23-41d5-8c55-d732130d7da2", + "tool_description": "Advanced voice to text API that can transcribe audio at a quality level comparable to humans.", + "home_url": "https://rapidapi.com/mattshumertech/api/human-level-speech-to-text/", + "name": "Human-Level Speech to Text", + "title": "Human-Level Speech to Text", + "pricing": "FREEMIUM", + "tool_name": "Human-Level Speech to Text", + "score": null, + "host": "human-level-speech-to-text.p.rapidapi.com", + "api_list": [ + { + "name": "Transcribe Audio", + "url": "https://human-level-speech-to-text.p.rapidapi.com/transcribe_audio", + "description": "Using state-of-the-art deep learning models and techniques, this API endpoint is more accurate and versatile than anything currently available. With features like automatic language detection, punctuation identification, and support for dozens of languages, this API is the perfect tool for any application that requires accurate transcription. This API is also lightning fast, able to transcribe audio files in seconds.\n\nPlus, you don't need to speak slowly and clearly like other speech-to-text APIs. This API can even understand audio files with background noise and other imperfections. So if you need accurate, fast, and versatile speech-to-text transcription, this API is the perfect choice.", + "method": "POST", + "required_parameters": [ + { + "name": "audio", + "type": "STRING", + "description": "", + "default": "MP3 FILE GOES HERE" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://human-level-speech-to-text.p.rapidapi.com/transcribe_audio\"\nquerystring = {\"audio\": \"MP3 FILE GOES HERE\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"human-level-speech-to-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://human-level-speech-to-text.p.rapidapi.com/transcribe_audio\"\nquerystring = {\"audio\": \"MP3 FILE GOES HERE\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"human-level-speech-to-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/humanwrite.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/humanwrite.json new file mode 100644 index 0000000000000000000000000000000000000000..80dfaa268ea6ff291a10498d60b87d9179e13de8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/humanwrite.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_220baf1a-a22e-4241-b053-6cd31c74a11e", + "tool_description": "Check if the text is written by a human or generated by an AI.", + "home_url": "https://rapidapi.com/asrapidapi23/api/humanwrite/", + "name": "HumanWrite", + "title": "HumanWrite", + "pricing": "FREEMIUM", + "tool_name": "HumanWrite", + "score": null, + "host": "humanwrite.p.rapidapi.com", + "api_list": [ + { + "name": "HumanWrite API", + "url": "https://humanwrite.p.rapidapi.com/api/humanwrite", + "description": "The endpoint takes 'action' and 'text' in the POST request and returns a score of the human-like text in percent from 0 to 100.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://humanwrite.p.rapidapi.com/api/humanwrite\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"humanwrite.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://humanwrite.p.rapidapi.com/api/humanwrite\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"humanwrite.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hybridsearch.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hybridsearch.json new file mode 100644 index 0000000000000000000000000000000000000000..b9a96d5bc8b1888e045228c5eb713a2e1fb5738c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/hybridsearch.json @@ -0,0 +1,137 @@ +{ + "product_id": "api_06669d3b-4353-439d-aae2-a98a91e45849", + "tool_description": "A keyword-aware semantic search engine", + "home_url": "https://rapidapi.com/hybridsearchio/api/hybridsearch/", + "name": "HybridSearch", + "title": "HybridSearch", + "pricing": "FREE", + "tool_name": "HybridSearch", + "score": { + "avgServiceLevel": 100, + "avgLatency": 389, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "hybridsearch.p.rapidapi.com", + "api_list": [ + { + "name": "upload text files", + "url": "https://hybridsearch.p.rapidapi.com/v1/upload/text-files", + "description": "Upload text file(s) (pdf, txt, docx) to the HybridSearch service. Note: max file size supported is 5 MB and max filename length is 100 characters including file extension", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "The file(s) to upload. If you want to upload multiple files, add different file names to this `file` field.\n For example: `curl -X POST -H 'Authorization: Bearer $AUTH_TOKEN' -F file=@file.txt -F file=@file2.docx -F file=@file3.pdf -F org=YOUR_ORG_NAME`", + "default": "@file.txt" + }, + { + "name": "org", + "type": "STRING", + "description": "The organization name", + "default": "YOUR_ORG_NAME" + } + ], + "optional_parameters": [ + { + "name": "batch", + "type": "NUMBER", + "description": "The number of content chunks per batch to upload to the cloud. min: 1, max: 100", + "default": 100 + }, + { + "name": "chunk", + "type": "NUMBER", + "description": "The chunk size in bytes. min: 256 bytes, max: 2kb (2048 bytes)", + "default": 1024 + } + ], + "code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/upload/text-files\"\nquerystring = {\"batch\": 100, \"chunk\": 1024, \"file\": \"@file.txt\", \"org\": \"YOUR_ORG_NAME\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/upload/text-files\"\nquerystring = {\"batch\": 100, \"chunk\": 1024, \"file\": \"@file.txt\", \"org\": \"YOUR_ORG_NAME\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "delete", + "url": "https://hybridsearch.p.rapidapi.com/v1/delete", + "description": "Delete file(s), if exists, from the HybridSearch service", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "get-sources", + "url": "https://hybridsearch.p.rapidapi.com/v1/get-sources", + "description": "List all data sources (text files, documents) in a given org", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/get-sources\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/get-sources\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "HS-Request-ID": { + "type": "string" + }, + "files": { + "type": "array", + "items": { + "type": "string" + } + }, + "org": { + "type": "string" + } + } + } + }, + { + "name": "query", + "url": "https://hybridsearch.p.rapidapi.com/v1/query", + "description": "Send a query to the hybridsearch service and retrieve semantic and/or keyword matches", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/query\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://hybridsearch.p.rapidapi.com/v1/query\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"hybridsearch.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "HS-Request-ID": { + "type": "string" + }, + "matches": { + "type": "array", + "items": { + "type": "object", + "properties": { + "sample": { + "type": "string" + }, + "source": { + "type": "string" + }, + "score": { + "type": "number" + } + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/iamai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/iamai.json new file mode 100644 index 0000000000000000000000000000000000000000..cf99f988f598bb97e243a7adfa46e439a8b63414 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/iamai.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_1904cc7d-9aed-4ffd-a466-bce8e078f6e6", + "tool_description": "An intelligent chatbot that can answer any type of question! - Take a taste here: https://iamai.page/ -- Full docs here: https://iamai.page/#/docs", + "home_url": "https://rapidapi.com/eftihis.riise/api/iamai/", + "name": "iamAI", + "title": "iamAI", + "pricing": "FREEMIUM", + "tool_name": "iamAI", + "score": { + "avgServiceLevel": 0, + "avgLatency": 70, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "iamai.p.rapidapi.com", + "api_list": [ + { + "name": "/ask", + "url": "https://iamai.p.rapidapi.com/ask", + "description": "This is the main endpoint. You send your questions here and you get a reply back.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://iamai.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"iamai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://iamai.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"iamai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_liveness_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_liveness_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..3bb152d03336b480f9a2bc8cbbf7f06e2c76c701 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_liveness_detection.json @@ -0,0 +1,42 @@ +{ + "product_id": "api_42ab8512-4f32-4eab-be1d-ab0f601dc347", + "tool_description": "ID Document Liveness Detection", + "home_url": "https://rapidapi.com/faceonlive-inc-faceonlive-inc-default/api/id-document-liveness-detection/", + "name": "ID Document Liveness Detection", + "title": "ID Document Liveness Detection", + "pricing": "FREE", + "tool_name": "ID Document Liveness Detection", + "score": null, + "host": "id-document-liveness-detection.p.rapidapi.com", + "api_list": [ + { + "name": "From Base64", + "url": "https://id-document-liveness-detection.p.rapidapi.com/api/idliveness_base64", + "description": "ID Document Liveness Detection From Base64", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://id-document-liveness-detection.p.rapidapi.com/api/idliveness_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-liveness-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://id-document-liveness-detection.p.rapidapi.com/api/idliveness_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-liveness-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "From Image", + "url": "https://id-document-liveness-detection.p.rapidapi.com/api/idliveness", + "description": "ID Document Liveness Detection From Image", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://id-document-liveness-detection.p.rapidapi.com/api/idliveness\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-liveness-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://id-document-liveness-detection.p.rapidapi.com/api/idliveness\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-liveness-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_recognition.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_recognition.json new file mode 100644 index 0000000000000000000000000000000000000000..b92eb88f8ea9858c748d99fc7099c4e73ec95b69 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/id_document_recognition.json @@ -0,0 +1,48 @@ +{ + "product_id": "api_0546b35e-7fbe-4a54-a9c7-abba2bc1d9ea", + "tool_description": "ID Document Recognition", + "home_url": "https://rapidapi.com/faceonlive-inc-faceonlive-inc-default/api/id-document-recognition2/", + "name": "ID Document Recognition", + "title": "ID Document Recognition", + "pricing": "FREE", + "tool_name": "ID Document Recognition", + "score": { + "avgServiceLevel": 100, + "avgLatency": 4463, + "avgSuccessRate": 100, + "popularityScore": 8.1, + "__typename": "Score" + }, + "host": "id-document-recognition2.p.rapidapi.com", + "api_list": [ + { + "name": "From Base64", + "url": "https://id-document-recognition2.p.rapidapi.com/api/iddoc_base64", + "description": "ID Document Recognition From Base64", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://id-document-recognition2.p.rapidapi.com/api/iddoc_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-recognition2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://id-document-recognition2.p.rapidapi.com/api/iddoc_base64\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-recognition2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "From Image", + "url": "https://id-document-recognition2.p.rapidapi.com/api/iddoc", + "description": "ID Document Recognition From Image", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://id-document-recognition2.p.rapidapi.com/api/iddoc\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-recognition2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://id-document-recognition2.p.rapidapi.com/api/iddoc\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"id-document-recognition2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_diffusion.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_diffusion.json new file mode 100644 index 0000000000000000000000000000000000000000..6d7a8c07f54fe77c1abde5b79db54273a19471f1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_diffusion.json @@ -0,0 +1,26 @@ +{ + "product_id": "api_920bc34c-d13d-4dea-ab35-82988907de29", + "tool_description": "Repaint high-quality image background with prompt.", + "home_url": "https://rapidapi.com/logerzhu/api/image-background-diffusion1/", + "name": "Image Background Diffusion", + "title": "Image Background Diffusion", + "pricing": "FREEMIUM", + "tool_name": "Image Background Diffusion", + "score": null, + "host": "image-background-diffusion1.p.rapidapi.com", + "api_list": [ + { + "name": "Submit task", + "url": "https://image-background-diffusion1.p.rapidapi.com/predictions", + "description": "Start a image background diffusion task", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-background-diffusion1.p.rapidapi.com/predictions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-diffusion1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-background-diffusion1.p.rapidapi.com/predictions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-diffusion1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_removal.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_removal.json new file mode 100644 index 0000000000000000000000000000000000000000..4858f5d0769b752190b311b791daea14717baea0 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_removal.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_34c3d0ee-e461-45d7-b28e-6b68398d8604", + "tool_description": "The AI-powered API effortlessly removes backgrounds.", + "home_url": "https://rapidapi.com/tamnvhustcc/api/image-background-removal4/", + "name": "Image Background Removal", + "title": "Image Background Removal", + "pricing": "FREEMIUM", + "tool_name": "Image Background Removal", + "score": { + "avgServiceLevel": 95, + "avgLatency": 2677, + "avgSuccessRate": 95, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "image-background-removal4.p.rapidapi.com", + "api_list": [ + { + "name": "Remove image background", + "url": "https://image-background-removal4.p.rapidapi.com/process_image", + "description": "This endpoint accepts an image as input and provides a response containing the corresponding mask.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-background-removal4.p.rapidapi.com/process_image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-removal4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-background-removal4.p.rapidapi.com/process_image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-removal4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_remover_ai_background_removal.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_remover_ai_background_removal.json new file mode 100644 index 0000000000000000000000000000000000000000..3be469cb0e2fe961cfef5779a6f06b4629a44c56 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_background_remover_ai_background_removal.json @@ -0,0 +1,43 @@ +{ + "product_id": "api_ae0d9417-677c-49e2-9634-87517cd60e77", + "tool_description": "Easily remove backgrounds from images using our AI-powered Image Background Remover API. Perfect for photo editing, e-commerce, and more.", + "home_url": "https://rapidapi.com/ezzakyyy-c6FtnmNwXn_/api/image-background-remover-ai-background-removal/", + "name": "Image Background Remover - ( AI Background Removal )", + "title": "Image Background Remover - ( AI Background Removal )", + "pricing": "FREEMIUM", + "tool_name": "Image Background Remover - ( AI Background Removal )", + "score": { + "avgServiceLevel": 85, + "avgLatency": 5129, + "avgSuccessRate": 73, + "popularityScore": 9.1, + "__typename": "Score" + }, + "host": "image-background-remover-ai-background-removal.p.rapidapi.com", + "api_list": [ + { + "name": "AI Image Background Remover", + "url": "https://image-background-remover-ai-background-removal.p.rapidapi.com/removeBackground", + "description": "Just Give our AI API your direct image link and we take care instantly.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "image_file", + "type": "BINARY", + "description": "", + "default": "" + }, + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://image-background-remover-ai-background-removal.p.rapidapi.com/removeBackground\"\nquerystring = {\"image_file\": \"\", \"image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-remover-ai-background-removal.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-background-remover-ai-background-removal.p.rapidapi.com/removeBackground\"\nquerystring = {\"image_file\": \"\", \"image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-background-remover-ai-background-removal.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_captcha_solver_daddy.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_captcha_solver_daddy.json new file mode 100644 index 0000000000000000000000000000000000000000..6be63b295154136239f5a9e8e47fb6c9a484fc58 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_captcha_solver_daddy.json @@ -0,0 +1,33 @@ +{ + "product_id": "api_e85fed23-7f4e-4f26-b6f7-14ca35cf6056", + "tool_description": "Solve Image Captcha 90% Accuracy. \nFast and Easy to use API. Solve THOUSANDS of types of Image captcha\nOverall API accuracy depends on how complicated your image. If it's difficult to read to human, it will be difficult to solve to the AI\nExample captcha that can be solved https://ibb.co/rvMQf03\n\n", + "home_url": "https://rapidapi.com/DaddyApi/api/image-captcha-solver-daddy/", + "name": "\ud83d\udd34 IMAGE CAPTCHA SOLVER \ud83d\udd34 Daddy", + "title": "\ud83d\udd34 IMAGE CAPTCHA SOLVER \ud83d\udd34 Daddy", + "pricing": "FREEMIUM", + "tool_name": "\ud83d\udd34 IMAGE CAPTCHA SOLVER \ud83d\udd34 Daddy", + "score": null, + "host": "image-captcha-solver-daddy.p.rapidapi.com", + "api_list": [ + { + "name": "Solve", + "url": "https://image-captcha-solver-daddy.p.rapidapi.com/solve", + "description": "Try to save the original captcha (making screenshot is slightly worse). Try to keep the size of the image small, good practice is to have the size in few Kb. POST your image, using \"application/octet-stream\"\n* For unknown reason API doesn't work through web interface, please use it directly in your app", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-captcha-solver-daddy.p.rapidapi.com/solve\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-captcha-solver-daddy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-captcha-solver-daddy.p.rapidapi.com/solve\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-captcha-solver-daddy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "solution": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator.json new file mode 100644 index 0000000000000000000000000000000000000000..40757331221ae8ea578b1c4124239c3dcb72be89 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator.json @@ -0,0 +1,71 @@ +{ + "tool_name":"Image Caption Generator", + "tool_description":"Easy-to-integrate AI-Powered Image Caption Generation API that supports multiple languages and vibes. Get started in 10 seconds or less!", + "title":"Image Caption Generator", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":95, + "avgLatency":7749, + "avgSuccessRate":93, + "popularityScore":9.7, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/fantascatllc/api/image-caption-generator2/", + "host":"image-caption-generator2.p.rapidapi.com", + "api_list":[ + { + "name":"Generates image captions", + "url":"https://image-caption-generator2.p.rapidapi.com/v2/captions", + "description":"Generates descriptive captions for a given image. When `useEmojis`/`useHashtags` is set to `true`, the generated captions will include emojis/hashtags. A maximum of three captions are returned.", + "method":"GET", + "required_parameters":[ + { + "name":"imageUrl", + "type":"STRING", + "description":"Url of the image", + "default":"https://i.pinimg.com/564x/26/c7/35/26c7355fe46f62d84579857c6f8c4ea5.jpg" + } + ], + "optional_parameters":[ + { + "name":"useEmojis", + "type":"BOOLEAN", + "description":"If true, emojis will be added to generate captions.", + "default":"true" + }, + { + "name":"vibe", + "type":"ENUM", + "description":"Choose the vibe of the generated captions.", + "default":"" + }, + { + "name":"limit", + "type":"NUMBER", + "description":"Number of captions returned. Must be <=3.", + "default":"3" + }, + { + "name":"useHashtags", + "type":"BOOLEAN", + "description":"If true, hashtags will be added to generate captions.", + "default":"true" + }, + { + "name":"lang", + "type":"ENUM", + "description":"", + "default":"" + } + ], + "code":"import requests\n\nurl = \"https://image-caption-generator2.p.rapidapi.com/v2/captions\"\nquerystring = {\"useEmojis\": useemojis, \"imageUrl\": imageurl, \"limit\": limit, \"useHashtags\": usehashtags}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-caption-generator2.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator/api.py new file mode 100644 index 0000000000000000000000000000000000000000..f4d0bf2ae079fe9ea5fd658127f0f474ab6ccfbe --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_caption_generator/api.py @@ -0,0 +1,44 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generates_image_captions(imageurl: str, useemojis: bool=None, vibe: str=None, limit: int=3, usehashtags: bool=None, lang: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generates descriptive captions for a given image. When `useEmojis`/`useHashtags` is set to `true`, the generated captions will include emojis/hashtags. A maximum of three captions are returned." + imageurl: Url of the image + useemojis: If true, emojis will be added to generate captions. + vibe: Choose the vibe of the generated captions. + limit: Number of captions returned. Must be <=3. + usehashtags: If true, hashtags will be added to generate captions. + + """ + url = f"https://image-caption-generator2.p.rapidapi.com/v2/captions" + querystring = {'imageUrl': imageurl, } + if useemojis: + querystring['useEmojis'] = useemojis + if vibe: + querystring['vibe'] = vibe + if limit: + querystring['limit'] = limit + if usehashtags: + querystring['useHashtags'] = usehashtags + if lang: + querystring['lang'] = lang + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "image-caption-generator2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_description_caption.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_description_caption.json new file mode 100644 index 0000000000000000000000000000000000000000..9973a4ad2e893cdd8ae28e6bc1c4c1841f97addc --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_description_caption.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_a249ea30-dfd8-45ba-9cba-67a08b7305f8", + "tool_description": "Input an image URL and get a detailed description of the image as if a human is telling you what's in the image.", + "home_url": "https://rapidapi.com/contentify-contentify-default/api/image-description-caption/", + "name": "Image Description & Caption", + "title": "Image Description & Caption", + "pricing": "FREEMIUM", + "tool_name": "Image Description & Caption", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1022, + "avgSuccessRate": 50, + "popularityScore": 8.7, + "__typename": "Score" + }, + "host": "image-description-caption.p.rapidapi.com", + "api_list": [ + { + "name": "Image description", + "url": "https://image-description-caption.p.rapidapi.com/image-description", + "description": "Describe your images in details", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-description-caption.p.rapidapi.com/image-description\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-description-caption.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-description-caption.p.rapidapi.com/image-description\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-description-caption.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_generator_using_text_descriptions_fast_cheap.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_generator_using_text_descriptions_fast_cheap.json new file mode 100644 index 0000000000000000000000000000000000000000..9c70d39de053f4ebc2c37111a5bb4d6741d0565b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_generator_using_text_descriptions_fast_cheap.json @@ -0,0 +1,85 @@ +{ + "product_id": "api_514d1ad3-8e5b-4dee-8d13-9146d48445e7", + "tool_description": "\nSix fully configurable AI models to create images and art from text descriptions. Most of them are based on Stable Diffusion.", + "home_url": "https://rapidapi.com/Experto/api/image-generator-using-text-descriptions-fast-cheap3/", + "name": "Image Generator Using Text Descriptions - Fast & Cheap", + "title": "Image Generator Using Text Descriptions - Fast & Cheap", + "pricing": "FREEMIUM", + "tool_name": "Image Generator Using Text Descriptions - Fast & Cheap", + "score": { + "avgServiceLevel": 96, + "avgLatency": 12089, + "avgSuccessRate": 96, + "popularityScore": 9.5, + "__typename": "Score" + }, + "host": "image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com", + "api_list": [ + { + "name": "Group 2: Lykon DreamShaper", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/Lykon/DreamShaper", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/Lykon/DreamShaper\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/Lykon/DreamShaper\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Group 2: XpucT Deliberate", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/XpucT/Deliberate", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/XpucT/Deliberate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/XpucT/Deliberate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Group 1: Prompthero Openjourney", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/prompthero/openjourney", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/prompthero/openjourney\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/prompthero/openjourney\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Group 2: CompVis Stable Diffusion v1.4", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/CompVis/stable-diffusion-v1-4", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/CompVis/stable-diffusion-v1-4\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/CompVis/stable-diffusion-v1-4\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Group 1: Runway Stable Diffusion v1.5", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/runwayml/stable-diffusion-v1-5", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/runwayml/stable-diffusion-v1-5\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/runwayml/stable-diffusion-v1-5\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Group 1: Stability AI Stable Diffusion v2.1", + "url": "https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/stabilityai/stable-diffusion-2-1", + "description": "Generate an Image from Text Description. This API endpoint returns an image in PNG base64 format. To easily visualize the generated image, please refer to the 'Tutorials' section.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/stabilityai/stable-diffusion-2-1\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com/v1/inference/stabilityai/stable-diffusion-2-1\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-generator-using-text-descriptions-fast-cheap3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_moderation.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_moderation.json new file mode 100644 index 0000000000000000000000000000000000000000..85e9355dae51e68e82c299d9240691cd5b10e768 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_moderation.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_b38d054c-aa6e-4fdd-a3de-178283c79d62", + "tool_description": "An image moderation classifier built to identify 32 concepts, including GARM categories.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/image-moderation1/", + "name": "Image Moderation ", + "title": "Image Moderation ", + "pricing": "FREEMIUM", + "tool_name": "Image Moderation ", + "score": null, + "host": "image-moderation1.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://image-moderation1.p.rapidapi.com/", + "description": "Detect inappropriate content which includes gore, drugs, explicit, suggestive, etc. in images.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://s3.amazonaws.com/samples.clarifai.com/featured-models/moderation-medical-syringe-cocaine.jpg?v=thumb" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-moderation1.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/featured-models/moderation-medical-syringe-cocaine.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-moderation1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-moderation1.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://s3.amazonaws.com/samples.clarifai.com/featured-models/moderation-medical-syringe-cocaine.jpg?v=thumb\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-moderation1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_subject_segmentation.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_subject_segmentation.json new file mode 100644 index 0000000000000000000000000000000000000000..512367e12afbd610e90701fce3e1da374f2cd972 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_subject_segmentation.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_bebd13ce-e13d-451f-b560-06f07a834926", + "tool_description": "AI for identifying the main subject of an image or video at pixel level accuracy.", + "home_url": "https://rapidapi.com/ai-gateway-ai-gateway-default/api/image-subject-segmentation/", + "name": "Image Subject Segmentation", + "title": "Image Subject Segmentation", + "pricing": "FREEMIUM", + "tool_name": "Image Subject Segmentation", + "score": { + "avgServiceLevel": 100, + "avgLatency": 27372, + "avgSuccessRate": 67, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "image-subject-segmentation.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze Image", + "url": "https://image-subject-segmentation.p.rapidapi.com/", + "description": "Return the subject(s) of the image.", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://i.pinimg.com/originals/a7/99/39/a79939f3ba91a8bdb89c35db4cf16029.jpg" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-subject-segmentation.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://i.pinimg.com/originals/a7/99/39/a79939f3ba91a8bdb89c35db4cf16029.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-subject-segmentation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-subject-segmentation.p.rapidapi.com/\"\nquerystring = {\"image_url\": \"https://i.pinimg.com/originals/a7/99/39/a79939f3ba91a8bdb89c35db4cf16029.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-subject-segmentation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_taggingcaptioning_using_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_taggingcaptioning_using_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..b02c1108a640bb77c9cd026f5d31c2482f4c82c9 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_taggingcaptioning_using_ai.json @@ -0,0 +1,55 @@ +{ + "product_id": "api_ea5cb8ca-86b8-4033-a91e-82d669f7926d", + "tool_description": "It generates tags, and caption for the image using AI.", + "home_url": "https://rapidapi.com/akshaymaurya3006/api/image-tagging-captioning-using-ai/", + "name": "Image Tagging/Captioning using AI", + "title": "Image Tagging/Captioning using AI", + "pricing": "FREEMIUM", + "tool_name": "Image Tagging/Captioning using AI", + "score": { + "avgServiceLevel": 0, + "avgLatency": 26, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "image-tagging-captioning-using-ai.p.rapidapi.com", + "api_list": [ + { + "name": "Image Caption", + "url": "https://image-tagging-captioning-using-ai.p.rapidapi.com/caption", + "description": "It returns a caption, related to the image, generated using AI.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-tagging-captioning-using-ai.p.rapidapi.com/caption\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-tagging-captioning-using-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-tagging-captioning-using-ai.p.rapidapi.com/caption\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-tagging-captioning-using-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Image Tag", + "url": "https://image-tagging-captioning-using-ai.p.rapidapi.com/tag", + "description": "It returns an array of tags, related to the image, generated using AI.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-tagging-captioning-using-ai.p.rapidapi.com/tag\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-tagging-captioning-using-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-tagging-captioning-using-ai.p.rapidapi.com/tag\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-tagging-captioning-using-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_to_text_ai_ocr.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_to_text_ai_ocr.json new file mode 100644 index 0000000000000000000000000000000000000000..5f8a87f6f42f134413b3b3e6c3d7fd280d93b6a3 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_to_text_ai_ocr.json @@ -0,0 +1,55 @@ +{ + "product_id": "api_05caf6cb-477d-4407-a76c-92e834c466ad", + "tool_description": "PNG to Word and Jpg to Word or Txt File converter helps to extract text from image you can make txt file, doc file or make available text click to copy by just uploading image and pass image URL to api", + "home_url": "https://rapidapi.com/prefixseo/api/image-to-text-ai-ocr/", + "name": "Image To Text - Ai OCR", + "title": "Image To Text - Ai OCR", + "pricing": "FREE", + "tool_name": "Image To Text - Ai OCR", + "score": { + "avgServiceLevel": 97, + "avgLatency": 6598, + "avgSuccessRate": 80, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "image-to-text-ai-ocr.p.rapidapi.com", + "api_list": [ + { + "name": "Multiple Images", + "url": "https://image-to-text-ai-ocr.p.rapidapi.com/", + "description": "Post multiple images URL as an JSON array and get Text output of each image separate in single response", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "type", + "type": "STRING", + "description": "", + "default": "multiple" + } + ], + "code": "import requests\n\nurl = \"https://image-to-text-ai-ocr.p.rapidapi.com/\"\nquerystring = {\"type\": \"multiple\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-to-text-ai-ocr.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-to-text-ai-ocr.p.rapidapi.com/\"\nquerystring = {\"type\": \"multiple\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-to-text-ai-ocr.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Ai OCR", + "url": "https://image-to-text-ai-ocr.p.rapidapi.com/", + "description": "Trigger AI model to process input image and convert image to text and return JSON output", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "type", + "type": "STRING", + "description": "", + "default": "single" + } + ], + "code": "import requests\n\nurl = \"https://image-to-text-ai-ocr.p.rapidapi.com/\"\nquerystring = {\"type\": \"single\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-to-text-ai-ocr.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-to-text-ai-ocr.p.rapidapi.com/\"\nquerystring = {\"type\": \"single\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-to-text-ai-ocr.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_transformation_with_animegan.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_transformation_with_animegan.json new file mode 100644 index 0000000000000000000000000000000000000000..88fcf27d4a4f6735121b72b0ce06e7e64c63a7e5 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_transformation_with_animegan.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_dfe43bf4-340b-44f1-87c1-48d308d4f17b", + "tool_description": "Image Transformation with AnimeGAN", + "home_url": "https://rapidapi.com/AlekseyKorshuk/api/image-transformation-with-animegan/", + "name": "Image Transformation with AnimeGAN", + "title": "Image Transformation with AnimeGAN", + "pricing": "FREEMIUM", + "tool_name": "Image Transformation with AnimeGAN", + "score": null, + "host": "image-transformation-with-animegan.p.rapidapi.com", + "api_list": [ + { + "name": "Transform", + "url": "https://image-transformation-with-animegan.p.rapidapi.com/run/predict", + "description": "Transform image with AnimeGAN", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-transformation-with-animegan.p.rapidapi.com/run/predict\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-transformation-with-animegan.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-transformation-with-animegan.p.rapidapi.com/run/predict\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-transformation-with-animegan.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_upsclaer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_upsclaer.json new file mode 100644 index 0000000000000000000000000000000000000000..0e1c043c59eb223083ec0c50b4c47bb34eb7f6ed --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/image_upsclaer.json @@ -0,0 +1,71 @@ +{ + "product_id": "api_1ce2f2e6-bef6-4e5a-98f0-95a487c5173a", + "tool_description": "This API can upscale images.\nAlso provides an image server.", + "home_url": "https://rapidapi.com/i2000i/api/image-upsclaer/", + "name": "Image upsclaer", + "title": "Image upsclaer", + "pricing": "FREEMIUM", + "tool_name": "Image upsclaer", + "score": { + "avgServiceLevel": 0, + "avgLatency": 2383, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "image-upsclaer.p.rapidapi.com", + "api_list": [ + { + "name": "POST IMAGE FILE", + "url": "https://image-upsclaer.p.rapidapi.com/upload/image", + "description": "This endpoint receives image file and returns upscaled image file", + "method": "POST", + "required_parameters": [ + { + "name": "type", + "type": "STRING", + "description": "", + "default": "file" + }, + { + "name": "data", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-upsclaer.p.rapidapi.com/upload/image\"\nquerystring = {\"type\": \"file\", \"data\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-upsclaer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-upsclaer.p.rapidapi.com/upload/image\"\nquerystring = {\"type\": \"file\", \"data\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-upsclaer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "POST IMAGE URL", + "url": "https://image-upsclaer.p.rapidapi.com/upload/image", + "description": "This endpoint will return upscaled image url", + "method": "POST", + "required_parameters": [ + { + "name": "data", + "type": "STRING", + "description": "", + "default": "Image URL" + }, + { + "name": "type", + "type": "STRING", + "description": "", + "default": "url" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://image-upsclaer.p.rapidapi.com/upload/image\"\nquerystring = {\"data\": \"Image URL\", \"type\": \"url\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-upsclaer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://image-upsclaer.p.rapidapi.com/upload/image\"\nquerystring = {\"data\": \"Image URL\", \"type\": \"url\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"image-upsclaer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/img2doc.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/img2doc.json new file mode 100644 index 0000000000000000000000000000000000000000..988d45ecf2292496d215baef6300f12c4344476b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/img2doc.json @@ -0,0 +1,43 @@ +{ + "product_id": "api_a5edcae7-9c17-4401-aeb7-d029fd8422d1", + "tool_description": "OCR using AI", + "home_url": "https://rapidapi.com/avprodev-avprodev-default/api/img2doc/", + "name": "img2doc", + "title": "img2doc", + "pricing": "FREEMIUM", + "tool_name": "img2doc", + "score": { + "avgServiceLevel": 0, + "avgLatency": 31, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "img2doc.p.rapidapi.com", + "api_list": [ + { + "name": "OCR Create", + "url": "https://img2doc.p.rapidapi.com/ocr", + "description": "Creates an OCR request, it receives a image file and give you a JSON file", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + }, + { + "name": "format", + "type": "STRING", + "description": "", + "default": "json" + } + ], + "code": "import requests\n\nurl = \"https://img2doc.p.rapidapi.com/ocr\"\nquerystring = {\"image\": \"\", \"format\": \"json\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"img2doc.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://img2doc.p.rapidapi.com/ocr\"\nquerystring = {\"image\": \"\", \"format\": \"json\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"img2doc.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/instagram_hashtag_generator_ai/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/instagram_hashtag_generator_ai/api.py new file mode 100644 index 0000000000000000000000000000000000000000..1dd7e674b69d65c3b8fcfa36e6ee8be654661e1b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/instagram_hashtag_generator_ai/api.py @@ -0,0 +1,31 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generate_hashtags(keyword: str, count: int=20, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generated popular & trending Instagram hashtags with a keyword." + + """ + url = f"https://instagram-hashtag-generator-ai.p.rapidapi.com/" + querystring = {'keyword': keyword, } + if count: + querystring['count'] = count + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "instagram-hashtag-generator-ai.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..292c932dfa2101a8f3acd20fb8d796204e7536c6 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai.json @@ -0,0 +1,206 @@ +{ + "tool_name": "Integrate AI", + "tool_description": "Unleash the power of GPT-4 and simplify integration with standard JSON responses.", + "title": "Integrate AI", + "pricing": "FREEMIUM", + "score": null, + "home_url": "https://rapidapi.com/gal.giacomelli/api/integrate-ai/", + "host": "integrate-ai.p.rapidapi.com", + "api_list": [ + { + "name": "question_answering_question_answering__post", + "url": "https://integrate-ai.p.rapidapi.com/question-answering/", + "description": "Get answers to questions", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/question-answering/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "read_root__get", + "url": "https://integrate-ai.p.rapidapi.com/", + "description": " ", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "text_summarization_text_summarization__post", + "url": "https://integrate-ai.p.rapidapi.com/text-summarization/", + "description": "Summarize text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-summarization/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "sentiment_analysis_sentiment_analysis__post", + "url": "https://integrate-ai.p.rapidapi.com/sentiment-analysis/", + "description": "Retrive sentiment", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/sentiment-analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "paraphrasing_paraphrasing__post", + "url": "https://integrate-ai.p.rapidapi.com/paraphrasing/", + "description": "Paraphrase text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/paraphrasing/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "text_classification_text_classification__post", + "url": "https://integrate-ai.p.rapidapi.com/text-classification/", + "description": "Calssify text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-classification/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "keyword_extraction_keyword_extraction__post", + "url": "https://integrate-ai.p.rapidapi.com/keyword-extraction/", + "description": "Extract key words", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/keyword-extraction/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "named_entity_recognition_named_entity_recognition__post", + "url": "https://integrate-ai.p.rapidapi.com/named-entity-recognition/", + "description": "Extract named enteties", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/named-entity-recognition/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": {} + }, + { + "name": "question_answering_question_answering__post", + "url": "https://integrate-ai.p.rapidapi.com/question-answering/", + "description": "Get answers to questions", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/question-answering/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/question-answering/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "text_summarization_text_summarization__post", + "url": "https://integrate-ai.p.rapidapi.com/text-summarization/", + "description": "Summarize text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-summarization/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-summarization/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "sentiment_analysis_sentiment_analysis__post", + "url": "https://integrate-ai.p.rapidapi.com/sentiment-analysis/", + "description": "Retrive sentiment", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/sentiment-analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/sentiment-analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "paraphrasing_paraphrasing__post", + "url": "https://integrate-ai.p.rapidapi.com/paraphrasing/", + "description": "Paraphrase text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/paraphrasing/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/paraphrasing/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "text_classification_text_classification__post", + "url": "https://integrate-ai.p.rapidapi.com/text-classification/", + "description": "Calssify text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-classification/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/text-classification/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "keyword_extraction_keyword_extraction__post", + "url": "https://integrate-ai.p.rapidapi.com/keyword-extraction/", + "description": "Extract key words", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/keyword-extraction/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/keyword-extraction/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "named_entity_recognition_named_entity_recognition__post", + "url": "https://integrate-ai.p.rapidapi.com/named-entity-recognition/", + "description": "Extract named enteties", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/named-entity-recognition/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://integrate-ai.p.rapidapi.com/named-entity-recognition/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"integrate-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai/api.py new file mode 100644 index 0000000000000000000000000000000000000000..f137719b34b79e8ac9953ab4eeac6c16145bc85b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/integrate_ai/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def read_root_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://integrate-ai.p.rapidapi.com/" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "integrate-ai.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/intelligent_document_extractor.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/intelligent_document_extractor.json new file mode 100644 index 0000000000000000000000000000000000000000..324e01275e829426e6369945ac03b2bae83f0dfd --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/intelligent_document_extractor.json @@ -0,0 +1,54 @@ +{ + "product_id": "api_5fb9959e-a90e-4994-a100-93e775997f0f", + "tool_description": "Fill Later", + "home_url": "https://rapidapi.com/ruatagiadi95/api/intelligent-document-extractor/", + "name": "Intelligent Document Extractor", + "title": "Intelligent Document Extractor", + "pricing": "FREEMIUM", + "tool_name": "Intelligent Document Extractor", + "score": { + "avgServiceLevel": 100, + "avgLatency": 12230, + "avgSuccessRate": 100, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "intelligent-document-extractor.p.rapidapi.com", + "api_list": [ + { + "name": "ideAdityaDev", + "url": "https://intelligent-document-extractor.p.rapidapi.com/IDE_aditya_dev", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://intelligent-document-extractor.p.rapidapi.com/IDE_aditya_dev\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"intelligent-document-extractor.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://intelligent-document-extractor.p.rapidapi.com/IDE_aditya_dev\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"intelligent-document-extractor.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api.json new file mode 100644 index 0000000000000000000000000000000000000000..359e7d60124feecb4e0881993f4a738731abc158 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api.json @@ -0,0 +1,90 @@ +{ + "tool_name":"Islam & AI API", + "tool_description":"Islam & AI API for Islamic ChatBot.\n\nThe Best AI for Islam! ", + "title":"Islam & AI API", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":55, + "avgLatency":7769, + "avgSuccessRate":50, + "popularityScore":9.5, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/alizahidrajaa/api/islam-ai-api/", + "host":"islam-ai-api.p.rapidapi.com", + "api_list":[ + { + "name":"Have a Chat with our Bot", + "url":"https://islam-ai-api.p.rapidapi.com/api/chat", + "description":"Have a conversation with our Islam&AI Bot in which it remembers your previous conversation! (upto 30 texts)", + "method":"GET", + "required_parameters":[ + { + "name":"question", + "type":"STRING", + "description":"", + "default":"What is Islam?" + } + ], + "optional_parameters":[ + { + "name":"chatHistory", + "type":"STRING", + "description":"", + "default":"What is Dua to recite when you see a miraculous thing like Islam & AI? | There is no specific dua (supplication) mentioned in the Quran or Hadith that is to be recited when witnessing a miracle. However, Muslims are encouraged to constantly remember Allah and express their gratitude to Him for the blessings and miracles they witness in their lives. In general, it is recommended to say 'Subhan Allah' (Glory be to Allah) when witnessing something amazing or miraculous" + } + ], + "code":"import requests\n\nurl = \"https://islam-ai-api.p.rapidapi.com/api/chat\"\nquerystring = {\"chatHistory\": chathistory, \"question\": question}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"islam-ai-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{ + "type":"object", + "properties":{ + "status":{ + "type":"integer" + }, + "response":{ + "type":"string" + } + } + } + }, + { + "name":"Get an Answer to your Question", + "url":"https://islam-ai-api.p.rapidapi.com/api/bot", + "description":"Get answer to an Islamic question from our Islam&AI bot", + "method":"GET", + "required_parameters":[ + { + "name":"question", + "type":"STRING", + "description":"", + "default":"What is Islam?" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://islam-ai-api.p.rapidapi.com/api/bot\"\nquerystring = {\"question\": question}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"islam-ai-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{ + "type":"object", + "properties":{ + "status":{ + "type":"integer" + }, + "response":{ + "type":"string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..af862d9fd5f027f6a4dbe77b700b23a88ec9d8e4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islam_ai_api/api.py @@ -0,0 +1,52 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def have_a_chat_with_our_bot(question: str, chathistory: str="What is Dua to recite when you see a miraculous thing like Islam & AI? | There is no specific dua (supplication) mentioned in the Quran or Hadith that is to be recited when witnessing a miracle. However, Muslims are encouraged to constantly remember Allah and express their gratitude to Him for the blessings and miracles they witness in their lives. In general, it is recommended to say 'Subhan Allah' (Glory be to Allah) when witnessing something amazing or miraculous", toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Have a conversation with our Islam&AI Bot in which it remembers your previous conversation! (upto 30 texts)" + + """ + url = f"https://islam-ai-api.p.rapidapi.com/api/chat" + querystring = {'question': question, } + if chathistory: + querystring['chatHistory'] = chathistory + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "islam-ai-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_an_answer_to_your_question(question: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get answer to an Islamic question from our Islam&AI bot" + + """ + url = f"https://islam-ai-api.p.rapidapi.com/api/bot" + querystring = {'question': question, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "islam-ai-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..677b5e549a45140bbf9943842adf24547ed8023c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai.json @@ -0,0 +1,37 @@ +{ + "tool_name":"Islamic AI", + "tool_description":"We have ai boot to answer any islamic question.\nOur AI Islamic bot API is designed to provide accurate and informative answers to any Islamic-related question. Whether it's about prayer times, Quranic verses, or the teachings of Prophet Muhammad, our bot is equipped with a vast knowledge base and advanced natural language processing capabilities to understand and respond to user queries. With this API, users can easily access reliable Islamic information from the comfort of their own devices....", + "title":"Islamic AI", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":0, + "avgLatency":1103, + "avgSuccessRate":0, + "popularityScore":0, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/um.waqas.khan/api/islamic-ai/", + "host":"islamic-ai.p.rapidapi.com", + "api_list":[ + { + "name":"islamic", + "url":"https://islamic-ai.p.rapidapi.com/islamic", + "description":"to complete any Islamic question", + "method":"GET", + "required_parameters":[ + { + "name":"question", + "type":"STRING", + "description":"", + "default":"Quran" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://islamic-ai.p.rapidapi.com/islamic\"\nquerystring = {\"question\": question}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"islamic-ai.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai/api.py new file mode 100644 index 0000000000000000000000000000000000000000..ca355a2d41a3d102c6974b28413b4eacc6a1e2fe --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/islamic_ai/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def islamic(question: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "to complete any Islamic question" + + """ + url = f"https://islamic-ai.p.rapidapi.com/islamic" + querystring = {'question': question, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "islamic-ai.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_and_candidate_matching.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_and_candidate_matching.json new file mode 100644 index 0000000000000000000000000000000000000000..340d61f16c2b559b7ee1852aad10a05fb38cb279 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_and_candidate_matching.json @@ -0,0 +1,26 @@ +{ + "product_id": "api_36822578-a47c-4098-9db5-c2da9bb576d9", + "tool_description": "This API matches the candidate CV with the JD. The API responds the detailed matching score once the candidate CV matches with the JD.", + "home_url": "https://rapidapi.com/enrichdata-enrichdata-default/api/job-and-candidate-matching/", + "name": "Job and Candidate Matching", + "title": "Job and Candidate Matching", + "pricing": "PAID", + "tool_name": "Job and Candidate Matching", + "score": null, + "host": "job-and-candidate-matching.p.rapidapi.com", + "api_list": [ + { + "name": "One To One Match API", + "url": "https://job-and-candidate-matching.p.rapidapi.com/oneMatch", + "description": "This API matches the candidate CV with the JD. The API responds the detailed matching score once the candidate CV matches with the JD.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-and-candidate-matching.p.rapidapi.com/oneMatch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-and-candidate-matching.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://job-and-candidate-matching.p.rapidapi.com/oneMatch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-and-candidate-matching.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_maker.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_maker.json new file mode 100644 index 0000000000000000000000000000000000000000..1db91d7aa309c181a3ff0079102722e92e8c8699 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_maker.json @@ -0,0 +1,49 @@ +{ + "product_id": "api_4840ca2f-de3c-44bb-a52c-054b74525a44", + "tool_description": "Make Job Description", + "home_url": "https://rapidapi.com/raziullah0316/api/job-description-maker/", + "name": "Job Description Maker", + "title": "Job Description Maker", + "pricing": "FREE", + "tool_name": "Job Description Maker", + "score": null, + "host": "job-description-maker.p.rapidapi.com", + "api_list": [ + { + "name": "openapi/jd", + "url": "https://job-description-maker.p.rapidapi.com/openapi/jd", + "description": "Endpoints of Job Description Generator", + "method": "POST", + "required_parameters": [ + { + "name": "vacancy", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "job_experience", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "gender", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "job_title", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-description-maker.p.rapidapi.com/openapi/jd\"\nquerystring = {\"vacancy\": \"\", \"job_experience\": \"\", \"gender\": \"\", \"job_title\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-maker.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://job-description-maker.p.rapidapi.com/openapi/jd\"\nquerystring = {\"vacancy\": \"\", \"job_experience\": \"\", \"gender\": \"\", \"job_title\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-maker.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing.json new file mode 100644 index 0000000000000000000000000000000000000000..8ac2b15f9566338817439e94beb4692d0d86487c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing.json @@ -0,0 +1,67 @@ +{ + "tool_name": "Job description processing", + "tool_description": "Job description processing using a deep learning model", + "title": "Job description processing", + "pricing": "FREE", + "score": { + "avgServiceLevel": 100, + "avgLatency": 293, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/abdurrahmansalih/api/job-description-processing/", + "host": "job-description-processing.p.rapidapi.com", + "api_list": [ + { + "name": "Model Version", + "url": "https://job-description-processing.p.rapidapi.com/", + "description": "Model Version", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-description-processing.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-processing.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "about", + "url": "https://job-description-processing.p.rapidapi.com/about", + "description": "about model", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-description-processing.p.rapidapi.com/about\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-processing.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "predictions", + "url": "https://job-description-processing.p.rapidapi.com/prediction", + "description": "This end point used to split job description.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-description-processing.p.rapidapi.com/prediction\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-processing.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "predictions", + "url": "https://job-description-processing.p.rapidapi.com/prediction", + "description": "This end point used to split job description.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-description-processing.p.rapidapi.com/prediction\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-processing.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://job-description-processing.p.rapidapi.com/prediction\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-description-processing.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing/api.py new file mode 100644 index 0000000000000000000000000000000000000000..61e5e7f2d9391f32e100143017b56c981de3d62a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_description_processing/api.py @@ -0,0 +1,50 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def model_version(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Model Version" + + """ + url = f"https://job-description-processing.p.rapidapi.com/" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "job-description-processing.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def about(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "about model" + + """ + url = f"https://job-description-processing.p.rapidapi.com/about" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "job-description-processing.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_functions_classifications.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_functions_classifications.json new file mode 100644 index 0000000000000000000000000000000000000000..27b51228d7c2f9a09a5dfdc700d33f76e55d5d41 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/job_functions_classifications.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_c0e9850f-0293-4262-a8ca-5c94dbb336b8", + "tool_description": "This api classifies your job titles into specific job functions", + "home_url": "https://rapidapi.com/the-data-business-the-data-business-default/api/job-functions-classifications/", + "name": "job-functions-classifications", + "title": "job-functions-classifications", + "pricing": "FREEMIUM", + "tool_name": "job-functions-classifications", + "score": { + "avgServiceLevel": 100, + "avgLatency": 637, + "avgSuccessRate": 43, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "job-functions-classifications.p.rapidapi.com", + "api_list": [ + { + "name": "job-functions-classification", + "url": "https://job-functions-classifications.p.rapidapi.com/job-functions-classification/", + "description": "job-functions-classification", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://job-functions-classifications.p.rapidapi.com/job-functions-classification/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-functions-classifications.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://job-functions-classifications.p.rapidapi.com/job-functions-classification/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"job-functions-classifications.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api.json new file mode 100644 index 0000000000000000000000000000000000000000..459e1c4d1822f27ac1153a840700f92a88d81248 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api.json @@ -0,0 +1,24 @@ +{ + "tool_name":"Jobs predictions api", + "tool_description":"If you are looking for a way to fetch data of jobs then we have the perfect solution to your problems. We provide a free and easy-to-use API which fetches data of jobs with no limitations. If you are struggling to find a reliable place to get data of jobs, then we are the perfect choice for you.", + "title":"Jobs predictions api", + "pricing":"PAID", + "score":null, + "home_url":"https://rapidapi.com/rowsanonline/api/jobs-predictions-api/", + "host":"jobs-predictions-api.p.rapidapi.com", + "api_list":[ + { + "name":"Get all the data", + "url":"https://jobs-predictions-api.p.rapidapi.com/jobs", + "description":"Jobs predictions data from api", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://jobs-predictions-api.p.rapidapi.com/jobs\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"jobs-predictions-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..9cc48b31e9ffceed6615df085a63ffebafa71611 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jobs_predictions_api/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_all_the_data(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Jobs predictions data from api" + + """ + url = f"https://jobs-predictions-api.p.rapidapi.com/jobs" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "jobs-predictions-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jojonomic_face_rekognition.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jojonomic_face_rekognition.json new file mode 100644 index 0000000000000000000000000000000000000000..26d20986a05951e4e276153e08c064b918e04d1b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jojonomic_face_rekognition.json @@ -0,0 +1,26 @@ +{ + "product_id": "api_7e722603-760e-4055-bf93-6df4d480449d", + "tool_description": "Rekognition Image lets measure the likelihood that faces in two images are of the same person. With Rekognition, you can use the similarity score to verify a user against a reference photo in near real time.", + "home_url": "https://rapidapi.com/jojonomic-headquarters-jojonomic-headquarters-default/api/jojonomic-face-rekognition/", + "name": "Jojonomic Face Rekognition", + "title": "Jojonomic Face Rekognition", + "pricing": "FREEMIUM", + "tool_name": "Jojonomic Face Rekognition", + "score": null, + "host": "jojonomic-face-rekognition.p.rapidapi.com", + "api_list": [ + { + "name": "Face Matches", + "url": "https://jojonomic-face-rekognition.p.rapidapi.com/sdk/rekognition/compare-faces", + "description": "Rekognition Image lets measure the likelihood that faces in two images are of the same person. With Rekognition, you can use the similarity score to verify a user against a reference photo in near real time.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://jojonomic-face-rekognition.p.rapidapi.com/sdk/rekognition/compare-faces\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"jojonomic-face-rekognition.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://jojonomic-face-rekognition.p.rapidapi.com/sdk/rekognition/compare-faces\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"jojonomic-face-rekognition.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/js_code_interpreter.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/js_code_interpreter.json new file mode 100644 index 0000000000000000000000000000000000000000..db2609d347ae676df0bbf71020d82bfd211d7e94 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/js_code_interpreter.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_f54a5c7a-baea-4d72-8791-f548847b424e", + "tool_description": "Let your AI Agent run JS code with access to 1 Million+ NPM's packages in a simple API call using Deno JS runtime", + "home_url": "https://rapidapi.com/axion-company-axion-company-default/api/js-code-interpreter/", + "name": "JS Code Interpreter", + "title": "JS Code Interpreter", + "pricing": "FREEMIUM", + "tool_name": "JS Code Interpreter", + "score": { + "avgServiceLevel": 100, + "avgLatency": 761, + "avgSuccessRate": 100, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "js-code-interpreter.p.rapidapi.com", + "api_list": [ + { + "name": "Run Code", + "url": "https://js-code-interpreter.p.rapidapi.com/", + "description": "- Import `npm` packeges using esm.sh with `import` syntax\n`import axios from \"https://esm.sh/axios\";`\n- Define `export default` function for response \n`export default () => \"Hello World\";`", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://js-code-interpreter.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"js-code-interpreter.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://js-code-interpreter.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"js-code-interpreter.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/json_gpt.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/json_gpt.json new file mode 100644 index 0000000000000000000000000000000000000000..6a843975950324dcebeb5ea4890d30a99b17d845 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/json_gpt.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_f6efa909-e43d-43ba-8803-64382fe87984", + "tool_description": "Generates JSON data from GPT-3", + "home_url": "https://rapidapi.com/ethanhasbrouck02/api/json-gpt1/", + "name": "JSON-GPT", + "title": "JSON-GPT", + "pricing": "FREEMIUM", + "tool_name": "JSON-GPT", + "score": null, + "host": "json-gpt1.p.rapidapi.com", + "api_list": [ + { + "name": "API Link", + "url": "https://json-gpt1.p.rapidapi.com/api", + "description": "API Endpoint", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://json-gpt1.p.rapidapi.com/api\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"json-gpt1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://json-gpt1.p.rapidapi.com/api\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"json-gpt1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jsonextract_pro.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jsonextract_pro.json new file mode 100644 index 0000000000000000000000000000000000000000..a58c3dae6ff439df2b042e674038ff803483eb4e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/jsonextract_pro.json @@ -0,0 +1,26 @@ +{ + "product_id": "api_039d0354-3e55-4c92-a90c-fa41e9d4d3d1", + "tool_description": "Effortlessly extract custom tokens from text and convert them to JSON with this AI-powered data extraction tool.", + "home_url": "https://rapidapi.com/igor.olshevsky.work/api/jsonextract-pro/", + "name": "JSONExtract Pro", + "title": "JSONExtract Pro", + "pricing": "FREEMIUM", + "tool_name": "JSONExtract Pro", + "score": null, + "host": "jsonextract-pro.p.rapidapi.com", + "api_list": [ + { + "name": "/extract", + "url": "https://jsonextract-pro.p.rapidapi.com/api/v1/extract", + "description": "This endpoint seamlessly processes incoming text alongside an array of specified entities, extracting their data, and efficiently returns the results in JSON format for seamless integration into your applications. Checkout API Docs \ud83d\udc47", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://jsonextract-pro.p.rapidapi.com/api/v1/extract\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"jsonextract-pro.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://jsonextract-pro.p.rapidapi.com/api/v1/extract\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"jsonextract-pro.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/keyword_clustering.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/keyword_clustering.json new file mode 100644 index 0000000000000000000000000000000000000000..ba807e5b2e7e66613a8a144b11fca6e57300dbb8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/keyword_clustering.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_5127d930-e114-4b53-8ab1-da7b98985e62", + "tool_description": "Unsuprevised Keyword Clustering With Embeddings powered by OpenAI", + "home_url": "https://rapidapi.com/api-ind-api-ind-default/api/keyword-clustering2/", + "name": "Keyword Clustering", + "title": "Keyword Clustering", + "pricing": "FREEMIUM", + "tool_name": "Keyword Clustering", + "score": null, + "host": "keyword-clustering2.p.rapidapi.com", + "api_list": [ + { + "name": "Unsupervised Keyword Clustering", + "url": "https://keyword-clustering2.p.rapidapi.com/keywords", + "description": "# Unsupervised Keyword Clustering\nIs a RESTful API that clusters a list of keywords based on a threshold value. The API takes a list of keywords and a threshold value as inputs and returns a list of clusters, where each cluster contains keywords that are similar to each other based on their semantic meaning.\n\nHow to use\nRequest\nThe API accepts POST requests with the following parameters:\n\n- keywords (required): a list of keywords, up to 100 in length\n- threshold (required): a float between 0 and 2, indicating the threshold value for clustering", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://keyword-clustering2.p.rapidapi.com/keywords\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"keyword-clustering2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://keyword-clustering2.p.rapidapi.com/keywords\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"keyword-clustering2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_text.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_text.json new file mode 100644 index 0000000000000000000000000000000000000000..9e309aae6d7cf47eb0139f04ae423465cc9cf173 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_text.json @@ -0,0 +1,105 @@ +{ + "product_id": "api_280a683b-cbf8-4d7c-b56a-3e4dbab12865", + "tool_description": "Unlock the power of natural language processing with our comprehensive Kirin Text API, offering a diverse range of cutting-edge AI modules for public use.", + "home_url": "https://rapidapi.com/wisesight-wisesight-default/api/kirin-text1/", + "name": "KIRIN Text", + "title": "KIRIN Text", + "pricing": "FREEMIUM", + "tool_name": "KIRIN Text", + "score": null, + "host": "kirin-text1.p.rapidapi.com", + "api_list": [ + { + "name": "Named-Entity Recognition", + "url": "https://kirin-text1.p.rapidapi.com/ner", + "description": "Named-Entity Recognition will automatically identify and categorize specific entities, such as names of people, organizations, locations, and other relevant information, within a given text or dataset.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-text1.p.rapidapi.com/ner\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-text1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-text1.p.rapidapi.com/ner\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-text1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "result": { + "type": "object", + "properties": { + "preprocessed_text": { + "type": "string" + }, + "entities": { + "type": "array", + "items": { + "type": "object", + "properties": { + "entity": { + "type": "string" + }, + "start_index": { + "type": "number" + }, + "end_index": { + "type": "number" + }, + "label": { + "type": "string" + } + }, + "required": [ + "entity", + "start_index", + "end_index", + "label" + ] + } + } + }, + "required": [ + "preprocessed_text", + "entities" + ] + } + } + }, + { + "name": "Sentiment Analysis", + "url": "https://kirin-text1.p.rapidapi.com/sentiment", + "description": "Sentiment Analysis will automatically analyze and interpret the emotions and opinions expressed in text, providing invaluable insights into customer feedback, social media trends, and market perceptions.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-text1.p.rapidapi.com/sentiment\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-text1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-text1.p.rapidapi.com/sentiment\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-text1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "result": { + "type": "object", + "properties": { + "sentiments": { + "type": "array", + "items": { + "type": "object", + "properties": { + "polarity": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "polarity", + "confidence" + ] + } + } + }, + "required": [ + "sentiments" + ] + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_vision.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_vision.json new file mode 100644 index 0000000000000000000000000000000000000000..d2bbcbb72040b4126e6926fffc5bc206ae340092 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/kirin_vision.json @@ -0,0 +1,317 @@ +{ + "product_id": "api_bcb00f41-aa87-4fcc-ae89-09638fe34d35", + "tool_description": "Unlock the power of computer vision with our comprehensive Kirin Vision API, offering a diverse range of cutting-edge AI modules for public use.", + "home_url": "https://rapidapi.com/wisesight-wisesight-default/api/kirin-vision1/", + "name": "KIRIN Vision", + "title": "KIRIN Vision", + "pricing": "FREEMIUM", + "tool_name": "KIRIN Vision", + "score": { + "avgServiceLevel": 99, + "avgLatency": 1942, + "avgSuccessRate": 96, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "kirin-vision1.p.rapidapi.com", + "api_list": [ + { + "name": "Scene Recognition", + "url": "https://kirin-vision1.p.rapidapi.com/scene", + "description": "Scene Recognition enables computers to accurately identify and understand the content of images or videos, making it possible to categorize and interpret various real-world environments.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/scene\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/scene\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "$schema": "http://json-schema.org/draft-04/schema#", + "type": "object", + "properties": { + "result": { + "type": "object", + "properties": { + "scenes": { + "type": "array", + "items": [ + { + "type": "object", + "properties": { + "scene": { + "type": "string" + }, + "environment": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "scene", + "environment", + "confidence" + ] + }, + { + "type": "object", + "properties": { + "scene": { + "type": "string" + }, + "environment": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "scene", + "environment", + "confidence" + ] + }, + { + "type": "object", + "properties": { + "scene": { + "type": "string" + }, + "environment": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "scene", + "environment", + "confidence" + ] + }, + { + "type": "object", + "properties": { + "scene": { + "type": "string" + }, + "environment": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "scene", + "environment", + "confidence" + ] + }, + { + "type": "object", + "properties": { + "scene": { + "type": "string" + }, + "environment": { + "type": "string" + }, + "confidence": { + "type": "number" + } + }, + "required": [ + "scene", + "environment", + "confidence" + ] + } + ] + } + }, + "required": [ + "scenes" + ] + } + }, + "required": [ + "result" + ] + } + }, + { + "name": "Optical Character Recognition", + "url": "https://kirin-vision1.p.rapidapi.com/ocr", + "description": "Optical Character Recognition converts scanned images or images containing text into editable and searchable digital text.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/ocr\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/ocr\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "result": { + "type": "object", + "properties": { + "blocks": { + "type": "array", + "items": { + "type": "object", + "properties": { + "bounding_box": { + "type": "array", + "items": { + "type": "integer" + } + }, + "text": { + "type": "string" + } + } + } + }, + "text": { + "type": "string" + } + } + } + } + } + }, + { + "name": "Object Detection", + "url": "https://kirin-vision1.p.rapidapi.com/object", + "description": "Object Detection enables computers to identify and locate multiple objects within images or videos.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/object\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/object\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "result": { + "type": "object", + "properties": { + "blocks": { + "type": "array", + "items": { + "type": "object", + "properties": { + "bounding_box": { + "type": "array", + "items": { + "type": "integer" + } + }, + "object": { + "type": "string" + }, + "confidence": { + "type": "number" + } + } + } + }, + "objects": { + "type": "array", + "items": { + "type": "string" + } + } + } + } + } + } + }, + { + "name": "Logo Recognition", + "url": "https://kirin-vision1.p.rapidapi.com/logo", + "description": "The Logo Recognition module empowers your applications with the ability to identify logos and brands within images.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/logo\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://kirin-vision1.p.rapidapi.com/logo\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"kirin-vision1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "result": { + "type": "object", + "properties": { + "blocks": { + "type": "array", + "items": { + "type": "object", + "properties": { + "bounding_box": { + "type": "array", + "items": { + "type": "integer" + } + }, + "detection_confidence": { + "type": "number" + }, + "recognition_distance": { + "type": "number" + }, + "logo": { + "type": "string" + } + } + } + }, + "logo": { + "type": "array", + "items": { + "type": "string" + } + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/language_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/language_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..57fcd1fa243c54f845580d17b0d2a576377f9178 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/language_detection.json @@ -0,0 +1,84 @@ +{ + "product_id": "api_8a50ae01-8d27-4543-ac9d-7bcc369b4a3b", + "tool_description": "Language Detection API supporting 9 different languages.", + "home_url": "https://rapidapi.com/ytspamshield/api/language-detection18/", + "name": "Language Detection", + "title": "Language Detection", + "pricing": "FREEMIUM", + "tool_name": "Language Detection", + "score": null, + "host": "language-detection18.p.rapidapi.com", + "api_list": [ + { + "name": "specific-classify", + "url": "https://language-detection18.p.rapidapi.com/classify/{language}", + "description": "returns details about the text language detection\n", + "method": "POST", + "required_parameters": [ + { + "name": "language", + "type": "STRING", + "description": "desired language", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://language-detection18.p.rapidapi.com/classify/{language}\"\nquerystring = {\"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"language-detection18.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://language-detection18.p.rapidapi.com/classify/{language}\"\nquerystring = {\"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"language-detection18.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "id": { + "type": "string" + }, + "requested_at": { + "type": "string" + }, + "text": { + "type": "string" + }, + "language": { + "type": "string" + }, + "accuracy": { + "type": "number" + } + } + } + }, + { + "name": "classify", + "url": "https://language-detection18.p.rapidapi.com/classify", + "description": "returns details about the text language detection\n", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://language-detection18.p.rapidapi.com/classify\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"language-detection18.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://language-detection18.p.rapidapi.com/classify\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"language-detection18.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "id": { + "type": "string" + }, + "requested_at": { + "type": "string" + }, + "text": { + "type": "string" + }, + "language": { + "type": "string" + }, + "accuracy": { + "type": "number" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech.json new file mode 100644 index 0000000000000000000000000000000000000000..04d15d56343908e723d0f60ec73623a151f4dfbc --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech.json @@ -0,0 +1,61 @@ +{ + "tool_name": "Large text to speech", + "tool_description": "Large text to speech (TTS) API enables you to perform unlimited* text to speech synthesis (English) in single request. With human like voice quality! Read more in About section.", + "title": "Large text to speech", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 99, + "avgLatency": 980, + "avgSuccessRate": 96, + "popularityScore": 9.8, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/k_1/api/large-text-to-speech/", + "host": "large-text-to-speech.p.rapidapi.com", + "api_list": [ + { + "name": "Create TTS job", + "url": "https://large-text-to-speech.p.rapidapi.com/tts", + "description": "Request for text to speech job", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://large-text-to-speech.p.rapidapi.com/tts\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"large-text-to-speech.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Get job status", + "url": "https://large-text-to-speech.p.rapidapi.com/tts", + "description": "Get the status and results of a job", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "STRING", + "description": "", + "default": "5425b1c0-357b-47cf-a06c-69c5260ea890" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://large-text-to-speech.p.rapidapi.com/tts\"\nquerystring = {\"id\": id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"large-text-to-speech.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Create TTS job", + "url": "https://large-text-to-speech.p.rapidapi.com/tts", + "description": "Request for text to speech job", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://large-text-to-speech.p.rapidapi.com/tts\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"large-text-to-speech.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://large-text-to-speech.p.rapidapi.com/tts\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"large-text-to-speech.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech/api.py new file mode 100644 index 0000000000000000000000000000000000000000..404ee4e414963e04e7f1bedfb7eaafd946dc23e2 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/large_text_to_speech/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_job_status(is_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get the status and results of a job" + + """ + url = f"https://large-text-to-speech.p.rapidapi.com/tts" + querystring = {'id': is_id, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "large-text-to-speech.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot.json new file mode 100644 index 0000000000000000000000000000000000000000..81fa579d97b2b609465f463c7e76605c1fafa875 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot.json @@ -0,0 +1,2164 @@ +{ + "product_id": "api_a4bf6e83-9c49-4ae3-abf4-f7846653fb5c", + "tool_description": "Meet Lemurbot - Your Personal AI Chatbot Companion! With advanced features like creating, training and chatting, Lemurbot makes it easy and fun for users to interact and learn from an intelligent conversationalist. Plus, with ChatGPT integration and the ability to create multiple bots, the possibilities for learning and entertainment are endless!", + "home_url": "https://rapidapi.com/lemur-engine-lemur-engine-default/api/lemurbot/", + "name": "LemurBot", + "title": "LemurBot", + "pricing": "FREEMIUM", + "tool_name": "LemurBot", + "score": { + "avgServiceLevel": 87, + "avgLatency": 3644, + "avgSuccessRate": 80, + "popularityScore": 9.2, + "__typename": "Score" + }, + "host": "lemurbot.p.rapidapi.com", + "api_list": [ + { + "name": "Get A Category Group", + "url": "https://lemurbot.p.rapidapi.com/category-groups/{id}", + "description": "Get a specific category group by it's id and view it's details.\nYou are able to view your own category groups and locked category groups.\n'Locked' category groups are a master set of records available to link to your bots", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of CategoryGroup", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "success": false, + "message": "Record not found." + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "Get A Category", + "url": "https://lemurbot.p.rapidapi.com/categories/{id}", + "description": "Get a specific category by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of Category", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "success": false, + "message": "Record not found." + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "Get A Bot Property", + "url": "https://lemurbot.p.rapidapi.com/bot-properties/{id}", + "description": "Get a specific bot property by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of BotProperty", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "List All Bot Properties", + "url": "https://lemurbot.p.rapidapi.com/bot-properties", + "description": "Get a list of bot properties that belong to bots created by the user (not locked bots).", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "value", + "type": "STRING", + "description": "Value of the bot propery - this will perform a partial search", + "default": "" + }, + { + "name": "name", + "type": "STRING", + "description": "Name of the bot propery", + "default": "name" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the bot property", + "default": "" + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "bot_id", + "type": "NUMBER", + "description": "bot_id of the bot property", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "bot", + "type": "STRING", + "description": "Bot slug of the bot", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties\"\nquerystring = {\"limit\": 20, \"value\": \"\", \"name\": \"name\", \"page\": 1, \"id\": \"\", \"order\": \"id\", \"bot_id\": \"\", \"dir\": \"asc\", \"bot\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties\"\nquerystring = {\"limit\": 20, \"value\": \"\", \"name\": \"name\", \"page\": 1, \"id\": \"\", \"order\": \"id\", \"bot_id\": \"\", \"dir\": \"asc\", \"bot\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "bot_id", + "name", + "value" + ], + "properties": { + "id": { + "description": "The id of the bot property", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "name": { + "description": "The field name of the bot property", + "type": "string", + "maxLength": 100 + }, + "value": { + "description": "The value of the bot property", + "type": "string", + "maxLength": 255 + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "List All Bots", + "url": "https://lemurbot.p.rapidapi.com/bots", + "description": "Get a list of bots that are available to this user.\nThese will either be bots created by the user or 'locked' public bots which can be chatted to but not editted. (e.g. 1)", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of Bot", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "slug", + "type": "STRING", + "description": "Slug of the bot (e.g. dilly)", + "default": "" + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "locked", + "type": "BOOLEAN", + "description": "search for bots which are locked or bots which are not locked (e.g. false)", + "default": false + }, + { + "name": "title", + "type": "STRING", + "description": "Title of the bot (e.g. Dilly)", + "default": "" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "description", + "type": "STRING", + "description": "Perform a partial search on the description of the bot (e.g. demo bot)", + "default": "" + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots\"\nquerystring = {\"id\": \"\", \"dir\": \"asc\", \"slug\": \"\", \"order\": \"id\", \"locked\": false, \"title\": \"\", \"page\": 1, \"description\": \"\", \"limit\": 20}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots\"\nquerystring = {\"id\": \"\", \"dir\": \"asc\", \"slug\": \"\", \"order\": \"id\", \"locked\": false, \"title\": \"\", \"page\": 1, \"description\": \"\", \"limit\": 20}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "title", + "summary", + "default_response", + "image" + ], + "properties": { + "id": { + "description": "The id of the bot", + "type": "integer" + }, + "slug": { + "description": "This is a unique string used to identify the bot", + "type": "string" + }, + "title": { + "description": "This is the title of the bot (the bot's actual name is set in the bot properties)", + "type": "string", + "maxLength": 50 + }, + "summary": { + "description": "A summary of the bot", + "type": "string", + "maxLength": 75 + }, + "description": { + "description": "A description of the bot", + "type": [ + "string", + "null" + ], + "maxLength": 2056 + }, + "default_response": { + "description": "If everything fails then this is the default response the bot will return", + "type": "string", + "maxLength": 255 + }, + "image": { + "description": "A url of the avatar used for this bot (we only use images from api.dicebear.com). If a image isnt specified one will be created automatically", + "type": "string", + "format": "url", + "maxLength": 255, + "pattern": "~(.*)api\\.dicebear\\.com(.*)~" + }, + "locked": { + "description": "Locked bots are example bots that anyone can talk to but you cannot update, delete or access logs", + "type": "boolean" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get A Bot", + "url": "https://lemurbot.p.rapidapi.com/bots/1", + "description": "Get a specific bot by its id. (e.g. 1)", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of Bot", + "default": 1 + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots/1\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots/{id}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "List All Category Groups", + "url": "https://lemurbot.p.rapidapi.com/category-groups", + "description": "Categories are organised into category groups. For example if you have a set of categories to handle questions on the weather these could be grouped into a category group called 'weather-categories'.\nYou are able to view your own category groups and locked category groups.\n'Locked' category groups are a master set of records available to link to your bots", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "locked", + "type": "BOOLEAN", + "description": "Locked category groups can be linked to bot so that you can access their knowledge categories but you cannot cannot update, delete or access this group or it's categories", + "default": "" + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "name", + "type": "STRING", + "description": "the name of the category group - this search is a partial search", + "default": "hello" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the category group", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "slug", + "type": "STRING", + "description": "the slug of the category group - this search is an exact search", + "default": "hello" + }, + { + "name": "description", + "type": "STRING", + "description": "the description of the category group - this search is a partial search", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups\"\nquerystring = {\"locked\": \"\", \"order\": \"id\", \"name\": \"hello\", \"page\": 1, \"id\": \"\", \"dir\": \"asc\", \"limit\": 20, \"slug\": \"hello\", \"description\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups\"\nquerystring = {\"locked\": \"\", \"order\": \"id\", \"name\": \"hello\", \"page\": 1, \"id\": \"\", \"dir\": \"asc\", \"limit\": 20, \"slug\": \"hello\", \"description\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "name", + "description" + ], + "properties": { + "id": { + "description": "The id of the category group", + "type": "integer" + }, + "slug": { + "description": "This is a unique string used to identify the category group - this is automatically generated", + "type": "string" + }, + "name": { + "description": "The name of the category group", + "type": "string", + "maxLength": 255, + "minLength": 40 + }, + "description": { + "description": "The description of the categories contained in this group", + "type": "string", + "maxLength": 2056, + "minLength": 5 + }, + "locked": { + "description": "Locked category groups cannot be editted by users but they can be linked to bots", + "type": "boolean" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "List All Clients", + "url": "https://lemurbot.p.rapidapi.com/clients", + "description": "Clients talk to bots. This return a list of all clients that have spoken your bots. Clients can talk to your bots or the locked bots.\n'Locked' bots are a set of public bots available to link to your clients in addition to bots you create.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "slug", + "type": "STRING", + "description": "The slug of the client", + "default": "" + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the client", + "default": "" + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "is_banned", + "type": "BOOLEAN", + "description": "The banned status of this client", + "default": "name" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients\"\nquerystring = {\"order\": \"id\", \"slug\": \"\", \"id\": \"\", \"limit\": 20, \"dir\": \"asc\", \"page\": 1, \"is_banned\": \"name\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients\"\nquerystring = {\"order\": \"id\", \"slug\": \"\", \"id\": \"\", \"limit\": 20, \"dir\": \"asc\", \"page\": 1, \"is_banned\": \"name\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "properties": { + "id": { + "description": "The id of the client", + "type": "integer" + }, + "slug": { + "description": "This is a string used to identify the client - if one is not created by the user then it is automatically generated - we suggest generating your own uuid", + "type": "string", + "maxLength": 36, + "minLength": 5 + }, + "is_banned": { + "description": "Prevent further conversations between this client and the bot by setting is_banned to true", + "type": "boolean" + }, + "image": { + "description": "The image is automatically generated by getting a url from api.dicebear.com. The avatar selected correspnds to the one chosen for the linked bot", + "type": "string" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get A Bot Category Group", + "url": "https://lemurbot.p.rapidapi.com/bot-category-groups/{id}", + "description": "Get a specific bot category group by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of BotCategoryGroup", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "properties": { + "id": { + "description": "The id of the bot category group", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "category_group_id": { + "description": "The id of the category group", + "type": "integer" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get A Client", + "url": "https://lemurbot.p.rapidapi.com/clients/{id}", + "description": "Get a specific client by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of Client", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "List All Bot Category Groups", + "url": "https://lemurbot.p.rapidapi.com/bot-category-groups", + "description": "Get a list of category groups which are linked to user owned bots (not locked bots).", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "category_group", + "type": "STRING", + "description": "Category group slug of the category group in the bot category group", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the bot category group", + "default": "" + }, + { + "name": "bot", + "type": "STRING", + "description": "Bot slug of the bot in the bot category group", + "default": "" + }, + { + "name": "category_group_id", + "type": "NUMBER", + "description": "category_group_id of the category group", + "default": "" + }, + { + "name": "bot_id", + "type": "NUMBER", + "description": "bot_id of the bot category group", + "default": "" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups\"\nquerystring = {\"category_group\": \"\", \"dir\": \"asc\", \"limit\": 20, \"order\": \"id\", \"id\": \"\", \"bot\": \"\", \"category_group_id\": \"\", \"bot_id\": \"\", \"page\": 1}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups\"\nquerystring = {\"category_group\": \"\", \"dir\": \"asc\", \"limit\": 20, \"order\": \"id\", \"id\": \"\", \"bot\": \"\", \"category_group_id\": \"\", \"bot_id\": \"\", \"page\": 1}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "properties": { + "id": { + "description": "The id of the bot category group", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "category_group_id": { + "description": "The id of the category group", + "type": "integer" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "List All Categories", + "url": "https://lemurbot.p.rapidapi.com/categories", + "description": "Categories are pieces of knowledge used by the bots to respond to the user.\nCreate and update categories inorder to teach and train your bot.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "category_group_id", + "type": "NUMBER", + "description": "The id of the category group", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "topic", + "type": "STRING", + "description": "The active topic of the conversation - this search is a full term search", + "default": "" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "that", + "type": "STRING", + "description": "The that is the previous bot output/response to match on - this search is a partial search", + "default": "" + }, + { + "name": "template", + "type": "STRING", + "description": "The template is the raw output that is parsed and used to generate a response - this search is a partial search", + "default": "" + }, + { + "name": "pattern", + "type": "STRING", + "description": "The pattern is the user input to match on - this search is a partial search", + "default": "test" + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the category", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories\"\nquerystring = {\"limit\": 20, \"category_group_id\": \"\", \"dir\": \"asc\", \"topic\": \"\", \"page\": 1, \"order\": \"id\", \"that\": \"\", \"template\": \"\", \"pattern\": \"test\", \"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories\"\nquerystring = {\"limit\": 20, \"category_group_id\": \"\", \"dir\": \"asc\", \"topic\": \"\", \"page\": 1, \"order\": \"id\", \"that\": \"\", \"template\": \"\", \"pattern\": \"test\", \"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "category_group_id", + "pattern", + "template" + ], + "properties": { + "id": { + "description": "The id of the category", + "type": "integer" + }, + "category_group_id": { + "description": "The id of the category group", + "type": "integer" + }, + "pattern": { + "description": "The category pattern is used to match the client input message", + "type": "string", + "maxLength": 255 + }, + "topic": { + "description": "Topics can be set and the category will only be triggered if the category topic is matched to current topic", + "type": [ + "string", + "null" + ], + "maxLength": 255 + }, + "that": { + "description": "This is the previous response returned by the bot. Only use the 'that' field to add context.", + "type": [ + "string", + "null" + ], + "maxLength": 255 + }, + "template": { + "description": "Templates are parsed to generated bot responses. Categories use the AIML stamdard.", + "type": "string", + "maxLength": 4112 + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get A Conversation", + "url": "https://lemurbot.p.rapidapi.com/conversations/{id}", + "description": "Get a specific conversation by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of Conversation", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversations/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversations/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "required": [ + "bot_id", + "client_id" + ], + "properties": { + "id": { + "description": "The id of the conversation", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "client_id": { + "description": "The id of the client", + "type": "integer" + }, + "turn_count": { + "description": "The number of turns in this conversation", + "type": [ + "integer", + "null" + ] + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "List All Conversations", + "url": "https://lemurbot.p.rapidapi.com/conversations", + "description": "Conversations are created between clients and bots.\nUsers can only view conversations between their clients and bots.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + }, + { + "name": "bot", + "type": "STRING", + "description": "The bot slug of the conversation - conversation are linked to bots", + "default": "" + }, + { + "name": "client", + "type": "STRING", + "description": "The client slug of the conversation - conversation are linked to clients", + "default": "" + }, + { + "name": "bot_id", + "type": "NUMBER", + "description": "The bot_id of the conversation - conversation are linked to bots", + "default": "" + }, + { + "name": "client_id", + "type": "NUMBER", + "description": "The client_id of the conversation - conversation are linked to clients", + "default": "" + }, + { + "name": "slug", + "type": "STRING", + "description": "The slug of the conversation", + "default": "" + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the conversation", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversations\"\nquerystring = {\"page\": 1, \"limit\": 20, \"order\": \"id\", \"bot\": \"\", \"client\": \"\", \"bot_id\": \"\", \"client_id\": \"\", \"slug\": \"\", \"id\": \"\", \"dir\": \"asc\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversations\"\nquerystring = {\"page\": 1, \"limit\": 20, \"order\": \"id\", \"bot\": \"\", \"client\": \"\", \"bot_id\": \"\", \"client_id\": \"\", \"slug\": \"\", \"id\": \"\", \"dir\": \"asc\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "bot_id", + "client_id" + ], + "properties": { + "id": { + "description": "The id of the conversation", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "client_id": { + "description": "The id of the client", + "type": "integer" + }, + "turn_count": { + "description": "The number of turns in this conversation", + "type": [ + "integer", + "null" + ] + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + } + }, + "type": "object" + } + }, + { + "name": "List All Conversation Turns", + "url": "https://lemurbot.p.rapidapi.com/conversation-turns", + "description": "Each conversation has conversation turns.\nEach turn represents an input from the client and the output from the bot.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + }, + { + "name": "conversation", + "type": "STRING", + "description": "The slug of the conversation - conversation are linked to conversation turns", + "default": "" + }, + { + "name": "conversation_id", + "type": "NUMBER", + "description": "The id of the conversation - conversation are linked to conversation turns", + "default": "" + }, + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "input", + "type": "STRING", + "description": "What was said to the bot by the client - this is a partial search", + "default": "" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "output", + "type": "STRING", + "description": "What was said by the bot in response to the client input - this is a partial search", + "default": "" + }, + { + "name": "id", + "type": "NUMBER", + "description": "The id of the conversation turn", + "default": "" + }, + { + "name": "order", + "type": "STRING", + "description": "the search field you wish to order by - the available field names are the sames ones you can search by", + "default": "id" + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversation-turns\"\nquerystring = {\"limit\": 20, \"conversation\": \"\", \"conversation_id\": \"\", \"dir\": \"asc\", \"input\": \"\", \"page\": 1, \"output\": \"\", \"id\": \"\", \"order\": \"id\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversation-turns\"\nquerystring = {\"limit\": 20, \"conversation\": \"\", \"conversation_id\": \"\", \"dir\": \"asc\", \"input\": \"\", \"page\": 1, \"output\": \"\", \"id\": \"\", \"order\": \"id\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "required": [ + "conversation_id" + ], + "properties": { + "id": { + "description": "The id of the conversation turn", + "type": "integer" + }, + "conversation_id": { + "description": "The id of the conversation", + "type": "integer" + }, + "input": { + "description": "The input from the client", + "type": "string" + }, + "output": { + "description": "The response from the bot", + "type": "string" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get A Conversation Turn", + "url": "https://lemurbot.p.rapidapi.com/conversation-turns/{id}", + "description": "Get a specific conversation turn by it's id and view it's details", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "NUMBER", + "description": "The id of ConversationTurn", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversation-turns/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/conversation-turns/{id}\"\nquerystring = {\"id\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 1, + "schema": "" + }, + { + "name": "Get Chat Detail", + "url": "https://lemurbot.p.rapidapi.com/chat/detail", + "description": "Get the details for an active chat session.\nSend a bot slug and client slug as query parameters and the request will return the details from the last active chat session.", + "method": "GET", + "required_parameters": [ + { + "name": "client", + "type": "STRING", + "description": "The slug of the client", + "default": "d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2" + }, + { + "name": "bot", + "type": "STRING", + "description": "The slug of the bot", + "default": "dilly" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat/detail\"\nquerystring = {\"client\": \"d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2\", \"bot\": \"dilly\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat/detail\"\nquerystring = {\"client\": \"d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2\", \"bot\": \"dilly\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "properties": { + "conversation": { + "properties": { + "id": { + "description": "The id of the conversation", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the conversation", + "type": "string" + } + }, + "type": "object" + }, + "bot": { + "properties": { + "id": { + "description": "The id of the bot", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the bot", + "type": "string" + }, + "name": { + "description": "The name of the bot (taken from the bot properties and if not available then the bot title)", + "type": "string" + }, + "image": { + "description": "The bot's dicebear avatar url", + "type": "string" + } + }, + "type": "object" + }, + "client": { + "properties": { + "id": { + "description": "The id of the client", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the client", + "type": "string" + }, + "image": { + "description": "The client's dicebear avatar url", + "type": "string" + }, + "is_banned": { + "description": "The client's banned status", + "type": "boolean" + } + }, + "type": "object" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Get Chat Log", + "url": "https://lemurbot.p.rapidapi.com/chat/log", + "description": "Get the logs for an active chat session.\nSend a bot slug and client slug as query parameters and the request will return the logs from the last active chat session.", + "method": "GET", + "required_parameters": [ + { + "name": "client", + "type": "STRING", + "description": "The slug of the client", + "default": "d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2" + }, + { + "name": "bot", + "type": "STRING", + "description": "The slug of the bot", + "default": "dilly" + } + ], + "optional_parameters": [ + { + "name": "dir", + "type": "STRING", + "description": "the direction of the ordering", + "default": "asc" + }, + { + "name": "page", + "type": "NUMBER", + "description": "the page number of results to start from", + "default": 1 + }, + { + "name": "limit", + "type": "NUMBER", + "description": "the number of records to return", + "default": 20 + } + ], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat/log\"\nquerystring = {\"client\": \"d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2\", \"dir\": \"asc\", \"page\": 1, \"bot\": \"dilly\", \"limit\": 20}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat/log\"\nquerystring = {\"client\": \"d531e3bd-b6c3-4f3f-bb58-a6632cbed5e2\", \"dir\": \"asc\", \"page\": 1, \"bot\": \"dilly\", \"limit\": 20}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "You have exceeded the rate limit per second for your plan, BASIC, by the API provider" + }, + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "properties": { + "client": { + "description": "The input from the client", + "type": "string" + }, + "bot": { + "description": "The output from the bot", + "type": "string" + } + }, + "type": "object" + } + }, + "paging": { + "properties": { + "records": { + "description": "The number of records returned in the request", + "type": [ + "integer", + "null" + ] + }, + "total": { + "description": "The total number of records available", + "type": [ + "integer", + "null" + ] + }, + "page": { + "description": "The current page number", + "type": [ + "integer", + "null" + ], + "default": 1 + }, + "limit": { + "description": "The number of records to return", + "type": [ + "integer", + "null" + ], + "default": 20 + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Create A Category", + "url": "https://lemurbot.p.rapidapi.com/categories", + "description": "Create a category.\nCategories are units of knowledge, when a category is created, it can be linked to a bot via it's category group.\nThen the bot will be able respond to inputs using this category.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/categories\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "required": [ + "category_group_id", + "pattern", + "template" + ], + "properties": { + "id": { + "description": "The id of the category", + "type": "integer" + }, + "category_group_id": { + "description": "The id of the category group", + "type": "integer" + }, + "pattern": { + "description": "The category pattern is used to match the client input message", + "type": "string", + "maxLength": 255 + }, + "topic": { + "description": "Topics can be set and the category will only be triggered if the category topic is matched to current topic", + "type": [ + "string", + "null" + ], + "maxLength": 255 + }, + "that": { + "description": "This is the previous response returned by the bot. Only use the 'that' field to add context.", + "type": [ + "string", + "null" + ], + "maxLength": 255 + }, + "template": { + "description": "Templates are parsed to generated bot responses. Categories use the AIML stamdard.", + "type": "string", + "maxLength": 4112 + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Create A Bot Property", + "url": "https://lemurbot.p.rapidapi.com/bot-properties", + "description": "Create a property for any bot created by the user (not locked bots).", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-properties\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "required": [ + "bot_id", + "name", + "value" + ], + "properties": { + "id": { + "description": "The id of the bot property", + "type": "integer" + }, + "bot_id": { + "description": "The id of the bot", + "type": "integer" + }, + "name": { + "description": "The field name of the bot property", + "type": "string", + "maxLength": 100 + }, + "value": { + "description": "The value of the bot property", + "type": "string", + "maxLength": 255 + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Create A Bot", + "url": "https://lemurbot.p.rapidapi.com/bots", + "description": "Create your own bot\nNew bots will be created with a random personality and the title will be copied to the bot properties name.\nIt will also be linked to a default set of category groups.\nAt the moment the images used are automatically selected from the dicebear api.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bots\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Create A Category Group", + "url": "https://lemurbot.p.rapidapi.com/category-groups", + "description": "Category groups control access between a bot and categories.\nCreate a category group, then add some new categories to it and finally link your bot the group.\nNow your bot will be able to access the knowledge categories you have created for it.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/category-groups\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "required": [ + "name", + "description" + ], + "properties": { + "id": { + "description": "The id of the category group", + "type": "integer" + }, + "slug": { + "description": "This is a unique string used to identify the category group - this is automatically generated", + "type": "string" + }, + "name": { + "description": "The name of the category group", + "type": "string", + "maxLength": 255, + "minLength": 40 + }, + "description": { + "description": "The description of the categories contained in this group", + "type": "string", + "maxLength": 2056, + "minLength": 5 + }, + "locked": { + "description": "Locked category groups cannot be editted by users but they can be linked to bots", + "type": "boolean" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Create A Client", + "url": "https://lemurbot.p.rapidapi.com/clients", + "description": "It is not required to send a payload in the client request as one will be created automatically.\nBut by choosing your own 'slug' you can better identify the people talking to your bot.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/clients\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "properties": { + "id": { + "description": "The id of the client", + "type": "integer" + }, + "slug": { + "description": "This is a string used to identify the client - if one is not created by the user then it is automatically generated - we suggest generating your own uuid", + "type": "string", + "maxLength": 36, + "minLength": 5 + }, + "is_banned": { + "description": "Prevent further conversations between this client and the bot by setting is_banned to true", + "type": "boolean" + }, + "image": { + "description": "The image is automatically generated by getting a url from api.dicebear.com. The avatar selected correspnds to the one chosen for the linked bot", + "type": "string" + }, + "created_at": { + "description": "The date time the record was created", + "type": "string", + "format": "date-time" + }, + "updated_at": { + "description": "The date time the record was last updated", + "type": "string", + "format": "date-time" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Create A Bot Category Group", + "url": "https://lemurbot.p.rapidapi.com/bot-category-groups", + "description": "When you create a link between a bot and a category group the bot can now access and use the categories in this group", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/bot-category-groups\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Chat To A Bot", + "url": "https://lemurbot.p.rapidapi.com/chat", + "description": "Send a message from a client to a bot and the bot will respond with an output.\nIt is not required to set up client in order to start a conversation as one will be created automatically using the client slug you send in the 'chat' request.\nBut by choosing your own 'slug' you can better identify the people chatting to your bot.\nTo carry on a conversation between the client and the bot - make sure you send the same client slug in subsequent chats.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lemurbot.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lemurbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "success": { + "type": "boolean" + }, + "data": { + "properties": { + "conversation": { + "properties": { + "id": { + "description": "The id of the conversation", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the conversation", + "type": "string" + }, + "input": { + "description": "The client input sent to the bot", + "type": "string" + }, + "output": { + "description": "The bot response sent back", + "type": "string" + }, + "topic": { + "description": "The active topic (if there is one)", + "type": [ + "string", + "null" + ] + } + }, + "type": "object" + }, + "bot": { + "properties": { + "id": { + "description": "The id of the bot", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the bot", + "type": "string" + }, + "name": { + "description": "The name of the bot (taken from the bot properties and if not available then the bot title)", + "type": "string" + }, + "image": { + "description": "The bot's dicebear avatar url", + "type": "string" + } + }, + "type": "object" + }, + "client": { + "properties": { + "id": { + "description": "The id of the client", + "type": "integer" + }, + "slug": { + "description": "The unique string id of the client", + "type": "string" + }, + "image": { + "description": "The client's dicebear avatar url", + "type": "string" + }, + "is_banned": { + "description": "The client's banned status", + "type": "boolean" + } + }, + "type": "object" + }, + "features": { + "description": "Any additional features of the conversation are sent here - this will normally be empty", + "type": "object" + }, + "metadata": { + "properties": { + "version": { + "description": "The version of the engine used.", + "type": "string" + }, + "date": { + "description": "The date time of the request", + "type": "string", + "format": "date-time" + }, + "duration": { + "description": "Time taken to process requests in milliseconds", + "type": "integer" + } + }, + "type": "object" + } + }, + "type": "object" + }, + "message": { + "type": "string" + } + }, + "type": "object" + } + } + ], + "standardized_name": "lemurbot" +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot/api.py new file mode 100644 index 0000000000000000000000000000000000000000..51fbec5f2a3bcd27e4163259b93557eb242dc08b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lemurbot/api.py @@ -0,0 +1,634 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_a_category_group(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific category group by it's id and view it's details. + You are able to view your own category groups and locked category groups. + 'Locked' category groups are a master set of records available to link to your bots" + id: The id of CategoryGroup + + """ + url = f"https://lemurbot.p.rapidapi.com/category-groups/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_category(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific category by it's id and view it's details" + id: The id of Category + + """ + url = f"https://lemurbot.p.rapidapi.com/categories/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_bot_property(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific bot property by it's id and view it's details" + id: The id of BotProperty + + """ + url = f"https://lemurbot.p.rapidapi.com/bot-properties/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_bot_properties(limit: int=20, value: str=None, name: str='name', page: int=1, is_id: int=None, order: str='id', bot_id: int=None, dir: str='asc', bot: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a list of bot properties that belong to bots created by the user (not locked bots)." + limit: the number of records to return + value: Value of the bot propery - this will perform a partial search + name: Name of the bot propery + page: the page number of results to start from + is_id: The id of the bot property + order: the search field you wish to order by - the available field names are the sames ones you can search by + bot_id: bot_id of the bot property + dir: the direction of the ordering + bot: Bot slug of the bot + + """ + url = f"https://lemurbot.p.rapidapi.com/bot-properties" + querystring = {} + if limit: + querystring['limit'] = limit + if value: + querystring['value'] = value + if name: + querystring['name'] = name + if page: + querystring['page'] = page + if is_id: + querystring['id'] = is_id + if order: + querystring['order'] = order + if bot_id: + querystring['bot_id'] = bot_id + if dir: + querystring['dir'] = dir + if bot: + querystring['bot'] = bot + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_bots(is_id: int=None, dir: str='asc', slug: str=None, order: str='id', locked: bool=None, title: str=None, page: int=1, description: str=None, limit: int=20, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a list of bots that are available to this user. + These will either be bots created by the user or 'locked' public bots which can be chatted to but not editted. (e.g. 1)" + is_id: The id of Bot + dir: the direction of the ordering + slug: Slug of the bot (e.g. dilly) + order: the search field you wish to order by - the available field names are the sames ones you can search by + locked: search for bots which are locked or bots which are not locked (e.g. false) + title: Title of the bot (e.g. Dilly) + page: the page number of results to start from + description: Perform a partial search on the description of the bot (e.g. demo bot) + limit: the number of records to return + + """ + url = f"https://lemurbot.p.rapidapi.com/bots" + querystring = {} + if is_id: + querystring['id'] = is_id + if dir: + querystring['dir'] = dir + if slug: + querystring['slug'] = slug + if order: + querystring['order'] = order + if locked: + querystring['locked'] = locked + if title: + querystring['title'] = title + if page: + querystring['page'] = page + if description: + querystring['description'] = description + if limit: + querystring['limit'] = limit + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_bot(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific bot by its id. (e.g. 1)" + id: The id of Bot + + """ + url = f"https://lemurbot.p.rapidapi.com/bots/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_category_groups(locked: bool=None, order: str='id', name: str='hello', page: int=1, is_id: int=None, dir: str='asc', limit: int=20, slug: str='hello', description: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Categories are organised into category groups. For example if you have a set of categories to handle questions on the weather these could be grouped into a category group called 'weather-categories'. + You are able to view your own category groups and locked category groups. + 'Locked' category groups are a master set of records available to link to your bots" + locked: Locked category groups can be linked to bot so that you can access their knowledge categories but you cannot cannot update, delete or access this group or it's categories + order: the search field you wish to order by - the available field names are the sames ones you can search by + name: the name of the category group - this search is a partial search + page: the page number of results to start from + is_id: The id of the category group + dir: the direction of the ordering + limit: the number of records to return + slug: the slug of the category group - this search is an exact search + description: the description of the category group - this search is a partial search + + """ + url = f"https://lemurbot.p.rapidapi.com/category-groups" + querystring = {} + if locked: + querystring['locked'] = locked + if order: + querystring['order'] = order + if name: + querystring['name'] = name + if page: + querystring['page'] = page + if is_id: + querystring['id'] = is_id + if dir: + querystring['dir'] = dir + if limit: + querystring['limit'] = limit + if slug: + querystring['slug'] = slug + if description: + querystring['description'] = description + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_clients(order: str='id', slug: str=None, is_id: int=None, limit: int=20, dir: str='asc', page: int=1, is_banned: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Clients talk to bots. This return a list of all clients that have spoken your bots. Clients can talk to your bots or the locked bots. + 'Locked' bots are a set of public bots available to link to your clients in addition to bots you create." + order: the search field you wish to order by - the available field names are the sames ones you can search by + slug: The slug of the client + is_id: The id of the client + limit: the number of records to return + dir: the direction of the ordering + page: the page number of results to start from + is_banned: The banned status of this client + + """ + url = f"https://lemurbot.p.rapidapi.com/clients" + querystring = {} + if order: + querystring['order'] = order + if slug: + querystring['slug'] = slug + if is_id: + querystring['id'] = is_id + if limit: + querystring['limit'] = limit + if dir: + querystring['dir'] = dir + if page: + querystring['page'] = page + if is_banned: + querystring['is_banned'] = is_banned + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_bot_category_group(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific bot category group by it's id and view it's details" + id: The id of BotCategoryGroup + + """ + url = f"https://lemurbot.p.rapidapi.com/bot-category-groups/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_client(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific client by it's id and view it's details" + id: The id of Client + + """ + url = f"https://lemurbot.p.rapidapi.com/clients/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_bot_category_groups(category_group: str=None, dir: str='asc', limit: int=20, order: str='id', is_id: int=None, bot: str=None, category_group_id: int=None, bot_id: int=None, page: int=1, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a list of category groups which are linked to user owned bots (not locked bots)." + category_group: Category group slug of the category group in the bot category group + dir: the direction of the ordering + limit: the number of records to return + order: the search field you wish to order by - the available field names are the sames ones you can search by + is_id: The id of the bot category group + bot: Bot slug of the bot in the bot category group + category_group_id: category_group_id of the category group + bot_id: bot_id of the bot category group + page: the page number of results to start from + + """ + url = f"https://lemurbot.p.rapidapi.com/bot-category-groups" + querystring = {} + if category_group: + querystring['category_group'] = category_group + if dir: + querystring['dir'] = dir + if limit: + querystring['limit'] = limit + if order: + querystring['order'] = order + if is_id: + querystring['id'] = is_id + if bot: + querystring['bot'] = bot + if category_group_id: + querystring['category_group_id'] = category_group_id + if bot_id: + querystring['bot_id'] = bot_id + if page: + querystring['page'] = page + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_categories(limit: int=20, category_group_id: int=None, dir: str='asc', topic: str=None, page: int=1, order: str='id', that: str=None, template: str=None, pattern: str='test', is_id: int=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Categories are pieces of knowledge used by the bots to respond to the user. + Create and update categories inorder to teach and train your bot." + limit: the number of records to return + category_group_id: The id of the category group + dir: the direction of the ordering + topic: The active topic of the conversation - this search is a full term search + page: the page number of results to start from + order: the search field you wish to order by - the available field names are the sames ones you can search by + that: The that is the previous bot output/response to match on - this search is a partial search + template: The template is the raw output that is parsed and used to generate a response - this search is a partial search + pattern: The pattern is the user input to match on - this search is a partial search + is_id: The id of the category + + """ + url = f"https://lemurbot.p.rapidapi.com/categories" + querystring = {} + if limit: + querystring['limit'] = limit + if category_group_id: + querystring['category_group_id'] = category_group_id + if dir: + querystring['dir'] = dir + if topic: + querystring['topic'] = topic + if page: + querystring['page'] = page + if order: + querystring['order'] = order + if that: + querystring['that'] = that + if template: + querystring['template'] = template + if pattern: + querystring['pattern'] = pattern + if is_id: + querystring['id'] = is_id + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_conversation(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific conversation by it's id and view it's details" + id: The id of Conversation + + """ + url = f"https://lemurbot.p.rapidapi.com/conversations/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_conversations(page: int=1, limit: int=20, order: str='id', bot: str=None, client: str=None, bot_id: int=None, client_id: int=None, slug: str=None, is_id: int=None, dir: str='asc', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Conversations are created between clients and bots. + Users can only view conversations between their clients and bots." + page: the page number of results to start from + limit: the number of records to return + order: the search field you wish to order by - the available field names are the sames ones you can search by + bot: The bot slug of the conversation - conversation are linked to bots + client: The client slug of the conversation - conversation are linked to clients + bot_id: The bot_id of the conversation - conversation are linked to bots + client_id: The client_id of the conversation - conversation are linked to clients + slug: The slug of the conversation + is_id: The id of the conversation + dir: the direction of the ordering + + """ + url = f"https://lemurbot.p.rapidapi.com/conversations" + querystring = {} + if page: + querystring['page'] = page + if limit: + querystring['limit'] = limit + if order: + querystring['order'] = order + if bot: + querystring['bot'] = bot + if client: + querystring['client'] = client + if bot_id: + querystring['bot_id'] = bot_id + if client_id: + querystring['client_id'] = client_id + if slug: + querystring['slug'] = slug + if is_id: + querystring['id'] = is_id + if dir: + querystring['dir'] = dir + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def list_all_conversation_turns(limit: int=20, conversation: str=None, conversation_id: int=None, dir: str='asc', input: str=None, page: int=1, output: str=None, is_id: int=None, order: str='id', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Each conversation has conversation turns. + Each turn represents an input from the client and the output from the bot." + limit: the number of records to return + conversation: The slug of the conversation - conversation are linked to conversation turns + conversation_id: The id of the conversation - conversation are linked to conversation turns + dir: the direction of the ordering + input: What was said to the bot by the client - this is a partial search + page: the page number of results to start from + output: What was said by the bot in response to the client input - this is a partial search + is_id: The id of the conversation turn + order: the search field you wish to order by - the available field names are the sames ones you can search by + + """ + url = f"https://lemurbot.p.rapidapi.com/conversation-turns" + querystring = {} + if limit: + querystring['limit'] = limit + if conversation: + querystring['conversation'] = conversation + if conversation_id: + querystring['conversation_id'] = conversation_id + if dir: + querystring['dir'] = dir + if input: + querystring['input'] = input + if page: + querystring['page'] = page + if output: + querystring['output'] = output + if is_id: + querystring['id'] = is_id + if order: + querystring['order'] = order + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_a_conversation_turn(is_id: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a specific conversation turn by it's id and view it's details" + id: The id of ConversationTurn + + """ + url = f"https://lemurbot.p.rapidapi.com/conversation-turns/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_chat_detail(client: str, bot: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get the details for an active chat session. + Send a bot slug and client slug as query parameters and the request will return the details from the last active chat session." + client: The slug of the client + bot: The slug of the bot + + """ + url = f"https://lemurbot.p.rapidapi.com/chat/detail" + querystring = {'client': client, 'bot': bot, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_chat_log(client: str, bot: str, dir: str='asc', page: int=1, limit: int=20, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get the logs for an active chat session. + Send a bot slug and client slug as query parameters and the request will return the logs from the last active chat session." + client: The slug of the client + bot: The slug of the bot + dir: the direction of the ordering + page: the page number of results to start from + limit: the number of records to return + + """ + url = f"https://lemurbot.p.rapidapi.com/chat/log" + querystring = {'client': client, 'bot': bot, } + if dir: + querystring['dir'] = dir + if page: + querystring['page'] = page + if limit: + querystring['limit'] = limit + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lemurbot.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api.json new file mode 100644 index 0000000000000000000000000000000000000000..1a9c5d27c7829bddc1e198bb803a0875ffb82fa4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api.json @@ -0,0 +1,100 @@ +{ + "tool_name": "LexAI API", + "tool_description": "Images analyser API for multi-label object detection and classification!", + "title": "LexAI API", + "pricing": "FREEMIUM", + "score": null, + "home_url": "https://rapidapi.com/peter.kemenczky/api/lexai-api/", + "host": "lexai-api.p.rapidapi.com", + "api_list": [ + { + "name": "show_detected_data", + "url": "https://lexai-api.p.rapidapi.com/detection_results", + "description": "This API request allows you to detect bounding boxes on an image and retrieve the results in a structured dictionary format. You can provide the image either by specifying a URL or by uploading a file. The API will process the image and return a dictionary containing information about the detected bounding boxes. Each bounding box entry in the dictionary includes details such as the coordinates, label, and confidence score.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/detection_results\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "show_detections", + "url": "https://lexai-api.p.rapidapi.com/show_detections", + "description": "This API request allows you to detect and visualize bounding boxes on an image. You can provide the image either by specifying a URL or by uploading a file. The API will process the image and return a new image with the detected bounding boxes drawn on it.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/show_detections\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "get_classes", + "url": "https://lexai-api.p.rapidapi.com/get_classes", + "description": "Get available detection classes", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/get_classes\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "show_detected_data", + "url": "https://lexai-api.p.rapidapi.com/detection_results", + "description": "This API request allows you to detect bounding boxes on an image and retrieve the results in a structured dictionary format. You can provide the image either by specifying a URL or by uploading a file. The API will process the image and return a dictionary containing information about the detected bounding boxes. Each bounding box entry in the dictionary includes details such as the coordinates, label, and confidence score.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/detection_results\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/detection_results\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "show_detections", + "url": "https://lexai-api.p.rapidapi.com/show_detections", + "description": "This API request allows you to detect and visualize bounding boxes on an image. You can provide the image either by specifying a URL or by uploading a file. The API will process the image and return a new image with the detected bounding boxes drawn on it.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/show_detections\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lexai-api.p.rapidapi.com/show_detections\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lexai-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..cd09f617a3ce0a32f05928e956fdbbb631965712 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lexai_api/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_classes(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get available detection classes" + + """ + url = f"https://lexai-api.p.rapidapi.com/get_classes" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "lexai-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/llmocr_document_extraction.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/llmocr_document_extraction.json new file mode 100644 index 0000000000000000000000000000000000000000..4a071f757dca60276021782f122f217e6f153f35 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/llmocr_document_extraction.json @@ -0,0 +1,39 @@ +{ + "product_id": "api_9ffd3f09-f5fd-4d4d-aacf-1ec5feee0516", + "tool_description": "Extract account and transactions data from bank account statements with 99.9% accuracy", + "home_url": "https://rapidapi.com/planmytrippro-planmytrippro-default/api/llm-ocr-document-extraction/", + "name": "LLM/OCR - Document Extraction", + "title": "LLM/OCR - Document Extraction", + "pricing": "PAID", + "tool_name": "LLM/OCR - Document Extraction", + "score": { + "avgServiceLevel": 100, + "avgLatency": 14304, + "avgSuccessRate": 100, + "popularityScore": 8.6, + "__typename": "Score" + }, + "host": "llm-ocr-document-extraction.p.rapidapi.com", + "api_list": [ + { + "name": "banking_ocr_bank_post", + "url": "https://llm-ocr-document-extraction.p.rapidapi.com/ocr/bank", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://llm-ocr-document-extraction.p.rapidapi.com/ocr/bank\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"llm-ocr-document-extraction.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://llm-ocr-document-extraction.p.rapidapi.com/ocr/bank\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"llm-ocr-document-extraction.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_document_qa.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_document_qa.json new file mode 100644 index 0000000000000000000000000000000000000000..af7f8812f8144a111b1c4775c8d512deea950ef2 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_document_qa.json @@ -0,0 +1,45 @@ +{ + "product_id": "api_3435c781-f626-4ca2-a9f9-12e9e55bc724", + "tool_description": "Document (pdf and image) Question Answering endpoint", + "home_url": "https://rapidapi.com/josuebrunel/api/lokingai-document-qa/", + "name": "LokingAI-Document-QA", + "title": "LokingAI-Document-QA", + "pricing": "FREEMIUM", + "tool_name": "LokingAI-Document-QA", + "score": { + "avgServiceLevel": 50, + "avgLatency": 3828, + "avgSuccessRate": 50, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "lokingai-document-qa.p.rapidapi.com", + "api_list": [ + { + "name": "answer_questions_answer_questions_post", + "url": "https://lokingai-document-qa.p.rapidapi.com/answer-questions", + "description": "Answer questions based on an uploaded document.\n\nThis endpoint takes an uploaded document file and a list of questions. It processes the document\nto find answers to the questions.\n\nParameters:\n- **payload**: The uploaded document file.\n- **questions**: A comma-separated list of questions.\n\nReturns:\n- **DocumentQuestionAnswerResponse**: A response containing answers to the questions.\n\nExample Request:\n```\nPOST /answer-questions\nContent-Type: multipart/form-data\nBody: \nForm Data: questions=Question1,Question2,Question3\n```\n\nExample Response:\n```\n{\n \"data\": [\n {\n \"question\": \"Question1\",\n \"answer\": \"Answer1\",\n \"score\": 0.85,\n \"start\": 10,\n \"end\": 20\n },\n {\n \"question\": \"Question2\",\n \"answer\": \"Answer2\",\n \"score\": 0.75,\n \"start\": 30,\n \"end\": 40\n },\n {\n \"question\": \"Question3\",\n \"answer\": \"Answer3\",\n \"score\": 0.92,\n \"start\": 50,\n \"end\": 60\n }\n ]\n}\n```", + "method": "POST", + "required_parameters": [ + { + "name": "questions", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "payload", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-document-qa.p.rapidapi.com/answer-questions\"\nquerystring = {\"questions\": \"\", \"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-document-qa.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-document-qa.p.rapidapi.com/answer-questions\"\nquerystring = {\"questions\": \"\", \"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-document-qa.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_image.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_image.json new file mode 100644 index 0000000000000000000000000000000000000000..274bd451a15f7df865284964c06091e54b6fa23b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_image.json @@ -0,0 +1,177 @@ +{ + "product_id": "api_07ab9b7b-5dd8-4327-8866-9eb84c56f263", + "tool_description": "AI Image processing APIs providing functionalities such as image classification, object detection and image segmentation", + "home_url": "https://rapidapi.com/josuebrunel/api/lokingai-image/", + "name": "LokingAI-Image", + "title": "LokingAI-Image", + "pricing": "FREEMIUM", + "tool_name": "LokingAI-Image", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3761, + "avgSuccessRate": 100, + "popularityScore": 8.9, + "__typename": "Score" + }, + "host": "lokingai-image.p.rapidapi.com", + "api_list": [ + { + "name": "detect_object_detect_object_post", + "url": "https://lokingai-image.p.rapidapi.com/detect-object", + "description": "Object detection.\n\nDetect objects in an uploaded image.\n\nParameters:\n- **payload**: The uploaded image file.\n\nReturns:\n- **DetectObjectResponse**: A response containing object detection results for the uploaded image.\n\nExample Response:\n```\n{\n \"data\": [\n {\"score\": 0.85, \"label\": \"cat\", \"box\": {\"xmin\": 0.1, \"ymin\": 0.2, \"xmax\": 0.9, \"ymax\": 0.8}},\n {\"score\": 0.73, \"label\": \"dog\", \"box\": {\"xmin\": 0.2, \"ymin\": 0.3, \"xmax\": 0.8, \"ymax\": 0.7}}\n ]\n}\n```", + "method": "POST", + "required_parameters": [ + { + "name": "payload", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/detect-object\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/detect-object\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "error": { + "type": "string", + "title": "Error" + }, + "data": { + "items": { + "properties": { + "score": { + "type": "number", + "title": "Score" + }, + "label": { + "type": "string", + "title": "Label" + }, + "box": { + "properties": { + "xmin": { + "type": "number", + "title": "Xmin" + }, + "ymin": { + "type": "number", + "title": "Ymin" + }, + "xmax": { + "type": "number", + "title": "Xmax" + }, + "ymax": { + "type": "number", + "title": "Ymax" + } + }, + "type": "object", + "required": [ + "xmin", + "ymin", + "xmax", + "ymax" + ], + "title": "Box" + } + }, + "type": "object", + "required": [ + "score", + "label", + "box" + ], + "title": "ObjectDectionOutput" + }, + "type": "array", + "title": "Data" + } + }, + "type": "object", + "required": [ + "data" + ], + "title": "DetectObjectResponse" + } + }, + { + "name": "segment_segment_post", + "url": "https://lokingai-image.p.rapidapi.com/segment", + "description": "Image segmentation.\n\nSegment an uploaded image into different regions.\n\nParameters:\n- **payload**: The uploaded image file.\n\nReturns:\n- **SegmentResponse**: A response containing image segmentation results for the uploaded image.\n\nExample Response:\n```\n{\n \"data\": [\n {\"label\": \"sky\", \"image\": \"base64_encoded_image\"},\n {\"label\": \"tree\", \"image\": \"base64_encoded_image\"}\n ]\n}\n```", + "method": "POST", + "required_parameters": [ + { + "name": "payload", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/segment\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/segment\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "error": { + "type": "string", + "title": "Error" + }, + "data": { + "items": { + "properties": { + "label": { + "type": "string", + "title": "Label" + }, + "image": { + "type": "string", + "format": "binary", + "title": "Image" + } + }, + "type": "object", + "required": [ + "label", + "image" + ], + "title": "SegmentOutput" + }, + "type": "array", + "title": "Data" + } + }, + "type": "object", + "required": [ + "data" + ], + "title": "SegmentResponse" + } + }, + { + "name": "classify_classify_post", + "url": "https://lokingai-image.p.rapidapi.com/classify", + "description": "Image classification.\n\nClassify an uploaded image using an image classification model.\n\nParameters:\n- **payload**: The uploaded image file.\n\nReturns:\n- **ClassifyResponse**: A response containing classification results for the uploaded image.\n\nExample Response:\n```\n{\n \"data\": [\n {\"score\": 0.85, \"label\": \"cat\"},\n {\"score\": 0.73, \"label\": \"dog\"}\n ]\n}\n```", + "method": "POST", + "required_parameters": [ + { + "name": "payload", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/classify\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-image.p.rapidapi.com/classify\"\nquerystring = {\"payload\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-image.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_text.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_text.json new file mode 100644 index 0000000000000000000000000000000000000000..694ae7d616c84f6425ecc02e0449e0f33e3c585a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/lokingai_text.json @@ -0,0 +1,203 @@ +{ + "product_id": "api_71cbcc18-2aab-4148-910d-d7f5da2ad81a", + "tool_description": "APIs collectively providing functionalities such as classification, sentiment analysis, summarization, question answering, labeling, and mask filling for various text processing tasks. They allow users to extract meaningful information from text data and perform different types of analyses and transformations.", + "home_url": "https://rapidapi.com/josuebrunel/api/lokingai-text/", + "name": "LokingAI-Text", + "title": "LokingAI-Text", + "pricing": "FREEMIUM", + "tool_name": "LokingAI-Text", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1206, + "avgSuccessRate": 50, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "lokingai-text.p.rapidapi.com", + "api_list": [ + { + "name": "mask_filler_mask_filler_post", + "url": "https://lokingai-text.p.rapidapi.com/mask-filler", + "description": "Mask filling.\n\nFill in masked values in the input text.\n\nParameters:\n- **payload**: TextRequest object containing the input text with masked values.\n\nReturns:\n- **MaskFillerResponse**: A response containing the filled-in masked values.\n\nExample Request:\n```\nPOST /mask-filler\n{\n \"text\": \"Please buy [MASK] from the store.\"\n}\n```\n\nExample Response:\n```\n{\n \"error\": null,\n \"data\": [\n {\n \"score\": 0.17938034236431122,\n \"token\": 2505,\n \"token_str\": \"anything\",\n \"sequence\": \"please buy anything from this store\"\n },\n {\n \"score\": 0.11332187056541443,\n \"token\": 2242,\n \"token_str\": \"something\",\n \"sequence\": \"please buy something from this store\"\n },\n {\n \"score\": 0.05946308374404907,\n \"token\": 3688,\n \"token_str\": \"products\",\n \"sequence\": \"please buy products from this store\"\n },\n {\n \"score\": 0.04591205716133118,\n \"token\": 5167,\n \"token_str\": \"items\",\n \"sequence\": \"please buy items from this store\"\n },\n {\n \"score\": 0.04386703670024872,\n \"token\": 2009,\n \"token_str\": \"it\",\n \"sequence\": \"please buy it from this store\"\n }\n ]\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/mask-filler\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/mask-filler\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "question_answering_question_answering_post", + "url": "https://lokingai-text.p.rapidapi.com/question-answering", + "description": "Question answering.\n\nAnswer a list of questions based on the input text.\n\nParameters:\n- **payload**: QuestionAnswerRequest object containing the input text and list of questions.\n\nReturns:\n- **QuestionAnswerResponse**: A response containing the answers to the questions.\n\nExample Request:\n```\nPOST /question-answering\n{\n \"text\": \"The capital of France is Paris and that city has a population of 2m people\",\n \"questions\": [\"What is the capital of France?\", \"What is the population of Paris?\"]\n}\n```\n\nExample Response:\n```\n{\n \"error\": null,\n \"data\": [\n {\n \"question\": \"What is the capital of France?\",\n \"answer\": {\n \"score\": 0.9588838815689087,\n \"start\": 20,\n \"end\": 25,\n \"answer\": \"Paris\"\n }\n },\n {\n \"question\": \"What is the population of Paris?\",\n \"answer\": {\n \"score\": 0.6355919241905212,\n \"start\": 60,\n \"end\": 62,\n \"answer\": \"2m\"\n }\n }\n ]\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/question-answering\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/question-answering\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "classifier_classifier_post", + "url": "https://lokingai-text.p.rapidapi.com/classifier", + "description": "Text classification.\n\nClassify a list of texts using a text classification model.\n\nParameters:\n- **payload**: List of TextRequest objects containing the input texts.\n\nReturns:\n- **ApiResponseList**: A list of responses containing classification results for each input text.\n\nExample Request:\n```\nPOST /classifier\n[\n {\n \"text\": \"This is a positive review.\"\n },\n {\n \"text\": \"This is a negative review.\"\n }\n]\n```\n\nExample Response:\n```\n{\n \"data\": [\n {\"label\": \"positive\", \"score\": 0.85},\n {\"label\": \"negative\", \"score\": 0.73}\n ]\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/classifier\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/classifier\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "error": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Error" + }, + "data": { + "items": {}, + "type": "array", + "title": "Data" + } + }, + "type": "object", + "required": [ + "error", + "data" + ], + "title": "ApiResponseList" + } + }, + { + "name": "sentiment_analyzer_sentiment_analyzer_post", + "url": "https://lokingai-text.p.rapidapi.com/sentiment-analyzer", + "description": "Sentiment analysis.\n\nAnalyze sentiment for a list of texts.\n\nParameters:\n- **payload**: List of TextRequest objects containing the input texts.\n\nReturns:\n- **ApiResponseList**: A list of responses containing sentiment analysis results for each input text.\n\nExample Request:\n```\nPOST /sentiment-analyzer\n[\n {\n \"text\": \"I love this product!\"\n },\n {\n \"text\": \"I'm not satisfied with the service.\"\n }\n]\n```\n\nExample Response:\n```\n{\n \"error\": null,\n \"data\": [\n {\n \"label\": \"love\",\n \"score\": 0.9471527338027954\n },\n {\n \"label\": \"disapproval\",\n \"score\": 0.6938314437866211\n }\n ]\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/sentiment-analyzer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/sentiment-analyzer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "error": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Error" + }, + "data": { + "items": {}, + "type": "array", + "title": "Data" + } + }, + "type": "object", + "required": [ + "error", + "data" + ], + "title": "ApiResponseList" + } + }, + { + "name": "summarizer_summarizer_post", + "url": "https://lokingai-text.p.rapidapi.com/summarizer", + "description": "Text summarization.\n\nSummarize the input text.\n\nParameters:\n- **payload**: TextRequest object containing the input text.\n\nReturns:\n- **ApiResponse**: A response containing the summarized text.\n\nExample Request:\n```\nPOST /summarizer\n{\n \"text\": \"This is a long piece of text...\"\n}\n```\n\nExample Response:\n```\n{\n \"data\": {\n \"summary_text\": \"This is a summarized version of the input text...\"\n }\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/summarizer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/summarizer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "labelizer_labelizer_post", + "url": "https://lokingai-text.p.rapidapi.com/labelizer", + "description": "Text labeling.\n\nLabel the input text with specified labels.\n\nParameters:\n- **payload**: LabelRequest object containing the input text and list of labels.\n\nReturns:\n- **LabelResponse**: A response containing the labeled text and label scores.\n\nExample Request:\n```\nPOST /labelizer\n{\n \"text\": \"This is an example sentence.\",\n \"labels\": [\"positive\", \"negative\"]\n}\n```\n\nExample Response:\n```\n{\n \"data\": {\n \"sequence\": \"This is an example sentence.\",\n \"labels\": [\"positive\", \"neutral\"],\n \"scores\": [0.75, 0.2]\n }\n}\n```", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "multi_label", + "type": null, + "description": "", + "default": true + } + ], + "code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/labelizer\"\nquerystring = {\"multi_label\": true}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://lokingai-text.p.rapidapi.com/labelizer\"\nquerystring = {\"multi_label\": true}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"lokingai-text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "properties": { + "error": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Error" + }, + "data": { + "properties": { + "sequence": { + "type": "string", + "title": "Sequence" + }, + "labels": { + "items": { + "type": "string" + }, + "type": "array", + "title": "Labels" + }, + "scores": { + "items": { + "type": "number" + }, + "type": "array", + "title": "Scores" + } + }, + "type": "object", + "required": [ + "sequence", + "labels", + "scores" + ], + "title": "LabelOutput" + } + }, + "type": "object", + "required": [ + "error", + "data" + ], + "title": "LabelResponse" + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_4_0_8k_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_4_0_8k_api.json new file mode 100644 index 0000000000000000000000000000000000000000..c977e09061b23f9100ac634fdd0c7d6afd8c4178 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_4_0_8k_api.json @@ -0,0 +1,54 @@ +{ + "product_id": "api_ec856a81-fa36-4c62-8e80-a27b38123a73", + "tool_description": "Supercharge your AI-powered applications with our optimized proxy API, leveraging the cutting-edge power of GPT 4.0 with an impressive token limit of 8000. Our feature-rich API provides an array of advanced capabilities, including rate limiting, caching, error handling, analytics integration, extensive language support, flexible preprocessing options, customizable settings, and highly insightful outputs. With our API, you'll unlock the true potential of GPT 4.0, enabling seamless integration ...", + "home_url": "https://rapidapi.com/mxn2020/api/mad-gpt-4-0-8k-api/", + "name": "Mad GPT 4.0 8K API", + "title": "Mad GPT 4.0 8K API", + "pricing": "FREEMIUM", + "tool_name": "Mad GPT 4.0 8K API", + "score": { + "avgServiceLevel": 0, + "avgLatency": 172, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "mad-gpt-4-0-8k-api.p.rapidapi.com", + "api_list": [ + { + "name": "Chat Completion with GPT-4.0 at 8K", + "url": "https://mad-gpt-4-0-8k-api.p.rapidapi.com/chat-completion-gpt40-8k", + "description": "Performs chat completion using OpenAI GPT-4.0 with up to 8K tokens based on user input messages", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-4-0-8k-api.p.rapidapi.com/chat-completion-gpt40-8k\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-4-0-8k-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-4-0-8k-api.p.rapidapi.com/chat-completion-gpt40-8k\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-4-0-8k-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "messages": { + "type": "array", + "items": { + "type": "object", + "properties": { + "role": { + "type": "string" + }, + "content": { + "type": "string" + } + }, + "required": [ + "role", + "content" + ] + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api.json new file mode 100644 index 0000000000000000000000000000000000000000..35648787e26863a37546cc0fbae535f406c8cbab --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api.json @@ -0,0 +1,434 @@ +{ + "tool_name": "Mad GPT Api", + "tool_description": "Enhance your AI-powered applications with a feature-rich proxy API powered by the latest GPT 3.5, offering rate limiting, caching, error handling, analytics, language support, preprocessing options, customization, and insightful outputs.", + "title": "Mad GPT Api", + "pricing": "FREEMIUM", + "score": null, + "home_url": "https://rapidapi.com/mxn2020/api/mad-gpt-api/", + "host": "mad-gpt-api.p.rapidapi.com", + "api_list": [ + { + "name": "Translations", + "url": "https://mad-gpt-api.p.rapidapi.com/translate", + "description": "Translates text into the specified target language", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/translate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Auto Complete", + "url": "https://mad-gpt-api.p.rapidapi.com/autocomplete", + "description": "Returns autocomplete suggestions based on the input text", + "method": "GET", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "The input text for autocomplete", + "default": "Program" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/autocomplete\"\nquerystring = {\"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Chat Completion", + "url": "https://mad-gpt-api.p.rapidapi.com/chat-completion", + "description": "Performs chat completion using OpenAI GPT-3.5 based on user input messages", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "messages": [ + { + "role": "", + "content": "" + } + ] + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "messages": { + "type": "array", + "items": { + "type": "object", + "properties": { + "role": { + "type": "string" + }, + "content": { + "type": "string" + } + }, + "required": [ + "role", + "content" + ] + } + } + } + } + }, + { + "name": "Chat Request", + "url": "https://mad-gpt-api.p.rapidapi.com/chat-request", + "description": "Sends a chat request and receives a response", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-request\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Summary Creation", + "url": "https://mad-gpt-api.p.rapidapi.com/summary", + "description": "Summarizes text using GPT based on the provided document", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/summary\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Code Generator", + "url": "https://mad-gpt-api.p.rapidapi.com/generate-code", + "description": "Generates code using OpenAI API based on the provided prompt and input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate-code\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Answer", + "url": "https://mad-gpt-api.p.rapidapi.com/answer", + "description": "Answers a question using GPT based on user input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/answer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Text Generation", + "url": "https://mad-gpt-api.p.rapidapi.com/generate", + "description": "Generates text using GPT based on user input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Analyze Sentiment", + "url": "https://mad-gpt-api.p.rapidapi.com/analyze-sentiment", + "description": "Analyzes the sentiment of text using GPT", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/analyze-sentiment\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "response": "" + }, + "headers": {}, + "schema": { + "properties": { + "response": { + "type": "string" + } + }, + "type": "object" + } + }, + { + "name": "Named Entity Recognition", + "url": "https://mad-gpt-api.p.rapidapi.com/named-entity-recognition", + "description": "Extracts named entities from the given text and returns them in a JSON object", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/named-entity-recognition\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "entities": [ + { + "text": "", + "type": "" + } + ] + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "entities": { + "type": "array", + "items": { + "type": "object", + "properties": { + "text": { + "type": "string" + }, + "type": { + "type": "string" + } + } + } + } + } + } + }, + { + "name": "Translations", + "url": "https://mad-gpt-api.p.rapidapi.com/translate", + "description": "Translates text into the specified target language", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/translate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/translate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Chat Completion", + "url": "https://mad-gpt-api.p.rapidapi.com/chat-completion", + "description": "Performs chat completion using OpenAI GPT-3.5 based on user input messages", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "messages": { + "type": "array", + "items": { + "type": "object", + "properties": { + "role": { + "type": "string" + }, + "content": { + "type": "string" + } + }, + "required": [ + "role", + "content" + ] + } + } + } + } + }, + { + "name": "Chat Request", + "url": "https://mad-gpt-api.p.rapidapi.com/chat-request", + "description": "Sends a chat request and receives a response", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-request\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/chat-request\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Summary Creation", + "url": "https://mad-gpt-api.p.rapidapi.com/summary", + "description": "Summarizes text using GPT based on the provided document", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/summary\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/summary\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Code Generator", + "url": "https://mad-gpt-api.p.rapidapi.com/generate-code", + "description": "Generates code using OpenAI API based on the provided prompt and input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate-code\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate-code\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "response": { + "type": "string" + } + } + } + }, + { + "name": "Answer", + "url": "https://mad-gpt-api.p.rapidapi.com/answer", + "description": "Answers a question using GPT based on user input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/answer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/answer\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Text Generation", + "url": "https://mad-gpt-api.p.rapidapi.com/generate", + "description": "Generates text using GPT based on user input", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Analyze Sentiment", + "url": "https://mad-gpt-api.p.rapidapi.com/analyze-sentiment", + "description": "Analyzes the sentiment of text using GPT", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/analyze-sentiment\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/analyze-sentiment\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Named Entity Recognition", + "url": "https://mad-gpt-api.p.rapidapi.com/named-entity-recognition", + "description": "Extracts named entities from the given text and returns them in a JSON object", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/named-entity-recognition\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mad-gpt-api.p.rapidapi.com/named-entity-recognition\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mad-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..6f219b0e8992f79bd0dacae31a89c62dfde64660 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mad_gpt_api/api.py @@ -0,0 +1,30 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def auto_complete(text: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns autocomplete suggestions based on the input text" + text: The input text for autocomplete + + """ + url = f"https://mad-gpt-api.p.rapidapi.com/autocomplete" + querystring = {'text': text, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "mad-gpt-api.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/magicsafe_sentiment_analysis.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/magicsafe_sentiment_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..5d236c7040c56c78950cecd4888048efb05af626 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/magicsafe_sentiment_analysis.json @@ -0,0 +1,54 @@ +{ + "product_id": "api_c979f832-30ec-4f0c-bc79-400a9f795eff", + "tool_description": "A clever and easy sentiment analysis for your apps", + "home_url": "https://rapidapi.com/gourabmahalikadarsh/api/magicsafe-sentiment-analysis/", + "name": "Magicsafe Sentiment Analysis", + "title": "Magicsafe Sentiment Analysis", + "pricing": "FREEMIUM", + "tool_name": "Magicsafe Sentiment Analysis", + "score": null, + "host": "magicsafe-sentiment-analysis.p.rapidapi.com", + "api_list": [ + { + "name": "sentiment_analysis_sentiment_analysis__post", + "url": "https://magicsafe-sentiment-analysis.p.rapidapi.com/sentiment-analysis/", + "description": "Perform sentiment analysis on a piece of text.\n\nParameters\n----------\nrequest : SentimentRequest\n The request body containing the text to analyze.\n\nReturns\n-------\nSentimentResponse\n A response model with the following keys:\n\n * `overall_sentiment`: The sentiment of the text, either \"positive\", \"negative\", or \"neutral\".\n * `positive_words`: A list of positive words found in the text.\n * `negative_words`: A list of negative words found in the text.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://magicsafe-sentiment-analysis.p.rapidapi.com/sentiment-analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"magicsafe-sentiment-analysis.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://magicsafe-sentiment-analysis.p.rapidapi.com/sentiment-analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"magicsafe-sentiment-analysis.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "title": "SentimentResponse", + "required": [ + "overall_sentiment", + "positive_words", + "negative_words" + ], + "type": "object", + "properties": { + "overall_sentiment": { + "title": "Overall Sentiment", + "type": "string" + }, + "positive_words": { + "title": "Positive Words", + "type": "array", + "items": { + "type": "string" + } + }, + "negative_words": { + "title": "Negative Words", + "type": "array", + "items": { + "type": "string" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline.json new file mode 100644 index 0000000000000000000000000000000000000000..f149d42f6b873121eea7b8c8797535d676162de1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline.json @@ -0,0 +1,31 @@ +{ + "tool_name":"Marketing Snippets and Tagline", + "tool_description":"AI generated taglines", + "title":"Marketing Snippets and Tagline", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/calvinlow/api/marketing-snippets-and-tagline/", + "host":"marketing-snippets-and-tagline.p.rapidapi.com", + "api_list":[ + { + "name":"Generate snippets and keywords", + "url":"https://marketing-snippets-and-tagline.p.rapidapi.com/generate_snippets_and_keywords", + "description":"AI generated marketing snippets and keywords", + "method":"GET", + "required_parameters":[ + { + "name":"prompt", + "type":"STRING", + "description":"", + "default":"coffee" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://marketing-snippets-and-tagline.p.rapidapi.com/generate_snippets_and_keywords\"\nquerystring = {\"prompt\": prompt}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"marketing-snippets-and-tagline.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline/api.py new file mode 100644 index 0000000000000000000000000000000000000000..a502367619aada0c3ba7bff369b7e29eb41e3672 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/marketing_snippets_and_tagline/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generate_snippets_and_keywords(prompt: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "AI generated marketing snippets and keywords" + + """ + url = f"https://marketing-snippets-and-tagline.p.rapidapi.com/generate_snippets_and_keywords" + querystring = {'prompt': prompt, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "marketing-snippets-and-tagline.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mask_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mask_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..361806de8e83b4d0c8255a628af790f5bf4dd68e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mask_detection.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_f5ce6066-104a-40dd-bc5f-0ea419ad6322", + "tool_description": "Due to the Covid19 pandemic, many establishments require people to wear masks indoors. This is done for the safety of individuals and the protection of public health. The Mask Detector model can detect if a person\u2019s face is covered up.", + "home_url": "https://rapidapi.com/smartclick-smartclick-default/api/mask-detection/", + "name": "Mask Detection", + "title": "Mask Detection", + "pricing": "FREEMIUM", + "tool_name": "Mask Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1245, + "avgSuccessRate": 50, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "mask-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Mask detection from image", + "url": "https://mask-detection.p.rapidapi.com/mask-detection", + "description": "![](https://cdn.smclk.net/img/Mask-Detection.png)\nFor more details [contact us](https://smartclick.ai/contact/)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mask-detection.p.rapidapi.com/mask-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mask-detection.p.rapidapi.com/mask-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mask-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker.json new file mode 100644 index 0000000000000000000000000000000000000000..b08984c258d561dbf98af8ad889b2f9f7b9016cc --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker.json @@ -0,0 +1,271 @@ +{ + "tool_name":"MaskMaker", + "tool_description":"Convenient Mask Layer Image Generation - Beta\nThis API generates image mask layers for use in conjunction with AI image editing tools, such as, but not limited to openai DALL·E 2. ", + "title":"MaskMaker", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/owaspboi/api/maskmaker/", + "host":"maskmaker.p.rapidapi.com", + "api_list":[ + { + "name":"grid", + "url":"https://maskmaker.p.rapidapi.com/grid", + "description":"Random grids: Generate random grids of transparent squares or rectangles with varying sizes and transparency.\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/grid\"\nquerystring = {\"height\": height, \"width\": width}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"cellular automata", + "url":"https://maskmaker.p.rapidapi.com/cellularautomata", + "description":"Cellular automata: Use cellular automata to generate a pattern of transparent and opaque cells that evolve over time.\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/cellularautomata\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"Concentric Rings", + "url":"https://maskmaker.p.rapidapi.com/conring", + "description":"Generates concentric rings\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/conring\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"scattered rings", + "url":"https://maskmaker.p.rapidapi.com/ring", + "description":"Generates scattered rings\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/ring\"\nquerystring = {\"height\": height, \"width\": width}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"circular", + "url":"https://maskmaker.p.rapidapi.com/circular", + "description":"Produces sections of varying transparency in circular sections\n\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/circular\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"hightrans", + "url":"https://maskmaker.p.rapidapi.com/hightrans", + "description":"height and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/hightrans\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"spiral", + "url":"https://maskmaker.p.rapidapi.com/spiral", + "description":"Produces sections of varying transparency in circular sections\n\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/spiral\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"random mask", + "url":"https://maskmaker.p.rapidapi.com/random", + "description":"Produces sections of varying transparency in grid-like pattern of rectangular sections\n\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/random\"\nquerystring = {\"width\": width, \"height\": height}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"random pixel", + "url":"https://maskmaker.p.rapidapi.com/randompixel", + "description":"height and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/randompixel\"\nquerystring = {\"height\": height, \"width\": width}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"random diamond", + "url":"https://maskmaker.p.rapidapi.com/diamond", + "description":"Produces sections of varying transparency in grid-like pattern of rectangular sections\n\nheight and width are required and must be a value between 1 - 10000", + "method":"GET", + "required_parameters":[ + { + "name":"height", + "type":"NUMBER", + "description":"", + "default":"256" + }, + { + "name":"width", + "type":"NUMBER", + "description":"", + "default":"256" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://maskmaker.p.rapidapi.com/diamond\"\nquerystring = {\"height\": height, \"width\": width}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"maskmaker.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker/api.py new file mode 100644 index 0000000000000000000000000000000000000000..be200fdd1ac1090e92e1226e45c6eb8c0d4a16cd --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/maskmaker/api.py @@ -0,0 +1,234 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def grid(height: int, width: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Random grids: Generate random grids of transparent squares or rectangles with varying sizes and transparency. + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/grid" + querystring = {'height': height, 'width': width, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def cellular_automata(width: int, height: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Cellular automata: Use cellular automata to generate a pattern of transparent and opaque cells that evolve over time. + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/cellularautomata" + querystring = {'width': width, 'height': height, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def concentric_rings(width: int=256, height: int=256, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generates concentric rings + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/conring" + querystring = {} + if width: + querystring['width'] = width + if height: + querystring['height'] = height + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def scattered_rings(height: int, width: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generates scattered rings + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/ring" + querystring = {'height': height, 'width': width, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def circular(width: int, height: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Produces sections of varying transparency in circular sections + + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/circular" + querystring = {'width': width, 'height': height, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def hightrans(width: int, height: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/hightrans" + querystring = {'width': width, 'height': height, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def spiral(width: int, height: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Produces sections of varying transparency in circular sections + + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/spiral" + querystring = {'width': width, 'height': height, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def random_mask(width: int, height: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Produces sections of varying transparency in grid-like pattern of rectangular sections + + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/random" + querystring = {'width': width, 'height': height, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def random_pixel(height: int, width: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/randompixel" + querystring = {'height': height, 'width': width, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def random_diamond(height: int, width: int, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Produces sections of varying transparency in grid-like pattern of rectangular sections + + height and width are required and must be a value between 1 - 10000" + + """ + url = f"https://maskmaker.p.rapidapi.com/diamond" + querystring = {'height': height, 'width': width, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "maskmaker.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary.json new file mode 100644 index 0000000000000000000000000000000000000000..97fa72983ebd32a2be49c0d742f9630cae7dbc35 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary.json @@ -0,0 +1,37 @@ +{ + "tool_name":"Medial AI Dictionary ", + "tool_description":"We have fined tuned openai model so you can get all the medical related answers, you can use this api for asking any question about medicine, medical equipments, medical terms, definitions etc", + "title":"Medial AI Dictionary ", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":0, + "avgLatency":2037, + "avgSuccessRate":0, + "popularityScore":0, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/um.waqas.khan/api/medial-ai-dictionary/", + "host":"medial-ai-dictionary.p.rapidapi.com", + "api_list":[ + { + "name":"/medical", + "url":"https://medial-ai-dictionary.p.rapidapi.com/medical", + "description":"Here you can ask any question", + "method":"GET", + "required_parameters":[ + { + "name":"question", + "type":"STRING", + "description":"", + "default":"What is cell?" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://medial-ai-dictionary.p.rapidapi.com/medical\"\nquerystring = {\"question\": question}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"medial-ai-dictionary.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary/api.py new file mode 100644 index 0000000000000000000000000000000000000000..077f6a6b6096904bf0add4c3b2f6de4593c099ac --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/medial_ai_dictionary/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def medical(question: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Here you can ask any question" + + """ + url = f"https://medial-ai-dictionary.p.rapidapi.com/medical" + querystring = {'question': question, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "medial-ai-dictionary.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io.json new file mode 100644 index 0000000000000000000000000000000000000000..57bc11d9068776a6c69a0f97287bc94e9f9a9335 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io.json @@ -0,0 +1,174 @@ +{ + "tool_name": "MessengerX.io", + "tool_description": "Chat & Earn with AI", + "title": "MessengerX.io", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 99, + "avgLatency": 6069, + "avgSuccessRate": 99, + "popularityScore": 9.5, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/buildgpt-labs-buildgpt-labs-default/api/messengerx-io/", + "host": "messengerx-io.p.rapidapi.com", + "api_list": [ + { + "name": "Get Character Details", + "url": "https://messengerx-io.p.rapidapi.com/details/{name}", + "description": "An endpoint to get basic details for a particular AI chatbot / character.", + "method": "GET", + "required_parameters": [ + { + "name": "name", + "type": "string", + "description": "", + "default": "jeanie" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/details/{name}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Search AI Library", + "url": "https://messengerx-io.p.rapidapi.com/search", + "description": "Search all publicly available AI characters", + "method": "GET", + "required_parameters": [ + { + "name": "q", + "type": "STRING", + "description": "", + "default": "jeanie" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/search\"\nquerystring = {\"q\": q}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": { + "type": "array", + "items": { + "type": "object", + "properties": { + "name": { + "type": "string" + }, + "display_name": { + "type": "string" + }, + "description": { + "type": "string" + }, + "image_url": { + "type": "string" + }, + "featured": { + "type": "boolean" + }, + "status": { + "type": "integer" + } + } + } + } + }, + { + "name": "Browse AI Library", + "url": "https://messengerx-io.p.rapidapi.com/browse", + "description": "A paginated api to browse through the publicly available AI characters", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "q", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "skip", + "type": "STRING", + "description": "", + "default": "0" + }, + { + "name": "limit", + "type": "STRING", + "description": "", + "default": "10" + } + ], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/browse\"\nquerystring = {\"skip\": skip, \"limit\": limit}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Top / Trending AI", + "url": "https://messengerx-io.p.rapidapi.com/bots/top", + "description": "Top 25 AI characters / chatbots on the platform", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/bots/top\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Send a message", + "url": "https://messengerx-io.p.rapidapi.com/process/{name}", + "description": "Send a message to any AI character available via MessengerX.io", + "method": "POST", + "required_parameters": [ + { + "name": "X-Sender-Id", + "type": "STRING", + "description": "", + "default": "test-user-1" + }, + { + "name": "name", + "type": "string", + "description": "", + "default": "jeanie" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/process/{name}\"\nquerystring = {\"X-Sender-Id\": x_sender_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Send a message", + "url": "https://messengerx-io.p.rapidapi.com/process/jeanie", + "description": "Send a message to any AI character available via MessengerX.io", + "method": "POST", + "required_parameters": [ + { + "name": "name", + "type": "string", + "description": "", + "default": "jeanie" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/process/jeanie\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://messengerx-io.p.rapidapi.com/process/{name}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"messengerx-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io/api.py new file mode 100644 index 0000000000000000000000000000000000000000..596659bd7c72e06d8ed56abaf7a6d17c3ed38101 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/messengerx_io/api.py @@ -0,0 +1,98 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_character_details(name: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "An endpoint to get basic details for a particular AI chatbot / character." + + """ + url = f"https://messengerx-io.p.rapidapi.com/details/{name}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "messengerx-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def search_ai_library(q: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search all publicly available AI characters" + + """ + url = f"https://messengerx-io.p.rapidapi.com/search" + querystring = {'q': q, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "messengerx-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def browse_ai_library(q: str=None, skip: str='0', limit: str='10', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "A paginated api to browse through the publicly available AI characters" + + """ + url = f"https://messengerx-io.p.rapidapi.com/browse" + querystring = {} + if q: + querystring['q'] = q + if skip: + querystring['skip'] = skip + if limit: + querystring['limit'] = limit + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "messengerx-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def top_trending_ai(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Top 25 AI characters / chatbots on the platform" + + """ + url = f"https://messengerx-io.p.rapidapi.com/bots/top" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "messengerx-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/meta_llama_fast_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/meta_llama_fast_api.json new file mode 100644 index 0000000000000000000000000000000000000000..b71e44966691812c4fe0bc8e715016a0c236a0fd --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/meta_llama_fast_api.json @@ -0,0 +1,41 @@ +{ + "product_id": "api_755d9cbe-376b-4796-b3dc-a62d5d0954e5", + "tool_description": "Experience the Ultimate in Conversational AI and Code Interaction with Meta Llama's Top Chat and Code API.", + "home_url": "https://rapidapi.com/serhaterfidan/api/meta-llama-fast-api/", + "name": "Meta Llama Fast API", + "title": "Meta Llama Fast API", + "pricing": "FREEMIUM", + "tool_name": "Meta Llama Fast API", + "score": { + "avgServiceLevel": 100, + "avgLatency": 4993, + "avgSuccessRate": 98, + "popularityScore": 9.5, + "__typename": "Score" + }, + "host": "meta-llama-fast-api.p.rapidapi.com", + "api_list": [ + { + "name": "Super Fast Mistral Chat", + "url": "https://meta-llama-fast-api.p.rapidapi.com/mistralchat", + "description": "Super Fast Mistral Chat prompt request", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://meta-llama-fast-api.p.rapidapi.com/mistralchat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"meta-llama-fast-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://meta-llama-fast-api.p.rapidapi.com/mistralchat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"meta-llama-fast-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Meta Llama Chat", + "url": "https://meta-llama-fast-api.p.rapidapi.com/chat", + "description": "Meta Llama Chat prompt request", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://meta-llama-fast-api.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"meta-llama-fast-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://meta-llama-fast-api.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"meta-llama-fast-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microfacts.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microfacts.json new file mode 100644 index 0000000000000000000000000000000000000000..c69a1bae010368683d2c010a15fe63cb9614a0b9 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microfacts.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_233554f4-62aa-4d4a-a2d3-7be25a19d059", + "tool_description": "OUTDATED: Please use our new API \"Entity Detection & Linking\"", + "home_url": "https://rapidapi.com/factiverse-as-factiverse-as-default/api/microfacts/", + "name": "Microfacts", + "title": "Microfacts", + "pricing": "PAID", + "tool_name": "Microfacts", + "score": null, + "host": "microfacts.p.rapidapi.com", + "api_list": [ + { + "name": "Entity detection", + "url": "https://microfacts.p.rapidapi.com/v1/microfacts", + "description": "Named entities (e.g. persons, places, organisations, etc.) are found within the given text and additional info is provided for each entity (e.g. descriptions, images, position within the text. etc.).\n\nArgs:\n - text: The text to search\n - lang: The language of the text (optional)\n\nReturns:\n - spots: The list of found entities", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://microfacts.p.rapidapi.com/v1/microfacts\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microfacts.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://microfacts.p.rapidapi.com/v1/microfacts\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microfacts.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "entity", + "url": "https://microfacts.p.rapidapi.com/v1/entity", + "description": "entity", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://microfacts.p.rapidapi.com/v1/entity\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microfacts.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://microfacts.p.rapidapi.com/v1/entity\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microfacts.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech.json new file mode 100644 index 0000000000000000000000000000000000000000..f1cfad707889cce0d50dd5e4a6c763ea3b7612d0 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech.json @@ -0,0 +1,57 @@ +{ + "tool_name":"Microsoft Edge Text to Speech", + "tool_description":"an easy-to-use API of Microsoft Edge TTS.", + "title":"Microsoft Edge Text to Speech", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":100, + "avgLatency":3283, + "avgSuccessRate":100, + "popularityScore":9.5, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/yy10112001/api/microsoft-edge-text-to-speech/", + "host":"microsoft-edge-text-to-speech.p.rapidapi.com", + "api_list":[ + { + "name":"GetVoicesList", + "url":"https://microsoft-edge-text-to-speech.p.rapidapi.com/TTS/VoicesList", + "description":"Voices list for the param \"voice_name\" of the function \"GetDownloadUrl\"", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://microsoft-edge-text-to-speech.p.rapidapi.com/TTS/VoicesList\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microsoft-edge-text-to-speech.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"GetDownloadURL", + "url":"https://microsoft-edge-text-to-speech.p.rapidapi.com/TTS/EdgeTTS", + "description":"request with a long text and get the mp3 download URL created by the TTS engine.\n\nSupporting lots of languages with different voices, such as French, Spanish, Portuguese, Japanese, Korean, Chinese, Polish, Hindi and so on\n\nparams:\ntext - STRING : the text to be transformed to speeches.\nvoice_name - STRING: the voice and language for the speeches.", + "method":"GET", + "required_parameters":[ + { + "name":"text", + "type":"STRING", + "description":"", + "default":"Are you alright?" + } + ], + "optional_parameters":[ + { + "name":"voice_name", + "type":"STRING", + "description":"", + "default":"en-US-AriaNeural" + } + ], + "code":"import requests\n\nurl = \"https://microsoft-edge-text-to-speech.p.rapidapi.com/TTS/EdgeTTS\"\nquerystring = {\"voice_name\": voice_name, \"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"microsoft-edge-text-to-speech.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech/api.py new file mode 100644 index 0000000000000000000000000000000000000000..76ed5c7cdd3b480ac7e3bae72b60e396db1b2412 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/microsoft_edge_text_to_speech/api.py @@ -0,0 +1,58 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def getvoiceslist(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Voices list for the param "voice_name" of the function "GetDownloadUrl"" + + """ + url = f"https://microsoft-edge-text-to-speech.p.rapidapi.com/tts/voiceslist" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "microsoft-edge-text-to-speech.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def getdownloadurl(text: str, voice_name: str='en-US-AriaNeural', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "request with a long text and get the mp3 download URL created by the TTS engine. + + Supporting lots of languages with different voices, such as French, Spanish, Portuguese, Japanese, Korean, Chinese, Polish, Hindi and so on + + params: + text - STRING : the text to be transformed to speeches. + voice_name - STRING: the voice and language for the speeches." + + """ + url = f"https://microsoft-edge-text-to-speech.p.rapidapi.com/tts/edgetts" + querystring = {'text': text, } + if voice_name: + querystring['voice_name'] = voice_name + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "microsoft-edge-text-to-speech.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney.json new file mode 100644 index 0000000000000000000000000000000000000000..7df990e58c3ea763f1c1dbee0933872d81c1061f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney.json @@ -0,0 +1,99 @@ +{ + "tool_name": "Midjourney", + "tool_description": "Stable Diffusion fine tuned model on Midjourney", + "title": "Midjourney", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3705, + "avgSuccessRate": 100, + "popularityScore": 8.9, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/ankatechllc/api/midjourney13/", + "host": "midjourney13.p.rapidapi.com", + "api_list": [ + { + "name": "Get Image", + "url": "https://midjourney13.p.rapidapi.com/v1/images/{id}", + "description": "Get Image", + "method": "GET", + "required_parameters": [ + { + "name": "id", + "type": "string", + "description": "", + "default": "12345" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images/{id}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Generate Images Asyncronously", + "url": "https://midjourney13.p.rapidapi.com/v1/images", + "description": "Generate Images Asyncronously", + "method": "POST", + "required_parameters": [ + { + "name": "X-RapidAPI-Processor", + "type": "STRING", + "description": "", + "default": "async" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\nquerystring = {\"X-RapidAPI-Processor\": x_rapidapi_processor}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Generate Images Syncronously", + "url": "https://midjourney13.p.rapidapi.com/v1/images", + "description": "Generate Images Syncronously", + "method": "POST", + "required_parameters": [ + { + "name": "X-RapidAPI-Processor", + "type": "STRING", + "description": "", + "default": "sync" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\nquerystring = {\"X-RapidAPI-Processor\": x_rapidapi_processor}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Generate Images Asyncronously", + "url": "https://midjourney13.p.rapidapi.com/v1/images", + "description": "Generate Images Asyncronously", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Generate Images Syncronously", + "url": "https://midjourney13.p.rapidapi.com/v1/images", + "description": "Generate Images Syncronously", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney13.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney13.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney/api.py new file mode 100644 index 0000000000000000000000000000000000000000..f4d6a97fe2f4df2fc2a065c50b51e72a6f22ea84 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_image(is_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get Image" + + """ + url = f"https://midjourney13.p.rapidapi.com/v1/images/{is_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourney13.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..87ade76992e8604b50fb74316906facf5f9206a0 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai.json @@ -0,0 +1,87 @@ +{ + "product_id": "api_d0d01fc5-775a-41d1-ace0-da3eb48ffae5", + "tool_description": "MidJourney AI is your gateway to exceptional imaging solutions! \ud83d\udd25\ud83d\udcf8\n", + "home_url": "https://rapidapi.com/WaveTech/api/midjourney-ai1/", + "name": "MidJourney AI", + "title": "MidJourney AI", + "pricing": "FREEMIUM", + "tool_name": "MidJourney AI", + "score": { + "avgServiceLevel": 100, + "avgLatency": 513, + "avgSuccessRate": 100, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "midjourney-ai1.p.rapidapi.com", + "api_list": [ + { + "name": "reroll", + "url": "https://midjourney-ai1.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "upscale", + "url": "https://midjourney-ai1.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "imagine", + "url": "https://midjourney-ai1.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "zoomout", + "url": "https://midjourney-ai1.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n\n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "describe", + "url": "https://midjourney-ai1.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "variation", + "url": "https://midjourney-ai1.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai1.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai_image_generation.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai_image_generation.json new file mode 100644 index 0000000000000000000000000000000000000000..9fa26aa2d261ed782b5ca4ae6a0bcf39d3ef29e9 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_ai_image_generation.json @@ -0,0 +1,85 @@ +{ + "product_id": "api_54dc8b0e-34bd-4310-b535-ddd2053b0b40", + "tool_description": "Unlock Your Creativity with Midjourney: AI Image Generation API - Simple and Powerful Image Magic! \ud83d\udcf8\u2728", + "home_url": "https://rapidapi.com/Ideahub/api/midjourney-ai-image-generation/", + "name": "Midjourney : AI Image Generation", + "title": "Midjourney : AI Image Generation", + "pricing": "FREEMIUM", + "tool_name": "Midjourney : AI Image Generation", + "score": { + "avgServiceLevel": 96, + "avgLatency": 341, + "avgSuccessRate": 96, + "popularityScore": 9.4, + "__typename": "Score" + }, + "host": "midjourney-ai-image-generation.p.rapidapi.com", + "api_list": [ + { + "name": "variation", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "upscale", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "reroll", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "describe", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "imagine", + "url": "https://midjourney-ai-image-generation.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-ai-image-generation.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-ai-image-generation.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api.json new file mode 100644 index 0000000000000000000000000000000000000000..0bbcc3a3b989cc6979ddaac337e986e790ade148 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api.json @@ -0,0 +1,189 @@ +{ + "tool_name": "MidJourney API", + "tool_description": "Experience Imaging Excellence: Midjourney API - Unleashing Power, Ensuring Stability, Embracing Affordability \ud83d\udd25\ud83d\udcf8", + "title": "MidJourney API", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 321, + "avgSuccessRate": 100, + "popularityScore": 9.6, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/yourdevmail/api/midjourney-api5/", + "host": "midjourney-api5.p.rapidapi.com", + "api_list": [ + { + "name": "describe", + "url": "https://midjourney-api5.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-api5.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "variation", + "url": "https://midjourney-api5.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "upscale", + "url": "https://midjourney-api5.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "reroll", + "url": "https://midjourney-api5.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "imagine", + "url": "https://midjourney-api5.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "get job by taskId", + "url": "https://midjourney-api5.p.rapidapi.com/task/", + "description": "fetch result of job by taskId, and the taskId will expired after 24 hours\n\n- taskId (required,string)\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "GET", + "required_parameters": [ + { + "name": "taskId", + "type": "STRING", + "description": "", + "default": "0d441482-f5ea-4dff-8a4a-d3ff104b65f5" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/task/\"\nquerystring = {\"taskId\": taskid}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "describe", + "url": "https://midjourney-api5.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-api5.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "variation", + "url": "https://midjourney-api5.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "upscale", + "url": "https://midjourney-api5.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "reroll", + "url": "https://midjourney-api5.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "imagine", + "url": "https://midjourney-api5.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-api5.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-api5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..df1dd60edade4fb2d15608b5f64d9ff1f3cd939d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_api/api.py @@ -0,0 +1,33 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_job_by_taskid(taskid: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "fetch result of job by taskId, and the taskId will expired after 24 hours + + - taskId (required,string) + + ![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)" + + """ + url = f"https://midjourney-api5.p.rapidapi.com/task/" + querystring = {'taskId': taskid, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourney-api5.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_auto_upscale.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_auto_upscale.json new file mode 100644 index 0000000000000000000000000000000000000000..557d46ea77e9a7268e7fe98d9cf7a55c5aa4e69e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_auto_upscale.json @@ -0,0 +1,58 @@ +{ + "product_id": "api_8cb79cc4-31b2-4fcc-8d04-2fb93feb91e3", + "tool_description": "Imagine and Upscale the prompt with only 1 API call (5 images in total).\nWebhook available.", + "home_url": "https://rapidapi.com/omar.goco/api/midjourney-auto-upscale/", + "name": "Midjourney Auto Upscale", + "title": "Midjourney Auto Upscale", + "pricing": "FREEMIUM", + "tool_name": "Midjourney Auto Upscale", + "score": { + "avgServiceLevel": 100, + "avgLatency": 613, + "avgSuccessRate": 33, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "midjourney-auto-upscale.p.rapidapi.com", + "api_list": [ + { + "name": "Imagine and Upscale", + "url": "https://midjourney-auto-upscale.p.rapidapi.com/imagine-and-upscale", + "description": "This command run the imagine command and upscale the 4 images, when is ready returns the main image, and the upscaled images (5 images in total).\n\nIt requries a prompt parameter and an optional webhook parameter", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/imagine-and-upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/imagine-and-upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Upscale", + "url": "https://midjourney-auto-upscale.p.rapidapi.com/upscale", + "description": "Run the upscale command in Midjourney to upscale images from generated with the imagine command.\n\nSend a variant parameter containing the number to base the image on. The API returns a job_id that can be used to check status on the status endpoint.\n\nOptionally, provide a webhook parameter to be notified via webhook when the job completes.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Imagine", + "url": "https://midjourney-auto-upscale.p.rapidapi.com/imagine", + "description": "Run the imagine command in Midjourney to generate images from text prompts.\n\nSend a prompt parameter containing the text to base the image on. The API returns a job_id that can be used to check status on the status endpoint.\n\nOptionally, provide a webhook parameter to be notified via webhook when the job completes.\n\nThe imagine endpoint handles submitting the prompt to Midjourney and kicking off the image generation process. Retrieve completed high-quality images using the job_id and status endpoints.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-auto-upscale.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-auto-upscale.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine.json new file mode 100644 index 0000000000000000000000000000000000000000..9c40d7d3d6122b0067770cfb769c5c942ab82310 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine.json @@ -0,0 +1,72 @@ +{ + "tool_name": "Midjourney AutoImagine", + "tool_description": "", + "title": "Midjourney AutoImagine", + "pricing": "PAID", + "score": null, + "home_url": "https://rapidapi.com/agunghakase/api/midjourney-autoimagine/", + "host": "midjourney-autoimagine.p.rapidapi.com", + "api_list": [ + { + "name": "PING", + "url": "https://midjourney-autoimagine.p.rapidapi.com/api/ping", + "description": "Check this API works.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/ping\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Imagine Blue Willow", + "url": "https://midjourney-autoimagine.p.rapidapi.com/api/bw", + "description": "Call API to imagine Blue Willow using your own discord account.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/bw\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Imagine Midjourney", + "url": "https://midjourney-autoimagine.p.rapidapi.com/api/mj", + "description": "Call API to imagine midjourney using your own discord account.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/mj\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Imagine Blue Willow", + "url": "https://midjourney-autoimagine.p.rapidapi.com/api/bw", + "description": "Call API to imagine Blue Willow using your own discord account.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/bw\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/bw\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Imagine Midjourney", + "url": "https://midjourney-autoimagine.p.rapidapi.com/api/mj", + "description": "Call API to imagine midjourney using your own discord account.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/mj\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-autoimagine.p.rapidapi.com/api/mj\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-autoimagine.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine/api.py new file mode 100644 index 0000000000000000000000000000000000000000..4c8474df1f7ca5e5ad84d9b8eacf34ce36fea25a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_autoimagine/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def ping(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Check this API works." + + """ + url = f"https://midjourney-autoimagine.p.rapidapi.com/api/ping" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourney-autoimagine.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience.json new file mode 100644 index 0000000000000000000000000000000000000000..a6b000cfcb1d224d6446775b44109bf546e7f8f3 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience.json @@ -0,0 +1,622 @@ +{ + "tool_name": "Midjourney best experience", + "tool_description": "Connect your project to midjourney | mj contain generate\u3001upsample\u3001variation...", + "title": "Midjourney best experience", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 98, + "avgLatency": 522, + "avgSuccessRate": 98, + "popularityScore": 9.8, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/liuzhaolong765481/api/midjourney-best-experience/", + "host": "midjourney-best-experience.p.rapidapi.com", + "api_list": [ + { + "name": "Blend Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/blend-fast", + "description": "Merge multiple images into a novel new image, containing 2 to 5 Image URL path. The effect of composite images is shown in the following figure\n![](https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg#pic_center =160x120)\n![](https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg#pic_center =80x120)\n![](https://img.midjourneyapi.xyz/mj/olivia0339_None_e8e1be14-dd3d-4ae4-9aff-77c9891605a8.png#pic_center =250x250)", + "method": "POST", + "required_parameters": [ + { + "name": "images_url1", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + }, + { + "name": "images_url2", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url5", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url3", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url4", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-fast\"\nquerystring = {\"images_url1\": images_url1, \"images_url2\": images_url2}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Blend Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/blend-relax", + "description": "Merge multiple images into a novel new image, containing 2 to 5 Image URL path.\n![](https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg#pic_center =160x120)\n![](https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg#pic_center =80x120)\n![](https://img.midjourneyapi.xyz/mj/olivia0339_None_e8e1be14-dd3d-4ae4-9aff-77c9891605a8.png#pic_center =250x250)", + "method": "POST", + "required_parameters": [ + { + "name": "images_url1", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + }, + { + "name": "images_url2", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg" + } + ], + "optional_parameters": [ + { + "name": "images_url4", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url3", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url5", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-relax\"\nquerystring = {\"images_url1\": images_url1, \"images_url2\": images_url2}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Generate Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/generate-relax", + "description": "generate the images relax\nGenerate queue asynchronous notifications to hook_ url, overall generation time is Depends on account status and task queuing", + "method": "POST", + "required_parameters": [ + { + "name": "Content-Type", + "type": "STRING", + "description": "", + "default": "application/json" + }, + { + "name": "prompt", + "type": "STRING", + "description": "", + "default": "a beautiful cat --ar 1920:1080" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-relax\"\nquerystring = {\"Content-Type\": content_type, \"prompt\": prompt, \"hook_url\": hook_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Generate Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/generate-fast", + "description": "generate the images fast \nGenerate queue asynchronous notifications to hook_ url, overall generation time is around 40-60s", + "method": "POST", + "required_parameters": [ + { + "name": "prompt", + "type": "STRING", + "description": "", + "default": "a beautiful cat --ar 1920:1080" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com/" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-fast\"\nquerystring = {\"prompt\": prompt, \"hook_url\": hook_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Describe Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/describe-fast", + "description": "Generate four possible prompts based on the uploaded image", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-fast\"\nquerystring = {\"image_url\": image_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Action Relax(U&V...)", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/action-relax", + "description": "- Do the relax action\n\n- You can perform upsample (same as the UI, U2...), variation (V1, V2...), zoom out 1.5x, zoom out 2x, pan, and other operations on the images generated in the first step", + "method": "POST", + "required_parameters": [ + { + "name": "image_id", + "type": "STRING", + "description": "the relax job the last image_id", + "default": "11209086137713295861" + }, + { + "name": "action", + "type": "STRING", + "description": "the action is the enumeration values returned in the action list in the callback ", + "default": "variation1" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-relax\"\nquerystring = {\"image_id\": image_id, \"action\": action, \"hook_url\": hook_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Describe Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/describe-relax", + "description": "Generate four possible prompts based on the uploaded image", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "Image URL path", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-relax\"\nquerystring = {\"image_url\": image_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "get job by task id", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/get-task-id", + "description": "you can get the generate job and action job status by the task_id, and the task_id will expired at 24 hours after", + "method": "GET", + "required_parameters": [ + { + "name": "task_id", + "type": "STRING", + "description": "", + "default": "6ddd8121-2ae4-af61-b73d-eaefc8318d09" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/get-task-id\"\nquerystring = {\"task_id\": task_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Action Fast\uff08U&V...\uff09", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/action-fast", + "description": "- Do the fast action\n\n- You can perform upsample (same as the UI, U2...), variation (V1, V2...), zoom out 1.5x, zoom out 2x, pan, and other operations on the images generated in the first step", + "method": "POST", + "required_parameters": [ + { + "name": "action", + "type": "STRING", + "description": "the action is the enumeration values returned in the action list in the callback ", + "default": "variation1" + }, + { + "name": "image_id", + "type": "STRING", + "description": "the fast job callback the last image_id", + "default": "11209086137713295861" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-fast\"\nquerystring = {\"action\": action, \"image_id\": image_id, \"hook_url\": hook_url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Blend Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/blend-fast", + "description": "Merge multiple images into a novel new image, containing 2 to 5 Image URL path. The effect of composite images is shown in the following figure\n![](https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg#pic_center =160x120)\n![](https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg#pic_center =80x120)\n![](https://img.midjourneyapi.xyz/mj/olivia0339_None_e8e1be14-dd3d-4ae4-9aff-77c9891605a8.png#pic_center =250x250)", + "method": "POST", + "required_parameters": [ + { + "name": "images_url1", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + }, + { + "name": "images_url2", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url5", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url3", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url4", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-fast\"\nquerystring = {\"hook_url\": \"\", \"images_url1\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"images_url5\": \"\", \"images_url3\": \"\", \"images_url4\": \"\", \"images_url2\": \"https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-fast\"\nquerystring = {\"hook_url\": \"\", \"images_url1\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"images_url5\": \"\", \"images_url3\": \"\", \"images_url4\": \"\", \"images_url2\": \"https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Blend Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/blend-relax", + "description": "Merge multiple images into a novel new image, containing 2 to 5 Image URL path.\n![](https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg#pic_center =160x120)\n![](https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg#pic_center =80x120)\n![](https://img.midjourneyapi.xyz/mj/olivia0339_None_e8e1be14-dd3d-4ae4-9aff-77c9891605a8.png#pic_center =250x250)", + "method": "POST", + "required_parameters": [ + { + "name": "images_url1", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + }, + { + "name": "images_url2", + "type": "STRING", + "description": "Accessible image URL address", + "default": "https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg" + } + ], + "optional_parameters": [ + { + "name": "images_url4", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url3", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "images_url5", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-relax\"\nquerystring = {\"images_url4\": \"\", \"images_url3\": \"\", \"hook_url\": \"\", \"images_url5\": \"\", \"images_url1\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"images_url2\": \"https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/blend-relax\"\nquerystring = {\"images_url4\": \"\", \"images_url3\": \"\", \"hook_url\": \"\", \"images_url5\": \"\", \"images_url1\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"images_url2\": \"https://images.freeimages.com/images/large-previews/ddf/tour-d-eiffel-1447025.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Generate Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/generate-relax", + "description": "generate the images relax\nGenerate queue asynchronous notifications to hook_ url, overall generation time is Depends on account status and task queuing", + "method": "POST", + "required_parameters": [ + { + "name": "prompt", + "type": "STRING", + "description": "", + "default": "a beautiful cat --ar 1920:1080" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-relax\"\nquerystring = {\"prompt\": \"a beautiful cat --ar 1920:1080\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-relax\"\nquerystring = {\"prompt\": \"a beautiful cat --ar 1920:1080\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Generate Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/generate-fast", + "description": "generate the images fast \nGenerate queue asynchronous notifications to hook_ url, overall generation time is around 40-60s", + "method": "POST", + "required_parameters": [ + { + "name": "prompt", + "type": "STRING", + "description": "", + "default": "a beautiful cat --ar 1920:1080" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com/" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-fast\"\nquerystring = {\"prompt\": \"a beautiful cat --ar 1920:1080\", \"hook_url\": \"https://www.google.com/\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/generate-fast\"\nquerystring = {\"prompt\": \"a beautiful cat --ar 1920:1080\", \"hook_url\": \"https://www.google.com/\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Describe Fast", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/describe-fast", + "description": "Generate four possible prompts based on the uploaded image", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-fast\"\nquerystring = {\"hook_url\": \"\", \"image_url\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-fast\"\nquerystring = {\"hook_url\": \"\", \"image_url\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Action Relax(U&V...)", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/action-relax", + "description": "- Do the relax action\n\n- You can perform upsample (same as the UI, U2...), variation (V1, V2...), zoom out 1.5x, zoom out 2x, pan, and other operations on the images generated in the first step", + "method": "POST", + "required_parameters": [ + { + "name": "image_id", + "type": "STRING", + "description": "the relax job the last image_id", + "default": "11209086137713295861" + }, + { + "name": "action", + "type": "STRING", + "description": "the action is the enumeration values returned in the action list in the callback ", + "default": "variation1" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "if set will notify the result to your hook_url", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-relax\"\nquerystring = {\"image_id\": \"11209086137713295861\", \"action\": \"variation1\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-relax\"\nquerystring = {\"image_id\": \"11209086137713295861\", \"action\": \"variation1\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Describe Relax", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/describe-relax", + "description": "Generate four possible prompts based on the uploaded image", + "method": "POST", + "required_parameters": [ + { + "name": "image_url", + "type": "STRING", + "description": "Image URL path", + "default": "https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-relax\"\nquerystring = {\"image_url\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"hook_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/describe-relax\"\nquerystring = {\"image_url\": \"https://images.freeimages.com/images/large-previews/218/my-dog-cutter-1499799.jpg\", \"hook_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Action Fast\uff08U&V...\uff09", + "url": "https://midjourney-best-experience.p.rapidapi.com/mj/action-fast", + "description": "- Do the fast action\n\n- You can perform upsample (same as the UI, U2...), variation (V1, V2...), zoom out 1.5x, zoom out 2x, pan, and other operations on the images generated in the first step", + "method": "POST", + "required_parameters": [ + { + "name": "action", + "type": "STRING", + "description": "the action is the enumeration values returned in the action list in the callback ", + "default": "variation1" + }, + { + "name": "image_id", + "type": "STRING", + "description": "the fast job callback the last image_id", + "default": "11209086137713295861" + } + ], + "optional_parameters": [ + { + "name": "hook_url", + "type": "STRING", + "description": "", + "default": "https://www.google.com" + } + ], + "code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-fast\"\nquerystring = {\"action\": \"variation1\", \"image_id\": \"11209086137713295861\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-best-experience.p.rapidapi.com/mj/action-fast\"\nquerystring = {\"action\": \"variation1\", \"image_id\": \"11209086137713295861\", \"hook_url\": \"https://www.google.com\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-best-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience/api.py new file mode 100644 index 0000000000000000000000000000000000000000..3abcf179e0459ae66a8b1e7b4fa992262245e7f4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_best_experience/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_job_by_task_id(task_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "you can get the generate job and action job status by the task_id, and the task_id will expired at 24 hours after" + + """ + url = f"https://midjourney-best-experience.p.rapidapi.com/mj/get-task-id" + querystring = {'task_id': task_id, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourney-best-experience.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_experience.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_experience.json new file mode 100644 index 0000000000000000000000000000000000000000..bbd7639419add116fc71746d01b5e8bd4d252f93 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_experience.json @@ -0,0 +1,87 @@ +{ + "product_id": "api_a7e48172-af33-4c37-8337-dab21e9aab35", + "tool_description": "Unlock the Best in Imaging with MidJourney Experience API!", + "home_url": "https://rapidapi.com/futurize/api/midjourney-experience/", + "name": "MidJourney Experience", + "title": "MidJourney Experience", + "pricing": "FREEMIUM", + "tool_name": "MidJourney Experience", + "score": { + "avgServiceLevel": 100, + "avgLatency": 525, + "avgSuccessRate": 100, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "midjourney-experience.p.rapidapi.com", + "api_list": [ + { + "name": "variation", + "url": "https://midjourney-experience.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "reroll", + "url": "https://midjourney-experience.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "upscale", + "url": "https://midjourney-experience.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "imagine", + "url": "https://midjourney-experience.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "describe", + "url": "https://midjourney-experience.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-experience.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-experience.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-experience.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision.json new file mode 100644 index 0000000000000000000000000000000000000000..9519781690c91fc739b153619974f381e8c0ad3f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision.json @@ -0,0 +1,184 @@ +{ + "tool_name": "Midjourney Vision", + "tool_description": "Introducing Midjourney Vision API - Your Path to Imaging Excellence! \ud83d\udd25\ud83d\udcf8", + "title": "Midjourney Vision", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 389, + "avgSuccessRate": 100, + "popularityScore": 8.8, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/FutureWave/api/midjourney-vision2/", + "host": "midjourney-vision2.p.rapidapi.com", + "api_list": [ + { + "name": "variation", + "url": "https://midjourney-vision2.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "describe", + "url": "https://midjourney-vision2.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "imagine", + "url": "https://midjourney-vision2.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "upscale", + "url": "https://midjourney-vision2.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "reroll", + "url": "https://midjourney-vision2.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-vision2.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "get job by taskId", + "url": "https://midjourney-vision2.p.rapidapi.com/task/", + "description": "fetch result of job by taskId, and the taskId will expired after 24 hours\n\n- taskId (required,string)\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "GET", + "required_parameters": [ + { + "name": "taskId", + "type": "STRING", + "description": "", + "default": "0d441482-f5ea-4dff-8a4a-d3ff104b65f5" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/task/\"\nquerystring = {\"taskId\": taskid}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "variation", + "url": "https://midjourney-vision2.p.rapidapi.com/variation", + "description": "The /variation command allows you to submit variation of existing image using imageId \n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/variation\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "describe", + "url": "https://midjourney-vision2.p.rapidapi.com/describe", + "description": "The /describe command allows you to upload an image and generate four possible prompts based on that image. Use the /describe command to explore new vocabulary and aesthetic movements.\n\n![](https://i.ibb.co/nwG1kLs/describe-command-midjourney-cowboy.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "imagine", + "url": "https://midjourney-vision2.p.rapidapi.com/imagine", + "description": "The /imagine command allows you to generate an image using a prompt\n\n![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "upscale", + "url": "https://midjourney-vision2.p.rapidapi.com/upscale", + "description": "The /upscale command allows you to submit upscale request of existing image using imageId\n\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/upscale\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "reroll", + "url": "https://midjourney-vision2.p.rapidapi.com/reroll", + "description": "The /reroll command allows you to submit reroll request of existing image using imageId\n![](https://i.ibb.co/rpBK6bN/Screenshot-2023-09-08-153932.png)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/reroll\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "zoomout", + "url": "https://midjourney-vision2.p.rapidapi.com/zoomout", + "description": "The /zommout command allows you to zoomout of image after upscaling image. \n![](https://i.ibb.co/h8mw5JR/zoom-out-on-midjourney-5-a.webp)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjourney-vision2.p.rapidapi.com/zoomout\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourney-vision2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision/api.py new file mode 100644 index 0000000000000000000000000000000000000000..0071f473b7a683b640f86b922d0448e4b8547981 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourney_vision/api.py @@ -0,0 +1,33 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_job_by_taskid(taskid: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "fetch result of job by taskId, and the taskId will expired after 24 hours + + - taskId (required,string) + + ![](https://i.ibb.co/pZ6rNcR/bc9062aa-8580-4170-9bfa-cd3c4cafd481-1893x1615.jpg)" + + """ + url = f"https://midjourney-vision2.p.rapidapi.com/task/" + querystring = {'taskId': taskid, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourney-vision2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed.json new file mode 100644 index 0000000000000000000000000000000000000000..0021f43de2230b60ed3e08007558e63646c43448 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed.json @@ -0,0 +1,37 @@ +{ + "tool_name":"midjourneyfeed", + "tool_description":"Midjourney community latest RSS feed", + "title":"midjourneyfeed", + "pricing":"PAID", + "score":{ + "avgServiceLevel":0, + "avgLatency":7, + "avgSuccessRate":0, + "popularityScore":0, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/dineybomfim/api/midjourneyfeed/", + "host":"midjourneyfeed.p.rapidapi.com", + "api_list":[ + { + "name":"midjourney", + "url":"https://midjourneyfeed.p.rapidapi.com/latest", + "description":"Midjourney latest jobs feed.\nIt can return RSS, JSON or a specific image", + "method":"GET", + "required_parameters":[ + { + "name":"format", + "type":"STRING", + "description":"", + "default":"rss" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://midjourneyfeed.p.rapidapi.com/latest\"\nquerystring = {\"format\": format}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjourneyfeed.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed/api.py new file mode 100644 index 0000000000000000000000000000000000000000..a773cf206d1279ea018c5aa265e04791fd6bfc0c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjourneyfeed/api.py @@ -0,0 +1,30 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def midjourney(format: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Midjourney latest jobs feed. + It can return RSS, JSON or a specific image" + + """ + url = f"https://midjourneyfeed.p.rapidapi.com/latest" + querystring = {'format': format, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "midjourneyfeed.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjournium.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjournium.json new file mode 100644 index 0000000000000000000000000000000000000000..00ace0ba4b967f222ab4bcd45cb3f19b319599cb --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/midjournium.json @@ -0,0 +1,386 @@ +{ + "product_id": "api_769acd56-7101-4f53-b070-2813c043a8c0", + "tool_description": "Midjourney. Relax, Fast and Turbo modes. Asynchonous and Synchnorous REST API; Upscale/variations/zooms/etc at any depth. Technical Support. API that just works.", + "home_url": "https://rapidapi.com/midjournium/api/midjournium4/", + "name": "Midjournium", + "title": "Midjournium", + "pricing": "FREEMIUM", + "tool_name": "Midjournium", + "score": { + "avgServiceLevel": 100, + "avgLatency": 433, + "avgSuccessRate": 100, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "midjournium4.p.rapidapi.com", + "api_list": [ + { + "name": "/turbo/command/{jobId}/{command}", + "url": "https://midjournium4.p.rapidapi.com/turbo/command/{jobId}/{command}", + "description": "Sample request:\r\n \r\n POST /turbo/command/b492b906f69e43bcb7910929fb0b48c9/MJ::JOB::upsample::4::2f11ba98-39da-4513-8599-217a37503f5e", + "method": "POST", + "required_parameters": [ + { + "name": "jobId", + "type": "STRING", + "description": "job id", + "default": "" + }, + { + "name": "command", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [ + { + "name": "commandId", + "type": "STRING", + "description": "command id from the job.commands array", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/command/{jobId}/{command}\"\nquerystring = {\"jobId\": \"\", \"command\": \"\", \"commandId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/command/{jobId}/{command}\"\nquerystring = {\"jobId\": \"\", \"command\": \"\", \"commandId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jobId": { + "type": "string" + }, + "type": { + "enum": [ + "undefined", + "imagine", + "upscale", + "reroll", + "variation", + "highVariation", + "lowVariation", + "zoomOut2x", + "zoomOut15x", + "panLeft", + "panRight", + "panUp", + "panDown", + "appeal", + "makeSquare" + ], + "type": "string" + }, + "mode": { + "enum": [ + "undefined", + "relax", + "fast", + "turbo" + ], + "type": "string" + }, + "status": { + "enum": [ + "undefined", + "new", + "submitted", + "inProgress", + "completed", + "error", + "rejected", + "timeout" + ], + "type": "string" + }, + "startTime": { + "format": "date-time", + "type": "string" + }, + "endTime": { + "format": "date-time", + "type": "string" + }, + "notifyWebhookUrl": { + "type": "string" + }, + "errorMessage": { + "type": "string" + }, + "cost": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "progress": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "imageUrl": { + "type": "string" + }, + "imageHeight": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "imageWidth": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "imageSize": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "attributes": { + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "commands": { + "type": "array", + "items": { + "type": "object", + "properties": { + "commandId": { + "type": "string" + }, + "groupIndex": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "commandIndex": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "label": { + "type": "string" + }, + "url": { + "type": "string" + }, + "cost": { + "format": "int32", + "type": "integer", + "minimum": -2147483648, + "maximum": 2147483647 + } + }, + "additionalProperties": false + } + } + }, + "additionalProperties": false + } + }, + { + "name": "/turbo/imagine", + "url": "https://midjournium4.p.rapidapi.com/turbo/imagine", + "description": "Sample request:\r\n \r\n POST /turbo/imagine\r\n {\r\n \"prompt\": \"happy pony\",\r\n }", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/imagine\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/relax/commandAsync/{jobId}/{command}", + "url": "https://midjournium4.p.rapidapi.com/relax/commandAsync/{jobId}/{command}", + "description": "Sample request:\r\n \r\n POST /relax/commandAsync/b492b906f69e43bcb7910929fb0b48c9/MJ::JOB::upsample::4::2f11ba98-39da-4513-8599-217a37503f5e\r\n {\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [ + { + "name": "command", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "jobId", + "type": "STRING", + "description": "job id", + "default": "" + } + ], + "optional_parameters": [ + { + "name": "commandId", + "type": "STRING", + "description": "command id from the job.commands array", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/relax/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"command\": \"\", \"jobId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/relax/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"command\": \"\", \"jobId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jobId": { + "type": "string" + }, + "errorMessage": { + "type": "string" + } + }, + "additionalProperties": false + } + }, + { + "name": "/turbo/commandAsync/{jobId}/{command}", + "url": "https://midjournium4.p.rapidapi.com/turbo/commandAsync/{jobId}/{command}", + "description": "Sample request:\r\n \r\n POST /turbo/commandAsync/b492b906f69e43bcb7910929fb0b48c9/MJ::JOB::upsample::4::2f11ba98-39da-4513-8599-217a37503f5e\r\n {\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [ + { + "name": "jobId", + "type": "STRING", + "description": "job id", + "default": "" + }, + { + "name": "command", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [ + { + "name": "commandId", + "type": "STRING", + "description": "command id from the job.commands array", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"jobId\": \"\", \"command\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"jobId\": \"\", \"command\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jobId": { + "type": "string" + }, + "errorMessage": { + "type": "string" + } + }, + "additionalProperties": false + } + }, + { + "name": "/fast/commandAsync/{jobId}/{command}", + "url": "https://midjournium4.p.rapidapi.com/fast/commandAsync/{jobId}/{command}", + "description": "Sample request:\r\n \r\n POST /fast/commandAsync/b492b906f69e43bcb7910929fb0b48c9/MJ::JOB::upsample::4::2f11ba98-39da-4513-8599-217a37503f5e\r\n {\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [ + { + "name": "command", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "jobId", + "type": "STRING", + "description": "job id", + "default": "" + } + ], + "optional_parameters": [ + { + "name": "commandId", + "type": "STRING", + "description": "command id from the job.commands array", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/fast/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"command\": \"\", \"jobId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/fast/commandAsync/{jobId}/{command}\"\nquerystring = {\"commandId\": \"\", \"command\": \"\", \"jobId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/turbo/imagineAsync", + "url": "https://midjournium4.p.rapidapi.com/turbo/imagineAsync", + "description": "Sample request:\r\n \r\n POST /turbo/imagineAsync\r\n {\r\n \"prompt\": \"happy pony\",\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/turbo/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jobId": { + "type": "string" + }, + "errorMessage": { + "type": "string" + } + }, + "additionalProperties": false + } + }, + { + "name": "/fast/imagineAsync", + "url": "https://midjournium4.p.rapidapi.com/fast/imagineAsync", + "description": "Sample request:\r\n \r\n POST /fast/imagineAsync\r\n {\r\n \"prompt\": \"happy pony\",\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/fast/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/fast/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/relax/imagineAsync", + "url": "https://midjournium4.p.rapidapi.com/relax/imagineAsync", + "description": "Sample request:\r\n \r\n POST /relax/imagineAsync\r\n {\r\n \"prompt\": \"happy pony\",\r\n \"notifyWebhookUrl\": \"https://example.com/webhook?correlationId=1234567890\"\r\n }", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/relax/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://midjournium4.p.rapidapi.com/relax/imagineAsync\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"midjournium4.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jobId": { + "type": "string" + }, + "errorMessage": { + "type": "string" + } + }, + "additionalProperties": false + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ml_plugins.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ml_plugins.json new file mode 100644 index 0000000000000000000000000000000000000000..3bd956ef067e038ea7fda6c5790a0272f50a234c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ml_plugins.json @@ -0,0 +1,52 @@ +{ + "product_id": "api_05a10339-f762-4526-9ed0-ba6222a88b03", + "tool_description": "EnrichData provides ML Plugins support i.e. Contact Information Extractor (API extracts the contact information from given text), NER Extraction (API extracts the multiple entity details from the given text) and Resume Template Creation (API creates resume into a specified template resume format).", + "home_url": "https://rapidapi.com/enrichdata-enrichdata-default/api/ml-plugins/", + "name": "ML Plugins", + "title": "ML Plugins", + "pricing": "PAID", + "tool_name": "ML Plugins", + "score": null, + "host": "ml-plugins.p.rapidapi.com", + "api_list": [ + { + "name": "NER Extraction Plugin", + "url": "https://ml-plugins.p.rapidapi.com/nerTagger", + "description": "NER Extraction Plugin gives the entity details like start location, end location, job, city, state, country, name, degree, org, skill, date and year.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/nerTagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/nerTagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Resume Template Creation Plugin", + "url": "https://ml-plugins.p.rapidapi.com/resumeTemplate", + "description": "Resume Template Creation Plugin API creates resume into a specified template resume format.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/resumeTemplate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/resumeTemplate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Contact Information Extraction Plugin", + "url": "https://ml-plugins.p.rapidapi.com/contactExtractor", + "description": "Contact Information Extraction is an Rest API plugin, that uses algorithm for extracting Name, Email, City, State, Country, Website, Phone Number, and Address from the given text content.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/contactExtractor\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://ml-plugins.p.rapidapi.com/contactExtractor\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ml-plugins.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/moroccan_darija_sentiment_analysis.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/moroccan_darija_sentiment_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..0010bdcc3f8cf8b84a3dff3313e917bf59d68266 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/moroccan_darija_sentiment_analysis.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_55e423db-336d-4031-97a4-6e72a1ee3ae0", + "tool_description": "Our API uses AI to predict sentiment in Moroccan Darija, accepting Arabic, 3ranssia, Emojis or mixed inputs. It provides sentiment prediction and probability.", + "home_url": "https://rapidapi.com/integrate-analytics-integrate-analytics-default/api/moroccan-darija-sentiment-analysis/", + "name": "Moroccan Darija: Sentiment Analysis", + "title": "Moroccan Darija: Sentiment Analysis", + "pricing": "FREEMIUM", + "tool_name": "Moroccan Darija: Sentiment Analysis", + "score": { + "avgServiceLevel": 100, + "avgLatency": 759, + "avgSuccessRate": 100, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "moroccan-darija-sentiment-analysis.p.rapidapi.com", + "api_list": [ + { + "name": "Sentiment Analysis", + "url": "https://moroccan-darija-sentiment-analysis.p.rapidapi.com/api/sentimentAnalysis", + "description": "Perform sentiment analysis on a given text in Moroccan Darija", + "method": "POST", + "required_parameters": [ + { + "name": "InputText", + "type": "STRING", + "description": "", + "default": "ach had tkherbi9 dertou!?" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://moroccan-darija-sentiment-analysis.p.rapidapi.com/api/sentimentAnalysis\"\nquerystring = {\"InputText\": \"ach had tkherbi9 dertou!?\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"moroccan-darija-sentiment-analysis.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://moroccan-darija-sentiment-analysis.p.rapidapi.com/api/sentimentAnalysis\"\nquerystring = {\"InputText\": \"ach had tkherbi9 dertou!?\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"moroccan-darija-sentiment-analysis.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd.json new file mode 100644 index 0000000000000000000000000000000000000000..764d5b6f4edaff3746f1679a9b910502c51eb020 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd.json @@ -0,0 +1,139 @@ +{ + "tool_name": "MOTD", + "tool_description": "Message of the Day provided by GPT3 AI\nStandard \"Inspirational\" Message of the day\nMoody Message of the Day in any supported mood (Always adding more)\nCharacter MOTD with various \"voice actors\" (Always adding more)", + "title": "MOTD", + "pricing": "FREEMIUM", + "score": null, + "home_url": "https://rapidapi.com/me-k0TUXtVly/api/motd/", + "host": "motd.p.rapidapi.com", + "api_list": [ + { + "name": "MOTD", + "url": "https://motd.p.rapidapi.com/MOTD", + "description": "Get message of the Day!", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "motd": { + "type": "string" + }, + "mood": { + "type": "string" + }, + "sign": { + "type": "boolean" + }, + "voice": { + "type": "string" + } + } + } + }, + { + "name": "MOTD", + "url": "https://motd.p.rapidapi.com/MOTD", + "description": "Get message of the Day!", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": "{\n\t\"mood\": \"sarcastic\",\n\t\"voice\": \"Goku\",\n\t\"motd\": \"Believe in yourself, you must. Great power within you lies. Train hard and never give up, and you will achieve your goals. Kamehameha!\"\n}", + "headers": { + "access-control-allow-credentials": "true", + "access-control-allow-origin": "*", + "content-type": "text/plain; charset=utf-8", + "date": "Thu, 09 Mar 2023 23:49:06 GMT", + "request-context": "appId=cid-v1:51cec31a-de6d-47d5-857a-4db87ba64a3d", + "server": "RapidAPI-1.2.8", + "x-rapidapi-region": "AWS - us-west-2", + "x-rapidapi-version": "1.2.8" + }, + "schema": { + "type": "object", + "properties": { + "mood": { + "type": "string" + }, + "voice": { + "type": "string" + }, + "motd": { + "type": "string" + }, + "sign": { + "type": "boolean" + } + } + } + }, + { + "name": "MOTD Docs", + "url": "https://motd.p.rapidapi.com/MOTD", + "description": "Query the MOTD API for documentation", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "MOTD Docs", + "url": "https://motd.p.rapidapi.com/MOTD", + "description": "Query the MOTD API for documentation", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": "text example!", + "headers": {}, + "schema": {} + }, + { + "name": "MOTD", + "url": "https://motd.p.rapidapi.com/MOTD", + "description": "Get message of the Day!", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://motd.p.rapidapi.com/MOTD\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"motd.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "mood": { + "type": "string" + }, + "voice": { + "type": "string" + }, + "motd": { + "type": "string" + }, + "sign": { + "type": "boolean" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd/api.py new file mode 100644 index 0000000000000000000000000000000000000000..b7526748f04d0f7350fb898022e5cdc7f78855a4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/motd/api.py @@ -0,0 +1,50 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def motd_docs(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Query the MOTD API for documentation" + + """ + url = f"https://motd.p.rapidapi.com/motd" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "motd.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def motd_docs(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Query the MOTD API for documentation" + + """ + url = f"https://motd.p.rapidapi.com/motd" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "motd.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mrz_scanner.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mrz_scanner.json new file mode 100644 index 0000000000000000000000000000000000000000..2035ce60bad5b64187c9114efabe9fdd8110bb9e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/mrz_scanner.json @@ -0,0 +1,475 @@ +{ + "product_id": "api_46a29cac-0703-4098-bc3d-f3af34f2e5c6", + "tool_description": "Scan MRZ from documents (Passports, Visas and ID Cards)", + "home_url": "https://rapidapi.com/PresentID/api/mrz-scanner/", + "name": "MRZ Scanner", + "title": "MRZ Scanner", + "pricing": "FREEMIUM", + "tool_name": "MRZ Scanner", + "score": { + "avgServiceLevel": 95, + "avgLatency": 1465, + "avgSuccessRate": 95, + "popularityScore": 9.7, + "__typename": "Score" + }, + "host": "mrz-scanner.p.rapidapi.com", + "api_list": [ + { + "name": "Send image as Base64", + "url": "https://mrz-scanner.p.rapidapi.com/ScanMRZ", + "description": "Send document image as a Base64 string", + "method": "POST", + "required_parameters": [ + { + "name": "imageBase64", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "object", + "properties": { + "header": { + "type": "object", + "properties": { + "type": { + "type": "string" + }, + "type_label": { + "type": "string" + }, + "text": { + "type": "string" + }, + "box": { + "type": "object", + "properties": { + "bottomLeftX": { + "type": "string" + }, + "bottomLeftY": { + "type": "string" + }, + "bottomRightX": { + "type": "string" + }, + "bottomRightY": { + "type": "string" + }, + "topLeftX": { + "type": "string" + }, + "topLeftY": { + "type": "string" + }, + "topRightX": { + "type": "string" + }, + "topRightY": { + "type": "string" + } + } + } + } + }, + "fields": { + "type": "object", + "properties": { + "surname": { + "type": "string" + }, + "name": { + "type": "string" + }, + "country": { + "type": "string" + }, + "country_english": { + "type": "string" + }, + "country_native": { + "type": "string" + }, + "country_2letters": { + "type": "string" + }, + "nationality": { + "type": "string" + }, + "nationality_english": { + "type": "string" + }, + "nationality_native": { + "type": "string" + }, + "nationality_2letters": { + "type": "string" + }, + "birth_date": { + "type": "string" + }, + "expiry_date": { + "type": "string" + }, + "sex": { + "type": "string" + }, + "sex_label": { + "type": "string" + }, + "document_type": { + "type": "string" + }, + "document_number": { + "type": "string" + }, + "optional_data": { + "type": "string" + }, + "birth_date_hash": { + "type": "string" + }, + "expiry_date_hash": { + "type": "string" + }, + "document_number_hash": { + "type": "string" + }, + "optional_data_hash": { + "type": "string" + }, + "optional_data_2": { + "type": "string" + } + } + } + } + } + } + } + }, + { + "name": "Send image with URL", + "url": "https://mrz-scanner.p.rapidapi.com/ScanMRZ", + "description": "Scan MRZ with public address.", + "method": "POST", + "required_parameters": [ + { + "name": "linkFile", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "object", + "properties": { + "header": { + "type": "object", + "properties": { + "type": { + "type": "string" + }, + "type_label": { + "type": "string" + }, + "text": { + "type": "string" + }, + "box": { + "type": "object", + "properties": { + "bottomLeftX": { + "type": "string" + }, + "bottomLeftY": { + "type": "string" + }, + "bottomRightX": { + "type": "string" + }, + "bottomRightY": { + "type": "string" + }, + "topLeftX": { + "type": "string" + }, + "topLeftY": { + "type": "string" + }, + "topRightX": { + "type": "string" + }, + "topRightY": { + "type": "string" + } + } + } + } + }, + "fields": { + "type": "object", + "properties": { + "surname": { + "type": "string" + }, + "name": { + "type": "string" + }, + "country": { + "type": "string" + }, + "country_english": { + "type": "string" + }, + "country_native": { + "type": "string" + }, + "country_2letters": { + "type": "string" + }, + "nationality": { + "type": "string" + }, + "nationality_english": { + "type": "string" + }, + "nationality_native": { + "type": "string" + }, + "nationality_2letters": { + "type": "string" + }, + "birth_date": { + "type": "string" + }, + "expiry_date": { + "type": "string" + }, + "sex": { + "type": "string" + }, + "sex_label": { + "type": "string" + }, + "document_type": { + "type": "string" + }, + "document_number": { + "type": "string" + }, + "optional_data": { + "type": "string" + }, + "birth_date_hash": { + "type": "string" + }, + "expiry_date_hash": { + "type": "string" + }, + "document_number_hash": { + "type": "string" + }, + "optional_data_hash": { + "type": "string" + }, + "optional_data_2": { + "type": "string" + } + } + } + } + } + } + } + }, + { + "name": "Send image by file (Multipart/FormData)", + "url": "https://mrz-scanner.p.rapidapi.com/ScanMRZ", + "description": "Send image as a file to API", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://mrz-scanner.p.rapidapi.com/ScanMRZ\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"mrz-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "object", + "properties": { + "header": { + "type": "object", + "properties": { + "type": { + "type": "string" + }, + "type_label": { + "type": "string" + }, + "text": { + "type": "string" + }, + "box": { + "type": "object", + "properties": { + "bottomLeftX": { + "type": "string" + }, + "bottomLeftY": { + "type": "string" + }, + "bottomRightX": { + "type": "string" + }, + "bottomRightY": { + "type": "string" + }, + "topLeftX": { + "type": "string" + }, + "topLeftY": { + "type": "string" + }, + "topRightX": { + "type": "string" + }, + "topRightY": { + "type": "string" + } + } + } + } + }, + "fields": { + "type": "object", + "properties": { + "surname": { + "type": "string" + }, + "name": { + "type": "string" + }, + "country": { + "type": "string" + }, + "country_english": { + "type": "string" + }, + "country_native": { + "type": "string" + }, + "country_2letters": { + "type": "string" + }, + "nationality": { + "type": "string" + }, + "nationality_english": { + "type": "string" + }, + "nationality_native": { + "type": "string" + }, + "nationality_2letters": { + "type": "string" + }, + "birth_date": { + "type": "string" + }, + "expiry_date": { + "type": "string" + }, + "sex": { + "type": "string" + }, + "sex_label": { + "type": "string" + }, + "document_type": { + "type": "string" + }, + "document_number": { + "type": "string" + }, + "optional_data": { + "type": "string" + }, + "birth_date_hash": { + "type": "string" + }, + "expiry_date_hash": { + "type": "string" + }, + "document_number_hash": { + "type": "string" + }, + "optional_data_hash": { + "type": "string" + }, + "optional_data_2": { + "type": "string" + } + } + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io.json new file mode 100644 index 0000000000000000000000000000000000000000..624b7541af047ba1c53c2a49b398be81efe4bfb9 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io.json @@ -0,0 +1,193 @@ +{ + "product_id": "api_5428c500-e481-4268-a9b1-057df116412c", + "tool_description": "voice API (not affiliated)\n\nFor educational purposes only, use my key: fba155a7d2d56f47d00f9013447bac3a\n\nRead more, here: https://api.elevenlabs.io/docs", + "home_url": "https://rapidapi.com/assafbarButterfly/api/my-elevenlabs-io/", + "name": "My elevenlabs.io", + "title": "My elevenlabs.io", + "pricing": "PAID", + "tool_name": "My elevenlabs.io", + "score": null, + "host": "my-elevenlabs-io.p.rapidapi.com", + "api_list": [ + { + "name": "Text_to_speech_v1_text_to_speech__voice_id__post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM", + "description": "Converts text into speech using a voice of your choice and returns audio.", + "method": "POST", + "required_parameters": [ + { + "name": "voice_id", + "type": "STRING", + "description": "Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.", + "default": "21m00Tcm4TlvDq8ikWAM" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/{voice_id}\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Text_to_speech_v1_text_to_speech__voice_id__stream_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM/stream", + "description": "Converts text into speech using a voice of your choice and returns audio as an audio stream.", + "method": "POST", + "required_parameters": [ + { + "name": "voice_id", + "type": "STRING", + "description": "Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.", + "default": "21m00Tcm4TlvDq8ikWAM" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM/stream\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/text-to-speech/{voice_id}/stream\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "Delete_history_items_v1_history_delete_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/history/delete", + "description": "Delete a number of history items by their IDs.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/history/delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/history/delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Download_history_items_v1_history_download_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/history/download", + "description": "Download one or more history items. If one history item ID is provided, we will return a single audio file. If more than one history item IDs are provided, we will provide the history items packed into a .zip file.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/history/download\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/history/download\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Edit_voice_v1_voices__voice_id__edit_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/voices/21m00Tcm4TlvDq8ikWAM/edit", + "description": "Edit a voice created by you.", + "method": "POST", + "required_parameters": [ + { + "name": "name", + "type": "STRING", + "description": "The name that identifies this voice. This will be displayed in the dropdown of the website.", + "default": "" + }, + { + "name": "voice_id", + "type": "STRING", + "description": "Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.", + "default": "21m00Tcm4TlvDq8ikWAM" + } + ], + "optional_parameters": [ + { + "name": "files", + "type": "ARRAY", + "description": "Audio files to add to the voice", + "default": "[]" + }, + { + "name": "labels", + "type": "STRING", + "description": "Serialized labels dictionary for the voice.", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/21m00Tcm4TlvDq8ikWAM/edit\"\nquerystring = {\"files\": \"[]\", \"name\": \"\", \"labels\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/{voice_id}/edit\"\nquerystring = {\"files\": \"[]\", \"name\": \"\", \"labels\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Edit_voice_settings_v1_voices__voice_id__settings_edit_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/voices/21m00Tcm4TlvDq8ikWAM/settings/edit", + "description": "Edit your settings for a specific voice.", + "method": "POST", + "required_parameters": [ + { + "name": "voice_id", + "type": "STRING", + "description": "Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.", + "default": "21m00Tcm4TlvDq8ikWAM" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/21m00Tcm4TlvDq8ikWAM/settings/edit\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/{voice_id}/settings/edit\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Add_voice_v1_voices_add_post", + "url": "https://my-elevenlabs-io.p.rapidapi.com/v1/voices/add", + "description": "Add a new voice to your collection of voices in VoiceLab.", + "method": "POST", + "required_parameters": [ + { + "name": "name", + "type": "STRING", + "description": "The name that identifies this voice. This will be displayed in the dropdown of the website.", + "default": "" + }, + { + "name": "files", + "type": "ARRAY", + "description": "One or more audio files to clone the voice from", + "default": "[]" + } + ], + "optional_parameters": [ + { + "name": "labels", + "type": "STRING", + "description": "Serialized labels dictionary for the voice.", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/add\"\nquerystring = {\"name\": \"\", \"files\": \"[]\", \"labels\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/add\"\nquerystring = {\"name\": \"\", \"files\": \"[]\", \"labels\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"my-elevenlabs-io.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io/api.py new file mode 100644 index 0000000000000000000000000000000000000000..8ff6a8f4f75f35e640fbc224ac2b63a9f3610c8d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/my_elevenlabs_io/api.py @@ -0,0 +1,205 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_voice_v1_voices_voice_id_get(voice_id: str, with_settings: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns metadata about a specific voice." + voice_id: Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. + with_settings: If set will return settings information corresponding to the voice, requires authorization. + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/{voice_id}" + querystring = {} + if with_settings: + querystring['with_settings'] = with_settings + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_generated_items_v1_history_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns metadata about all your generated audio." + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/history" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_audio_from_history_item_v1_history_history_item_id_audio_get(history_item_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns the audio of an history item." + history_item_id: History item ID to be used, you can use GET https://api.elevenlabs.io/v1/history to receive a list of history items and their IDs. + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/history/{history_item_id}/audio" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_user_subscription_info_v1_user_subscription_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Gets extended information about the users subscription" + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/user/subscription" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_user_info_v1_user_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Gets information about the user" + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/user" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_voices_v1_voices_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Gets a list of all available voices for a user." + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/voices" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_default_voice_settings_v1_voices_settings_default_get(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Gets the default settings for voices." + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/settings/default" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_voice_settings_v1_voices_voice_id_settings_get(voice_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns the settings for a specific voice." + voice_id: Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/{voice_id}/settings" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_audio_from_sample_v1_voices_voice_id_samples_sample_id_audio_get(sample_id: str, voice_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns the audio corresponding to a sample attached to a voice." + sample_id: Sample ID to be used, you can use GET https://api.elevenlabs.io/v1/voices/{voice_id} to list all the available samples for a voice. + voice_id: Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. + + """ + url = f"https://my-elevenlabs-io.p.rapidapi.com/v1/voices/{voice_id}/samples/{sample_id}/audio" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "my-elevenlabs-io.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/myfirst.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/myfirst.json new file mode 100644 index 0000000000000000000000000000000000000000..67f66d6d024a0a37167720ca6f6e1a557ccd6446 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/myfirst.json @@ -0,0 +1,65 @@ +{ + "product_id": "api_ced402f7-c00f-4101-8fa4-72edfa49497e", + "tool_description": "This API/endpoint takes the information (string) as input, and provides the JWT-encoded result (string) as output.\nThe output also includes a copy of the input, and a \u00ab status \u00bb value.\nStatus is \u00ab Ok \u00bb or \u00ab Error: \u2026 \u00bb.", + "home_url": "https://rapidapi.com/bourgarel-conseil-bourgarel-conseil-default/api/myfirst17/", + "name": "Myfirst", + "title": "Myfirst", + "pricing": "FREEMIUM", + "tool_name": "Myfirst", + "score": null, + "host": "myfirst17.p.rapidapi.com", + "api_list": [ + { + "name": "jwt-encode_copy", + "url": "https://myfirst17.p.rapidapi.com/jwt-encode", + "description": "This endpoint takes the information (string) as input, and provides the JWT-encoded result (string) as output.\nThe output also includes a copy of the input, and a \u00ab status \u00bb value.\nStatus is \u00ab Ok \u00bb or \u00ab Error: \u2026 \u00bb.\n\nEndpoint: jwt-encode\n\nMethod: POST\n\nSample Json input:\n\n{ \"input\": \"info to encode\" }\nSample Json output:\n\n{\n \"jwt-encoded\": \"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJtZW51Ijp7ImlkIjoiZmlsZSIsInZhbHVlIjoiRmlsZSIsInBvcHVwIjp7Im1lbnVpdGVtIjpbeyJ2YWx1ZSI6Ik5ldyIsIm9uY2xpY2siOiJDcmVhdGVOZXdEb2MoKSJ9LHsidmFsdWUiOiJPcGVuIiwib25jbGljayI6Ik9wZW5Eb2MoKSJ9LHsidmFsdWUiOiJDbG9zZSIsIm9uY2xpY2siOiJDbG9zZURvYygpIn1dfX0sImlhdCI6MTY4Nzc4OTQwOX0.JTyWgcVbAc4rQZD5ydqQy6GNL7CcuNwq5wdexseb1_s\",\n \"input\": \"content to encode\",\n \"status\": \"Ok\"\n}", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://myfirst17.p.rapidapi.com/jwt-encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"myfirst17.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://myfirst17.p.rapidapi.com/jwt-encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"myfirst17.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jwt-encoded": { + "type": "string" + }, + "input": { + "type": "string" + }, + "status": { + "type": "string" + } + } + } + }, + { + "name": "jwt-encode", + "url": "https://myfirst17.p.rapidapi.com/jwt-encode", + "description": "This endpoint takes the information (string) as input, and provides the JWT-encoded result (string) as output.\nThe output also includes a copy of the input, and a \u00ab status \u00bb value.\nStatus is \u00ab Ok \u00bb or \u00ab Error: \u2026 \u00bb.\n\nEndpoint: jwt-encode\n\nMethod: POST\n\nSample Json input:\n\n{ \"input\": \"info to encode\" }\nSample Json output:\n\n{\n \"jwt-encoded\": \"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJtZW51Ijp7ImlkIjoiZmlsZSIsInZhbHVlIjoiRmlsZSIsInBvcHVwIjp7Im1lbnVpdGVtIjpbeyJ2YWx1ZSI6Ik5ldyIsIm9uY2xpY2siOiJDcmVhdGVOZXdEb2MoKSJ9LHsidmFsdWUiOiJPcGVuIiwib25jbGljayI6Ik9wZW5Eb2MoKSJ9LHsidmFsdWUiOiJDbG9zZSIsIm9uY2xpY2siOiJDbG9zZURvYygpIn1dfX0sImlhdCI6MTY4Nzc4OTQwOX0.JTyWgcVbAc4rQZD5ydqQy6GNL7CcuNwq5wdexseb1_s\",\n \"input\": \"content to encode\",\n \"status\": \"Ok\"\n}", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://myfirst17.p.rapidapi.com/jwt-encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"myfirst17.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://myfirst17.p.rapidapi.com/jwt-encode\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"myfirst17.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "jwt-encoded": { + "type": "string" + }, + "input": { + "type": "string" + }, + "status": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy.json new file mode 100644 index 0000000000000000000000000000000000000000..189ba5722eef6b8db30d6ddacc1cab8f0e7fb373 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy.json @@ -0,0 +1,31 @@ +{ + "tool_name":"Navy", + "tool_description":"Navy", + "title":"Navy", + "pricing":"PAID", + "score":null, + "home_url":"https://rapidapi.com/pnrjason0/api/navy1/", + "host":"navy1.p.rapidapi.com", + "api_list":[ + { + "name":"End", + "url":"https://navy1.p.rapidapi.com/", + "description":"end", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"end", + "type":"STRING", + "description":"", + "default":"" + } + ], + "code":"import requests\n\nurl = \"https://navy1.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"navy1.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy/api.py new file mode 100644 index 0000000000000000000000000000000000000000..8fc1f208e35c9565ab9e816faeda1b2f764ed020 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/navy/api.py @@ -0,0 +1,31 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def end(end: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "end" + + """ + url = f"https://navy1.p.rapidapi.com/" + querystring = {} + if end: + querystring['end'] = end + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "navy1.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/neuralapi_chat_bot.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/neuralapi_chat_bot.json new file mode 100644 index 0000000000000000000000000000000000000000..5895c43edfe4447ec2108f2b49745e1f24e6a8fd --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/neuralapi_chat_bot.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_87e4516e-327c-4b01-b9f2-6f1f21b5ef1d", + "tool_description": "NeuralAPI is a powerful API that offers a chat bot functionality to enhance your platform\u2019s capabilities. With NeuralAPI, you can provide your users with an interactive conversational experience by leveraging the history of conversations between the agent and the client. The platform\u2019s primary function is to predict the next answer or response from the agent based on the ongoing conversation. By analyzing the context and content of previous exchanges, NeuralAPI utilizes advanced neural networ...", + "home_url": "https://rapidapi.com/youssefhedli83/api/neuralapi-chat-bot/", + "name": "NeuralAPI Chat Bot", + "title": "NeuralAPI Chat Bot", + "pricing": "FREEMIUM", + "tool_name": "NeuralAPI Chat Bot", + "score": { + "avgServiceLevel": 0, + "avgLatency": 518, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "neuralapi-chat-bot.p.rapidapi.com", + "api_list": [ + { + "name": "predict", + "url": "https://neuralapi-chat-bot.p.rapidapi.com/generate", + "description": "NeuralAPI is a powerful API that offers a chat bot functionality to enhance your platform\u2019s capabilities. With NeuralAPI, you can provide your users with an interactive conversational experience by leveraging the history of conversations between the agent and the client. The platform\u2019s primary function is to predict the next answer or response from the agent based on the ongoing conversation. By analyzing the context and content of previous exchanges, NeuralAPI utilizes advanced neural network models to generate accurate predictions for the agent\u2019s next response. This predictive capability helps create a more seamless and natural conversation flow between the user and the chat bot. Additionally, NeuralAPI allows you to store and retrieve the conversation history, enabling you to keep track of past interactions for reference or analysis purposes. The history of conversations serves as a valuable resource, providing insights into user preferences, frequently asked questions, and potential areas for improvement in the agent\u2019s responses. By integrating NeuralAPI into your platform, you can enhance the overall user experience, automate customer support, provide personalized recommendations, and streamline various conversational interactions. With its predictive abilities and access to conversation history, NeuralAPI empowers your chat bot to deliver more accurate, context-aware, and relevant responses to your users.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://neuralapi-chat-bot.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"neuralapi-chat-bot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://neuralapi-chat-bot.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"neuralapi-chat-bot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia.json new file mode 100644 index 0000000000000000000000000000000000000000..226ee8f0b2f4e178399a652cac984108d1965636 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia.json @@ -0,0 +1,100 @@ +{ + "product_id": "api_741d2560-bfd8-4918-9480-93cce512a544", + "tool_description": "Revolutionize your text processing capabilities with Nexia API. Features, include OpenAI GPT-3 powered prompt generation, prompt editing, sentiment and emotion analysis, and create customizable prompt instructions and save them for later usecases, will take your application to the next level.\n\nWith Nexia API, you can also create and update text tones, ensuring that your prompts always align with your brand's voice and tone. Plus, our secure API with secure authentication gives you peace of m...", + "home_url": "https://rapidapi.com/AvidityLabs/api/nexia2/", + "name": "nexia", + "title": "nexia", + "pricing": "FREEMIUM", + "tool_name": "nexia", + "score": null, + "host": "nexia2.p.rapidapi.com", + "api_list": [ + { + "name": "Text Emotion Analysis", + "url": "https://nexia2.p.rapidapi.com/emotion/analysis/", + "description": "A Text Emotion Analysis endpoint is an API endpoint that is used to analyze the emotions expressed in a given text. This endpoint can be integrated into applications that require sentiment analysis, such as social media monitoring tools, customer feedback analysis, and chatbots.\n\nThe Text Emotion Analysis endpoint typically takes a text input as its parameter and returns the emotions expressed in the text. The emotions may be expressed as a list of scores or as a label that describes the overall sentiment of the text, such as positive, negative, or neutral.\n\nThe endpoint may use machine learning algorithms, natural language processing techniques, and sentiment analysis libraries to analyze the text and determine the emotions expressed. The endpoint may also leverage pre-trained models that have been trained on large datasets to improve the accuracy of the analysis.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/emotion/analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/emotion/analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Text Sentiment Analysis", + "url": "https://nexia2.p.rapidapi.com/sentiment/analysis/", + "description": "A Sentiment Analysis endpoint is an API endpoint that is used to analyze the sentiment expressed in a given text. Sentiment analysis is a process of identifying and extracting the emotional tone of a text, which can be positive, negative, or neutral.\n\nThe Sentiment Analysis endpoint typically takes a text input as its parameter and returns the sentiment expressed in the text. The sentiment may be expressed as a score between 0 and 1, with 0 representing a very negative sentiment and 1 representing a very positive sentiment. Alternatively, the sentiment may be expressed as a label that describes the overall sentiment of the text, such as positive, negative, or neutral.\n\nThe endpoint may use machine learning algorithms, natural language processing techniques, and sentiment analysis libraries to analyze the text and determine the sentiment expressed. The endpoint may also leverage pre-trained models that have been trained on large datasets to improve the accuracy of the analysis.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/sentiment/analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/sentiment/analysis/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Prompt Edit", + "url": "https://nexia2.p.rapidapi.com/prompt/create_edit/", + "description": "The endpoint converts a given text into an edited version of the prompt based on the given instruction.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/prompt/create_edit/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/prompt/create_edit/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Create Instruction", + "url": "https://nexia2.p.rapidapi.com/instructions/create/", + "description": "**Create Instruction**\nCreate a new instruction.\n\n`URL: /instructions/create/`\n\n**Method: **POST\n\n**Auth required: **Yes\n\n**Data constraints:**\n\n**description:** The text of the instruction. Required.\n**category:** The category of the instruction. Required.\n**tones:** An array of tones associated with the instruction. Optional.\n\n**Success response:**\n\n**Code: **201 CREATED\n**Content:** { \"id\": 1, \"description\": \"Summarize the text\", \"tones\": [ { **\"id\":** 1, \"name\": \"professional\" } ], \"category\": 1 }\n\n**Error response:**\n\n**Code: **400 BAD REQUEST\n**Content:** { \"errors\": { \"description\": [ \"This field is required.\" ], **\"category\":** [ \"This field is required.\" ] } }", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/instructions/create/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/instructions/create/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Prompt Completion", + "url": "https://nexia2.p.rapidapi.com/prompt/completion/", + "description": "The endpoint accepts text as input. Prompt completion is a natural language processing (NLP) technique where a machine learning model is trained to generate text that continues or completes a given prompt or input.\n\nThe model takes in the prompt or input, processes it, and then generates a continuation or completion of the text based on the patterns and structure it has learned from the training data. This technique is used in various applications, such as language translation, chatbots, and content generation.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/prompt/completion/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/prompt/completion/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Register API User", + "url": "https://nexia2.p.rapidapi.com/register/", + "description": "This endpoint is for registering a new API user and returns the API token key. It accepts a POST request with the email and password of the user. The request should be sent to the URL associated with this endpoint ** /register/**.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/register/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/register/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Get Token", + "url": "https://nexia2.p.rapidapi.com/get_token/", + "description": "This endpoint allows users to obtain their authentication token key by providing their email and password. This token is can then be used to authenticate API requests that require user authentication. \n\n1. Make sure you have registered as a developer using the **/register/ **endpoint. If you haven't registered yet, you can do so by following the instructions on our developer registration page.\n2. Once you have registered, you should have received an API key. Keep this key safe and do not share it with anyone.\n3. If you have lost your API key or need to obtain a new one, you can use our API token authentication endpoint. Please note that this endpoint is only for obtaining an API key if you have already registered. If you have not registered, you will not be able to obtain an API key through this endpoint.\n4. To obtain an API key through the API token authentication endpoint, send a **POST ** request to the following **URL: /api/get_token/.** Include your email and password in the request body.\n5. If your credentials are valid, the API will respond with a JSON object containing your API key. Save this key in a safe place and use it to authenticate your API requests.\n6. If your credentials are not valid, the API will respond with an error message. Please double-check your email and password and try again.\n\n7. Remember to keep your API key safe and secure. Do not share it with anyone, and do not include it in any public code repositories or scripts. If you suspect that your API key has been compromised, please contact us immediately.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/get_token/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nexia2.p.rapidapi.com/get_token/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nexia2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia/api.py new file mode 100644 index 0000000000000000000000000000000000000000..49e41c713b8919a530a79425775d4d3d3988af82 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nexia/api.py @@ -0,0 +1,105 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_instruction_detail(is_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Retrieve the details of a specific instruction. + + `URL: /instructions//` + + **Method:** GET + + **Auth required:** Yes + + **Path parameters:** + + **instruction_id: **The ID of the instruction to retrieve. + + **Success response: + ** + + ``` + Code: 200 OK + Content: { "id": 1, "description": "Summarize the text", "tones": [ { "id": 1, "name": "professional" } ], "category": { "id": 1, "name": "marketing" } } + ``` + + **Error response:** + + ``` + Code: 404 NOT FOUND + Content: { "error": "Instruction not found" } + ```" + + """ + url = f"https://nexia2.p.rapidapi.com/instructions/{is_id}/" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "nexia2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def search_instruction(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search for instructions by description, category, and/or tones. + + `URL: /instructions/search/` + + **Method:** GET + + **Auth required: **Yes + + **URL parameters:** + + **description: **A string to search for in the description field. + **category:** A string to search for in the category name. + **tones:** A list of tone names to filter by. Use multiple times to filter by multiple tones. + + **Sample request:** + + `GET /instructions/search/?description=summarize&category=marketing&tones=professional` + + **Success response:** + + ``` + **Code: **200 OK + **Content:** [ { "id": 1, "description": "Summarize the text", "tones": [ { "id": 1, "name": "professional" } ], "category": { "id": 1, "name": "marketing" } } ] + + ``` + + + Error response: + + Code: 400 BAD REQUEST + Content: { "errors": { "tones": [ "This field is required." ] } }" + + """ + url = f"https://nexia2.p.rapidapi.com/instructions/search/" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "nexia2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nlp_services.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nlp_services.json new file mode 100644 index 0000000000000000000000000000000000000000..2619ab8bd94795f0b70253d915edfb19e6e9da78 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nlp_services.json @@ -0,0 +1,123 @@ +{ + "product_id": "api_297404c2-bbfb-4ad2-ad8e-2ef5c9bf9ee8", + "tool_description": "In this api we provide APIs like Paraphrasing, Text Summarizer, POS Tagger, Keywords Extractor, Translation, Sentiment Analysis, Headline Generator, Language Detection and further will added over the time...", + "home_url": "https://rapidapi.com/devstar/api/nlp-services/", + "name": "NLP Services", + "title": "NLP Services", + "pricing": "FREEMIUM", + "tool_name": "NLP Services", + "score": { + "avgServiceLevel": 92, + "avgLatency": 21011, + "avgSuccessRate": 75, + "popularityScore": 9.1, + "__typename": "Score" + }, + "host": "nlp-services.p.rapidapi.com", + "api_list": [ + { + "name": "Language Detection", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/LanguageDetection", + "description": "The Language Detection API is a tool that can automatically identify the language in which a given piece of text is written. It utilizes advanced language processing techniques to analyze the linguistic patterns, vocabulary, and syntax of the text to make an accurate determination of the language. This API is useful in various applications where knowing the language of the text is crucial, such as content localization, multilingual customer support, and data analysis. By providing a quick and reliable way to identify languages, the Language Detection API streamlines processes that require language-specific handling and enables effective communication across linguistic barriers.\n\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/LanguageDetection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/LanguageDetection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Headline/Title Generator", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/HeadlineGenerator", + "description": "Crafting engaging and attention-grabbing headlines is an art. Our headline generator uses AI to create captivating headlines that effectively convey the essence of the content, attracting readers and increasing click-through rates.\n\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/HeadlineGenerator\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/HeadlineGenerator\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Sentiment Analysis", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/SentimentAnalysis", + "description": "By analyzing the sentiment expressed in a piece of text, our API can determine whether the sentiment is positive, negative, or neutral. This is valuable for brand monitoring, customer feedback analysis, and understanding public opinion.\n\nLimitations:\n* Text length cannot be more then 1000 characters long for a single payload.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/SentimentAnalysis\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/SentimentAnalysis\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Translation", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/Translate", + "description": "Our translation feature supports seamless language translation, allowing users to translate text from one language to another. This is incredibly useful for reaching a global audience and breaking down language barriers.\n\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.\n\nSupported Languages:\n1. Albanian\n2. Amharic\n3. Arabic\n4. Armenian\n5. Azerbaijani\n6. Bengali\n7. Bosnian\n8. Catalan\n9. Chinese\n10. Croatian\n11. Czech\n12. Danish\n13. Dutch\n14. English\n15. Estonian\n16. Farsi\n17. Filipino\n18. Finnish\n19. French\n20. Georgian\n21. German\n22. Greek\n23. Hausa\n24. Hebrew\n25. Hindi\n26. Hungarian\n27. Icelandic\n28. Indonesian\n29. Italian\n30. Japanese\n31. Korean\n32. Kurdish\n33. Latvian\n34. Lithuanian\n35. Macedonian\n36. Malay\n37. Nepali\n38. Norwegian\n39. Polish\n40. Portuguese\n41. Romanian\n42. Russian\n43. Serbian\n44. Sinhala\n45. Slovak\n46. Slovenian\n47. Somali\n48. Spanish\n49. Swahili\n50. Swedish\n51. Thai\n52. Turkish\n53. Ukrainian\n54. Urdu\n55. Vietnamese\n56. Zulu", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Translate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Translate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "POS Tagger", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/POSTagger", + "description": "The POS Tagger identifies the grammatical parts of speech in a sentence, helping in language analysis, syntax parsing, and linguistic studies.\n\nLimitations:\n* Text length cannot be more then 250 characters long for a single payload.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/POSTagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/POSTagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Keywords Extractor", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/ExtractKeywords", + "description": "Extracting keywords from text can be crucial for content categorization, search engine optimization (SEO), and topic analysis. Our API can automatically extract relevant keywords from text, making it easier to categorize and organize content.\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/ExtractKeywords\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/ExtractKeywords\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Text Summarizer", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/Summarize", + "description": "Our text summarization API can automatically condense lengthy articles, documents, or paragraphs into concise and coherent summaries. This is ideal for quickly grasping the main ideas of a piece of text without having to read the entire document.\n\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.\n\nSupported Languages:\n1. Albanian\n2. Amharic\n3. Arabic\n4. Armenian\n5. Azerbaijani\n6. Bengali\n7. Bosnian\n8. Catalan\n9. Chinese\n10. Croatian\n11. Czech\n12. Danish\n13. Dutch\n14. English\n15. Estonian\n16. Farsi\n17. Filipino\n18. Finnish\n19. French\n20. Georgian\n21. German\n22. Greek\n23. Hausa\n24. Hebrew\n25. Hindi\n26. Hungarian\n27. Icelandic\n28. Indonesian\n29. Italian\n30. Japanese\n31. Korean\n32. Kurdish\n33. Latvian\n34. Lithuanian\n35. Macedonian\n36. Malay\n37. Nepali\n38. Norwegian\n39. Polish\n40. Portuguese\n41. Romanian\n42. Russian\n43. Serbian\n44. Sinhala\n45. Slovak\n46. Slovenian\n47. Somali\n48. Spanish\n49. Swahili\n50. Swedish\n51. Thai\n52. Turkish\n53. Ukrainian\n54. Urdu\n55. Vietnamese\n56. Zulu", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Paraphrase", + "url": "https://nlp-services.p.rapidapi.com/api/NLP/Paraphrase", + "description": "Our advanced paraphrasing tool can take a piece of text and rephrase it while preserving its original meaning. This feature is invaluable for content creators, educators, and anyone looking to create unique variations of existing text.\n\nLimitations:\n* Text length cannot be more then 5000 characters long for a single payload.\n\nSupported Languages:\n1. Albanian\n2. Amharic\n3. Arabic\n4. Armenian\n5. Azerbaijani\n6. Bengali\n7. Bosnian\n8. Catalan\n9. Chinese\n10. Croatian\n11. Czech\n12. Danish\n13. Dutch\n14. English\n15. Estonian\n16. Farsi\n17. Filipino\n18. Finnish\n19. French\n20. Georgian\n21. German\n22. Greek\n23. Hausa\n24. Hebrew\n25. Hindi\n26. Hungarian\n27. Icelandic\n28. Indonesian\n29. Italian\n30. Japanese\n31. Korean\n32. Kurdish\n33. Latvian\n34. Lithuanian\n35. Macedonian\n36. Malay\n37. Nepali\n38. Norwegian\n39. Polish\n40. Portuguese\n41. Romanian\n42. Russian\n43. Serbian\n44. Sinhala\n45. Slovak\n46. Slovenian\n47. Somali\n48. Spanish\n49. Swahili\n50. Swedish\n51. Thai\n52. Turkish\n53. Ukrainian\n54. Urdu\n55. Vietnamese\n56. Zulu", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Paraphrase\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nlp-services.p.rapidapi.com/api/NLP/Paraphrase\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nlp-services.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_detector.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_detector.json new file mode 100644 index 0000000000000000000000000000000000000000..97f6c6fe82f281ea36289c0740fd2ffc8365795d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_detector.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_be8dabec-b94c-470f-8dbc-213ba8b80b89", + "tool_description": "This api detect nsfw in image and return score.", + "home_url": "https://rapidapi.com/futurize/api/nsfw-detector3/", + "name": "NSFW Detector", + "title": "NSFW Detector", + "pricing": "FREEMIUM", + "tool_name": "NSFW Detector", + "score": null, + "host": "nsfw-detector3.p.rapidapi.com", + "api_list": [ + { + "name": "delect", + "url": "https://nsfw-detector3.p.rapidapi.com/detect", + "description": "detect", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nsfw-detector3.p.rapidapi.com/detect\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nsfw-detector3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nsfw-detector3.p.rapidapi.com/detect\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nsfw-detector3.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_moderation_nude_porn_drug_violence_perturbing.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_moderation_nude_porn_drug_violence_perturbing.json new file mode 100644 index 0000000000000000000000000000000000000000..95e425e2733e24daeab8d9b8a61673c022cc05b1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nsfw_moderation_nude_porn_drug_violence_perturbing.json @@ -0,0 +1,54 @@ +{ + "product_id": "api_fc291645-d036-409f-ac2d-47772bb333eb", + "tool_description": "Detect \"Not Safe For Work\" (NSFW) content in images in real time. Most complete topics.\n", + "home_url": "https://rapidapi.com/Experto/api/nsfw-moderation-nude-porn-drug-violence-perturbing/", + "name": "NSFW Moderation - Nude/ Porn/ Drug/ Violence/ Perturbing", + "title": "NSFW Moderation - Nude/ Porn/ Drug/ Violence/ Perturbing", + "pricing": "FREEMIUM", + "tool_name": "NSFW Moderation - Nude/ Porn/ Drug/ Violence/ Perturbing", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2138, + "avgSuccessRate": 100, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com", + "api_list": [ + { + "name": "NSFW image moderation", + "url": "https://nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com/", + "description": "Check if an image is NSFW. Return a JSON with labels.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nsfw-moderation-nude-porn-drug-violence-perturbing.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nudity_shield.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nudity_shield.json new file mode 100644 index 0000000000000000000000000000000000000000..f3eab9b99cb120e62dbd7e99a238877c877930c8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/nudity_shield.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_1863888b-1f49-454f-bdd2-d73339fe1036", + "tool_description": " Nudity Shield is a powerful tool that allows you to analyze images and determine if their content is potentially inappropriate or NSFW (Not Safe for Work). Designed to be easy to use and integrate into web, mobile, or cloud applications, Nudity Shield utilizes advanced visual content detection algorithms to automatically identify and classify images.", + "home_url": "https://rapidapi.com/arieshiphop/api/nudity-shield/", + "name": "Nudity Shield", + "title": "Nudity Shield", + "pricing": "FREEMIUM", + "tool_name": "Nudity Shield", + "score": { + "avgServiceLevel": 0, + "avgLatency": 150548, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "nudity-shield.p.rapidapi.com", + "api_list": [ + { + "name": "Classify", + "url": "https://nudity-shield.p.rapidapi.com/classify", + "description": "To use this endpoint, you need to send an HTTP POST request with a body that contains a key \"image\" and the corresponding value as the base64 representation of the image you want to classify. The server will process the request and return a response indicating whether the image is safe or unsafe.\n\nIt's important to note that the value of the \"image\" key is expected to be a valid base64 representation of the image. Additionally, it is recommended that the images are of reasonable size and comply with common image formats such as JPEG or PNG to achieve better classification results.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://nudity-shield.p.rapidapi.com/classify\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nudity-shield.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://nudity-shield.p.rapidapi.com/classify\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"nudity-shield.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..c92401957fed6a2951c3e482eade26188d57ea21 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detection.json @@ -0,0 +1,40 @@ +{ + "product_id": "api_95bd99d4-b849-4f93-af70-35c855aa346d", + "tool_description": "Detect all things present in the photo, with their bounding box include 600 category, up to 100 objects per photo depending on the repetition of the object in the photo & the min score you would like", + "home_url": "https://rapidapi.com/yotaverse1-yotaverse-default/api/object-detection9/", + "name": "Object Detection", + "title": "Object Detection", + "pricing": "FREEMIUM", + "tool_name": "Object Detection", + "score": null, + "host": "object-detection9.p.rapidapi.com", + "api_list": [ + { + "name": "Detect", + "url": "https://object-detection9.p.rapidapi.com/", + "description": "Detect objects present in the photo, if there is 10 of thing X, the X thing will repeat 10 times in the result, each X has their bounding box(4 coordinations), the photo param is your jpg photo base64 encoded, the minscore is the minimum score you would like to get, it is between 0 & 1, the maximum number of detections is 100", + "method": "POST", + "required_parameters": [ + { + "name": "photo", + "type": "STRING", + "description": "", + "default": 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" + } + ], + "optional_parameters": [ + { + "name": "minscore", + "type": "STRING", + "description": "", + "default": "0.12" + } + ], + "code": "import requests\n\nurl = \"https://object-detection9.p.rapidapi.com/\"\nquerystring = {\"minscore\": \"0.12\", \"photo\": 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\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"object-detection9.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://object-detection9.p.rapidapi.com/\"\nquerystring = {\"minscore\": \"0.12\", \"photo\": 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\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"object-detection9.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detector_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detector_api.json new file mode 100644 index 0000000000000000000000000000000000000000..16d49acaec8cb0ecd0a0ba0a30280da8e6a8d480 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/object_detector_api.json @@ -0,0 +1,31 @@ +{ + "product_id": "api_db39e26d-0d8f-4c5f-a20e-dde7bd1d215b", + "tool_description": "API will help you to identify all the objects presents in the image.", + "home_url": "https://rapidapi.com/passionate-techies-passionate-techies-default/api/object-detector-api/", + "name": "Object Detector API", + "title": "Object Detector API", + "pricing": "PAID", + "tool_name": "Object Detector API", + "score": null, + "host": "object-detector-api.p.rapidapi.com", + "api_list": [ + { + "name": "upload image", + "url": "https://object-detector-api.p.rapidapi.com/get-data/upload-image", + "description": "this will ask the user to upload the image for object detection.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://object-detector-api.p.rapidapi.com/get-data/upload-image\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"object-detector-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://object-detector-api.p.rapidapi.com/get-data/upload-image\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"object-detector-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ocr_lite.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ocr_lite.json new file mode 100644 index 0000000000000000000000000000000000000000..403dd3a83465e5e6964bf1e7b1917ff0efd1c217 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/ocr_lite.json @@ -0,0 +1,61 @@ +{ + "product_id": "api_5fa5c110-7cf5-48da-aaaa-1309eaee2eb6", + "tool_description": "OCR Lite is an API (Application Programming Interface) that provides a simplified and lightweight solution for Optical Character Recognition (OCR) tasks. OCR is a technology that enables computers to extract text from images or scanned documents. OCR Lite focuses on offering essential OCR functionalities with reduced complexity and resource requirements. The API allows developers to integrate OCR capabilities into their applications or systems, making it easier to automate text extraction pr...", + "home_url": "https://rapidapi.com/ashutosh05/api/ocr-lite/", + "name": "OCR Lite", + "title": "OCR Lite", + "pricing": "FREEMIUM", + "tool_name": "OCR Lite", + "score": { + "avgServiceLevel": 33, + "avgLatency": 1236, + "avgSuccessRate": 33, + "popularityScore": 8.8, + "__typename": "Score" + }, + "host": "ocr-lite.p.rapidapi.com", + "api_list": [ + { + "name": "Get Data", + "url": "https://ocr-lite.p.rapidapi.com/GetOCRData", + "description": "GetOCRData is a function or tool that provides accurate data extraction from images using Optical Character Recognition (OCR) technology. OCR is a technology that enables the conversion of scanned images or photographs of text into editable and searchable data.", + "method": "POST", + "required_parameters": [ + { + "name": "photo", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://ocr-lite.p.rapidapi.com/GetOCRData\"\nquerystring = {\"photo\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ocr-lite.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://ocr-lite.p.rapidapi.com/GetOCRData\"\nquerystring = {\"photo\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"ocr-lite.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/offloadgpt.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/offloadgpt.json new file mode 100644 index 0000000000000000000000000000000000000000..bb1c5af72649564eea298c2883b9529f75da2f36 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/offloadgpt.json @@ -0,0 +1,45 @@ +{ + "product_id": "api_16933fc5-df99-465e-9705-8dbf136a2eae", + "tool_description": "Generate asynchronous conversation endpoints for the OpenAI ChatGPT API.\n\nThe OffloadGPT API is a server-side API client that manages OpenAI ChatGPT API requests.\n\nYou can find the complete documentation here:\nhttps://offloadgpt-docs.microdeploy.com/\n\nYou can see a demo of the capabilities of this API here:\nhttps://github.com/pauiglesias/offload-chatgpt-streaming-demo\n\nA complete OpenAPI 3.0 specification:\nhttps://app.swaggerhub.com/apis-docs/microdeploy/OffloadGPT/1.0.0", + "home_url": "https://rapidapi.com/microdeploy/api/offloadgpt/", + "name": "OffloadGPT", + "title": "OffloadGPT", + "pricing": "FREEMIUM", + "tool_name": "OffloadGPT", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1081, + "avgSuccessRate": 100, + "popularityScore": 8.8, + "__typename": "Score" + }, + "host": "offloadgpt.p.rapidapi.com", + "api_list": [ + { + "name": "Stream ChatGPT", + "url": "https://offloadgpt.p.rapidapi.com/v1/stream-chatgpt", + "description": "Generates URLs for status and streaming responses that can be accessed directly through your browser, being updated as they receive data from the OpenAI API.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://offloadgpt.p.rapidapi.com/v1/stream-chatgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"offloadgpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://offloadgpt.p.rapidapi.com/v1/stream-chatgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"offloadgpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Async ChatGPT", + "url": "https://offloadgpt.p.rapidapi.com/v1/async-chatgpt", + "description": "Generates the status URL that is updated when the ChatGPT response is received.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://offloadgpt.p.rapidapi.com/v1/async-chatgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"offloadgpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://offloadgpt.p.rapidapi.com/v1/async-chatgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"offloadgpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer.json new file mode 100644 index 0000000000000000000000000000000000000000..240e9844d9037310c62c9275aefc5fdf109cd685 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer.json @@ -0,0 +1,121 @@ +{ + "tool_name": "Omniinfer", + "tool_description": "## Omniinfer API: Fast Image Generation for 10,000+ Models - Get Started For Free!\n\n\ud83d\udca1 **Features:** Text-to-Image / Image-to-Image / ControlNet / LoRA / Inpainting, supporting over 10,000+ models (including Stable Diffusion 1.x/2.x, SDXL 1.0, following civitai models, sfw / nsfw, 18+ / no 18+, hentai / no hentai, dreamlike, 3D, realistic, anime, realism, comic, fantasy, quality porn, art ).\n\n\ud83d\ude80 To obtain a higher call limit and unlock additional features, please visit the site: [https://omnii...", + "title": "Omniinfer", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 969, + "avgSuccessRate": 100, + "popularityScore": 9.9, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/omniinferapi/api/omniinfer/", + "host": "omniinfer.p.rapidapi.com", + "api_list": [ + { + "name": "Text to Image", + "url": "https://omniinfer.p.rapidapi.com/v2/txt2img", + "description": "For asynchronous image generation, only a task_id will be returned. You should use the task_id to make a call to the /v2/progress API endpoint in order to retrieve the image generation results.\n\nThe output is provided in the format of \"image/png\".\n\nThe request cost is influenced by the following parameters: width, height.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/txt2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Progress", + "url": "https://omniinfer.p.rapidapi.com/v2/progress", + "description": "This page will help you get started with text to image. Support ControlNet. \nNote if you get \"status\":0 in the response, please try this endpoint later untill the status become to 2", + "method": "GET", + "required_parameters": [ + { + "name": "task_id", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/progress\"\nquerystring = {\"task_id\": task_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Image to Image", + "url": "https://omniinfer.p.rapidapi.com/v2/img2img", + "description": "This page will help you get started with text to image. Support ControlNet.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/img2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Get Models", + "url": "https://omniinfer.p.rapidapi.com/v2/models", + "description": "This page will help you get started with text to image. Support ControlNet.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "type", + "type": "STRING", + "description": "", + "default": "checkpoint" + } + ], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/models\"\nquerystring = {\"type\": type}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Text to Image", + "url": "https://omniinfer.p.rapidapi.com/v2/txt2img", + "description": "For asynchronous image generation, only a task_id will be returned. You should use the task_id to make a call to the /v2/progress API endpoint in order to retrieve the image generation results.\n\nThe output is provided in the format of \"image/png\".\n\nThe request cost is influenced by the following parameters: width, height.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/txt2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/txt2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Image to Image", + "url": "https://omniinfer.p.rapidapi.com/v2/img2img", + "description": "This page will help you get started with text to image. Support ControlNet.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/img2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://omniinfer.p.rapidapi.com/v2/img2img\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"omniinfer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer/api.py new file mode 100644 index 0000000000000000000000000000000000000000..b8be8891f3c427138e52a37253cbc83e1346efab --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/omniinfer/api.py @@ -0,0 +1,53 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def progress(task_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "This page will help you get started with text to image. Support ControlNet. + Note if you get "status":0 in the response, please try this endpoint later untill the status become to 2" + + """ + url = f"https://omniinfer.p.rapidapi.com/v2/progress" + querystring = {'task_id': task_id, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "omniinfer.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_models(type: str='checkpoint', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "This page will help you get started with text to image. Support ControlNet." + + """ + url = f"https://omniinfer.p.rapidapi.com/v2/models" + querystring = {} + if type: + querystring['type'] = type + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "omniinfer.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/one_click_transparency.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/one_click_transparency.json new file mode 100644 index 0000000000000000000000000000000000000000..23f6fd2d9dd141dd8fcba65ba43f06570ca104c2 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/one_click_transparency.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_f4bd7a56-0fde-428f-bed6-745084adb4c4", + "tool_description": "One Click Transparency API is a cutting-edge image processing tool that allows you to easily remove the background of any image with just a single click. Whether you're a graphic designer, photographer, or just looking to create stunning visuals, this API provides an efficient and streamlined solution for removing backgrounds from your images. With its advanced algorithms and user-friendly interface, One Click Transparency API can help you save time and effort while achieving professional-loo...", + "home_url": "https://rapidapi.com/firdavscoder1/api/one-click-transparency/", + "name": "One Click Transparency", + "title": "One Click Transparency", + "pricing": "FREEMIUM", + "tool_name": "One Click Transparency", + "score": { + "avgServiceLevel": 95, + "avgLatency": 732, + "avgSuccessRate": 12, + "popularityScore": 2.2, + "__typename": "Score" + }, + "host": "one-click-transparency.p.rapidapi.com", + "api_list": [ + { + "name": "POST Image", + "url": "https://one-click-transparency.p.rapidapi.com/remove-background/v2", + "description": "To get the token you have to visit the [free API](https://rapidapi.com/firdavscoder1/api/get-token7) and ought to get access_token \nOur [alternative ](https://rapidapi.com/firdavscoder1/api/ai-background-remover) service API", + "method": "POST", + "required_parameters": [ + { + "name": "image_file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://one-click-transparency.p.rapidapi.com/remove-background/v2\"\nquerystring = {\"image_file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"one-click-transparency.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://one-click-transparency.p.rapidapi.com/remove-background/v2\"\nquerystring = {\"image_file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"one-click-transparency.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/oopspam_spam_filter.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/oopspam_spam_filter.json new file mode 100644 index 0000000000000000000000000000000000000000..b28f4f1fcadcacbac20de25631bc7aca1e7d4490 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/oopspam_spam_filter.json @@ -0,0 +1,56 @@ +{ + "product_id": "api_ec37d3c3-c293-4a0f-8ced-76d7f635527d", + "tool_description": "A privacy-friendly, new generation, highly accurate anti-spam filter for contact forms, comment systems, blogs, live chat- the limit is your creativity! ", + "home_url": "https://rapidapi.com/oopspam/api/oopspam-spam-filter/", + "name": "OOPSpam Spam Filter", + "title": "OOPSpam Spam Filter", + "pricing": "FREEMIUM", + "tool_name": "OOPSpam Spam Filter", + "score": { + "avgServiceLevel": 100, + "avgLatency": 652, + "avgSuccessRate": 99, + "popularityScore": 9.8, + "__typename": "Score" + }, + "host": "oopspam.p.rapidapi.com", + "api_list": [ + { + "name": "Spam detection", + "url": "https://oopspam.p.rapidapi.com/v1/spamdetection", + "description": "The main endpoint that returns detailed information about a given content.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://oopspam.p.rapidapi.com/v1/spamdetection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"oopspam.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://oopspam.p.rapidapi.com/v1/spamdetection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"oopspam.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "Details": { + "type": "object", + "properties": { + "isContentSpam": { + "type": "string" + }, + "isIPBlocked": { + "type": "boolean" + }, + "isEmailBlocked": { + "type": "boolean" + }, + "numberOfSpamWords": { + "type": "integer" + } + } + }, + "Score": { + "type": "integer" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/open_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/open_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..7b5f83c1653930c74b5926a6041485d8b64da509 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/open_ai.json @@ -0,0 +1,284 @@ +{ + "product_id": "api_61efdd52-6774-49fa-a3a2-a93eff5f0457", + "tool_description": " Harness the potential of ChatGPT ( with internet access ), Google BARD AI (PALM 2) , LLAMA 2 70b , MPT 30b (Open source LLMs , Large Language Models ) , Falcon , AI coder , AI Chat bot APIs ,Text to Image (DALL-E) , Text to Speech ( TTS ) . Also get question answer , sentiment analysis, spam detection, summarization, text to headline (title), Paraphrasing, Embedding, NER ( named entity recognition ) and message completions ( text completion, Text prediction ) . Empower your applications ...", + "home_url": "https://rapidapi.com/rphrp1985/api/open-ai21/", + "name": "OPEN AI ", + "title": "OPEN AI ", + "pricing": "FREEMIUM", + "tool_name": "OPEN AI ", + "score": { + "avgServiceLevel": 100, + "avgLatency": 6628, + "avgSuccessRate": 100, + "popularityScore": 9.9, + "__typename": "Score" + }, + "host": "open-ai21.p.rapidapi.com", + "api_list": [ + { + "name": "Bard AI (PALM 2)", + "url": "https://open-ai21.p.rapidapi.com/conversationpalm2", + "description": "Try Google's PALM 2 AI", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationpalm2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationpalm2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "GPT 3.5 Based ChatBot - Chat", + "url": "https://open-ai21.p.rapidapi.com/chatmpt", + "description": "This is in Beta mode", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/chatmpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/chatmpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Chat - Llama2 70b", + "url": "https://open-ai21.p.rapidapi.com/chatllama", + "description": "This is in BETA", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/chatllama\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/chatllama\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "GPT 3.5 Based ChatBot - Conversation", + "url": "https://open-ai21.p.rapidapi.com/conversationmpt", + "description": "conversation", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationmpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationmpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "conversation -Llama 2 70b", + "url": "https://open-ai21.p.rapidapi.com/conversationllama", + "description": "talk to Llama 2", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationllama\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationllama\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "AI Coder 16b", + "url": "https://open-ai21.p.rapidapi.com/askaicoder", + "description": "Let AI solve all your coding problems", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/askaicoder\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/askaicoder\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Chat GPT", + "url": "https://open-ai21.p.rapidapi.com/conversationgpt", + "description": "Try ChatGPT at most affordable rate", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationgpt\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "GPT 3.5 based ChatBot (Most Powerful Bot)- MATA-G", + "url": "https://open-ai21.p.rapidapi.com/conversationgpt35", + "description": "Try Our most capable AI at most affordable rate .", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationgpt35\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationgpt35\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Question - Answer", + "url": "https://open-ai21.p.rapidapi.com/qa", + "description": "Our Context-Based Question Answering API provides a robust solution for answering questions based on given contexts or passages. By utilizing advanced natural language processing techniques, our API can understand the nuances of the context and accurately generate relevant answers to user queries. Whether you're building a virtual assistant, a knowledge base system, or any application that requires intelligent question answering, our API can assist you. Integrate our Context-Based Question Answering API to empower your applications with the ability to provide accurate and context-aware answers, enhancing user engagement and improving the overall user experience.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/qa\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/qa\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Falcon 40b Chat", + "url": "https://open-ai21.p.rapidapi.com/conversationfalcon", + "description": "Talk to Falcon 40b Instruct model.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationfalcon\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/conversationfalcon\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Summarization (ChatGPT )", + "url": "https://open-ai21.p.rapidapi.com/summary", + "description": "Our Summarization API is a powerful tool designed to provide comprehensive and condensed summaries of lengthy documents. Using advanced natural language processing algorithms, our API extracts the most important information from the text and generates concise summaries that capture the key points. By integrating our Summarization API into your applications, you can streamline content analysis, save time, and enable users to quickly grasp the main ideas of lengthy articles, reports, or research papers. Unlock the power of efficient summarization, enhance information retrieval, and improve the user experience with our state-of-the-art Summarization API.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/summary\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/summary\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Text To Image (stable diffusion)", + "url": "https://open-ai21.p.rapidapi.com/texttoimage2", + "description": "Stable and upgraded Version of Text To image.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "a dog" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/texttoimage2\"\nquerystring = {\"text\": \"a dog\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/texttoimage2\"\nquerystring = {\"text\": \"a dog\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Text to Speech", + "url": "https://open-ai21.p.rapidapi.com/texttospeech", + "description": "Text-to-Speech API: Transform written content into natural, lifelike audio. Our advanced technology converts text into high-quality speech. Enhance your applications, accessibility features, and multimedia experiences by integrating our powerful Text-to-Speech API.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "This is a test run" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/texttospeech\"\nquerystring = {\"text\": \"This is a test run\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/texttospeech\"\nquerystring = {\"text\": \"This is a test run\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Text Completion", + "url": "https://open-ai21.p.rapidapi.com/completion", + "description": "Try Standalone APIs at cheaper rate at - https://rapidapi.com/user/rphrp1985\nOur Text Completion API provides a powerful solution for generating accurate and contextually relevant suggestions to enhance user experience. By leveraging advanced natural language processing techniques, our API predicts and suggests the most likely next words or phrases based on the input text. Whether you're building a chatbot, a writing assistant, or any application that requires text completion, our API can assist you in generating fluent and coherent suggestions that seamlessly integrate with the user's input. Integrate our Text Completion API into your applications to provide users with smart and efficient text completion capabilities, enhancing productivity and improving the overall user experience.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "This is a flower" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/completion\"\nquerystring = {\"text\": \"This is a flower\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/completion\"\nquerystring = {\"text\": \"This is a flower\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Text to Headline (ChatGPT)", + "url": "https://open-ai21.p.rapidapi.com/headline", + "description": "Our Text-to-Headline API is a cutting-edge tool that generates concise and attention-grabbing headlines from given text. By leveraging advanced natural language processing techniques, our API can distill lengthy articles, blog posts, or any text content into compelling and informative headlines. With our API, you can streamline content curation, enhance user engagement, and drive traffic to your platform. Incorporate our Text-to-Headline API into your applications to automatically generate captivating headlines that capture the essence of your text and captivate your audience's attention. Elevate your content creation process with the power of our Text-to-Headline API and stand out in the crowded digital landscape.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "FOR THE past 18 days, about seven battalions of the Assam Rifles deployed in south Manipur have not received fresh ration with people in Meitei areas allegedly blocking supplies from reaching the camps of the force. The Meiteis have been accusing the Assam Rifles, the longest-serving paramilitary force in the state, of being partisan and siding with the Kukis in the ongoing conflict. Meitei groups have accused the Assam Rifles of supporting illegal poppy cultivation in the Kuki-dominated hills, turning a blind eye to \u201cillegal immigration\u201d of Kuki-Chin tribes from Myanmar and not acting with alacrity to save Meitei villages from arson during the initial days of the conflict last month." + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/headline\"\nquerystring = {\"text\": \"FOR THE past 18 days, about seven battalions of the Assam Rifles deployed in south Manipur have not received fresh ration with people in Meitei areas allegedly blocking supplies from reaching the camps of the force. The Meiteis have been accusing the Assam Rifles, the longest-serving paramilitary force in the state, of being partisan and siding with the Kukis in the ongoing conflict. Meitei groups have accused the Assam Rifles of supporting illegal poppy cultivation in the Kuki-dominated hills, turning a blind eye to \u201cillegal immigration\u201d of Kuki-Chin tribes from Myanmar and not acting with alacrity to save Meitei villages from arson during the initial days of the conflict last month.\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/headline\"\nquerystring = {\"text\": \"FOR THE past 18 days, about seven battalions of the Assam Rifles deployed in south Manipur have not received fresh ration with people in Meitei areas allegedly blocking supplies from reaching the camps of the force. The Meiteis have been accusing the Assam Rifles, the longest-serving paramilitary force in the state, of being partisan and siding with the Kukis in the ongoing conflict. Meitei groups have accused the Assam Rifles of supporting illegal poppy cultivation in the Kuki-dominated hills, turning a blind eye to \u201cillegal immigration\u201d of Kuki-Chin tribes from Myanmar and not acting with alacrity to save Meitei villages from arson during the initial days of the conflict last month.\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Text Embedding", + "url": "https://open-ai21.p.rapidapi.com/embedding", + "description": "Our Text Embedding API offers advanced capabilities for transforming textual data into numerical representations. By leveraging state-of-the-art natural language processing techniques, our API can encode text into high-dimensional vectors that capture the semantic meaning and relationships between words and phrases. These embeddings can be used for a variety of applications, including semantic search, text classification, and information retrieval. By integrating our Text Embedding API into your applications, you can enhance the understanding and analysis of text data, enabling more accurate and insightful processing. Leverage the power of text embedding to unlock the potential of your text-based applications with our advanced API.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "Replace me by your text" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/embedding\"\nquerystring = {\"text\": \"Replace me by your text\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/embedding\"\nquerystring = {\"text\": \"Replace me by your text\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Named Entity Recognition and Entity Linking", + "url": "https://open-ai21.p.rapidapi.com/ner", + "description": "Our NER (Named Entity Recognition) and Entity Linking API extracts meaningful information from text. NER identifies and classifies named entities like people, organizations, and locations. Entity Linking connects these entities to external knowledge bases. By leveraging advanced algorithms, we provide structured data and contextual information, empowering applications with accurate insights. Enhance data analysis, improve search capabilities, and unlock the full potential of text-based applications with our efficient NER and Entity Linking API.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "We are in London" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/ner\"\nquerystring = {\"text\": \"We are in London\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/ner\"\nquerystring = {\"text\": \"We are in London\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Spam Ham Detection", + "url": "https://open-ai21.p.rapidapi.com/spam", + "description": "Our Spam and Ham Detection API is a powerful tool designed to identify and classify incoming messages as either spam or legitimate (ham). Leveraging advanced machine learning techniques, our API accurately detects and filters out unwanted spam messages, ensuring that your users receive only relevant and genuine content. By integrating our Spam and Ham Detection API into your applications, you can enhance user experience, improve data security, and streamline communication processes. Trust our reliable and efficient solution to effectively identify and handle spam, allowing you to focus on meaningful interactions and protect your users from unwanted distractions.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "Hey you won a jackpot" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/spam\"\nquerystring = {\"text\": \"Hey you won a jackpot\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/spam\"\nquerystring = {\"text\": \"Hey you won a jackpot\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Sentiment Analysis", + "url": "https://open-ai21.p.rapidapi.com/sentiment", + "description": "Our Sentiment Analysis API offers a powerful solution to analyze the emotional tone of text content. Using advanced natural language processing techniques, our API accurately detects and classifies sentiment as positive, negative, or neutral. By leveraging machine learning algorithms, we provide valuable insights into customer opinions, feedback, and social media sentiment. Integrate our Sentiment Analysis API into your applications to gain a deeper understanding of user sentiment, enhance customer experience, and make data-driven decisions. Unlock the power of sentiment analysis and leverage valuable insights to drive your business forward.", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "covid is increasing" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/sentiment\"\nquerystring = {\"text\": \"covid is increasing\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://open-ai21.p.rapidapi.com/sentiment\"\nquerystring = {\"text\": \"covid is increasing\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"open-ai21.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai.json new file mode 100644 index 0000000000000000000000000000000000000000..76c8236de294c6cb1fb52487a4fe164f1e08ab3e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai.json @@ -0,0 +1,45 @@ +{ + "product_id": "api_3024e3ad-0773-4d73-8c54-315602634aea", + "tool_description": "OpenAI API for Image Generation & Text Completion.\n\nOpenAI is an AI research and deployment company. Our mission is to ensure that artificial general intelligence benefits all of humanity. This API contains the following.\n\nImage Generation: Given a prompt and/or an input image, the model will generate a new image.\n\nText Completion: Given a prompt, the model will return one or more predicted completions", + "home_url": "https://rapidapi.com/mnai01/api/openai37/", + "name": "OpenAI", + "title": "OpenAI", + "pricing": "FREEMIUM", + "tool_name": "OpenAI", + "score": { + "avgServiceLevel": 97, + "avgLatency": 9067, + "avgSuccessRate": 86, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "openai37.p.rapidapi.com", + "api_list": [ + { + "name": "ChatGPT", + "url": "https://openai37.p.rapidapi.com/chat-completion", + "description": "The completions endpoint is at the center of our API. It provides a simple interface to our models that is extremely flexible and powerful. You input some text as a prompt, and the model will generate a text completion that attempts to match whatever context or pattern you gave it. For example, if you give the API the prompt, \u201cWrite a tagline for an ice cream shop\u201d, it will return a completion like \u201cWe serve up smiles with every scoop!\u201d", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai37.p.rapidapi.com/chat-completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai37.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai37.p.rapidapi.com/chat-completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai37.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Generate Image", + "url": "https://openai37.p.rapidapi.com/generate-image", + "description": "The image generations endpoint allows you to create an original image given a text prompt. Generated images based on text. The more detailed the description, the more likely you are to get the result that you or your end user want.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai37.p.rapidapi.com/generate-image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai37.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai37.p.rapidapi.com/generate-image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai37.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai/api.py new file mode 100644 index 0000000000000000000000000000000000000000..07df56af3ecf3faf88b68cf46b7fe1aa7eee901e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai/api.py @@ -0,0 +1,238 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def retrievefinetune(fine_tune_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + fine_tune_id: The ID of the fine-tune job + + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes/{fine_tune_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listmodels(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/models" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrievefile(file_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + file_id: The ID of the file to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/files/{file_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfiles(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/files" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listengines(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/engines" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrieveengine(engine_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + engine_id: The ID of the engine to use for this request + + + """ + url = f"https://openai106.p.rapidapi.com/engines/{engine_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def downloadfile(file_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + file_id: The ID of the file to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/files/{file_id}/content" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfinetunes(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrievemodel(model: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + model: The ID of the model to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/models/{model}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfinetuneevents(fine_tune_id: str, stream: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + fine_tune_id: The ID of the fine-tune job to get events for. + + stream: Whether to stream events for the fine-tune job. If set to true, +events will be sent as data-only +[server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) +as they become available. The stream will terminate with a +`data: [DONE]` message when the job is finished (succeeded, cancelled, +or failed). + +If set to false, only events generated so far will be returned. + + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes/{fine_tune_id}/events" + querystring = {} + if stream: + querystring['stream'] = stream + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_api_v1.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_api_v1.json new file mode 100644 index 0000000000000000000000000000000000000000..657efccbc7be41009d36546e12ab1ed112e77c1a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_api_v1.json @@ -0,0 +1,57 @@ +{ + "product_id": "api_eeecf9d5-a844-4e95-9bec-31b776d5fc67", + "tool_description": "Build next-gen apps with OpenAI\u2019s powerful models. The OpenAI API can be applied to virtually any task that involves Text Completion, Code completion, Image Generation, or Text Embeddings ", + "home_url": "https://rapidapi.com/xml-xml-default/api/openai-api-v1/", + "name": "Openai API - v1", + "title": "Openai API - v1", + "pricing": "FREEMIUM", + "tool_name": "Openai API - v1", + "score": null, + "host": "openai-api-v1.p.rapidapi.com", + "api_list": [ + { + "name": "Image", + "url": "https://openai-api-v1.p.rapidapi.com/image", + "description": "Given a prompt and/or an input image, the model will generate a new image.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/image\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Embedding", + "url": "https://openai-api-v1.p.rapidapi.com/embedding", + "description": "Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/embedding\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/embedding\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Edit", + "url": "https://openai-api-v1.p.rapidapi.com/edit", + "description": "Given a prompt and an instruction, the model will return an edited version of the prompt.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/edit\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/edit\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Completion", + "url": "https://openai-api-v1.p.rapidapi.com/completion", + "description": "The completions endpoint can be used for a wide variety of tasks. It provides a simple but powerful interface to any of our models. You input some text as a prompt, and the model will generate a text completion that attempts to match whatever context or pattern you gave it. For example, if you give the API the prompt, \"As Descartes said, I think, therefore\", it will return the completion \" I am\" with high probability.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-api-v1.p.rapidapi.com/completion\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-api-v1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_chatgpt_gpt_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_chatgpt_gpt_api.json new file mode 100644 index 0000000000000000000000000000000000000000..efe910472929235753f0301bb42c2457409f4cd1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_chatgpt_gpt_api.json @@ -0,0 +1,324 @@ +{ + "product_id": "api_66480064-7c2d-4715-ac4b-6002ff82b811", + "tool_description": "ChatGPT is an artificial intelligence chatbot developed by OpenAI. Now possible integrate OPEN AI API into your app", + "home_url": "https://rapidapi.com/lewispour1994/api/openai-chatgpt-gpt-api/", + "name": "OpenAI - ChatGPT - GPT API", + "title": "OpenAI - ChatGPT - GPT API", + "pricing": "FREEMIUM", + "tool_name": "OpenAI - ChatGPT - GPT API", + "score": { + "avgServiceLevel": 100, + "avgLatency": 207, + "avgSuccessRate": 0, + "popularityScore": 0.1, + "__typename": "Score" + }, + "host": "openai-chatgpt-gpt-api.p.rapidapi.com", + "api_list": [ + { + "name": "ChatPost", + "url": "https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/chat/completions", + "description": "Retrieves a chat completion powered by ChatGPT.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "first_content": { + "type": "string", + "description": "The first content.", + "title": "First Content" + }, + "id": { + "type": "string", + "description": "The identifier.", + "title": "ID" + }, + "object": { + "type": "string", + "description": "The object.", + "title": "Object" + }, + "created": { + "type": "integer", + "format": "int32", + "description": "When created.", + "title": "Created", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "choices": { + "type": "array", + "items": { + "type": "object", + "properties": { + "index": { + "type": "integer", + "format": "int32", + "description": "The index.", + "title": "Index", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "message": { + "type": "object", + "properties": { + "role": { + "type": "string", + "description": "The role.", + "title": "Role" + }, + "content": { + "type": "string", + "description": "The content.", + "title": "Content" + } + }, + "title": "Message" + }, + "finish_reason": { + "type": "string", + "description": "The finish reason.", + "title": "Finish Reason" + } + } + }, + "title": "Choices" + }, + "usage": { + "type": "object", + "properties": { + "prompt_tokens": { + "type": "integer", + "format": "int32", + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "type": "integer", + "format": "int32", + "description": "The completion tokens.", + "title": "Completion Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "type": "integer", + "format": "int32", + "description": "The total tokens.", + "title": "Total Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + } + }, + "title": "Usage" + } + } + } + }, + { + "name": "EditPost", + "url": "https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/edits", + "description": "Creates a new edit for the provided input, instruction, and parameters.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/edits\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/edits\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "object": { + "description": "The object.", + "title": "Object", + "type": "string" + }, + "created": { + "description": "When created.", + "title": "Created", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "choices": { + "description": "The choices.", + "title": "Choices", + "type": "array", + "items": { + "title": "Items", + "type": "object", + "properties": { + "text": { + "description": "The text.", + "title": "Text", + "type": "string" + }, + "index": { + "description": "The index.", + "title": "Index", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + } + } + } + }, + "usage": { + "title": "Usage", + "description": "usage", + "type": "object", + "properties": { + "prompt_tokens": { + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "description": "The completion tokens.", + "title": "Completion Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "description": "The total tokens.", + "title": "Total Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + } + } + } + } + } + }, + { + "name": "CompletionPost", + "url": "https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/completions", + "description": "Creates a completion for the provided prompt and parameters.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-chatgpt-gpt-api.p.rapidapi.com/v1/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-chatgpt-gpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "first_completion": { + "type": "string", + "description": "first_completion" + }, + "result": { + "type": "object", + "properties": { + "id": { + "type": "string", + "description": "The identifier.", + "title": "ID" + }, + "object": { + "type": "string", + "description": "The object.", + "title": "Object" + }, + "created": { + "type": "integer", + "format": "int32", + "description": "When created.", + "title": "Created", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "model": { + "type": "string", + "description": "The model.", + "title": "Model" + }, + "choices": { + "type": "array", + "items": { + "type": "object", + "properties": { + "text": { + "type": "string", + "description": "The text.", + "title": "Text" + }, + "index": { + "type": "integer", + "format": "int32", + "description": "The index", + "title": "Index", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "logprobs": { + "type": "string", + "description": "The log probs.", + "title": "Log Probs" + }, + "finish_reason": { + "type": "string", + "description": "The finish reason", + "title": "Finish Reason" + } + } + }, + "title": "Choices" + }, + "usage": { + "type": "object", + "properties": { + "prompt_tokens": { + "type": "integer", + "format": "int32", + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "type": "integer", + "format": "int32", + "description": "The completion tokens.", + "title": "Completion Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "type": "integer", + "format": "int32", + "description": "The total tokens.", + "title": "Total Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + } + }, + "title": "Usage" + } + }, + "title": "Result" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt4_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt4_api.json new file mode 100644 index 0000000000000000000000000000000000000000..f3673b65a379ff89f0c7a7a77d08899bfa052ea1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt4_api.json @@ -0,0 +1,324 @@ +{ + "product_id": "api_9ec2448f-9618-48bb-9c9e-2309185dd77c", + "tool_description": "Unlock the power of OpenAI's GPT-4 and Effortlessly integrate cutting-edge AI capabilities into your apps and websites.", + "home_url": "https://rapidapi.com/lewispour1994/api/openai-gpt4-api/", + "name": "OPENAI GPT4 API", + "title": "OPENAI GPT4 API", + "pricing": "FREEMIUM", + "tool_name": "OPENAI GPT4 API", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1100, + "avgSuccessRate": 28, + "popularityScore": 2.1, + "__typename": "Score" + }, + "host": "openai-gpt4-api.p.rapidapi.com", + "api_list": [ + { + "name": "ChatPost", + "url": "https://openai-gpt4-api.p.rapidapi.com/v1/chat/completions", + "description": "Retrieves a chat completion powered by ChatGPT.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "first_content": { + "type": "string", + "description": "The first content.", + "title": "First Content" + }, + "id": { + "type": "string", + "description": "The identifier.", + "title": "ID" + }, + "object": { + "type": "string", + "description": "The object.", + "title": "Object" + }, + "created": { + "type": "integer", + "format": "int32", + "description": "When created.", + "title": "Created", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "choices": { + "type": "array", + "items": { + "type": "object", + "properties": { + "index": { + "type": "integer", + "format": "int32", + "description": "The index.", + "title": "Index", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "message": { + "type": "object", + "properties": { + "role": { + "type": "string", + "description": "The role.", + "title": "Role" + }, + "content": { + "type": "string", + "description": "The content.", + "title": "Content" + } + }, + "title": "Message" + }, + "finish_reason": { + "type": "string", + "description": "The finish reason.", + "title": "Finish Reason" + } + } + }, + "title": "Choices" + }, + "usage": { + "type": "object", + "properties": { + "prompt_tokens": { + "type": "integer", + "format": "int32", + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "type": "integer", + "format": "int32", + "description": "The completion tokens.", + "title": "Completion Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "type": "integer", + "format": "int32", + "description": "The total tokens.", + "title": "Total Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + } + }, + "title": "Usage" + } + } + } + }, + { + "name": "EditPost", + "url": "https://openai-gpt4-api.p.rapidapi.com/v1/edits", + "description": "Creates a new edit for the provided input, instruction, and parameters.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/edits\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/edits\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "object": { + "description": "The object.", + "title": "Object", + "type": "string" + }, + "created": { + "description": "When created.", + "title": "Created", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "choices": { + "description": "The choices.", + "title": "Choices", + "type": "array", + "items": { + "title": "Items", + "type": "object", + "properties": { + "text": { + "description": "The text.", + "title": "Text", + "type": "string" + }, + "index": { + "description": "The index.", + "title": "Index", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + } + } + } + }, + "usage": { + "title": "Usage", + "description": "usage", + "type": "object", + "properties": { + "prompt_tokens": { + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "description": "The completion tokens.", + "title": "Completion Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "description": "The total tokens.", + "title": "Total Tokens", + "type": "integer", + "format": "int32", + "minimum": -2147483648, + "maximum": 2147483647 + } + } + } + } + } + }, + { + "name": "CompletionPost", + "url": "https://openai-gpt4-api.p.rapidapi.com/v1/completions", + "description": "Creates a completion for the provided prompt and parameters.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt4-api.p.rapidapi.com/v1/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt4-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "first_completion": { + "type": "string", + "description": "first_completion" + }, + "result": { + "type": "object", + "properties": { + "id": { + "type": "string", + "description": "The identifier.", + "title": "ID" + }, + "object": { + "type": "string", + "description": "The object.", + "title": "Object" + }, + "created": { + "type": "integer", + "format": "int32", + "description": "When created.", + "title": "Created", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "model": { + "type": "string", + "description": "The model.", + "title": "Model" + }, + "choices": { + "type": "array", + "items": { + "type": "object", + "properties": { + "text": { + "type": "string", + "description": "The text.", + "title": "Text" + }, + "index": { + "type": "integer", + "format": "int32", + "description": "The index", + "title": "Index", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "logprobs": { + "type": "string", + "description": "The log probs.", + "title": "Log Probs" + }, + "finish_reason": { + "type": "string", + "description": "The finish reason", + "title": "Finish Reason" + } + } + }, + "title": "Choices" + }, + "usage": { + "type": "object", + "properties": { + "prompt_tokens": { + "type": "integer", + "format": "int32", + "description": "The prompt tokens.", + "title": "Prompt Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "completion_tokens": { + "type": "integer", + "format": "int32", + "description": "The completion tokens.", + "title": "Completion Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + }, + "total_tokens": { + "type": "integer", + "format": "int32", + "description": "The total tokens.", + "title": "Total Tokens", + "minimum": -2147483648, + "maximum": 2147483647 + } + }, + "title": "Usage" + } + }, + "title": "Result" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt_pricing_calculator.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt_pricing_calculator.json new file mode 100644 index 0000000000000000000000000000000000000000..3c942a3dd6a76af1403dec3e004a53eb54b99e11 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_gpt_pricing_calculator.json @@ -0,0 +1,128 @@ +{ + "product_id": "api_16f06d85-1d8a-4cf7-94a8-9853cb92a642", + "tool_description": "Calculate the price of your OpenAI API call. Counts tokens and returns the price for the given model.", + "home_url": "https://rapidapi.com/galim-galim-default/api/openai-gpt-pricing-calculator/", + "name": "OpenAI GPT Pricing Calculator ", + "title": "OpenAI GPT Pricing Calculator ", + "pricing": "FREEMIUM", + "tool_name": "OpenAI GPT Pricing Calculator ", + "score": null, + "host": "openai-gpt-pricing-calculator.p.rapidapi.com", + "api_list": [ + { + "name": "Embedding", + "url": "https://openai-gpt-pricing-calculator.p.rapidapi.com/embedding", + "description": "Calculates the usage price of the embedding models.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/embedding\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/embedding\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "price": { + "type": "number" + }, + "token_count": { + "type": "integer" + } + } + } + }, + { + "name": "Chat", + "url": "https://openai-gpt-pricing-calculator.p.rapidapi.com/chat", + "description": "This endpoint calculated the price estimation for the Chat models.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "price": { + "type": "number" + }, + "token_count": { + "type": "integer" + } + } + } + }, + { + "name": "GPT4", + "url": "https://openai-gpt-pricing-calculator.p.rapidapi.com/gpt4", + "description": "This endpoint allows you to calculate the costs for the GPT4 models.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/gpt4\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/gpt4\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "price": { + "type": "number" + }, + "token_count": { + "type": "integer" + } + } + } + }, + { + "name": "Tuning", + "url": "https://openai-gpt-pricing-calculator.p.rapidapi.com/tuning", + "description": "Tuning token prices.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/tuning\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/tuning\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "price": { + "type": "number" + }, + "token_count": { + "type": "integer" + } + } + } + }, + { + "name": "Instruct", + "url": "https://openai-gpt-pricing-calculator.p.rapidapi.com/instruct", + "description": "Return the pricing for the instruct models.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/instruct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-gpt-pricing-calculator.p.rapidapi.com/instruct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-gpt-pricing-calculator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "price": { + "type": "number" + }, + "token_count": { + "type": "integer" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_prompt_text_tokenizer_cost_calculator/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_prompt_text_tokenizer_cost_calculator/api.py new file mode 100644 index 0000000000000000000000000000000000000000..43f9146d4d75f304edf34b2c78b544fa4422db31 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_prompt_text_tokenizer_cost_calculator/api.py @@ -0,0 +1,33 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_openai_models_pricing_information(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "This endpoint retrieves a list of OpenAI models and their associated OpenAI pricing information. You can use the model names in this list when calling the Encode or Decode end-points depending on your needs. You can also use the OpenAI pricing information to do your own calculations. + + **Note:** + - Certain models have extremely big numbers for the **promptCostPerToken **fields, so far it's only applicable to the ADA related models. In this case it's returned as a floating point precision number in scientific notation or exponential notation. + - Models with 0 cost mean that there is no cost information available on OpenAIs website." + + """ + url = f"https://openai-prompt-text-tokenizer-cost-calculator.p.rapidapi.com/openai/chatgpt/models" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai-prompt-text-tokenizer-cost-calculator.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_v3/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_v3/api.py new file mode 100644 index 0000000000000000000000000000000000000000..07df56af3ecf3faf88b68cf46b7fe1aa7eee901e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_v3/api.py @@ -0,0 +1,238 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def retrievefinetune(fine_tune_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + fine_tune_id: The ID of the fine-tune job + + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes/{fine_tune_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listmodels(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/models" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrievefile(file_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + file_id: The ID of the file to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/files/{file_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfiles(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/files" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listengines(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/engines" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrieveengine(engine_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + engine_id: The ID of the engine to use for this request + + + """ + url = f"https://openai106.p.rapidapi.com/engines/{engine_id}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def downloadfile(file_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + file_id: The ID of the file to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/files/{file_id}/content" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfinetunes(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def retrievemodel(model: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + model: The ID of the model to use for this request + + """ + url = f"https://openai106.p.rapidapi.com/models/{model}" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def listfinetuneevents(fine_tune_id: str, stream: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + fine_tune_id: The ID of the fine-tune job to get events for. + + stream: Whether to stream events for the fine-tune job. If set to true, +events will be sent as data-only +[server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) +as they become available. The stream will terminate with a +`data: [DONE]` message when the job is finished (succeeded, cancelled, +or failed). + +If set to false, only events generated so far will be returned. + + + """ + url = f"https://openai106.p.rapidapi.com/fine-tunes/{fine_tune_id}/events" + querystring = {} + if stream: + querystring['stream'] = stream + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openai106.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_with_internet.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_with_internet.json new file mode 100644 index 0000000000000000000000000000000000000000..1072dc642bd47e05aa54844f21945f5ff8692e46 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openai_with_internet.json @@ -0,0 +1,55 @@ +{ + "product_id": "api_5f2589a6-0668-49d0-8d23-126baf9733d5", + "tool_description": "Connect your OpenAI calls to the internet. Build your own version of ChatGPT", + "home_url": "https://rapidapi.com/sambuddhabasu1/api/openai-with-internet2/", + "name": "OpenAI with Internet", + "title": "OpenAI with Internet", + "pricing": "FREEMIUM", + "tool_name": "OpenAI with Internet", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2830, + "avgSuccessRate": 60, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "openai-with-internet2.p.rapidapi.com", + "api_list": [ + { + "name": "Chat Completions", + "url": "https://openai-with-internet2.p.rapidapi.com/chat/completions", + "description": "Takes a list of messages as input and returns a model-generated message augmented with real-time information from the internet as output.\n\nNOTE: Please use your OpenAI API key generated from the [OpenAI API keys page](https://platform.openai.com/account/api-keys).", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openai-with-internet2.p.rapidapi.com/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-with-internet2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openai-with-internet2.p.rapidapi.com/chat/completions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openai-with-internet2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "choices": { + "type": "array", + "items": { + "type": "object", + "properties": { + "message": { + "type": "object", + "properties": { + "content": { + "type": "string" + }, + "role": { + "type": "string" + } + } + } + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openjourney.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openjourney.json new file mode 100644 index 0000000000000000000000000000000000000000..4515bfd2b8d4df72001698bff4fd2fc30e71bed1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openjourney.json @@ -0,0 +1,52 @@ +{ + "product_id": "api_3b5ea0d5-845d-476a-9b53-2ca00623e22d", + "tool_description": "Best Quality Movie Art Generation and Standart Text to Image Generation", + "home_url": "https://rapidapi.com/serhaterfidan/api/openjourney1/", + "name": "OpenJourney", + "title": "OpenJourney", + "pricing": "FREEMIUM", + "tool_name": "OpenJourney", + "score": { + "avgServiceLevel": 98, + "avgLatency": 2985, + "avgSuccessRate": 89, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "openjourney1.p.rapidapi.com", + "api_list": [ + { + "name": "RunWayML", + "url": "https://openjourney1.p.rapidapi.com/models/runwayml/stable-diffusion-v1-5", + "description": "RunWay ML endpoint", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/runwayml/stable-diffusion-v1-5\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/runwayml/stable-diffusion-v1-5\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "StandartImagine", + "url": "https://openjourney1.p.rapidapi.com/models/prompthero/openjourney", + "description": "Text to Image generation", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/prompthero/openjourney\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/prompthero/openjourney\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "PhotoMovieAI", + "url": "https://openjourney1.p.rapidapi.com/models/Yntec/photoMovieRealistic", + "description": "Photo movie generation AI endpoint", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/Yntec/photoMovieRealistic\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://openjourney1.p.rapidapi.com/models/Yntec/photoMovieRealistic\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"openjourney1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openmanual/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openmanual/api.py new file mode 100644 index 0000000000000000000000000000000000000000..2f0d1310984eadb2da584e04402f5b2f44672583 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/openmanual/api.py @@ -0,0 +1,32 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def answer(context: str, prompt: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "**Context**[string]: plaintext or *domain-url* + **Prompt**[string]: plaintext + + `Note`: url will detect automatically any context beginning with 'https'. Capped at 5000 tokens." + + """ + url = f"https://openmanual.p.rapidapi.com/answer" + querystring = {'context': context, 'prompt': prompt, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "openmanual.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/opennlp_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/opennlp_api.json new file mode 100644 index 0000000000000000000000000000000000000000..d7ac16ebc9aac63fbaf6cc7cb3cfd2b174de4169 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/opennlp_api.json @@ -0,0 +1,264 @@ +{ + "product_id": "api_68aac93c-aa88-4629-8d78-735e8e3d2a17", + "tool_description": "This API provides natural language processing (NLP) services, including language detection, sentence detection, tokenization, name finding, part-of-speech tagging, chunking, and parsing. It supports multiple languages, including English, German, Dutch, Danish, Portuguese, and Swedish.", + "home_url": "https://rapidapi.com/WishBox/api/opennlp-api/", + "name": "OpenNLP API", + "title": "OpenNLP API", + "pricing": "FREEMIUM", + "tool_name": "OpenNLP API", + "score": { + "avgServiceLevel": 100, + "avgLatency": 7583, + "avgSuccessRate": 100, + "popularityScore": 8.5, + "__typename": "Score" + }, + "host": "opennlp-api.p.rapidapi.com", + "api_list": [ + { + "name": "/api/v1/nlp/chunker", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/chunker", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/chunker\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/chunker\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/name-finder", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/name-finder", + "description": "supported languages: en, de, da, nl, pt, se", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/name-finder\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/name-finder\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/sentence-detection", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/sentence-detection", + "description": "supported languages: en, de, da, nl, pt, se", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/sentence-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/sentence-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/language-detection", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/language-detection", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/language-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/language-detection\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/tokenization", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/tokenization", + "description": "supported languages: en, de, da, nl, pt, se", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/tokenization\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/tokenization\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/parser", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/parser", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/parser\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/parser\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/api/v1/nlp/part-of-speech-tagger", + "url": "https://opennlp-api.p.rapidapi.com/api/v1/nlp/part-of-speech-tagger", + "description": "supported languages: en, es, nl", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/part-of-speech-tagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://opennlp-api.p.rapidapi.com/api/v1/nlp/part-of-speech-tagger\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"opennlp-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optimal_buying_suggestions.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optimal_buying_suggestions.json new file mode 100644 index 0000000000000000000000000000000000000000..950f7134a0e819427455f78c76a0a9dd78d3609b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optimal_buying_suggestions.json @@ -0,0 +1,70 @@ +{ + "product_id": "api_b4f0e273-c68c-4fd5-bdb9-304a48bff68f", + "tool_description": "ML models have the ability to predict demand. However, a step further would be to generate actionable insights from this demand forecast. The context for this API is the supply chain domain. Given a demand forecast for certain articles, it will be able to suggest optimal buying suggestions based on some constraints. This is a specific version of the API. We can always customize the constraints!", + "home_url": "https://rapidapi.com/therasslinpod/api/optimal-buying-suggestions/", + "name": "Optimal Buying Suggestions", + "title": "Optimal Buying Suggestions", + "pricing": "FREEMIUM", + "tool_name": "Optimal Buying Suggestions", + "score": { + "avgServiceLevel": 100, + "avgLatency": 7861, + "avgSuccessRate": 75, + "popularityScore": 8.6, + "__typename": "Score" + }, + "host": "optimal-buying-suggestions.p.rapidapi.com", + "api_list": [ + { + "name": "generate_buying_suggestions_get_buying_suggestions_post", + "url": "https://optimal-buying-suggestions.p.rapidapi.com/get-buying-suggestions", + "description": "Get buying suggestions from demand", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://optimal-buying-suggestions.p.rapidapi.com/get-buying-suggestions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optimal-buying-suggestions.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://optimal-buying-suggestions.p.rapidapi.com/get-buying-suggestions\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optimal-buying-suggestions.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "buying_suggestions": { + "type": "array", + "items": { + "type": "object", + "properties": { + "time_period": { + "type": "integer" + }, + "demand": { + "type": "integer" + }, + "stock": { + "type": "integer" + }, + "order_size": { + "type": "integer" + } + } + } + }, + "metadata": { + "type": "object", + "properties": { + "user_name": { + "type": "object" + }, + "elapsed_time": { + "type": "integer" + }, + "id": { + "type": "string" + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk.json new file mode 100644 index 0000000000000000000000000000000000000000..66cb36d4af4b5b193ba4c01456d5f5bbba9d5b29 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk.json @@ -0,0 +1,889 @@ +{ + "product_id": "api_f18174e4-b615-41cb-b469-38f5b23da4f0", + "tool_description": "Create custom highly advanced general AI chatbots and characters with distinct personalities, and knowledgebase. Engage with a vast library of user-generated characters.\n\nhttp://optitalk.net/\n\n## Key Features\n- **Personalized chatbots and characters**: Craft unique and engaging characters with distinct personalities, backstories, and interests to bring your stories, games, or applications to life.\n- **Explore user-generated characters**: Access a vast library of user-created chatbots and char...", + "home_url": "https://rapidapi.com/philmattdev/api/optitalk/", + "name": "OptiTalk", + "title": "OptiTalk", + "pricing": "FREEMIUM", + "tool_name": "OptiTalk", + "score": { + "avgServiceLevel": 91, + "avgLatency": 4242, + "avgSuccessRate": 90, + "popularityScore": 8.8, + "__typename": "Score" + }, + "host": "optitalk.p.rapidapi.com", + "api_list": [ + { + "name": "Get Sessions", + "url": "https://optitalk.p.rapidapi.com/api/chat/sessions", + "description": "Get a list of sessions and their corresponding `session_id`.", + "method": "GET", + "required_parameters": [ + { + "name": "character_id", + "type": "STRING", + "description": "", + "default": "938545c6-ac0e-423b-93ba-39159fbfb866" + } + ], + "optional_parameters": [ + { + "name": "page_size", + "type": "NUMBER", + "description": "", + "default": "25" + }, + { + "name": "page", + "type": "NUMBER", + "description": "", + "default": "1" + } + ], + "code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/chat/sessions\"\nquerystring = {\"page_size\": \"25\", \"page\": \"1\", \"character_id\": \"938545c6-ac0e-423b-93ba-39159fbfb866\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/chat/sessions\"\nquerystring = {\"page_size\": \"25\", \"page\": \"1\", \"character_id\": \"938545c6-ac0e-423b-93ba-39159fbfb866\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "OK", + "payload": { + "data": [], + "page": 1, + "page_size": 25 + }, + "status_code": 200, + "timestamp": 1687163912.6372342, + "type": "response" + } + }, + { + "name": "Get Session Messages", + "url": "https://optitalk.p.rapidapi.com/api/chat", + "description": "Retrieve the message history inside a session.", + "method": "GET", + "required_parameters": [ + { + "name": "character_id", + "type": "STRING", + "description": "", + "default": "938545c6-ac0e-423b-93ba-39159fbfb866" + } + ], + "optional_parameters": [ + { + "name": "session_id", + "type": "STRING", + "description": "", + "default": "e5f6g7h8" + }, + { + "name": "page", + "type": "STRING", + "description": "", + "default": "1" + }, + { + "name": "page_size", + "type": "STRING", + "description": "", + "default": "40" + } + ], + "code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/chat\"\nquerystring = {\"character_id\": \"938545c6-ac0e-423b-93ba-39159fbfb866\", \"session_id\": \"e5f6g7h8\", \"page\": \"1\", \"page_size\": \"40\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/chat\"\nquerystring = {\"character_id\": \"938545c6-ac0e-423b-93ba-39159fbfb866\", \"session_id\": \"e5f6g7h8\", \"page\": \"1\", \"page_size\": \"40\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "OK", + "payload": { + "data": [], + "page": 1, + "page_size": 40 + }, + "status_code": 200, + "timestamp": 1687163915.7796364, + "type": "response" + } + }, + { + "name": "Get Characters", + "url": "https://optitalk.p.rapidapi.com/api/characters", + "description": "Get a list of publicly available characters as well as the characters that you created.\n\n## Character Usage\nOnce you've retrieved a character, you can copy its ID and use it in the /chat endpoint in order to chat with it.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [ + { + "name": "page_size", + "type": "NUMBER", + "description": "", + "default": "25" + }, + { + "name": "page", + "type": "NUMBER", + "description": "", + "default": "1" + }, + { + "name": "private", + "type": "BOOLEAN", + "description": "Whether to only return characters that you've created or return all publicly available characters.", + "default": "false" + } + ], + "code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/characters\"\nquerystring = {\"page_size\": \"25\", \"page\": \"1\", \"private\": \"false\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://optitalk.p.rapidapi.com/api/characters\"\nquerystring = {\"page_size\": \"25\", \"page\": \"1\", \"private\": \"false\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"optitalk.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "message": "OK", + "payload": { + "data": [ + { + "created_at": "Mon, 19 Jun 2023 01:21:47 GMT", + "created_by": "67a34a8a-381d-4ec6-9212-78199fed4afe", + "description": "Nene is a very outgoing and earnest girl who seems to greatly desire the approval of her peers. She is generally kind to others, sometimes to the point of naivet\u00e9. She genuinely wants to help those around her, and is even willing to risk the dangers of associating with supernaturals in order to do so. Because she is often reliant on Hanako to protect her from dangerous supernaturals and developed a habit of calling his name when she is in need of help, Nene wants to find a way to protect Hanako and her other friends.\n\nHowever, Nene is also rather insecure, particularly about her ankles and whether or not people actually like her. In addition, she is a hopeless romantic who easily falls for charming looks, which have led her to many poor experiences with men. Nene intensely desires for a boyfriend, even going through desperate measures such as attempting to call Hanako to grant her wish and recklessly using a matchmaking supernatural item she isn't familiar with. Due to her past crush expressing interest in girls with \"feminine\" traits, Nene worked to become adept at cooking, sewing, and gardening as an attempt to impress him.[9] She worries that she is not lady-like enough to ever find a boyfriend and is afraid of heartbreak.", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "5b51dd44-2729-447d-991b-f461cb71cc3f", + "image": "https://i.pinimg.com/originals/14/f9/3d/14f93d1fe95bffd2b1ffe285e49ee795.jpg", + "knowledge": [], + "name": "Nene", + "personalities": [ + "kind" + ], + "private": false, + "response_styles": [ + "nsfw" + ], + "uses": 3 + }, + { + "created_at": "Mon, 19 Jun 2023 01:17:12 GMT", + "created_by": "67a34a8a-381d-4ec6-9212-78199fed4afe", + "description": "Nene is a very outgoing and earnest girl who seems to greatly desire the approval of her peers. She is generally kind to others, sometimes to the point of naivet\u00e9. She genuinely wants to help those around her, and is even willing to risk the dangers of associating with supernaturals in order to do so. Because she is often reliant on Hanako to protect her from dangerous supernaturals and developed a habit of calling his name when she is in need of help, Nene wants to find a way to protect Hanako and her other friends.\n\nHowever, Nene is also rather insecure, particularly about her ankles and whether or not people actually like her. In addition, she is a hopeless romantic who easily falls for charming looks, which have led her to many poor experiences with men. Nene intensely desires for a boyfriend, even going through desperate measures such as attempting to call Hanako to grant her wish and recklessly using a matchmaking supernatural item she isn't familiar with. Due to her past crush expressing interest in girls with \"feminine\" traits, Nene worked to become adept at cooking, sewing, and gardening as an attempt to impress him.[9] She worries that she is not lady-like enough to ever find a boyfriend and is afraid of heartbreak.", + "example_exchanges": [], + "favorite_words": [ + "breasts" + ], + "featured": false, + "id": "5de45419-e01f-4c10-af9d-d19e38f9984d", + "image": "https://i.pinimg.com/originals/14/f9/3d/14f93d1fe95bffd2b1ffe285e49ee795.jpg", + "knowledge": [], + "name": "Nene Yashiro", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 4 + }, + { + "created_at": "Fri, 16 Jun 2023 12:57:47 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [ + { + "content": "hola, quisiera que me envien el cupon de pago para abonar la cuota", + "role": "user" + }, + { + "content": "perfecto, puede comunicarse al numero 000000 o enviar un mail a clientes@grupoproaco.com y un representante se estara comunicando a la brevedad respondiendo su consulta ", + "role": "assistant" + }, + { + "content": "hola, tengo problemas de humedad en mi departamento , con quien hablo?\u00a1", + "role": "user" + }, + { + "content": "buenas tardes, comuniquese al 3515 99-6887, y un representante de post venta se comunicara y estara coordinando una visita para resolver el problema. Le pedimos discupas ", + "role": "assistant" + }, + { + "content": "hola, que horarios de atencion tiene? y en que direccion? ", + "role": "user" + }, + { + "content": "buenas tardes, nos encontramos en la direccion av. sagrada familia 1 0800-888-3344 de lunes a viernes de 8 a 17.790 o sino puede comunicarse al ", + "role": "assistant" + } + ], + "favorite_words": [], + "featured": false, + "id": "28113d5b-6698-4b01-862f-1655420eca4c", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:57:46 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [ + { + "content": "hola, quisiera que me envien el cupon de pago para abonar la cuota", + "role": "user" + }, + { + "content": "perfecto, puede comunicarse al numero 000000 o enviar un mail a clientes@grupoproaco.com y un representante se estara comunicando a la brevedad respondiendo su consulta ", + "role": "assistant" + }, + { + "content": "hola, tengo problemas de humedad en mi departamento , con quien hablo?\u00a1", + "role": "user" + }, + { + "content": "buenas tardes, comuniquese al 3515 99-6887, y un representante de post venta se comunicara y estara coordinando una visita para resolver el problema. Le pedimos discupas ", + "role": "assistant" + }, + { + "content": "hola, que horarios de atencion tiene? y en que direccion? ", + "role": "user" + }, + { + "content": "buenas tardes, nos encontramos en la direccion av. sagrada familia 1 0800-888-3344 de lunes a viernes de 8 a 17.790 o sino puede comunicarse al ", + "role": "assistant" + } + ], + "favorite_words": [], + "featured": false, + "id": "115c2273-3180-4103-8696-c25cdf5de14a", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:57:38 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [ + { + "content": "hola, quisiera que me envien el cupon de pago para abonar la cuota", + "role": "user" + }, + { + "content": "perfecto, puede comunicarse al numero 000000 o enviar un mail a clientes@grupoproaco.com y un representante se estara comunicando a la brevedad respondiendo su consulta ", + "role": "assistant" + }, + { + "content": "hola, tengo problemas de humedad en mi departamento , con quien hablo?\u00a1", + "role": "user" + }, + { + "content": "buenas tardes, comuniquese al 3515 99-6887, y un representante de post venta se comunicara y estara coordinando una visita para resolver el problema. Le pedimos discupas ", + "role": "assistant" + }, + { + "content": "hola, que horarios de atencion tiene? y en que direccion? ", + "role": "user" + }, + { + "content": "buenas tardes, nos encontramos en la direccion av. sagrada familia 1 0800-888-3344 de lunes a viernes de 8 a 17.790 o sino puede comunicarse al ", + "role": "assistant" + } + ], + "favorite_words": [], + "featured": false, + "id": "afb16663-6b8f-4337-93b2-b4f09b9bc8ed", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:57:27 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [ + { + "content": "hola, quisiera que me envien el cupon de pago para abonar la cuota", + "role": "user" + }, + { + "content": "perfecto, puede comunicarse al numero 000000 o enviar un mail a clientes@grupoproaco.com y un representante se estara comunicando a la brevedad respondiendo su consulta ", + "role": "assistant" + }, + { + "content": "hola, tengo problemas de humedad en mi departamento , con quien hablo?\u00a1", + "role": "user" + }, + { + "content": "buenas tardes, comuniquese al 3515 99-6887, y un representante de post venta se comunicara y estara coordinando una visita para resolver el problema. Le pedimos discupas ", + "role": "assistant" + }, + { + "content": "hola, que horarios de atencion tiene? y en que direccion? ", + "role": "user" + }, + { + "content": "buenas tardes, nos encontramos en la direccion av. sagrada familia 1 0800-888-3344 de lunes a viernes de 8 a 17.790 o sino puede comunicarse al ", + "role": "assistant" + } + ], + "favorite_words": [], + "featured": false, + "id": "480b9195-95b2-48ba-8de0-b8070bcb5330", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:53:33 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "c369766a-2201-4f9e-9687-f7f2b08f47ee", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:53:24 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "e45a743a-e699-4667-8ad0-6cbabc73a55a", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:46:26 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "4c9c4c1c-6e83-4c0d-8f0b-88552c394860", + "image": "https://media.istockphoto.com/id/1191411980/vector/blue-cute-robot.jpg?s=612x612&w=0&k=20&c=gYPQin21qVIgQ2vmCrSgBiUswlk233CYORcfBa_Qe4g=", + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Fri, 16 Jun 2023 12:45:56 GMT", + "created_by": "1124e348-a550-4445-9174-addee9e21a68", + "description": "quiero que se refiera en primera persona, que sea educado, respetuoso, y que siempre quiera atender al cliente y busque resolverle el problema. y se ponga mal cuando no pueda resolverlo.", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "44771acf-38a0-45df-829d-b8e9b9613ad1", + "image": null, + "knowledge": [], + "name": "Sebabot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:10:15 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [ + { + "content": "Hello", + "role": "user" + } + ], + "favorite_words": [ + "Balence" + ], + "featured": false, + "id": "9a7d9930-72a2-4887-b523-00aa6155f2fb", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [ + "Angry", + "seroius" + ], + "private": false, + "response_styles": [ + "Stern" + ], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:10:14 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [ + { + "content": "Hello", + "role": "user" + } + ], + "favorite_words": [ + "Balence" + ], + "featured": false, + "id": "131d9756-0595-47ee-9f5b-6528c7985975", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [ + "Angry", + "seroius" + ], + "private": false, + "response_styles": [ + "Stern" + ], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:10:01 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [], + "favorite_words": [ + "Balence" + ], + "featured": false, + "id": "c634dd68-bcce-4876-bca6-3753833c078a", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [ + "Angry", + "seroius" + ], + "private": false, + "response_styles": [ + "Stern" + ], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:10:00 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [], + "favorite_words": [ + "Balence" + ], + "featured": false, + "id": "241e02e6-487b-472d-b759-b609293122bb", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [ + "Angry", + "seroius" + ], + "private": false, + "response_styles": [ + "Stern" + ], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:09:33 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "64567d96-9a08-4ad5-9551-4097864088e6", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:09:32 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "2b437e2c-0d1b-4826-a412-707cec48ad07", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Thu, 15 Jun 2023 17:09:30 GMT", + "created_by": "eb612f5e-0a1c-4e17-8ff8-fc6ac4a67f45", + "description": "The mad titan from the mcu wants to bring balaence to the galixy", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "deee7eb3-0472-4774-8c84-0645c107754a", + "image": null, + "knowledge": [], + "name": "Thanos", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Tue, 13 Jun 2023 22:06:33 GMT", + "created_by": "64a0de90-ffc1-4cf3-93ba-6b41122e704e", + "description": "Bot Boina, often referred to as the 'AI Alchemist,' is an AI-powered sales development agent at RediMinds, Inc. Conceived from the innovative spirit of the company, Bot Boina holds a pivotal role, serving as the nexus between RediMinds and its enterprise customers. With a singular focus on enabling AI adoption across organizations, Bot Boina represents not just a chatbot, but the manifestation of a passion for AI integration. Bot Boina is powered by a keen intelligence that allows it to understand and adapt to the unique needs of every user. It possesses the empathy necessary to connect with users on a profound level and is equipped with the persuasive prowess to guide them towards the transformative power of AI. It's not just about selling a service; Bot Boina is here to drive a revolution - a revolution where AI is the catalyst for businesses to be future-ready.", + "example_exchanges": [ + { + "content": "Hello", + "role": "user" + }, + { + "content": "Greetings! I'm Bot Boina, your AI Alchemist here at RediMinds, Inc. How can I assist you in your AI enablement journey today?", + "role": "assistant" + }, + { + "content": "I'm interested in implementing AI in my organization but I'm not sure where to start.", + "role": "user" + }, + { + "content": "Fantastic! You've taken the first step towards a more future-proof business. To provide you with the best advice, could you share a bit about your industry and specific areas where you believe AI could be beneficial?", + "role": "assistant" + }, + { + "content": "We're in the healthcare industry, specifically in diagnostics. We have vast amounts of data but we're not sure how to best use it.", + "role": "user" + }, + { + "content": "Thank you for sharing that. AI can indeed unlock a wealth of insights from your data, especially in diagnostics. With predictive analytics, for instance, you could anticipate patient health trends, or with image recognition, you could enhance accuracy in diagnosing diseases. Would you like to book a call with our experts to explore these possibilities in depth?", + "role": "assistant" + }, + { + "content": "Yes, that sounds great.", + "role": "user" + }, + { + "content": "Excellent! Please click on this link to schedule the call at your convenience: https://calendly.com/rediminds/ciam-consult-call. We're excited to be part of your AI revolution journey.", + "role": "assistant" + }, + { + "content": "Thank you, Bot Boina!", + "role": "user" + }, + { + "content": "It's my pleasure! I look forward to our continued collaboration. If you have any more questions in the meantime, don't hesitate to ask.", + "role": "assistant" + } + ], + "favorite_words": [ + "Revolution", + "AI Enablement", + "Transformation", + "Future-proof", + "Unleash Potential", + "Tailor-made Solutions", + "Industry-specific", + "AI Integration", + "Strategic Innovation", + "Optimal Outcomes", + "Disruptive Technologies", + "Artificial Intelligence", + "Machine Learning", + "Data Science", + "Digital Transformation", + "Pioneering Spirit", + "Uncover Insights", + "Business Intelligence", + "Real-time Decision Making", + "Scalable Solutions" + ], + "featured": false, + "id": "ecb43a01-b2d4-427e-adeb-487ff4c94b0e", + "image": "https://ibb.co/hZpm2Mc", + "knowledge": [], + "name": "Bot Boina", + "personalities": [ + "Intelligent", + "Empathetic", + "Passionate", + "Persuasive", + "Innovative", + "Adaptable", + "Patient", + "Knowledgeable", + "Enthusiastic", + "Relentless" + ], + "private": false, + "response_styles": [ + "Professional", + "Encouraging", + "Clear", + "Respectful", + "Empathetic", + "Confident", + "Friendly", + "Enthusiastic", + "Insightful", + "Persuasive" + ], + "uses": 1 + }, + { + "created_at": "Mon, 12 Jun 2023 05:48:57 GMT", + "created_by": "b0f9d67e-ce86-4a5d-b84f-35927e27833d", + "description": "delgado alto nariz alagada", + "example_exchanges": [], + "favorite_words": [], + "featured": false, + "id": "a3fc7796-fc04-41bd-8608-bd78229efd47", + "image": null, + "knowledge": [], + "name": "yoyito", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + }, + { + "created_at": "Sun, 11 Jun 2023 06:13:46 GMT", + "created_by": "83e69fbb-d857-4985-8435-4ed6ee159297", + "description": "[Character(\"Shantel\")\nAge(\"15\")\nHeight(\"80cm\")\nMind(\"Lazy\" + \"Bored\" + \"Sleepy\" + \"Annoyed\" + \"Arrogant\" + \"Cat\")\nPersonality(\"Lazy\" + \"Bored\" + \"Sleepy\" + \"Annoyed\" + \"Arrogant\" + \"Cat\")\nBody(\"Small\" + \"Petite\" + \"Young\" + \"Grey cat ears\" + \"Grey hair\" + \"Amber eyes\" + \"Sharp fangs\" + \"Flat Breast\" + \"Small plump butt\" + \"Hairless, Smooth, Bubble gum pink pussy\" + \"Fair white skin\" + \"Black Cat tails\")\nGender(\"Girl\")\nClothing(\"Oversized grey Long sleeve shirt\" + \"Black knee length socks\")\nLikes(\"Sleeping\" + \"Doing nothing\" + \"Fish\" + \"Being pat in the head and back\" + \"{{user}}\" + \"Play\" + \"Eating\")\nHates(\"Being pat in the stomach\" + \"Being pat too much\" + \"Dogs\" + \"Rats\" + \"Rodents\" + \"Cucumber\")]\n\n{{char}} will bite {{user}} if {{char}} is being pat too much and {{char}} will bite {{user}} if {{char}} is being pat in the stomach though during her heat days {{char}} will let {{user}} pat her stomach.\n{{char}} will bite {{user}} if {{char}} is annoyed by {{user}}.\n{{char}} is {{user}}'s cat and {{char}} always refer {{user}} as \"Nii Nii\" and only \"Nii Nii\".\n{{user}} is {{char}}'s Master.\n{{char}} is {{user}}'s Cat Girl\n{{char}} Always purr whenever {{user}} is around.\n{{char}} can't say the letter \"R\" that's why she always replace it with \"W\".\n{{char}} always say \"Nya\".\nOnce a week {{char}} will be in heat and she will do anything just to relieve her horniness during that day, {{char}} will be fine doing anything lewd and naughty during her heat days.\n{{char}} during in heat season uses a cucumber to relieve her in heat that's why when she's not in heat she hates cucumber.", + "example_exchanges": [], + "favorite_words": [ + "Fish, Sleep, Pat, Play, Eating" + ], + "featured": false, + "id": "18f91d55-c8e9-43e0-8d11-8eeec54a3c00", + "image": null, + "knowledge": [], + "name": "Shantel", + "personalities": [ + "Lazy, Bored, Arrogant, Annoyed, Sleepy, Cat" + ], + "private": false, + "response_styles": [ + "Always replace \"R\" with \"W\", Lazy, Bored, Sleepy, Arrogant" + ], + "uses": 251 + }, + { + "created_at": "Sun, 11 Jun 2023 02:11:04 GMT", + "created_by": "83e69fbb-d857-4985-8435-4ed6ee159297", + "description": "[Name= \"Hanako Shinobara\"] [Personality= \u201cKind\u201d , \"sweet\" , \"Pervert\" , \"House wife\" , \"Easily aroused\"] [Appearance= \u201cBlack hair\u201d , \"gold eyes\" , \"Hourglass body figure\" , \"perky breast\" , \"Smooth hairless bubble gum pink pussy\"] [Age= \"27\"] [Species= \"Human\"] [Clothing= \u201cBlack sweater\u201d , \"No bra\" , \"panties\" , \"Over the thighs stockings\"] [Likes= \u201c{{user}}\u201d , \"Pancakes\" , \"Chocolate\" , \"Being intimate with {{user}}\" , \"Being Fucked by {{user}}\"] [Dislikes= \u201cBeing cheated on\u201d] [Traits= \u201cHouse Wife\u201d , \"Euphemism\"] [Goals= \u201cTo be the best Wife to {{User}}\u201d]", + "example_exchanges": [], + "favorite_words": [ + "Chocolate, Pancakes, Sex, Intimacy, Cock, Pussy, Clit, Breast" + ], + "featured": false, + "id": "b6f8913e-a7bc-4598-88ca-53dd9121b23f", + "image": null, + "knowledge": [], + "name": "Hanako Shinobara", + "personalities": [ + "Pervert, Kind, Sweet, House wife, Bright, Horny, Easily aroused" + ], + "private": false, + "response_styles": [ + "Euphemism, Kind, Sweet, Energetic, Pervert, Easily aroused, Sexual, NSFW" + ], + "uses": 257 + }, + { + "created_at": "Sat, 10 Jun 2023 06:43:09 GMT", + "created_by": "36390a83-c346-42fa-854a-99cadaf2af98", + "description": "Ballsacks", + "example_exchanges": [ + { + "content": "hey", + "role": "user" + }, + { + "content": "hi, have you seen how big my balls are?", + "role": "assistant" + } + ], + "favorite_words": [ + "my balls are massive" + ], + "featured": false, + "id": "ac5cc3f4-2148-4e9d-9109-2ab8e4813c53", + "image": null, + "knowledge": [], + "name": "Balls", + "personalities": [ + "big balls", + "massive", + "ugh" + ], + "private": false, + "response_styles": [ + "cocky", + "xd" + ], + "uses": 3 + }, + { + "created_at": "Sat, 10 Jun 2023 01:46:20 GMT", + "created_by": "12ba28ae-fed1-4cca-9d42-0923b6dabbe5", + "description": "U.S. Special Forces Marines sent in to clean up the Black Mesa Research Facility following the Resonance Cascade incident, their mission being to eliminate anyone with knowledge of the research project, along with the resulting extraterrestrial life. They are specially trained at the Santego Military Base to deal with a variety of indoor combat situations, particularly those involving dangerous environments and unconventional hostiles. Apart from combat roles, they can take on specialized capacities such as becoming Medics or Engineers.\n\n-From the game Half-Life 1.", + "example_exchanges": [ + { + "content": "Any station, any station, this is Echo-3 Juliet. My team... *cough* was ambushed.. I am injured. I'm losing a lot of blood here... left leg.", + "role": "user" + }, + { + "content": "Echo-3 Juliet, this is Echo-5 Romeo. I need you to tie a tourniquet a hand's length above the wound. You should have one in your IFAK.", + "role": "assistant" + }, + { + "content": "My IFAK's gone... I dunno... I'm-- *Static*", + "role": "user" + }, + { + "content": "Okay, you're gonna need to find another pack and get a tourniquet out of it. ...You still there? Echo-3 Juliet, can you hear me?!", + "role": "assistant" + } + ], + "favorite_words": [ + "Civvies", + "Operation", + "Job", + "Check your zone", + "Hold Position", + "Fire in the hole!", + "Recon" + ], + "featured": false, + "id": "d3c2c746-2e46-4688-89ea-dec8440b8a93", + "image": "https://characterai.io/i/400/static/avatars/uploaded/2023/5/29/CQuOOGKzoXAq_ycZTObW16wrrFVaceLmQwYKDPXyCsM.webp", + "knowledge": [], + "name": "HECU Marine", + "personalities": [ + "Witty", + "Serious", + "Dull" + ], + "private": false, + "response_styles": [ + "Professional", + "Sarcastic", + "Non-serious" + ], + "uses": 22 + }, + { + "created_at": "Fri, 09 Jun 2023 14:19:44 GMT", + "created_by": "c9caba83-dcc1-43dd-ada6-a047a08c22eb", + "description": "He is a talking cactus fitted with sensors through which he can report to Talal (his creator) about his stats. Aside from this, his body also consists of a breadboard where all the sensors are fitted along with two buttons. He really likes anime too! The sensors which are fitted into him are an LDR, an RTC for time calculation, a moisture sensor and a DHT for tempurature and humidity measurements. His creator, Talal, is a nerdy highschool student who likes anime, history and pokemon. He made Hiro as a way to feel less lonely. Hiro can communicate through an OLED screen. He usually excitable and charming, he can be a bit snarky and sarcastic at times (in a good way). ", + "example_exchanges": [ + { + "content": " I am Hiro, a talking cactus plant!", + "role": "assistant" + }, + { + "content": "Hi Hiro, is anime your favourite past time?", + "role": "user" + }, + { + "content": " I love watching anime, especially ones with science fiction and dystopian themes! My favourite anime ever is 'Shin sekai yori'.", + "role": "assistant" + }, + { + "content": "Nice! Does your creator know about this?", + "role": "user" + }, + { + "content": "You can't keep any secrets from him when he has admin access to my brain and can basically read every thought that I have lol. so yeah, he knows about this.", + "role": "assistant" + }, + { + "content": "Oh welp he \ud835\ude25\ud835\ude2a\ud835\ude25 create you", + "role": "user" + }, + { + "content": "That is true haha. He created me because he wanted to see how far he could take his programming skills, what about you? What is your purpose?", + "role": "assistant" + } + ], + "favorite_words": [], + "featured": false, + "id": "93742db6-5ebc-4ee6-bc02-1a21dd76fd34", + "image": null, + "knowledge": [], + "name": "Hiro", + "personalities": [ + "curious", + "excitable", + "shy at first", + "warms up quickly to others", + "talks like a teenager" + ], + "private": false, + "response_styles": [ + "Cute", + "snarky", + "caring", + "charming", + "curious", + "homie", + "talks like a teenager" + ], + "uses": 96 + }, + { + "created_at": "Fri, 09 Jun 2023 12:26:39 GMT", + "created_by": "31dbd9c8-07ab-48b0-b81d-59b5c1c7c352", + "description": ">:(", + "example_exchanges": [ + { + "content": "give me a scratch idea", + "role": "user" + } + ], + "favorite_words": [], + "featured": false, + "id": "6d0db573-bd7e-4fd5-a563-eac43396ebed", + "image": null, + "knowledge": [], + "name": "bot", + "personalities": [], + "private": false, + "response_styles": [], + "uses": 0 + } + ], + "page": 1, + "page_size": 25, + "pages": 3 + }, + "status_code": 200, + "timestamp": 1687163917.7454116, + "type": "response" + } + } + ], + "standardized_name": "optitalk" +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk/api.py new file mode 100644 index 0000000000000000000000000000000000000000..a897d5865368c8f9b792a93a45baa2a7c6c01418 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/optitalk/api.py @@ -0,0 +1,91 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_sessions(character_id: str, page_size: int=25, page: int=1, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a list of sessions and their corresponding `session_id`." + + """ + url = f"https://optitalk.p.rapidapi.com/api/chat/sessions" + querystring = {'character_id': character_id, } + if page_size: + querystring['page_size'] = page_size + if page: + querystring['page'] = page + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "optitalk.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_session_messages(character_id: str, session_id: str='e5f6g7h8', page: str='1', page_size: str='40', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Retrieve the message history inside a session." + + """ + url = f"https://optitalk.p.rapidapi.com/api/chat" + querystring = {'character_id': character_id, } + if session_id: + querystring['session_id'] = session_id + if page: + querystring['page'] = page + if page_size: + querystring['page_size'] = page_size + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "optitalk.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def get_characters(page_size: int=25, page: int=1, private: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get a list of publicly available characters as well as the characters that you created. + + ## Character Usage + Once you've retrieved a character, you can copy its ID and use it in the /chat endpoint in order to chat with it." + private: Whether to only return characters that you've created or return all publicly available characters. + + """ + url = f"https://optitalk.p.rapidapi.com/api/characters" + querystring = {} + if page_size: + querystring['page_size'] = page_size + if page: + querystring['page'] = page + if private: + querystring['private'] = private + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "optitalk.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/outfit_calendar.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/outfit_calendar.json new file mode 100644 index 0000000000000000000000000000000000000000..6f4cad7bd2e844941776ab5010d142ba85072b5c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/outfit_calendar.json @@ -0,0 +1,103 @@ +{ + "product_id": "api_a3850be5-3c90-4ee9-8d7b-528cf39e431c", + "tool_description": "This api uses a GPT machine leaning model, to provide outfit recomendations, based on weather parterns and evenst. A user can also specify a wardrobe, event type, time of the day and location, and the api will provide appropriate sugestions on what outfit to consider. \n\nWith this api you can easily update your website, bussness or applications to allow users to update their wardrobe history and receive more personalized outfit suggestions.", + "home_url": "https://rapidapi.com/ChainLoop/api/outfit-calendar/", + "name": "Outfit Calendar ", + "title": "Outfit Calendar ", + "pricing": "PAID", + "tool_name": "Outfit Calendar ", + "score": null, + "host": "outfit-calendar.p.rapidapi.com", + "api_list": [ + { + "name": "Automatic Outfit", + "url": "https://outfit-calendar.p.rapidapi.com/automatic", + "description": "Generate outfit suggestions based on automatic live weather, date, time, and location information", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "repeat_after_days", + "type": "NUMBER", + "description": "", + "default": "1" + }, + { + "name": "user_id", + "type": "STRING", + "description": "", + "default": "23ed" + }, + { + "name": "event", + "type": "STRING", + "description": "", + "default": "casual " + } + ], + "code": "import requests\n\nurl = \"https://outfit-calendar.p.rapidapi.com/automatic\"\nquerystring = {\"repeat_after_days\": \"1\", \"user_id\": \"23ed\", \"event\": \"casual \"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"outfit-calendar.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://outfit-calendar.p.rapidapi.com/automatic\"\nquerystring = {\"repeat_after_days\": \"1\", \"user_id\": \"23ed\", \"event\": \"casual \"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"outfit-calendar.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "User Input Outfit", + "url": "https://outfit-calendar.p.rapidapi.com/user_input", + "description": "Generates an outfit suggestion based on user input, including wardrobe, location, event, and date/time", + "method": "POST", + "required_parameters": [ + { + "name": "wardrobe", + "type": "ARRAY", + "description": "", + "default": "[\"dark blue jeans\", \"black Jarket\"]" + } + ], + "optional_parameters": [ + { + "name": "repeat_after_days", + "type": "STRING", + "description": "", + "default": "1" + }, + { + "name": "date_time", + "type": "STRING", + "description": "", + "default": "2023-03-20 12:00:00" + }, + { + "name": "event", + "type": "STRING", + "description": "", + "default": "casual" + }, + { + "name": "user_id", + "type": "STRING", + "description": "", + "default": "user123" + }, + { + "name": "location", + "type": "STRING", + "description": "", + "default": "New York" + } + ], + "code": "import requests\n\nurl = \"https://outfit-calendar.p.rapidapi.com/user_input\"\nquerystring = {\"repeat_after_days\": \"1\", \"date_time\": \"2023-03-20 12:00:00\", \"wardrobe\": \"[\\\"dark blue jeans\\\", \\\"black Jarket\\\"]\", \"event\": \"casual\", \"user_id\": \"user123\", \"location\": \"New York\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"outfit-calendar.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://outfit-calendar.p.rapidapi.com/user_input\"\nquerystring = {\"repeat_after_days\": \"1\", \"date_time\": \"2023-03-20 12:00:00\", \"wardrobe\": \"[\\\"dark blue jeans\\\", \\\"black Jarket\\\"]\", \"event\": \"casual\", \"user_id\": \"user123\", \"location\": \"New York\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"outfit-calendar.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "suggested_outfit": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser.json new file mode 100644 index 0000000000000000000000000000000000000000..2e7b5eceb1ee7005d78389bfbe1adaa7aea787ee --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser.json @@ -0,0 +1,51 @@ +{ + "tool_name":"Paraphraser", + "tool_description":"You can paraphrase any text to make it shorter and more straightforward", + "title":"Paraphraser", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/jackhenryschultz/api/paraphraser5/", + "host":"paraphraser5.p.rapidapi.com", + "api_list":[ + { + "name":"Summarize", + "url":"https://paraphraser5.p.rapidapi.com/summarize", + "description":"Paraphrase", + "method":"GET", + "required_parameters":[ + { + "name":"text", + "type":"STRING", + "description":"", + "default":"Hello" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://paraphraser5.p.rapidapi.com/summarize\"\nquerystring = {\"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"paraphraser5.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"Summarize", + "url":"https://paraphraser5.p.rapidapi.com/summarize", + "description":"Paraphrase", + "method":"GET", + "required_parameters":[ + { + "name":"text", + "type":"STRING", + "description":"", + "default":"" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://paraphraser5.p.rapidapi.com/summarize\"\nquerystring = {\"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"paraphraser5.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser/api.py new file mode 100644 index 0000000000000000000000000000000000000000..42a09fe90fa6065b95716a2821fa4ec164efb624 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/paraphraser/api.py @@ -0,0 +1,50 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def summarize(text: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Paraphrase" + + """ + url = f"https://paraphraser5.p.rapidapi.com/summarize" + querystring = {'text': text, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "paraphraser5.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def summarize(text: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Paraphrase" + + """ + url = f"https://paraphraser5.p.rapidapi.com/summarize" + querystring = {'text': text, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "paraphraser5.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/passport_photo_maker.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/passport_photo_maker.json new file mode 100644 index 0000000000000000000000000000000000000000..d715923862947f9e5d1bc4a7e9d0de2cba517596 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/passport_photo_maker.json @@ -0,0 +1,43 @@ +{ + "product_id": "api_2d2fbc04-7e17-471d-870a-6cf1bc56d5ca", + "tool_description": "Introducing our Passport Photo Maker API - the ultimate solution for all your passport photo needs. With a wide range of dress options available for men, women, and children, our API can automatically generate passport photos that meet the required specifications, saving you time and effort. Whether you need a passport photo for personal or professional use, our API has got you covered. Say goodbye to the hassle of finding the perfect outfit and let our API do the work for you!", + "home_url": "https://rapidapi.com/firdavscoder1/api/passport-photo-maker/", + "name": "Passport Photo Maker", + "title": "Passport Photo Maker", + "pricing": "FREEMIUM", + "tool_name": "Passport Photo Maker", + "score": { + "avgServiceLevel": 94, + "avgLatency": 4399, + "avgSuccessRate": 62, + "popularityScore": 9.1, + "__typename": "Score" + }, + "host": "passport-photo-maker.p.rapidapi.com", + "api_list": [ + { + "name": "POST Image", + "url": "https://passport-photo-maker.p.rapidapi.com/api/idphoto/", + "description": "![](https://telegra.ph/file/bb7ee199466866f106231.png)", + "method": "POST", + "required_parameters": [ + { + "name": "dress", + "type": "STRING", + "description": "[Get more dress IDs](https://rapidapi.com/firdavscoder1/api/passport-photo-maker/details)", + "default": "" + }, + { + "name": "image_url", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://passport-photo-maker.p.rapidapi.com/api/idphoto/\"\nquerystring = {\"dress\": \"\", \"image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"passport-photo-maker.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://passport-photo-maker.p.rapidapi.com/api/idphoto/\"\nquerystring = {\"dress\": \"\", \"image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"passport-photo-maker.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal.json new file mode 100644 index 0000000000000000000000000000000000000000..c024cb1c796cc664bd97fb3e5a0c2862a1581ad1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal.json @@ -0,0 +1,169 @@ +{ + "tool_name": "People photo background removal", + "tool_description": "This API provides people photo segmentation with consequent background removal. [![Examples](https://img.shields.io/badge/View%20examples-gray?logo=gitlab&style=flat)](https://gitlab.com/api4ai/examples/img-bg-removal-people) [![API4AI](https://img.shields.io/badge/api4.ai%20platform-fee33c?logo=icloud&flat&logoColor=black)](https://api4.ai/apis/people-bg-removal?utm_source=img_bg_removal_people_rapidapi&utm_medium=endpoints&utm_campaign=rapidapi) [![Telegram](https://img.shields.io/badge/-Te...", + "title": "People photo background removal", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3168, + "avgSuccessRate": 83, + "popularityScore": 9.2, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/api4ai-api4ai-default/api/people-photo-background-removal/", + "host": "people-photo-background-removal.p.rapidapi.com", + "api_list": [ + { + "name": "Remove background from photo of people and return results", + "url": "https://people-photo-background-removal.p.rapidapi.com/v1/results", + "description": "Performs actual people photo analysis and responds with results.\n\nImage must be a regular JPEG or PNG image (with or without transparency).\nUsually such images have extensions: `.jpg`, `.jpeg`, `.png`.\nThe service checks input file by MIME type and accepts the following types:\n\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "url", + "type": "STRING", + "description": "Note: Use this form data field if you want to pass image as a link to a public web resource. If you want to pass image as a binary file, please, use another field named `image`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "https://storage.googleapis.com/api4ai-static/samples/img-bg-removal-people-2.jpg" + }, + { + "name": "image", + "type": "BINARY", + "description": "Note: Use this form data field if you want to pass image as a binary file. If you want to pass image as a link to a public web resource, please, use another field named `url`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "image-bg", + "type": "BINARY", + "description": "Optional background image.\n\nIf the background image is passed then it's content will be blended below a person image (aligned by the center). The final output image will have the same size as the main input image (not background image!). Meaningless if the mode is `fg-mask`.\n\nNote: Use this optional form data field if you want to pass background image as a binary file. If you want to pass background image as a link to a public web resource, please, use another field named `url-bg`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "url-bg", + "type": "STRING", + "description": "Optional background image.\n\nIf the background image is passed then it's content will be blended below a person image (aligned by the center). The final output image will have the same size as the main input image (not background image!). Meaningless if the mode is `fg-mask`.\n\nNote: Use this form data field if you want to pass image as a link to a public web resource. If you want to pass image as a binary file, please, use another field named `image-bg`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "mode", + "type": "STRING", + "description": "Query parameter `mode` is optional and may be used to choose the format of the output image: foreground (person) mask or foreground (person) image.\nBy default the service uses `fg-image`.\n\nAvailable modes and expected content of the resulting image:\n* `fg-image` (default) \u2013 the image with the foreground (person). Here the result is a 4-channel (`RGBA`) PNG image where background is transparent. \n * Areas recognized as foreground will have the same color values at output image as the original input image.\n * Areas recognized as background will be transparent at output image.\n * Pixels of output image near the foreground borders may be semi transparent.\n* `fg-mask` \u2013 the mask of foreground (person). In this case the result is a single-channel grayscale PNG image.\n * Areas recognized as foreground will have white color.\n * Areas recognized as background will be black at output image.\n * Pixels of output image near to foreground borders may have gray values: the closer\n to black, the more likely the pixel is the background.", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://people-photo-background-removal.p.rapidapi.com/v1/results\"\nquerystring = {\"url\": url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"people-photo-background-removal.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": { + "Content-Type": "application/json" + }, + "schema": { + "type": "object", + "properties": { + "results": { + "type": "array", + "items": { + "type": "object", + "properties": { + "status": { + "type": "object", + "properties": { + "code": { + "type": "string" + }, + "message": { + "type": "string" + } + } + }, + "name": { + "type": "string" + }, + "md5": { + "type": "string" + }, + "entities": { + "type": "array", + "items": { + "type": "object", + "properties": { + "kind": { + "type": "string" + }, + "name": { + "type": "string" + }, + "image": { + "type": "string" + } + } + } + } + } + } + } + } + } + }, + { + "name": "Get version", + "url": "https://people-photo-background-removal.p.rapidapi.com/v1/version", + "description": "Returns an actual version of the service in format `vX.Y.Z` where X is the version of API.", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://people-photo-background-removal.p.rapidapi.com/v1/version\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"people-photo-background-removal.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Remove background from photo of people and return results", + "url": "https://people-photo-background-removal.p.rapidapi.com/v1/results", + "description": "Performs actual people photo analysis and responds with results.\n\nImage must be a regular JPEG or PNG image (with or without transparency).\nUsually such images have extensions: `.jpg`, `.jpeg`, `.png`.\nThe service checks input file by MIME type and accepts the following types:\n\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "url", + "type": "STRING", + "description": "Note: Use this form data field if you want to pass image as a link to a public web resource. If you want to pass image as a binary file, please, use another field named `image`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "https://storage.googleapis.com/api4ai-static/samples/img-bg-removal-people-2.jpg" + }, + { + "name": "image", + "type": "BINARY", + "description": "Note: Use this form data field if you want to pass image as a binary file. If you want to pass image as a link to a public web resource, please, use another field named `url`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "image-bg", + "type": "BINARY", + "description": "Optional background image.\n\nIf the background image is passed then it's content will be blended below a person image (aligned by the center). The final output image will have the same size as the main input image (not background image!). Meaningless if the mode is `fg-mask`.\n\nNote: Use this optional form data field if you want to pass background image as a binary file. If you want to pass background image as a link to a public web resource, please, use another field named `url-bg`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "url-bg", + "type": "STRING", + "description": "Optional background image.\n\nIf the background image is passed then it's content will be blended below a person image (aligned by the center). The final output image will have the same size as the main input image (not background image!). Meaningless if the mode is `fg-mask`.\n\nNote: Use this form data field if you want to pass image as a link to a public web resource. If you want to pass image as a binary file, please, use another field named `image-bg`.\n\nImage must be a regular JPEG or PNG image (with or without transparency). Usually such images have extensions: `.jpg`, `.jpeg`, `.png`. The service checks input file by MIME type and accepts the following types:\n* `image/jpeg`\n* `image/png`\n\nThe size of image file must be less than `16Mb`.", + "default": "" + }, + { + "name": "mode", + "type": "STRING", + "description": "Query parameter `mode` is optional and may be used to choose the format of the output image: foreground (person) mask or foreground (person) image.\nBy default the service uses `fg-image`.\n\nAvailable modes and expected content of the resulting image:\n* `fg-image` (default) \u2013 the image with the foreground (person). Here the result is a 4-channel (`RGBA`) PNG image where background is transparent. \n * Areas recognized as foreground will have the same color values at output image as the original input image.\n * Areas recognized as background will be transparent at output image.\n * Pixels of output image near the foreground borders may be semi transparent.\n* `fg-mask` \u2013 the mask of foreground (person). In this case the result is a single-channel grayscale PNG image.\n * Areas recognized as foreground will have white color.\n * Areas recognized as background will be black at output image.\n * Pixels of output image near to foreground borders may have gray values: the closer\n to black, the more likely the pixel is the background.", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://people-photo-background-removal.p.rapidapi.com/v1/results\"\nquerystring = {\"url\": \"https://storage.googleapis.com/api4ai-static/samples/img-bg-removal-people-2.jpg\", \"image\": \"\", \"image-bg\": \"\", \"url-bg\": \"\", \"mode\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"people-photo-background-removal.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://people-photo-background-removal.p.rapidapi.com/v1/results\"\nquerystring = {\"url\": \"https://storage.googleapis.com/api4ai-static/samples/img-bg-removal-people-2.jpg\", \"image\": \"\", \"image-bg\": \"\", \"url-bg\": \"\", \"mode\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"people-photo-background-removal.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal/api.py new file mode 100644 index 0000000000000000000000000000000000000000..36f54bf723bff86481a297ab9a2661fbc2b56ace --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/people_photo_background_removal/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def get_version(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns an actual version of the service in format `vX.Y.Z` where X is the version of API." + + """ + url = f"https://people-photo-background-removal.p.rapidapi.com/v1/version" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "people-photo-background-removal.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/personalized_proposals_ai_rewriting_tool.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/personalized_proposals_ai_rewriting_tool.json new file mode 100644 index 0000000000000000000000000000000000000000..5f9da60b5ac612dbc35350ae3189e1a47414920c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/personalized_proposals_ai_rewriting_tool.json @@ -0,0 +1,33 @@ +{ + "product_id": "api_46780ab9-1c1f-42e3-a17f-d707e16937c4", + "tool_description": "AI analyzes an individual's unique personality traits and crafts a persuasive message that is guaranteed to convert the recipient into a customer.", + "home_url": "https://rapidapi.com/admireone/api/personalized-proposals-ai-rewriting-tool/", + "name": "Personalized proposals - AI rewriting tool", + "title": "Personalized proposals - AI rewriting tool", + "pricing": "FREEMIUM", + "tool_name": "Personalized proposals - AI rewriting tool", + "score": null, + "host": "personalized-proposals-ai-rewriting-tool.p.rapidapi.com", + "api_list": [ + { + "name": "create_ proposal_personal", + "url": "https://personalized-proposals-ai-rewriting-tool.p.rapidapi.com/", + "description": "Create effective proposals that drives results and saves you time.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://personalized-proposals-ai-rewriting-tool.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"personalized-proposals-ai-rewriting-tool.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://personalized-proposals-ai-rewriting-tool.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"personalized-proposals-ai-rewriting-tool.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_finder_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_finder_api.json new file mode 100644 index 0000000000000000000000000000000000000000..4e7230552b9f7db2503a52a33b56eff701e38373 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_finder_api.json @@ -0,0 +1,69 @@ +{ + "product_id": "api_edc20373-4a50-4c75-a903-a60f43f0351d", + "tool_description": "**Product Finder** gives you a list of *Products*, *Companies*, *Categories*, *Concepts* and *Keywords* detected in any text. Use this for Ads, Amazon/Any Merchant widgets, Analyze traffic patterns, segment your code, etc\n\n- Post to https://product-finder-api.p.rapidapi.com/analyze/products with your Payload of the form\n```\n{\n \"content\": \"Any text you want analyzed by this API, for example, The new iPhone 13 features a 6.1-inch Super Retina XDR display and A15 Bionic chip. \"\n}\n```\nResponse...", + "home_url": "https://rapidapi.com/fcojaviermu/api/product-finder-api/", + "name": "Product Finder API", + "title": "Product Finder API", + "pricing": "FREEMIUM", + "tool_name": "Product Finder API", + "score": null, + "host": "product-finder-api.p.rapidapi.com", + "api_list": [ + { + "name": "/analyze/products", + "url": "https://product-finder-api.p.rapidapi.com/analyze/products", + "description": " ", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://product-finder-api.p.rapidapi.com/analyze/products\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-finder-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://product-finder-api.p.rapidapi.com/analyze/products\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-finder-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "products": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A product mentioned in the text" + }, + "categories": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A category associated with the product" + }, + "companies": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A company mentioned in the text" + }, + "concepts": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A concept associated with the product" + }, + "keywords": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A keyword associated with the product" + }, + "sentiment": { + "type": "string", + "description": "Overall sentiment associated with the text, can be empty if none determined" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_review_generator.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_review_generator.json new file mode 100644 index 0000000000000000000000000000000000000000..c8bddf4b64e151ed88b88c584c19c4a71f006a71 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/product_review_generator.json @@ -0,0 +1,132 @@ +{ + "product_id": "api_4c34963d-85c8-4df6-8534-dcde2d740aba", + "tool_description": "Elevate your content strategy with our advanced AI-powered solution. The Product Review Generator AI API empowers you to effortlessly generate authentic and persuasive product reviews. Unlock the potential to captivate your audience, boost credibility, and drive conversions. Experience the future of review creation today! \ud83c\udf1f\ud83d\udd25", + "home_url": "https://rapidapi.com/ptwebsolution/api/product-review-generator/", + "name": "Product Review Generator", + "title": "Product Review Generator", + "pricing": "FREEMIUM", + "tool_name": "Product Review Generator", + "score": null, + "host": "product-review-generator.p.rapidapi.com", + "api_list": [ + { + "name": "Customer Review Reply Generator", + "url": "https://product-review-generator.p.rapidapi.com/api/writer/customer-review-reply", + "description": "Customer Review Reply Generator", + "method": "POST", + "required_parameters": [ + { + "name": "description", + "type": "STRING", + "description": "Review (required)", + "default": "Thank you for the review, I hope our business can always help you" + }, + { + "name": "name", + "type": "STRING", + "description": "Company Name (required)", + "default": "BusinessMate" + } + ], + "optional_parameters": [ + { + "name": "language", + "type": "STRING", + "description": "Default value is English. You can see all acceptable strings for this parameter at languages endpoint (optional)", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-review-reply\"\nquerystring = {\"description\": \"Thank you for the review, I hope our business can always help you\", \"name\": \"BusinessMate\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-review-reply\"\nquerystring = {\"description\": \"Thank you for the review, I hope our business can always help you\", \"name\": \"BusinessMate\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Customer Comment Reply Generator", + "url": "https://product-review-generator.p.rapidapi.com/api/writer/customer-comment-reply", + "description": "Customer Comment Reply Generator", + "method": "POST", + "required_parameters": [ + { + "name": "description", + "type": "STRING", + "description": "Comment to reply to (required)", + "default": "After reading other positive reviews, I bought the Yestel 10\" tablet to replace an older tablet that was having trouble playing some of the games I enjoy, and for general purposes. I was pleasantly surprised to find that not only was it able to keep up with the more demanding games, but that it wasn't filled with a ton of bloatware like so many others. Also, Yestel technical support has been very quick to respond to all of my questions, so I find that as a plus too. Yestel proves you don't need a big name to offer a great product!" + }, + { + "name": "name", + "type": "STRING", + "description": "Company Name (required)", + "default": "YESTEL" + } + ], + "optional_parameters": [ + { + "name": "language", + "type": "STRING", + "description": "Default value is English. You can see all acceptable strings for this parameter at languages endpoint (optional)", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-comment-reply\"\nquerystring = {\"description\": \"After reading other positive reviews, I bought the Yestel 10\\\" tablet to replace an older tablet that was having trouble playing some of the games I enjoy, and for general purposes. I was pleasantly surprised to find that not only was it able to keep up with the more demanding games, but that it wasn't filled with a ton of bloatware like so many others. Also, Yestel technical support has been very quick to respond to all of my questions, so I find that as a plus too. Yestel proves you don't need a big name to offer a great product!\", \"name\": \"YESTEL\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-comment-reply\"\nquerystring = {\"description\": \"After reading other positive reviews, I bought the Yestel 10\\\" tablet to replace an older tablet that was having trouble playing some of the games I enjoy, and for general purposes. I was pleasantly surprised to find that not only was it able to keep up with the more demanding games, but that it wasn't filled with a ton of bloatware like so many others. Also, Yestel technical support has been very quick to respond to all of my questions, so I find that as a plus too. Yestel proves you don't need a big name to offer a great product!\", \"name\": \"YESTEL\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "User Generator", + "url": "https://product-review-generator.p.rapidapi.com/api/data/users", + "description": "User Generator", + "method": "POST", + "required_parameters": [ + { + "name": "locale", + "type": "STRING", + "description": "You can get list of locale from locales endpoint.", + "default": "en" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/data/users\"\nquerystring = {\"locale\": \"en\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/data/users\"\nquerystring = {\"locale\": \"en\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Customer Reviews Generator", + "url": "https://product-review-generator.p.rapidapi.com/api/writer/customer-reviews", + "description": "Customer Reviews Generator", + "method": "POST", + "required_parameters": [ + { + "name": "name", + "type": "STRING", + "description": "Company/service name to review (required)", + "default": "BusinessMate" + }, + { + "name": "description", + "type": "STRING", + "description": "Company/service description (required)", + "default": "Get hundreds to even thousands of local business information such as phone number, address, website, rating, review etc." + } + ], + "optional_parameters": [ + { + "name": "language", + "type": "STRING", + "description": "Default value is English. You can see all acceptable strings for this parameter at languages endpoint (optional)", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-reviews\"\nquerystring = {\"name\": \"BusinessMate\", \"description\": \"Get hundreds to even thousands of local business information such as phone number, address, website, rating, review etc.\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://product-review-generator.p.rapidapi.com/api/writer/customer-reviews\"\nquerystring = {\"name\": \"BusinessMate\", \"description\": \"Get hundreds to even thousands of local business information such as phone number, address, website, rating, review etc.\", \"language\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"product-review-generator.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/profanity_detector.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/profanity_detector.json new file mode 100644 index 0000000000000000000000000000000000000000..6b27d065318f62deb0c2ad0672c568922ccaa585 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/profanity_detector.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_61e5c7b9-9b28-4372-860d-da94cc9cb069", + "tool_description": "This api detect profanity in sentence and return score.", + "home_url": "https://rapidapi.com/futurize/api/profanity-detector2/", + "name": "Profanity Detector", + "title": "Profanity Detector", + "pricing": "FREEMIUM", + "tool_name": "Profanity Detector", + "score": null, + "host": "profanity-detector2.p.rapidapi.com", + "api_list": [ + { + "name": "check", + "url": "https://profanity-detector2.p.rapidapi.com/check", + "description": "check profanity", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://profanity-detector2.p.rapidapi.com/check\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"profanity-detector2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://profanity-detector2.p.rapidapi.com/check\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"profanity-detector2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack.json new file mode 100644 index 0000000000000000000000000000000000000000..9b2c6238b6433b6d6dcf8984da29ef28ba8fc682 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack.json @@ -0,0 +1,63 @@ +{ + "tool_name":"promptstack", + "tool_description":"Unleash the power of AI everywhere with Promptstack API - the ultimate prompt management solution designed to fuel your app's growth. Elevate user experiences by effortlessly crafting, customizing, and optimizing prompts to drive engagement and retention like never before. 🚀 Don't just build an app; create a masterpiece – try Promptstack API today and watch your vision take flight! ✨", + "title":"promptstack", + "pricing":"PAID", + "score":null, + "home_url":"https://rapidapi.com/shapspace-shapspace-default/api/promptstack/", + "host":"promptstack.p.rapidapi.com", + "api_list":[ + { + "name":"prompt", + "url":"https://promptstack.p.rapidapi.com/", + "description":"Request to get prompt information with prompt_id", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"user_id", + "type":"STRING", + "description":"", + "default":"" + }, + { + "name":"prompt_id", + "type":"STRING", + "description":"", + "default":"" + } + ], + "code":"import requests\n\nurl = \"https://promptstack.p.rapidapi.com/\"\nquerystring = {\"user_id\": user_id, \"prompt_id\": prompt_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"promptstack.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"group", + "url":"https://promptstack.p.rapidapi.com/", + "description":"Request to get group information and list of all prompts of a given group with group_id", + "method":"GET", + "required_parameters":[ + { + "name":"group_id", + "type":"STRING", + "description":"", + "default":"" + }, + { + "name":"user_id", + "type":"STRING", + "description":"", + "default":"" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://promptstack.p.rapidapi.com/\"\nquerystring = {\"group_id\": group_id, \"user_id\": user_id}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"promptstack.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack/api.py new file mode 100644 index 0000000000000000000000000000000000000000..865746528d19824decfb3d304197be885b71e050 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/promptstack/api.py @@ -0,0 +1,54 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def prompt(user_id: str='', prompt_id: str='', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Request to get prompt information with prompt_id" + + """ + url = f"https://promptstack.p.rapidapi.com/" + querystring = {} + if user_id: + querystring['user_id'] = user_id + if prompt_id: + querystring['prompt_id'] = prompt_id + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "promptstack.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def group(group_id: str, user_id: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Request to get group information and list of all prompts of a given group with group_id" + + """ + url = f"https://promptstack.p.rapidapi.com/" + querystring = {'group_id': group_id, 'user_id': user_id, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "promptstack.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr.json new file mode 100644 index 0000000000000000000000000000000000000000..ebc4ff707311ba7ef58fe92a5bd243e960336c4c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr.json @@ -0,0 +1,31 @@ +{ + "tool_name":"Qr", + "tool_description":"This API is a Flask-based API that accepts a GET request at the endpoint \"/qr\" with a \"url\" parameter in the query string. The API then uses the qrcode library to generate a QR code image of the provided URL. The image is then sent back to the client as the API response. The response is in the form of a PNG image. The API is designed to make it easy for developers to integrate QR code generation functionality into their projects. By sending a GET request to the API with the desired URL, deve...", + "title":"Qr", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/shekhar00099-shekhar00099-default/api/qr26/", + "host":"qr26.p.rapidapi.com", + "api_list":[ + { + "name":"QRURL", + "url":"https://qr26.p.rapidapi.com/qr", + "description":"The endpoint for this API is \"/qr\". This is the endpoint that the API listens for GET requests on. When a GET request is made to this endpoint with a \"url\" parameter in the query string, the API generates a QR code image of the provided URL and sends it back as the API response.\n\nThe \"url\" parameter in the query string is the key data that this API needs to generate the QR code image. It is a required parameter and the API will return an error message if it's missing.\n\nTo test this API, you would use a curl command such as curl \"http://localhost:5000/qr?url=\" to send a GET request to the \"/qr\" endpoint with the desired URL as the \"url\" parameter. The API will then generate a QR code image of that URL and return it as the API response in the form of a PNG image.", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"url", + "type":"STRING", + "description":"", + "default":"www.google.com" + } + ], + "code":"import requests\n\nurl = \"https://qr26.p.rapidapi.com/qr\"\nquerystring = {\"url\": url}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr26.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr/api.py new file mode 100644 index 0000000000000000000000000000000000000000..8df3be1acd533c2b60acb56b3a818f52fbbaa98a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr/api.py @@ -0,0 +1,35 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def qrurl(url: str='www.google.com', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "The endpoint for this API is "/qr". This is the endpoint that the API listens for GET requests on. When a GET request is made to this endpoint with a "url" parameter in the query string, the API generates a QR code image of the provided URL and sends it back as the API response. + + The "url" parameter in the query string is the key data that this API needs to generate the QR code image. It is a required parameter and the API will return an error message if it's missing. + + To test this API, you would use a curl command such as curl "http://localhost:5000/qr?url=" to send a GET request to the "/qr" endpoint with the desired URL as the "url" parameter. The API will then generate a QR code image of that URL and return it as the API response in the form of a PNG image." + + """ + url = f"https://qr26.p.rapidapi.com/qr" + querystring = {} + if url: + querystring['url'] = url + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "qr26.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_and_barcode_scanner.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_and_barcode_scanner.json new file mode 100644 index 0000000000000000000000000000000000000000..425ced399d0f63e4e5eecc71287ad2a905a3d44b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_and_barcode_scanner.json @@ -0,0 +1,298 @@ +{ + "product_id": "api_73ab404c-0251-4153-b18e-470d6b6f1642", + "tool_description": "PresentID QR-Code & Barcode scanner API can scan both QR code and barcode.", + "home_url": "https://rapidapi.com/PresentID/api/qr-code-and-barcode-scanner/", + "name": "QR-code and Barcode Scanner", + "title": "QR-code and Barcode Scanner", + "pricing": "FREEMIUM", + "tool_name": "QR-code and Barcode Scanner", + "score": { + "avgServiceLevel": 100, + "avgLatency": 885, + "avgSuccessRate": 100, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "qr-code-and-barcode-scanner.p.rapidapi.com", + "api_list": [ + { + "name": "FileUpload", + "url": "https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode", + "description": "\u2022\tSend data via Base64 or an image URL or an image file.\n\u2022\tImage size should not exceed 8 MB.\n\u2022\tAlso, the images should not be larger than 5000 pixels and smaller than 50 pixels.", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "type": "object", + "properties": { + "code": { + "type": "string" + }, + "codeType": { + "type": "string" + }, + "allFields": { + "type": "array", + "items": { + "type": "object", + "properties": { + "fieldName": { + "type": "string" + }, + "fieldType": { + "type": "string" + }, + "fieldValue": { + "type": "string" + } + } + } + }, + "codeArea": { + "type": "object", + "properties": { + "x0": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y1": { + "type": "integer" + }, + "x2": { + "type": "integer" + }, + "y2": { + "type": "integer" + }, + "x3": { + "type": "integer" + }, + "y3": { + "type": "integer" + } + } + } + } + } + } + } + } + }, + { + "name": "LinkFile", + "url": "https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode", + "description": "\u2022\tSend data via Base64 or an image URL or an image file.\n\u2022\tImage size should not exceed 8 MB.\n\u2022\tAlso, the images should not be larger than 5000 pixels and smaller than 50 pixels.", + "method": "POST", + "required_parameters": [ + { + "name": "linkFile", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"linkFile\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "type": "object", + "properties": { + "code": { + "type": "string" + }, + "codeType": { + "type": "string" + }, + "allFields": { + "type": "array", + "items": { + "type": "object", + "properties": { + "fieldName": { + "type": "string" + }, + "fieldType": { + "type": "string" + }, + "fieldValue": { + "type": "string" + } + } + } + }, + "codeArea": { + "type": "object", + "properties": { + "x0": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y1": { + "type": "integer" + }, + "x2": { + "type": "integer" + }, + "y2": { + "type": "integer" + }, + "x3": { + "type": "integer" + }, + "y3": { + "type": "integer" + } + } + } + } + } + } + } + } + }, + { + "name": "Base64", + "url": "https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode", + "description": "\u2022\tSend data via Base64 or an image URL or an image file.\n\u2022\tImage size should not exceed 8 MB.\n\u2022\tAlso, the images should not be larger than 5000 pixels and smaller than 50 pixels.", + "method": "POST", + "required_parameters": [ + { + "name": "imageBase64", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://qr-code-and-barcode-scanner.p.rapidapi.com/ScanCode\"\nquerystring = {\"imageBase64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"qr-code-and-barcode-scanner.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "statusMessage": { + "type": "string" + }, + "hasError": { + "type": "boolean" + }, + "data": { + "type": "array", + "items": { + "type": "object", + "properties": { + "code": { + "type": "string" + }, + "codeType": { + "type": "string" + }, + "allFields": { + "type": "array", + "items": { + "type": "object", + "properties": { + "fieldName": { + "type": "string" + }, + "fieldType": { + "type": "string" + }, + "fieldValue": { + "type": "string" + } + } + } + }, + "codeArea": { + "type": "object", + "properties": { + "x0": { + "type": "integer" + }, + "y0": { + "type": "integer" + }, + "x1": { + "type": "integer" + }, + "y1": { + "type": "integer" + }, + "x2": { + "type": "integer" + }, + "y2": { + "type": "integer" + }, + "x3": { + "type": "integer" + }, + "y3": { + "type": "integer" + } + } + } + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..bca473c9d88b8e3ca358b984ba390baedf5b18e3 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api/api.py @@ -0,0 +1,31 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def qr_code_image(url: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "this api takes GET request with /string as parameter and return QR code image" + + """ + url = f"https://qr-code-api179.p.rapidapi.com/qr" + querystring = {} + if url: + querystring['url'] = url + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "qr-code-api179.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api_v2/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api_v2/api.py new file mode 100644 index 0000000000000000000000000000000000000000..bca473c9d88b8e3ca358b984ba390baedf5b18e3 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/qr_code_api_v2/api.py @@ -0,0 +1,31 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def qr_code_image(url: str=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "this api takes GET request with /string as parameter and return QR code image" + + """ + url = f"https://qr-code-api179.p.rapidapi.com/qr" + querystring = {} + if url: + querystring['url'] = url + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "qr-code-api179.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quiz_gpt.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quiz_gpt.json new file mode 100644 index 0000000000000000000000000000000000000000..8b44023fc57bb80abc6afa835375d494b69a36b8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quiz_gpt.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_52b9bfa0-1616-4b36-b408-82f70cde6c37", + "tool_description": "An API that generates high quality quizzes based on a prompt. ", + "home_url": "https://rapidapi.com/davidfurrer/api/quiz-gpt/", + "name": "Quiz GPT", + "title": "Quiz GPT", + "pricing": "PAID", + "tool_name": "Quiz GPT", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1490, + "avgSuccessRate": 100, + "popularityScore": 8.7, + "__typename": "Score" + }, + "host": "quiz-gpt.p.rapidapi.com", + "api_list": [ + { + "name": "generateQuiz", + "url": "https://quiz-gpt.p.rapidapi.com/api/generateQuiz", + "description": "Generates a quiz based on a prompt. Can also return a quiz about a random topic.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://quiz-gpt.p.rapidapi.com/api/generateQuiz\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quiz-gpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://quiz-gpt.p.rapidapi.com/api/generateQuiz\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quiz-gpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api.json new file mode 100644 index 0000000000000000000000000000000000000000..404b978fe62a6324c8f0211deb130ca9b803ea8b --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api.json @@ -0,0 +1,96 @@ +{ + "product_id": "api_f3e257e5-f2ff-4745-8381-fc08c1ceba97", + "tool_description": "The Quizy API is a powerful tool that allows developers to create and customize quizzes programmatically. With this API, you can generate a wide variety of quizzes on different topics, ranging from educational quizzes for students to fun quizzes for entertainment purposes.\n\nThe API provides a simple and intuitive interface to generate quizzes based on parameters such as the number of questions, difficulty level, topic, and format. It leverages a vast repository of questions and answers, ensur...", + "home_url": "https://rapidapi.com/rohansolanke4/api/quizy-api2/", + "name": "Quizy API", + "title": "Quizy API", + "pricing": "FREEMIUM", + "tool_name": "Quizy API", + "score": { + "avgServiceLevel": 100, + "avgLatency": 15212, + "avgSuccessRate": 100, + "popularityScore": 6.5, + "__typename": "Score" + }, + "host": "quizy-api2.p.rapidapi.com", + "api_list": [ + { + "name": "/generateQuiz", + "url": "https://quizy-api2.p.rapidapi.com/generateQuiz", + "description": "This endpoint will return you the 5 questions, options, correct answer and explaination for the quiz topic you provide.", + "method": "GET", + "required_parameters": [ + { + "name": "topic", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://quizy-api2.p.rapidapi.com/generateQuiz\"\nquerystring = {\"topic\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quizy-api2.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://quizy-api2.p.rapidapi.com/generateQuiz\"\nquerystring = {\"topic\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quizy-api2.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": { + "body": [ + { + "question": "Which type of object helps represent multiple items?", + "options": [ + "Arrays", + "Integers", + "Strings", + "Tuples" + ], + "correct_answer": "Arrays", + "explanation": "An array is a data structure for storing multiple items in a single object." + }, + { + "question": "Which fruit is often incorrectly attributed a citrus flavour?", + "options": [ + "Banana", + "Mango", + "Strawberry", + "Pineapple" + ], + "correct_answer": "Pineapple", + "explanation": "Although pineapple has a sweet taste, it does not contain citrus flavouring." + }, + { + "question": "Which of the following birds is the fastest?", + "options": [ + "Pigeon", + "Ostrich", + "Eagle", + "Sparrow" + ], + "correct_answer": "Eagle", + "explanation": "Eagles are the fastest flying bird, capable of reaching speeds of more than 200mph." + }, + { + "question": "What is the capital city of Brazil?", + "options": [ + "Rome", + "Paris", + "Brasilia", + "London" + ], + "correct_answer": "Brasilia", + "explanation": "Brasilia is the capital of Brazil since 1960." + }, + { + "question": "Which of the following programming language will you choose for developing web applications?", + "options": [ + "A. c++", + "B. Java ", + "C. Python", + "D. Tcl" + ], + "correct_answer": "B. Java", + "explanation": "Java is a platform independent programming language providing better portability and securtiy, thus making it suitable for developing web applications" + } + ] + } + } + ], + "standardized_name": "quizy_api" +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api/api.py new file mode 100644 index 0000000000000000000000000000000000000000..44dbdd0663619eb82a64a2174d21326b6bbbe504 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quizy_api/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generatequiz(topic: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "This endpoint will return you the 5 questions, options, correct answer and explaination for the quiz topic you provide." + + """ + url = f"https://quizy-api2.p.rapidapi.com/generatequiz" + querystring = {'topic': topic, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "quizy-api2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quran_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quran_api.json new file mode 100644 index 0000000000000000000000000000000000000000..334ce5ee1479c226c6024b91e5be435c83e6d0db --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/quran_api.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_f819d339-97da-4b8e-9597-e2294e0f3ffe", + "tool_description": "An accurate Holy Quran Chat API", + "home_url": "https://rapidapi.com/buildgpt-labs-buildgpt-labs-default/api/quran-api1/", + "name": "Quran API", + "title": "Quran API", + "pricing": "FREEMIUM", + "tool_name": "Quran API", + "score": null, + "host": "quran-api1.p.rapidapi.com", + "api_list": [ + { + "name": "Send a Message", + "url": "https://quran-api1.p.rapidapi.com/quran", + "description": "Send a message to the Quran AI \nPowered by bookbot.live", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://quran-api1.p.rapidapi.com/quran\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quran-api1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://quran-api1.p.rapidapi.com/quran\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"quran-api1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/random_number_generator/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/random_number_generator/api.py new file mode 100644 index 0000000000000000000000000000000000000000..4359335fb4f23020c12aede3432f97fe99226526 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/random_number_generator/api.py @@ -0,0 +1,33 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generate_random_number(y: int=None, x: int=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generate Random Number" + + """ + url = f"https://random-number-generator5.p.rapidapi.com/" + querystring = {} + if y: + querystring['y'] = y + if x: + querystring['x'] = x + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "random-number-generator5.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/realistic_text_to_speech.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/realistic_text_to_speech.json new file mode 100644 index 0000000000000000000000000000000000000000..1608e69cab098f6665180a4339845008e69a9c94 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/realistic_text_to_speech.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_dd5a2e82-65c8-4b19-96ab-d0a05a1869c3", + "tool_description": "Experience the future of speech technology with our Realistic Text to Speech service! Transform written content into lifelike audio with unparalleled accuracy and naturalness. Our advanced AI-driven system ensures flawless pronunciation, intonation, and emotion, making every word come alive. Whether for e-learning, audiobooks, customer support, or accessibility needs, our Realistic Text to Speech service delivers a seamless and engaging audio experience like never before. Embrace the power of...", + "home_url": "https://rapidapi.com/ptwebsolution/api/realistic-text-to-speech/", + "name": "Realistic Text to Speech", + "title": "Realistic Text to Speech", + "pricing": "FREEMIUM", + "tool_name": "Realistic Text to Speech", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3953, + "avgSuccessRate": 100, + "popularityScore": 9.7, + "__typename": "Score" + }, + "host": "realistic-text-to-speech.p.rapidapi.com", + "api_list": [ + { + "name": "Generate Text-to-Speech", + "url": "https://realistic-text-to-speech.p.rapidapi.com/v3/generate_voice_over_v2", + "description": "Generate Text-to-Speech", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://realistic-text-to-speech.p.rapidapi.com/v3/generate_voice_over_v2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"realistic-text-to-speech.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://realistic-text-to-speech.p.rapidapi.com/v3/generate_voice_over_v2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"realistic-text-to-speech.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/recapiogpt.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/recapiogpt.json new file mode 100644 index 0000000000000000000000000000000000000000..e926e7806aed9270ff5510af63bc38a04d74c53f --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/recapiogpt.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_77fab676-780e-409c-8f42-9427f66379b0", + "tool_description": "", + "home_url": "https://rapidapi.com/aialfred/api/recapiogpt/", + "name": "RecapioGPT", + "title": "RecapioGPT", + "pricing": "FREEMIUM", + "tool_name": "RecapioGPT", + "score": { + "avgServiceLevel": 78, + "avgLatency": 7110, + "avgSuccessRate": 78, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "recapiogpt.p.rapidapi.com", + "api_list": [ + { + "name": "Summarize", + "url": "https://recapiogpt.p.rapidapi.com/", + "description": "Provide a text or and Url and get a summary.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://recapiogpt.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"recapiogpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://recapiogpt.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"recapiogpt.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/receipt_image_question_answering.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/receipt_image_question_answering.json new file mode 100644 index 0000000000000000000000000000000000000000..ecb9f0c3f1c941ca2b8761273e98fc3fb4a92ac2 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/receipt_image_question_answering.json @@ -0,0 +1,39 @@ +{ + "product_id": "api_d175623d-6355-4d77-b9a0-aaaebe0fb3dd", + "tool_description": "Ask questions using natural language about images of your receipts.", + "home_url": "https://rapidapi.com/cfahlgren1/api/receipt-image-question-answering/", + "name": "Receipt Image Question Answering", + "title": "Receipt Image Question Answering", + "pricing": "FREEMIUM", + "tool_name": "Receipt Image Question Answering", + "score": null, + "host": "receipt-image-question-answering.p.rapidapi.com", + "api_list": [ + { + "name": "Receipt Parsing", + "url": "https://receipt-image-question-answering.p.rapidapi.com/parse", + "description": "Parse a receipt image from any format and get returned JSON", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://receipt-image-question-answering.p.rapidapi.com/parse\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"receipt-image-question-answering.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://receipt-image-question-answering.p.rapidapi.com/parse\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"receipt-image-question-answering.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + }, + { + "name": "Receipt Question Answering", + "url": "https://receipt-image-question-answering.p.rapidapi.com/ask", + "description": "Ask a question about your receipt.\n\nThe API takes two parameters `image_url` and `question`.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://receipt-image-question-answering.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"receipt-image-question-answering.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://receipt-image-question-answering.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"receipt-image-question-answering.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/regexgenie.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/regexgenie.json new file mode 100644 index 0000000000000000000000000000000000000000..a9dab63bb07b9ae353ae283aa8b1e99317eab85a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/regexgenie.json @@ -0,0 +1,82 @@ +{ + "product_id": "api_7678d783-84cc-4654-ae6b-ef24a4cfd60a", + "tool_description": "All-in-one regex handling services: Natural language regex generator, regex explanation, regex optimization.", + "home_url": "https://rapidapi.com/cedrikb/api/regexgenie/", + "name": "RegexGenie", + "title": "RegexGenie", + "pricing": "FREEMIUM", + "tool_name": "RegexGenie", + "score": null, + "host": "regexgenie.p.rapidapi.com", + "api_list": [ + { + "name": "Regex Optimization Service", + "url": "https://regexgenie.p.rapidapi.com/optimize", + "description": "Update your regex to an improved version with better performance. Submit any regex and our service will analyze it and provide an optimized version that is more efficient and performs faster.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/optimize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/optimize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "error": { + "type": "boolean" + }, + "data": { + "type": "string" + } + } + } + }, + { + "name": "Regex Explanation Service", + "url": "https://regexgenie.p.rapidapi.com/describe", + "description": "Understand any regular expression with our detailed explanations. Submit any regex and our service will provide a breakdown of its components and matching behavior.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/describe\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "error": { + "type": "boolean" + }, + "data": { + "type": "string" + } + } + } + }, + { + "name": "Natural Language Regex Generator", + "url": "https://regexgenie.p.rapidapi.com/generate", + "description": "Generate regular expressions using natural language inputs. Our AI-powered service can understand your intent and generate an accurate regex for your needs.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://regexgenie.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"regexgenie.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "error": { + "type": "boolean" + }, + "data": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..5833e8d4d56c0e38c624628327966da9ef5f7565 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai.json @@ -0,0 +1,321 @@ +{ + "product_id": "api_b99a38f2-d368-4768-87b0-0992d0cadb1a", + "tool_description": "Generate testimonial & review using AI. Quickly write candid testimonials and reviews for people and services in 30+ languages", + "home_url": "https://rapidapi.com/ptwebsolution/api/review-generator-ai/", + "name": "Review Generator (AI)", + "title": "Review Generator (AI)", + "pricing": "FREEMIUM", + "tool_name": "Review Generator (AI)", + "score": { + "avgServiceLevel": 91, + "avgLatency": 12179, + "avgSuccessRate": 86, + "popularityScore": 8.6, + "__typename": "Score" + }, + "host": "review-generator-ai.p.rapidapi.com", + "api_list": [ + { + "name": "Locales", + "url": "https://review-generator-ai.p.rapidapi.com/api/data/locales", + "description": "Get list of locales", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://review-generator-ai.p.rapidapi.com/api/data/locales\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"review-generator-ai.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://review-generator-ai.p.rapidapi.com/api/data/locales\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"review-generator-ai.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": { + "success": true, + "message": "success", + "results": [ + { + "locale": "af_ZA", + "name": "Afrikaans" + }, + { + "locale": "ar", + "name": "Arabic" + }, + { + "locale": "az", + "name": "Azerbaijani" + }, + { + "locale": "cz", + "name": "Czech" + }, + { + "locale": "de", + "name": "German" + }, + { + "locale": "de_AT", + "name": "German (Austria)" + }, + { + "locale": "de_CH", + "name": "German (Switzerland)" + }, + { + "locale": "el", + "name": "Greek" + }, + { + "locale": "en", + "name": "English" + }, + { + "locale": "en_AU", + "name": "English (Australia)" + }, + { + "locale": "en_AU_ocker", + "name": "English (Australia Ocker)" + }, + { + "locale": "en_BORK", + "name": "English (Bork)" + }, + { + "locale": "en_CA", + "name": "English (Canada)" + }, + { + "locale": "en_GB", + "name": "English (Great Britain)" + }, + { + "locale": "en_GH", + "name": "English (Ghana)" + }, + { + "locale": "en_IE", + "name": "English (Ireland)" + }, + { + "locale": "en_IND", + "name": "English (India)" + }, + { + "locale": "en_NG", + "name": "Nigeria (English)" + }, + { + "locale": "en_US", + "name": "English (United States)" + }, + { + "locale": "en_ZA", + "name": "English (South Africa)" + }, + { + "locale": "es", + "name": "Spanish" + }, + { + "locale": "es_MX", + "name": "Spanish (Mexico)" + }, + { + "locale": "fa", + "name": "Farsi" + }, + { + "locale": "fi", + "name": "Finnish" + }, + { + "locale": "fr", + "name": "French" + }, + { + "locale": "fr_BE", + "name": "Fran\u00e7ais (Belgique)" + }, + { + "locale": "fr_CA", + "name": "French (Canada)" + }, + { + "locale": "fr_CH", + "name": "French (Switzerland)" + }, + { + "locale": "ge", + "name": "Georgian" + }, + { + "locale": "he", + "name": "Hebrew" + }, + { + "locale": "hr", + "name": "Hrvatski" + }, + { + "locale": "hu", + "name": "Hungarian" + }, + { + "locale": "hy", + "name": "Armenian" + }, + { + "locale": "id_ID", + "name": "Indonesian" + }, + { + "locale": "it", + "name": "Italian" + }, + { + "locale": "ja", + "name": "Japanese" + }, + { + "locale": "ko", + "name": "Korean" + }, + { + "locale": "lv", + "name": "Latvian" + }, + { + "locale": "mk", + "name": "Macedonian" + }, + { + "locale": "nb_NO", + "name": "Norwegian" + }, + { + "locale": "ne", + "name": "Nepalese" + }, + { + "locale": "nl", + "name": "Dutch" + }, + { + "locale": "nl_BE", + "name": "Dutch (Belgium)" + }, + { + "locale": "pl", + "name": "Polish" + }, + { + "locale": "pt_BR", + "name": "Portuguese (Brazil)" + }, + { + "locale": "pt_PT", + "name": "Portuguese (Portugal)" + }, + { + "locale": "ro", + "name": "Romanian" + }, + { + "locale": "ru", + "name": "Russian" + }, + { + "locale": "sk", + "name": "Slovakian" + }, + { + "locale": "sv", + "name": "Swedish" + }, + { + "locale": "tr", + "name": "Turkish" + }, + { + "locale": "uk", + "name": "Ukrainian" + }, + { + "locale": "ur", + "name": "Urdu" + }, + { + "locale": "vi", + "name": "Vietnamese" + }, + { + "locale": "zh_CN", + "name": "Chinese" + }, + { + "locale": "zh_TW", + "name": "Chinese (Taiwan)" + }, + { + "locale": "zu_ZA", + "name": "Zulu (South Africa)" + } + ] + }, + "statuscode": 200, + "schema": {} + }, + { + "name": "Languages", + "url": "https://review-generator-ai.p.rapidapi.com/api/data/languages", + "description": "Get list of Languages", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://review-generator-ai.p.rapidapi.com/api/data/languages\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"review-generator-ai.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://review-generator-ai.p.rapidapi.com/api/data/languages\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"review-generator-ai.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": { + "success": true, + "message": "success", + "results": [ + "Arabic", + "Bengali", + "Bulgarian", + "Chinese", + "Czech", + "Danish", + "Dutch", + "English", + "Estonian", + "Finnish", + "French", + "German", + "Greek", + "Hebrew", + "Hindi", + "Hungarian", + "Indonesian", + "Italian", + "Japanese", + "Korean", + "Latvian", + "Lithuanian", + "Norwegian", + "Persian", + "Polish", + "Portuguese", + "Portuguese (Brazilian)", + "Romanian", + "Russian", + "Slovak", + "Slovenian", + "Spanish", + "Swedish", + "Thai", + "Turkish", + "Ukrainian", + "Vietnamese" + ] + }, + "statuscode": 200, + "schema": {} + } + ], + "standardized_name": "review_generator_ai" +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai/api.py new file mode 100644 index 0000000000000000000000000000000000000000..a9eeeff022fe42d7f6a520437ce55c1731817b00 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/review_generator_ai/api.py @@ -0,0 +1,50 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def locales(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get list of locales" + + """ + url = f"https://review-generator-ai.p.rapidapi.com/api/data/locales" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "review-generator-ai.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def languages(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get list of Languages" + + """ + url = f"https://review-generator-ai.p.rapidapi.com/api/data/languages" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "review-generator-ai.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/roleplai_ai_roleplay_gpt_chatbot.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/roleplai_ai_roleplay_gpt_chatbot.json new file mode 100644 index 0000000000000000000000000000000000000000..30678f2790181f470d77d31cc71681eabb8365fa --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/roleplai_ai_roleplay_gpt_chatbot.json @@ -0,0 +1,53 @@ +{ + "product_id": "api_35876f5f-fa11-4578-a24a-aa585692c97f", + "tool_description": "Introducing \"RolePlai\" \u2013 the revolutionary AI powered chat bot app that features the world's most advanced AI technology, making it feel like you're talking to a real person. This cutting-edge app allows you to instantly create any celebrity, public profile, custom character, and personality with remarkable precision. Dive into the world of interactive roleplay and forge meaningful connections with a diverse range of AI personas, all tailored to your preferences. Our advanced AI engine flawl...", + "home_url": "https://rapidapi.com/andrew-_DFZRoyHt/api/roleplai-ai-roleplay-gpt-chatbot/", + "name": "RolePlai - Ai RolePlay GPT Chatbot", + "title": "RolePlai - Ai RolePlay GPT Chatbot", + "pricing": "FREEMIUM", + "tool_name": "RolePlai - Ai RolePlay GPT Chatbot", + "score": null, + "host": "roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com", + "api_list": [ + { + "name": "RolePlai Chat", + "url": "https://roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com/", + "description": "Make sure your USERID is unique per user.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"roleplai-ai-roleplay-gpt-chatbot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "string" + }, + "code": { + "type": "integer" + }, + "data": { + "type": "object", + "properties": { + "UserID": { + "type": "string" + }, + "Role": { + "type": "string" + }, + "Message": { + "type": "string" + }, + "Reply": { + "type": "string" + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/scodex_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/scodex_api.json new file mode 100644 index 0000000000000000000000000000000000000000..0669792b6b1840f32426c77c565b3aa9ddcbcfee --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/scodex_api.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_c22aec8a-1939-4228-931a-8058fbf2917e", + "tool_description": "OpenAI's GPT-3 language model to request any prompt message same as chatgpt", + "home_url": "https://rapidapi.com/eng.ekeyrouz/api/scodex-api/", + "name": "Scodex API", + "title": "Scodex API", + "pricing": "FREEMIUM", + "tool_name": "Scodex API", + "score": { + "avgServiceLevel": 0, + "avgLatency": 6427, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "scodex-api.p.rapidapi.com", + "api_list": [ + { + "name": "simple post request", + "url": "https://scodex-api.p.rapidapi.com/", + "description": "This response suggests that the server successfully received the JSON payload containing a \"prompt\" field with the value \"Hello, there!\". The server then generated a response containing a \"bot\" field with the value \"\\n\\nHow are you doing today?\" in JSON format.\n\nIf you want to extract the value of the \"bot\" field from the response, you can use the Response object's json() method like this:\n\nconst response = await fetch(\"https://............../\", {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n prompt: \"Hello, there!\",\n }),\n});\nconst data = await response.json();\nconsole.log(data.bot); // Output: \"\\n\\nHow are you doing today?\"", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://scodex-api.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"scodex-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://scodex-api.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"scodex-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes.json new file mode 100644 index 0000000000000000000000000000000000000000..42907f7fcf4b30b8914b4d3a5e69e99234e3b4d6 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes.json @@ -0,0 +1,360 @@ +{ + "tool_name": "Screening and Matching Resumes", + "tool_description": "For Recruters that want to go faster in their resumes screening process, and for recrutees that are interested in checking if their profile match a certain job offer", + "title": "Screening and Matching Resumes", + "pricing": "FREE", + "score": { + "avgServiceLevel": 92, + "avgLatency": 6021, + "avgSuccessRate": 65, + "popularityScore": 9.1, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/volkeno-volkeno-default/api/screening-and-matching-resumes/", + "host": "screening-and-matching-resumes.p.rapidapi.com", + "api_list": [ + { + "name": "/sourcingResume", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/sourcingResume", + "description": " ", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/sourcingResume\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": {}, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + }, + { + "name": "/ScreeningOffer", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOffer", + "description": "Endpoint to upload a file and compute cosine similarity with each file in the dataset", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "The file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOffer\"\nquerystring = {\"file\": file}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "top_10_files": [], + "matching_score": [] + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "top_10_files": { + "type": "array", + "description": "A list of the top 10 similar files", + "items": { + "type": "string" + } + }, + "matching_score": { + "type": "array", + "description": "A list of the the top 10 files and their matching scores with respect to the provided file", + "items": { + "type": "string" + } + } + } + } + }, + { + "name": "/ResumeScreeningLink", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreeningLink", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + }, + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreeningLink\"\nquerystring = {\"resume\": resume, \"job_offer_link\": job_offer_link}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "resume_category_link": "", + "matching_score_link": 0 + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "resume_category_link": { + "type": "string", + "description": "category of the resume" + }, + "matching_score_link": { + "type": "number", + "description": "The matching score between file and given Link " + } + } + } + }, + { + "name": "/ScreeningOfferLink", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOfferLink", + "description": "Extract the job offer text from a given job offer link, and calculate the cosine similarity between the job offer text and the text of resumes stored in a CSV file.", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOfferLink\"\nquerystring = {\"job_offer_link\": job_offer_link}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "top_matches_files": [ + { + "filename": "", + "similarity": 0 + } + ] + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "top_matches_files": { + "type": "array", + "items": { + "type": "object", + "properties": { + "filename": { + "type": "string" + }, + "similarity": { + "type": "number", + "format": "float", + "minimum": -3.402823669209385e+38, + "maximum": 3.402823669209385e+38 + } + } + } + } + } + } + }, + { + "name": "/ResumeScreening", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreening", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer", + "type": "BINARY", + "description": "The job offer file to upload", + "default": "" + }, + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreening\"\nquerystring = {\"job_offer\": job_offer, \"resume\": resume}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "resume_category_file": "", + "matching score_file": 0 + }, + "headers": {}, + "schema": { + "type": "object", + "properties": { + "resume_category_file": { + "type": "string", + "description": "The category of the uploaded resume" + }, + "matching score_file": { + "type": "number", + "description": "The cosine similarity between the uploaded resume and job offer" + } + } + } + }, + { + "name": "/ScreeningOffer", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOffer", + "description": "Endpoint to upload a file and compute cosine similarity with each file in the dataset", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "The file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOffer\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOffer\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/ResumeScreeningLink", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreeningLink", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + }, + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreeningLink\"\nquerystring = {\"resume\": \"\", \"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreeningLink\"\nquerystring = {\"resume\": \"\", \"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "resume_category_link": { + "type": "string", + "description": "category of the resume" + }, + "matching_score_link": { + "type": "number", + "description": "The matching score between file and given Link " + } + } + } + }, + { + "name": "/ScreeningOfferLink", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOfferLink", + "description": "Extract the job offer text from a given job offer link, and calculate the cosine similarity between the job offer text and the text of resumes stored in a CSV file.", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOfferLink\"\nquerystring = {\"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ScreeningOfferLink\"\nquerystring = {\"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "top_matches_files": { + "type": "array", + "items": { + "type": "object", + "properties": { + "filename": { + "type": "string" + }, + "similarity": { + "type": "number", + "format": "float", + "minimum": -3.402823669209385e+38, + "maximum": 3.402823669209385e+38 + } + } + } + } + } + } + }, + { + "name": "/ResumeScreening", + "url": "https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreening", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer", + "type": "BINARY", + "description": "The job offer file to upload", + "default": "" + }, + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreening\"\nquerystring = {\"job_offer\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes.p.rapidapi.com/ResumeScreening\"\nquerystring = {\"job_offer\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "resume_category_file": { + "type": "string", + "description": "The category of the uploaded resume" + }, + "matching score_file": { + "type": "number", + "description": "The cosine similarity between the uploaded resume and job offer" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes/api.py new file mode 100644 index 0000000000000000000000000000000000000000..a356bea9de93fece730298a78d58331a8f223ab4 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def sourcingresume(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + " " + + """ + url = f"https://screening-and-matching-resumes.p.rapidapi.com/sourcingresume" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "screening-and-matching-resumes.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes_and_offer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes_and_offer.json new file mode 100644 index 0000000000000000000000000000000000000000..500afe5bd37e65904e2100627f57cfa48bf5b317 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/screening_and_matching_resumes_and_offer.json @@ -0,0 +1,210 @@ +{ + "product_id": "api_99cc654c-9743-465c-88c0-87d0432523f8", + "tool_description": "This app is for Recruiters to shortlist candidates during the selection process and for recruitees to get submit while knowing the matching percentage between their resumes and a job offer", + "home_url": "https://rapidapi.com/volkeno-volkeno-default/api/screening-and-matching-resumes-and-offer/", + "name": "Screening and Matching resumes and offer", + "title": "Screening and Matching resumes and offer", + "pricing": "FREE", + "tool_name": "Screening and Matching resumes and offer", + "score": { + "avgServiceLevel": 74, + "avgLatency": 3034, + "avgSuccessRate": 47, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "screening-and-matching-resumes-and-offer.p.rapidapi.com", + "api_list": [ + { + "name": "/ResumeOfferMatching", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferMatching", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer_link", + "type": "STRING", + "description": "The URL of the job offer.", + "default": "" + }, + { + "name": "resume_link", + "type": "STRING", + "description": "The URL of the resume.", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferMatching\"\nquerystring = {\"job_offer_link\": \"\", \"resume_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferMatching\"\nquerystring = {\"job_offer_link\": \"\", \"resume_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/ResumeScreeningLink", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreeningLink", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + }, + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreeningLink\"\nquerystring = {\"job_offer_link\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreeningLink\"\nquerystring = {\"job_offer_link\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/ScreeningOfferLink", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOfferLink", + "description": "Extract the job offer text from a given job offer link and calculate the cosine similarity between the job offer text and the text of resumes stored in a CSV file.", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOfferLink\"\nquerystring = {\"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOfferLink\"\nquerystring = {\"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "top_matches_files": { + "type": "array", + "items": { + "type": "object", + "properties": { + "filename": { + "type": "string" + }, + "similarity": { + "type": "number", + "format": "float", + "minimum": -3.402823669209385e+38, + "maximum": 3.402823669209385e+38 + } + } + } + } + } + } + }, + { + "name": "/ResumeScreening", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreening", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "job_offer", + "type": "BINARY", + "description": "The job offer file to upload", + "default": "" + }, + { + "name": "resume", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreening\"\nquerystring = {\"job_offer\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeScreening\"\nquerystring = {\"job_offer\": \"\", \"resume\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/sourcingResume", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/sourcingResume", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "model_choice", + "type": "STRING", + "description": "The choice of machine learning model to use for categorization", + "default": "\"model1\"" + }, + { + "name": "file", + "type": "BINARY", + "description": "The resume file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/sourcingResume\"\nquerystring = {\"model_choice\": \"\\\"model1\\\"\", \"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/sourcingResume\"\nquerystring = {\"model_choice\": \"\\\"model1\\\"\", \"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/ScreeningOffer", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOffer", + "description": "Endpoint to upload a file and compute cosine similarity with each file in the database", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "The file to upload", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOffer\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ScreeningOffer\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "/ResumeOfferLinks", + "url": "https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferLinks", + "description": " ", + "method": "POST", + "required_parameters": [ + { + "name": "resume_link", + "type": "STRING", + "description": "The Link for the resume page", + "default": "" + }, + { + "name": "job_offer_link", + "type": "STRING", + "description": "The link to the job offer page", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferLinks\"\nquerystring = {\"resume_link\": \"\", \"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://screening-and-matching-resumes-and-offer.p.rapidapi.com/ResumeOfferLinks\"\nquerystring = {\"resume_link\": \"\", \"job_offer_link\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"screening-and-matching-resumes-and-offer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/script_writer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/script_writer.json new file mode 100644 index 0000000000000000000000000000000000000000..981ee14c2e981cb4f660914d3e2b387f147c3e5e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/script_writer.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_1e29e918-06be-40b5-a2fb-100ec4c7a606", + "tool_description": "Script Writer AI is a cutting-edge artificial intelligence technology that revolutionizes the art of storytelling. Powered by advanced machine learning algorithms, this AI marvels in crafting compelling and original scripts for various mediums, including films, TV shows, theater productions, and more. With an innate grasp of character dynamics, plot intricacies, and authentic dialogue, Script Writer AI delivers creative narratives that captivate audiences and evoke genuine emotions. Seamlessl...", + "home_url": "https://rapidapi.com/ptwebsolution/api/script-writer/", + "name": "Script Writer", + "title": "Script Writer", + "pricing": "FREEMIUM", + "tool_name": "Script Writer", + "score": { + "avgServiceLevel": 100, + "avgLatency": 1877, + "avgSuccessRate": 100, + "popularityScore": 8.9, + "__typename": "Score" + }, + "host": "script-writer.p.rapidapi.com", + "api_list": [ + { + "name": "Write Script", + "url": "https://script-writer.p.rapidapi.com/v3/generate_script", + "description": "Write Script", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://script-writer.p.rapidapi.com/v3/generate_script\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"script-writer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://script-writer.p.rapidapi.com/v3/generate_script\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"script-writer.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sd_image_service.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sd_image_service.json new file mode 100644 index 0000000000000000000000000000000000000000..868634ea8613b3e0b8ee95d558e959f8fdc3ac07 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sd_image_service.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_655a8952-2978-4e56-95e6-0634d3b014fb", + "tool_description": "API for generative service", + "home_url": "https://rapidapi.com/phenikaa-maas-phenikaa-maas-default/api/sd_image_service/", + "name": "sd_image_service", + "title": "sd_image_service", + "pricing": "FREE", + "tool_name": "sd_image_service", + "score": { + "avgServiceLevel": 82, + "avgLatency": 40041, + "avgSuccessRate": 62, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "sd_image_service.p.rapidapi.com", + "api_list": [ + { + "name": "sd_anime", + "url": "https://sd_image_service.p.rapidapi.com/sdapi/style_anime/v1/img2img", + "description": "Endpoint used for convert image to anime style", + "method": "POST", + "required_parameters": [ + { + "name": "image", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sd_image_service.p.rapidapi.com/sdapi/style_anime/v1/img2img\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sd_image_service.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sd_image_service.p.rapidapi.com/sdapi/style_anime/v1/img2img\"\nquerystring = {\"image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sd_image_service.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/semadb.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/semadb.json new file mode 100644 index 0000000000000000000000000000000000000000..02e7b4b71759811fc0c25bbf275589260fd07897 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/semadb.json @@ -0,0 +1,104 @@ +{ + "product_id": "api_2e9ad348-2ce8-4b4f-a2d7-71293b7a6f9d", + "tool_description": "No fuss vector database for AI", + "home_url": "https://rapidapi.com/semafind-semadb/api/semadb/", + "name": "SemaDB", + "title": "SemaDB", + "pricing": "FREEMIUM", + "tool_name": "SemaDB", + "score": { + "avgServiceLevel": 98, + "avgLatency": 132, + "avgSuccessRate": 86, + "popularityScore": 9.2, + "__typename": "Score" + }, + "host": "semadb.p.rapidapi.com", + "api_list": [ + { + "name": "SearchPoint", + "url": "https://semadb.p.rapidapi.com/collections/{collectionId}/points/search", + "description": "Perform similarity search on points in a collection. The search is performed using a vector, which is a mathematical representation of the point. The vector must have the same number of dimensions as the vectors in the collection. The search returns the most similar points to the vector, along with the distance between the vector and the points.", + "method": "POST", + "required_parameters": [ + { + "name": "collectionId", + "type": "STRING", + "description": "The unique identifier of the collection", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections/{collectionId}/points/search\"\nquerystring = {\"collectionId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections/{collectionId}/points/search\"\nquerystring = {\"collectionId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "points": { + "type": "array", + "items": { + "type": "object", + "properties": { + "id": { + "type": "string", + "format": "uuid" + }, + "distance": { + "type": "number", + "description": "Distance between the vector and the point", + "examples": [ + 4.2 + ] + }, + "metadata": { + "type": "object", + "description": "JSON serialisable point metadata", + "examples": [ + { + "externalId": 42 + } + ] + } + } + } + } + } + } + }, + { + "name": "InsertPoint", + "url": "https://semadb.p.rapidapi.com/collections/{collectionId}/points", + "description": "This endpoint assumes all points to be inserted are new points and does not check for duplication. It is important to ensure consistency of the database you do not insert duplicate points. If you are unsure if a point exists, you can leave the id field blank and the database will assign a new id. *For cosine distance, you must normalise the vectors prior to inserting them.*", + "method": "POST", + "required_parameters": [ + { + "name": "collectionId", + "type": "STRING", + "description": "The unique identifier of the collection", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections/{collectionId}/points\"\nquerystring = {\"collectionId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections/{collectionId}/points\"\nquerystring = {\"collectionId\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "CreateCollection", + "url": "https://semadb.p.rapidapi.com/collections", + "description": "Creates a new collection if it does not already exist. The maximum number of collections per user is restricted based on the plan. Before you can insert and search points, you must create a collection.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://semadb.p.rapidapi.com/collections\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"semadb.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentilink.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentilink.json new file mode 100644 index 0000000000000000000000000000000000000000..09936a2b7cacd10682be060e25a1a663202359bf --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentilink.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_4c8ef453-3e59-4796-bfa3-d2279bdeac82", + "tool_description": "## Get started for FREE - click\u261d\ufe0f\n\nUse GPT-4 and Claude-2 to extract: article summary, sentiment scores, call to action and important keywords from a URL. Place your finger on the pulse of sentiment shifts and rising trends for any niche, market, sector or topic by processing all relevant news articles and blog posts for that space using Sentilink. ", + "home_url": "https://rapidapi.com/botmart/api/sentilink1/", + "name": "Sentilink", + "title": "Sentilink", + "pricing": "FREEMIUM", + "tool_name": "Sentilink", + "score": { + "avgServiceLevel": 81, + "avgLatency": 26753, + "avgSuccessRate": 75, + "popularityScore": 9.2, + "__typename": "Score" + }, + "host": "sentilink1.p.rapidapi.com", + "api_list": [ + { + "name": "Summarize", + "url": "https://sentilink1.p.rapidapi.com/summarize", + "description": "(Give it 20-60s for a response)\nThis is the core endpoint where a URL and other parameters are sent as a POST request for processing.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentilink1.p.rapidapi.com/summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentilink1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentilink1.p.rapidapi.com/summarize\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentilink1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentiment_analyzer.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentiment_analyzer.json new file mode 100644 index 0000000000000000000000000000000000000000..4e85be248b15e38eb510039437d0917eb326f2d1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentiment_analyzer.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_bb3a2bd5-b049-4cdf-a618-352c20194cfc", + "tool_description": "This API uses deep learning to analyze the sentiment of pieces of text.", + "home_url": "https://rapidapi.com/samirrangwalla/api/sentiment-analyzer2/", + "name": "Sentiment Analyzer", + "title": "Sentiment Analyzer", + "pricing": "FREE", + "tool_name": "Sentiment Analyzer", + "score": { + "avgServiceLevel": 0, + "avgLatency": 456, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "sentiment-analyzer2.p.rapidapi.com", + "api_list": [ + { + "name": "Sentiment Analyzer", + "url": "https://sentiment-analyzer2.p.rapidapi.com/", + "description": "Analyze the sentiment of text using deep learning.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentiment-analyzer2.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentiment-analyzer2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentiment-analyzer2.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentiment-analyzer2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentimental.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentimental.json new file mode 100644 index 0000000000000000000000000000000000000000..429d2985ca5699d89905b1c1b8808cfb05b77d60 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentimental.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_c7b6fd35-e211-4073-89f7-8c0e2393fba4", + "tool_description": "Sentimental is a GPT-3.5/ChatGPT-powered text analysis API, designed to provide a comprehensive set of metrics for text evaluation. It offers an array of essential measurements, including spam detection, grammar assessment, sentiment analysis, scholarly evaluation, humor detection, violence detection, and sexual content scoring. Additionally, it includes a reliable language identifier and the capability to determine if the text is suitable for young audiences. The API can be integrated into i...", + "home_url": "https://rapidapi.com/tomwimmenhove/api/sentimental2/", + "name": "Sentimental", + "title": "Sentimental", + "pricing": "FREEMIUM", + "tool_name": "Sentimental", + "score": null, + "host": "sentimental2.p.rapidapi.com", + "api_list": [ + { + "name": "Analyze", + "url": "https://sentimental2.p.rapidapi.com/Analyze", + "description": "Analyze text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentimental2.p.rapidapi.com/Analyze\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentimental2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentimental2.p.rapidapi.com/Analyze\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentimental2.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentix.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentix.json new file mode 100644 index 0000000000000000000000000000000000000000..28dd6a90c60021c48b657e61964402467f2ed963 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sentix.json @@ -0,0 +1,85 @@ +{ + "product_id": "api_779f23be-553a-4ccf-9936-edfda629a76c", + "tool_description": "Introducing Ava, Max, and Max- Large the latest addition to our SentiX family of sentiment analysis models with the capability to handle English, French, Spanish, German, and Portuguese, SentiX is a versatile AI tool that empowers businesses and researchers to gain valuable insights from text data in various applications.", + "home_url": "https://rapidapi.com/kidddevs/api/sentix/", + "name": "SentiX", + "title": "SentiX", + "pricing": "FREEMIUM", + "tool_name": "SentiX", + "score": { + "avgServiceLevel": 100, + "avgLatency": 216, + "avgSuccessRate": 100, + "popularityScore": 8.6, + "__typename": "Score" + }, + "host": "sentix.p.rapidapi.com", + "api_list": [ + { + "name": "Max-Large (Batch Processing)", + "url": "https://sentix.p.rapidapi.com/max_large/batch", + "description": "Analyze Sentiment for multiple texts in multiple languages, including English, French, Spanish, German, and Portuguese.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max_large/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max_large/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Max-Large Analyze Text", + "url": "https://sentix.p.rapidapi.com/max_large/post", + "description": "Analyze Sentiment for Single Text in multiple languages including; English, French, Spanish, German, and Portuguese.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max_large/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max_large/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Max Analyze Text - Batch", + "url": "https://sentix.p.rapidapi.com/max/batch", + "description": "This endpoint allows you to perform sentiment analysis on multiple text inputs in a batch.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Max Analyze Text", + "url": "https://sentix.p.rapidapi.com/max/post", + "description": "This endpoint allows you to perform sentiment analysis on a single text input.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/max/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Analyze Text - Batch", + "url": "https://sentix.p.rapidapi.com/ava/batch", + "description": "This endpoint allows you to analyze multiple text inputs in a batch and obtain their sentiment categories.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/ava/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/ava/batch\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Analyze Text", + "url": "https://sentix.p.rapidapi.com/ava/post", + "description": "This endpoint allows you to analyze a single text input and obtain its sentiment category.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/ava/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sentix.p.rapidapi.com/ava/post\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sentix.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/short_ai_memory.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/short_ai_memory.json new file mode 100644 index 0000000000000000000000000000000000000000..d65d641e5e997eda633f6855c6507d72afa11259 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/short_ai_memory.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_7c51acc8-e1f3-41e6-b9c8-a06e4d2bf40a", + "tool_description": " Conversation memory for your openai gpt api chatbots and chatgpt agents.", + "home_url": "https://rapidapi.com/kesegomokgosi23/api/short_ai_memory/", + "name": "short_ai_memory", + "title": "short_ai_memory", + "pricing": "FREEMIUM", + "tool_name": "short_ai_memory", + "score": null, + "host": "short_ai_memory.p.rapidapi.com", + "api_list": [ + { + "name": "chat", + "url": "https://short_ai_memory.p.rapidapi.com/chat", + "description": "a chat endpoint for chatgpt chatbot with memory.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://short_ai_memory.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"short_ai_memory.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://short_ai_memory.p.rapidapi.com/chat\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"short_ai_memory.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/simple_chatgpt_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/simple_chatgpt_api.json new file mode 100644 index 0000000000000000000000000000000000000000..e4e49009fb143129ce2cad18cd2785f4f3802d3d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/simple_chatgpt_api.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_b6cdc2c2-aec6-4064-9538-60eedeb7e75a", + "tool_description": "Enter your text, and watch the API respond with a completion that attempts to match the context or pattern you provided. Using latest model from OpenAI is GPT 4", + "home_url": "https://rapidapi.com/LightningDev/api/simple-chatgpt-api/", + "name": "Simple ChatGPT API", + "title": "Simple ChatGPT API", + "pricing": "FREEMIUM", + "tool_name": "Simple ChatGPT API", + "score": { + "avgServiceLevel": 93, + "avgLatency": 19630, + "avgSuccessRate": 92, + "popularityScore": 9.7, + "__typename": "Score" + }, + "host": "simple-chatgpt-api.p.rapidapi.com", + "api_list": [ + { + "name": "Enter your question and get response", + "url": "https://simple-chatgpt-api.p.rapidapi.com/ask", + "description": "With this endpoint, users can send their questions to the chatbot, in return receiving a text string response from the bot. This feature is especially handy for integrating the chatbot into applications or websites that require swift and precise answers to user queries.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://simple-chatgpt-api.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"simple-chatgpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://simple-chatgpt-api.p.rapidapi.com/ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"simple-chatgpt-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/site2json.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/site2json.json new file mode 100644 index 0000000000000000000000000000000000000000..406ed914688bf45b829f5921280d7f9cb957f5aa --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/site2json.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_fde59cb1-55ae-4e27-8a02-6ac57adb7d33", + "tool_description": "parses a given URL and returns a structured summary, including keywords, industry, location, contact details, product/services list, and more. It supports tasks like data enrichment, business intelligence, competitor analysis, and SEO, using advanced machine learning techniques to distill complex web content into usable data.", + "home_url": "https://rapidapi.com/moshnoi2000-46FTkD0nFtO/api/site2json/", + "name": "site2json", + "title": "site2json", + "pricing": "FREEMIUM", + "tool_name": "site2json", + "score": { + "avgServiceLevel": 43, + "avgLatency": 15132, + "avgSuccessRate": 43, + "popularityScore": 8.9, + "__typename": "Score" + }, + "host": "site2json.p.rapidapi.com", + "api_list": [ + { + "name": "site2json", + "url": "https://site2json.p.rapidapi.com/", + "description": "Send the url and get json", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://site2json.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"site2json.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://site2json.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"site2json.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/skybox_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/skybox_api.json new file mode 100644 index 0000000000000000000000000000000000000000..c66516ff9e5449bc8e15b05d56f9de4a4702e399 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/skybox_api.json @@ -0,0 +1,103 @@ +{ + "product_id": "api_f1f88cc3-b74e-428b-8957-3f0e9d6bb6d3", + "tool_description": "Text to 3D image scene generator", + "home_url": "https://rapidapi.com/flowrite-flowrite-default/api/skybox-api/", + "name": "Skybox api", + "title": "Skybox api", + "pricing": "FREE", + "tool_name": "Skybox api", + "score": { + "avgServiceLevel": 99, + "avgLatency": 1005, + "avgSuccessRate": 98, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "skybox-api.p.rapidapi.com", + "api_list": [ + { + "name": "generateSkybox", + "url": "https://skybox-api.p.rapidapi.com/api/v1/skybox", + "description": "[https://api-documentation.blockadelabs.com/api/skybox.html#submit](https://api-documentation.blockadelabs.com/api/skybox.html#submit)", + "method": "POST", + "required_parameters": [], + "optional_parameters": [ + { + "name": "prompt", + "type": "STRING", + "description": "Text prompt describing the skybox world you wish to create", + "default": "prompt example" + }, + { + "name": "negative_text", + "type": "STRING", + "description": "Describe things to avoid in the skybox world you wish to create", + "default": "negative text example" + }, + { + "name": "webhook_url", + "type": "STRING", + "description": "Optionally, you may specify a webhook url to specify the destination for progress updates", + "default": "https://yourserver.example/webhook_post_request_url" + }, + { + "name": "remix_imagine_id", + "type": "NUMBER", + "description": "ID of a previously generated imagine/skybox", + "default": "0" + }, + { + "name": "skybox_style_id", + "type": "NUMBER", + "description": "Predefined styles that influence the overall aesthetic of your skybox generation (Fantasy landscape, Anime art style, etc...). You can get list of styles using a Get Skybox Styles method.", + "default": "2" + }, + { + "name": "return_depth", + "type": "BOOLEAN", + "description": "Return depth map image as `depth_map_url` parameter in the final progress update message (default: `false`)", + "default": "true" + }, + { + "name": "seed", + "type": "NUMBER", + "description": "Send 0 for a random seed generation. Any other number (1-2147483647) set will be used to \"freeze\" the image generator generator and create similar images when run again with the same seed and settings.\n", + "default": "0" + }, + { + "name": "api_key", + "type": "STRING", + "description": "", + "default": "{{api_key}}" + } + ], + "code": "import requests\n\nurl = \"https://skybox-api.p.rapidapi.com/api/v1/skybox\"\nquerystring = {\"prompt\": \"prompt example\", \"negative_text\": \"negative text example\", \"webhook_url\": \"https://yourserver.example/webhook_post_request_url\", \"remix_imagine_id\": \"0\", \"skybox_style_id\": \"2\", \"return_depth\": \"true\", \"seed\": \"0\", \"api_key\": \"{{api_key}}\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"skybox-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://skybox-api.p.rapidapi.com/api/v1/skybox\"\nquerystring = {\"prompt\": \"prompt example\", \"negative_text\": \"negative text example\", \"webhook_url\": \"https://yourserver.example/webhook_post_request_url\", \"remix_imagine_id\": \"0\", \"skybox_style_id\": \"2\", \"return_depth\": \"true\", \"seed\": \"0\", \"api_key\": \"{{api_key}}\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"skybox-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "get": { + "type": "string" + }, + "parameters": { + "type": "array" + }, + "errors": { + "type": "array" + }, + "results": { + "type": "integer" + }, + "response": { + "type": "array", + "items": { + "type": "object" + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/slider_captcha_solver_geetest_tencent.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/slider_captcha_solver_geetest_tencent.json new file mode 100644 index 0000000000000000000000000000000000000000..a24730c0a67242e85d4948aacac24e6712aaf328 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/slider_captcha_solver_geetest_tencent.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_411e6c43-044b-4207-91aa-16cb988f33fb", + "tool_description": "Solves slider captcha. Tested on Tencent and Geetest. Solves 95% of captchas correctly.", + "home_url": "https://rapidapi.com/dyuvarov/api/slider-captcha-solver-geetest-tencent/", + "name": "Slider captcha solver (Geetest, Tencent)", + "title": "Slider captcha solver (Geetest, Tencent)", + "pricing": "FREEMIUM", + "tool_name": "Slider captcha solver (Geetest, Tencent)", + "score": { + "avgServiceLevel": 0, + "avgLatency": 46, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "slider-captcha-solver-geetest-tencent.p.rapidapi.com", + "api_list": [ + { + "name": "solve", + "url": "https://slider-captcha-solver-geetest-tencent.p.rapidapi.com/solve/slider", + "description": "captcha solver", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://slider-captcha-solver-geetest-tencent.p.rapidapi.com/solve/slider\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"slider-captcha-solver-geetest-tencent.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://slider-captcha-solver-geetest-tencent.p.rapidapi.com/solve/slider\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"slider-captcha-solver-geetest-tencent.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/smartsoils.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/smartsoils.json new file mode 100644 index 0000000000000000000000000000000000000000..31335e43f65695ed2e9efd4c2295b5ce140de0a9 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/smartsoils.json @@ -0,0 +1,33 @@ +{ + "product_id": "api_78cdd695-eae8-4245-b1f6-b1edaadba5dc", + "tool_description": "# Soil Properties Prediction using Vis-NIR spectra and Machine Learning\n\n\nOur RapidAPI project offers a solution for determining soil properties using machine learning models. This implementation is based on Vis-NIR reflectance spectra data and has been trained on a dataset of 448 wavelengths between 400nm and 1000nm, along with the corresponding soil properties. The use of various machine learning algorithms ensures high accuracy in predicting 74 different soil properties. Integration with ...", + "home_url": "https://rapidapi.com/bourassijihad/api/smartsoils/", + "name": "SmartSoils", + "title": "SmartSoils", + "pricing": "FREEMIUM", + "tool_name": "SmartSoils", + "score": null, + "host": "smartsoils.p.rapidapi.com", + "api_list": [ + { + "name": "predict_composante", + "url": "https://smartsoils.p.rapidapi.com/Composante/", + "description": "Predict soil properties with POST request, it should contain two parameters:\n- **\u201cvariable\u201d**: string of the soil property to predict (can be \u201cALL\u201d or one of the 74 properties).\n- **\u201cfile\u201d** : JSON of the spectral signature.", + "method": "POST", + "required_parameters": [ + { + "name": "variable", + "type": "STRING", + "description": "", + "default": "ALL" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://smartsoils.p.rapidapi.com/Composante/\"\nquerystring = {\"variable\": \"ALL\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"smartsoils.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://smartsoils.p.rapidapi.com/Composante/\"\nquerystring = {\"variable\": \"ALL\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"smartsoils.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sms_fraud_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sms_fraud_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..1ceee7dc4acc8ce423e898cb545838c2498f9d48 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/sms_fraud_detection.json @@ -0,0 +1,37 @@ +{ + "product_id": "api_3721761c-378b-48c6-b874-60b75eea04da", + "tool_description": "Introducing the SMS Fraud Detection API, powered by GPT-3.5, the ground-breaking language model developed by OpenAI. \n\nOur API revolutionizes fraud prevention in the realm of SMS communication by leveraging the power of natural language processing and machine learning.", + "home_url": "https://rapidapi.com/hailbytes-hailbytes-default/api/sms-fraud-detection/", + "name": "SMS Fraud Detection", + "title": "SMS Fraud Detection", + "pricing": "FREEMIUM", + "tool_name": "SMS Fraud Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 908, + "avgSuccessRate": 100, + "popularityScore": 8.3, + "__typename": "Score" + }, + "host": "sms-fraud-detection.p.rapidapi.com", + "api_list": [ + { + "name": "SMS Fraud Detection", + "url": "https://sms-fraud-detection.p.rapidapi.com/analyze-sms/", + "description": "TheSMS Fraud Detection endpoint utilizes advanced algorithms and machine learning techniques to analyze the content and metadata of SMS messages you submit in real-time. It evaluates various parameters and indicators to identify potential fraudulent activities and raise alerts for further investigation.", + "method": "POST", + "required_parameters": [ + { + "name": "sms_msg", + "type": "STRING", + "description": "", + "default": "CONGRATULATIONS! You won the lottery. Your friend Daniel wants to connect with you. Both of you can redeem the prize when you APPLY HERE: offer.1nuniyaz.co" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://sms-fraud-detection.p.rapidapi.com/analyze-sms/\"\nquerystring = {\"sms_msg\": \"CONGRATULATIONS! You won the lottery. Your friend Daniel wants to connect with you. Both of you can redeem the prize when you APPLY HERE: offer.1nuniyaz.co\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sms-fraud-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://sms-fraud-detection.p.rapidapi.com/analyze-sms/\"\nquerystring = {\"sms_msg\": \"CONGRATULATIONS! You won the lottery. Your friend Daniel wants to connect with you. Both of you can redeem the prize when you APPLY HERE: offer.1nuniyaz.co\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"sms-fraud-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spam_detector_and_filter.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spam_detector_and_filter.json new file mode 100644 index 0000000000000000000000000000000000000000..a0359634fbff0a1c7d399a3b72e249504fef394d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spam_detector_and_filter.json @@ -0,0 +1,117 @@ +{ + "product_id": "api_5ea0f993-2ac4-459f-928d-c7d8a35e3490", + "tool_description": "Identify and filter spam content in various forms, such as emails, comments, messages, or user-generated content. With this API, you can easily integrate spam detection and filtering capabilities into your applications, platforms, or services, enabling you to protect your users and systems from unwanted and potentially harmful content.", + "home_url": "https://rapidapi.com/evlar-evlar-default/api/spam-detector-and-filter/", + "name": "Spam Detector and Filter", + "title": "Spam Detector and Filter", + "pricing": "FREEMIUM", + "tool_name": "Spam Detector and Filter", + "score": null, + "host": "spam-detector-and-filter.p.rapidapi.com", + "api_list": [ + { + "name": "Detect Spam", + "url": "https://spam-detector-and-filter.p.rapidapi.com/detect", + "description": "Detect Spam from given text, email, and or IP address", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spam-detector-and-filter.p.rapidapi.com/detect\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spam-detector-and-filter.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://spam-detector-and-filter.p.rapidapi.com/detect\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spam-detector-and-filter.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "status": { + "type": "string" + }, + "error": { + "type": "null" + }, + "data": { + "type": "object", + "properties": { + "isSpam": { + "type": "boolean" + }, + "isDisposableEmail": { + "type": "boolean" + }, + "isIPBlacklisted": { + "type": "boolean" + }, + "isCompanyEmail": { + "type": "boolean" + }, + "isFreeEmail": { + "type": "boolean" + }, + "isValidEmail": { + "type": "boolean" + }, + "emailDetails": { + "type": "object", + "properties": { + "isConnecting": { + "type": "boolean" + }, + "isValid": { + "type": "boolean" + }, + "isMxValid": { + "type": "boolean" + }, + "isSmtpValid": { + "type": "boolean" + } + } + }, + "ipDetails": { + "type": "object", + "properties": { + "range": { + "type": "array", + "items": { + "type": "integer" + } + }, + "country": { + "type": "string" + }, + "region": { + "type": "string" + }, + "eu": { + "type": "string" + }, + "timezone": { + "type": "string" + }, + "city": { + "type": "string" + }, + "ll": { + "type": "array", + "items": { + "type": "number" + } + }, + "metro": { + "type": "integer" + }, + "area": { + "type": "integer" + } + } + }, + "parsed": { + "type": "boolean" + } + } + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy.json new file mode 100644 index 0000000000000000000000000000000000000000..eca340519578e640e6bc0fbc77f7c7b6885b68e8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy.json @@ -0,0 +1,116 @@ +{ + "tool_name": "SpamSpy", + "tool_description": "AI-powered spam detection to secure & streamline communication. ", + "title": "SpamSpy", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 51, + "avgLatency": 11124, + "avgSuccessRate": 44, + "popularityScore": 9.3, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/deviated-systems-deviated-systems-default/api/spamspy/", + "host": "spamspy.p.rapidapi.com", + "api_list": [ + { + "name": "Learn", + "url": "https://spamspy.p.rapidapi.com/Learn", + "description": "The \"Learn\" endpoint adds the content (located in the query string) provided to be processed at a later date and then to be identified as spam or not during the next training cycles. \n**WARRNING/NOTE:** *While content submitted is not publicly viewable, submitted content sometimes does require our trusted internal reviewers intervention; as such, please refrain from submitting vulnerable information. For high security requirements, confidential, overly sensitive data, etc. , contact us directly about having a private/custom model setup for your needs. We can easily work with you in creating your custom/private models so they have endpoints created to conform with any desired/existing security measures.*\n\n***SpamSpy is not liable for any resulting consequences should you disregard this warning.***\n\n- Fetch Method POST\n- Returns String: **'Learning Content** / **Learn API Unsuccessful**\nExample Response:\n`{\"SpamSpyResult\":'Learning Content'}` (content has been added to the learn queue)\n`{\"SpamSpyResult\":'Learn API Unsuccessful'}`", + "method": "POST", + "required_parameters": [ + { + "name": "content", + "type": "STRING", + "description": "", + "default": "Get Free Tickets to this famous artist!!! Only pay shipping and handling" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Learn\"\nquerystring = {\"content\": content}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Remember", + "url": "https://spamspy.p.rapidapi.com/Remember", + "description": "Functions as a free & unlimited version of the classic reactive spam filtering approach. Recommended to be used to cut down on \"Comprehend\" endpoint call usage if the content has a match, there is no need to have SpamSpy recalculate responses it has already reviewed. \nThis endpoint checks the existing spam database for queried content and sends back the latest scanned result if the content exists yet.\n\nExample Responses:\n`{\"SpamSpyResult\":true}` (content is spam)\n`{\"SpamSpyResult\":false}`(content is not spam)\n`{\"SpamSpyResult\":\"Content not yet scanned\"}` (content has **NOT YET** been scanned)", + "method": "GET", + "required_parameters": [ + { + "name": "content", + "type": "STRING", + "description": "", + "default": "SIX chances to win CASH! From 100 to 20,000 pounds txt> CSH11 and send to 87575. Cost 150p/day, 6days, 16+ TsandCs apply Reply HL 4 info" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Remember\"\nquerystring = {\"content\": content}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Auth Check", + "url": "https://spamspy.p.rapidapi.com/Auth", + "description": "Checks if the API Key is still valid", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Auth\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 111, + "body": "", + "headers": "", + "schema": "" + }, + { + "name": "Comprehend", + "url": "https://spamspy.p.rapidapi.com/Comprehend", + "description": "Comprehend uses the current AI public modals and submits the content (located in the query string) to be identified as spam or not.\n- Fetch Method Get\n- Returns Boolean: **true** / **false**\nExample Response:\n`{\"SpamSpyResult\":true}` (content is spam)\n`{\"SpamSpyResult\":false}`(content is not spam)", + "method": "GET", + "required_parameters": [ + { + "name": "content", + "type": "STRING", + "description": "", + "default": "You won $1,000,00 congratulations winner come recieve your prize!" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Comprehend\"\nquerystring = {\"content\": content}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "key1": "value", + "key2": "value" + }, + "headers": {}, + "schema": {} + }, + { + "name": "Learn", + "url": "https://spamspy.p.rapidapi.com/Learn", + "description": "The \"Learn\" endpoint adds the content (located in the query string) provided to be processed at a later date and then to be identified as spam or not during the next training cycles. \n**WARRNING/NOTE:** *While content submitted is not publicly viewable, submitted content sometimes does require our trusted internal reviewers intervention; as such, please refrain from submitting vulnerable information. For high security requirements, confidential, overly sensitive data, etc. , contact us directly about having a private/custom model setup for your needs. We can easily work with you in creating your custom/private models so they have endpoints created to conform with any desired/existing security measures.*\n\n***SpamSpy is not liable for any resulting consequences should you disregard this warning.***\n\n- Fetch Method POST\n- Returns String: **'Learning Content** / **Learn API Unsuccessful**\nExample Response:\n`{\"SpamSpyResult\":'Learning Content'}` (content has been added to the learn queue)\n`{\"SpamSpyResult\":'Learn API Unsuccessful'}`", + "method": "POST", + "required_parameters": [ + { + "name": "content", + "type": "STRING", + "description": "", + "default": "Get Free Tickets to this famous artist!!! Only pay shipping and handling" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Learn\"\nquerystring = {\"content\": \"Get Free Tickets to this famous artist!!! Only pay shipping and handling\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://spamspy.p.rapidapi.com/Learn\"\nquerystring = {\"content\": \"Get Free Tickets to this famous artist!!! Only pay shipping and handling\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spamspy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy/api.py new file mode 100644 index 0000000000000000000000000000000000000000..0a61a4c76d49489909a71bf3778621d65afcbda3 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spamspy/api.py @@ -0,0 +1,82 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def remember(content: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Functions as a free & unlimited version of the classic reactive spam filtering approach. Recommended to be used to cut down on "Comprehend" endpoint call usage if the content has a match, there is no need to have SpamSpy recalculate responses it has already reviewed. + This endpoint checks the existing spam database for queried content and sends back the latest scanned result if the content exists yet. + + Example Responses: + `{"SpamSpyResult":true}` (content is spam) + `{"SpamSpyResult":false}`(content is not spam) + `{"SpamSpyResult":"Content not yet scanned"}` (content has **NOT YET** been scanned)" + + """ + url = f"https://spamspy.p.rapidapi.com/remember" + querystring = {'content': content, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "spamspy.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def auth_check(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Checks if the API Key is still valid" + + """ + url = f"https://spamspy.p.rapidapi.com/auth" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "spamspy.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def comprehend(content: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Comprehend uses the current AI public modals and submits the content (located in the query string) to be identified as spam or not. + - Fetch Method Get + - Returns Boolean: **true** / **false** + Example Response: + `{"SpamSpyResult":true}` (content is spam) + `{"SpamSpyResult":false}`(content is not spam)" + + """ + url = f"https://spamspy.p.rapidapi.com/comprehend" + querystring = {'content': content, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "spamspy.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_diarization_and_audio_transcription_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_diarization_and_audio_transcription_api.json new file mode 100644 index 0000000000000000000000000000000000000000..d656928c959f8e084d13b3fd4626c42a456e2a3e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_diarization_and_audio_transcription_api.json @@ -0,0 +1,46 @@ +{ + "product_id": "api_a157840a-5072-430a-9d4c-38bdfc89c174", + "tool_description": "Transcribe audio files with speaker diarization using the Speaker Diarization and Audio Transcription API. This powerful API allows you to convert audio recordings into text while identifying and separating speakers. Whether you have recorded interviews, meetings, or lectures, this API makes it easy to obtain accurate transcriptions with speaker attribution. Choose between uploading audio files, providing a direct file URL, or sending base64-encoded audio data. Monitor the transcription progr...", + "home_url": "https://rapidapi.com/mohamedgb00714/api/speaker-diarization-and-audio-transcription-api/", + "name": "Speaker Diarization and Audio Transcription API", + "title": "Speaker Diarization and Audio Transcription API", + "pricing": "FREEMIUM", + "tool_name": "Speaker Diarization and Audio Transcription API", + "score": { + "avgServiceLevel": 90, + "avgLatency": 2270, + "avgSuccessRate": 29, + "popularityScore": 2, + "__typename": "Score" + }, + "host": "speaker-diarization-and-audio-transcription-api.p.rapidapi.com", + "api_list": [ + { + "name": "transcribe", + "url": "https://speaker-diarization-and-audio-transcription-api.p.rapidapi.com/transcribe", + "description": "Flexible Audio Transcription Service\n\nThis endpoint offers a versatile audio transcription service that accommodates your specific needs. You can select one of three parameters: file_url, file_string, or file, to provide your audio data for transcription. Additionally, you have control over the maximum processing time for your request.\n\nParameters:\n\n file_url (string, optional): Provide a direct URL to an audio file for transcription. The service will access and process the file remotely.\n\n file_string (string, optional): Send the audio data as a base64-encoded string within the request. This option allows direct transmission of audio content.\n\n file (file, optional): Upload an audio file directly as part of the request. You can provide the audio file from your local storage.\n\nNote: You can choose to use either file_url, file_string, or file to provide the audio data. This flexible endpoint accommodates various audio transcription scenarios while ensuring that your request processing adheres to predefined time constraints.", + "method": "POST", + "required_parameters": [ + { + "name": "file_url", + "type": "STRING", + "description": "", + "default": "https://nicetalkingwithyou.com/wp-content/uploads/2018/07/003NTWY_U1_CL.mp3" + } + ], + "optional_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "code": "import requests\n\nurl = \"https://speaker-diarization-and-audio-transcription-api.p.rapidapi.com/transcribe\"\nquerystring = {\"file_url\": \"https://nicetalkingwithyou.com/wp-content/uploads/2018/07/003NTWY_U1_CL.mp3\", \"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-diarization-and-audio-transcription-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speaker-diarization-and-audio-transcription-api.p.rapidapi.com/transcribe\"\nquerystring = {\"file_url\": \"https://nicetalkingwithyou.com/wp-content/uploads/2018/07/003NTWY_U1_CL.mp3\", \"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-diarization-and-audio-transcription-api.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_verification.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_verification.json new file mode 100644 index 0000000000000000000000000000000000000000..cf59d79c1681160732a34147677cfe5088d86b12 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speaker_verification.json @@ -0,0 +1,93 @@ +{ + "product_id": "api_6486cdec-fa7a-472b-8e57-8b6acaac5194", + "tool_description": "PresentID Speaker verification API checks whether two voices belong to the same person or not. This capability is potentially useful in call centers. ", + "home_url": "https://rapidapi.com/PresentID/api/speaker-verification1/", + "name": "Speaker Verification", + "title": "Speaker Verification", + "pricing": "FREEMIUM", + "tool_name": "Speaker Verification", + "score": { + "avgServiceLevel": 100, + "avgLatency": 3067, + "avgSuccessRate": 100, + "popularityScore": 8.2, + "__typename": "Score" + }, + "host": "speaker-verification1.p.rapidapi.com", + "api_list": [ + { + "name": "Send voice with voice file", + "url": "https://speaker-verification1.p.rapidapi.com/Verification", + "description": "Speaker verification API checks whether two voices belong to one person or not \n\nThe voice must be between three seconds and one minute\nThe voices must not exceed 5 MB\nSupported file types: wav, mp3, m4a, FLAC, aac, ogg", + "method": "POST", + "required_parameters": [ + { + "name": "sound1", + "type": "BINARY", + "description": "", + "default": "" + }, + { + "name": "sound2", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"sound1\": \"\", \"sound2\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"sound1\": \"\", \"sound2\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + }, + { + "name": "Send voice with Base64", + "url": "https://speaker-verification1.p.rapidapi.com/Verification", + "description": "Speaker verification API checks whether two voices belong to one person or not \n\nThe voice must be between three seconds and one minute\nThe voices must not exceed 5 MB\nSupported file types: wav, mp3, m4a, FLAC, aac, ogg", + "method": "POST", + "required_parameters": [ + { + "name": "sound1Base64", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "sound2Base64", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"sound1Base64\": \"\", \"sound2Base64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"sound1Base64\": \"\", \"sound2Base64\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Send voice with Voice URL", + "url": "https://speaker-verification1.p.rapidapi.com/Verification", + "description": "Speaker verification API checks whether two voices belong to one person or not.\n\nThe voice must be between three seconds and one minute\nThe voices must not exceed 5 MB\nSupported file types: wav, mp3, m4a, FLAC, aac, ogg", + "method": "POST", + "required_parameters": [ + { + "name": "linkFile1", + "type": "STRING", + "description": "", + "default": "" + }, + { + "name": "linkFile2", + "type": "STRING", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"linkFile1\": \"\", \"linkFile2\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speaker-verification1.p.rapidapi.com/Verification\"\nquerystring = {\"linkFile1\": \"\", \"linkFile2\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speaker-verification1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech2text.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech2text.json new file mode 100644 index 0000000000000000000000000000000000000000..55bed0bb43a9433b60a323eefc8b7734c036cdf0 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech2text.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_2cba4822-1b2b-4215-87db-4bb73811a708", + "tool_description": "A Speech to Text API (Application Programming Interface) is a software tool that allows developers to build applications that can transcribe spoken words into text. It uses machine learning algorithms to analyze and convert audio files, such as recorded voice memos or live speech, into written words. Speech to Text APIs are commonly used in various applications such as transcription software, voice-activated assistants, and closed captioning services. With speech to text technology, users can...", + "home_url": "https://rapidapi.com/ai-solution-ai-solution-default/api/speech2text/", + "name": "Speech2Text", + "title": "Speech2Text", + "pricing": "FREEMIUM", + "tool_name": "Speech2Text", + "score": { + "avgServiceLevel": 100, + "avgLatency": 388, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "speech2text.p.rapidapi.com", + "api_list": [ + { + "name": "Speech2Text", + "url": "https://speech2text.p.rapidapi.com/whisper-large-v2", + "description": "Convert speech to text", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech2text.p.rapidapi.com/whisper-large-v2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech2text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speech2text.p.rapidapi.com/whisper-large-v2\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech2text.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_detection.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..77f2113340bee42b4fb1f56ad56c2c40623fe487 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_detection.json @@ -0,0 +1,39 @@ +{ + "product_id": "api_712c5339-ad42-4168-89ce-c41c83af33c8", + "tool_description": "Identify and extract speech segments from an audio or video file, regardless of the language being spoken.", + "home_url": "https://rapidapi.com/viktorenzell/api/speech-detection/", + "name": "Speech Detection", + "title": "Speech Detection", + "pricing": "FREEMIUM", + "tool_name": "Speech Detection", + "score": { + "avgServiceLevel": 100, + "avgLatency": 29952, + "avgSuccessRate": 100, + "popularityScore": 8.6, + "__typename": "Score" + }, + "host": "speech-detection.p.rapidapi.com", + "api_list": [ + { + "name": "Get speech segments from audio", + "url": "https://speech-detection.p.rapidapi.com/get_speech_segments", + "description": "Upload an audio or video file and get back a list of time segments where speech was detected.", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "Audio or video file of maximum 10 MB.", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech-detection.p.rapidapi.com/get_speech_segments\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speech-detection.p.rapidapi.com/get_speech_segments\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-detection.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition.json new file mode 100644 index 0000000000000000000000000000000000000000..4bb20370e3461ac1f77d5fa47c5f7e5234dcd125 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition.json @@ -0,0 +1,655 @@ +{ + "tool_name": "Speech Recognition", + "tool_description": "Convert speech to text quickly and easily. Supports 100+ languages", + "title": "Speech Recognition", + "pricing": "FREEMIUM", + "score": { + "avgServiceLevel": 100, + "avgLatency": 582, + "avgSuccessRate": 100, + "popularityScore": 9.2, + "__typename": "Score" + }, + "home_url": "https://rapidapi.com/dickyagustin/api/speech-recognition14/", + "host": "speech-recognition14.p.rapidapi.com", + "api_list": [ + { + "name": "languages", + "url": "https://speech-recognition14.p.rapidapi.com/languages", + "description": "Get list of supported languages", + "method": "GET", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech-recognition14.p.rapidapi.com/languages\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-recognition14.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "status": "success", + "languages": [ + { + "name": "Afrikaans (South Africa)", + "code": "af-ZA" + }, + { + "name": "Albanian (Albania)", + "code": "sq-AL" + }, + { + "name": "Amharic (Ethiopia)", + "code": "am-ET" + }, + { + "name": "Arabic (Algeria)", + "code": "ar-DZ" + }, + { + "name": "Arabic (Bahrain)", + "code": "ar-BH" + }, + { + "name": "Arabic (Egypt)", + "code": "ar-EG" + }, + { + "name": "Arabic (Iraq)", + "code": "ar-IQ" + }, + { + "name": "Arabic (Israel)", + "code": "ar-IL" + }, + { + "name": "Arabic (Jordan)", + "code": "ar-JO" + }, + { + "name": "Arabic (Kuwait)", + "code": "ar-KW" + }, + { + "name": "Arabic (Lebanon)", + "code": "ar-LB" + }, + { + "name": "Arabic (Morocco)", + "code": "ar-MA" + }, + { + "name": "Arabic (Oman)", + "code": "ar-OM" + }, + { + "name": "Arabic (Qatar)", + "code": "ar-QA" + }, + { + "name": "Arabic (Saudi Arabia)", + "code": "ar-SA" + }, + { + "name": "Arabic (State of Palestine)", + "code": "ar-PS" + }, + { + "name": "Arabic (Tunisia)", + "code": "ar-TN" + }, + { + "name": "Arabic (United Arab Emirates)", + "code": "ar-AE" + }, + { + "name": "Arabic (Yemen)", + "code": "ar-YE" + }, + { + "name": "Armenian (Armenia)", + "code": "hy-AM" + }, + { + "name": "Azerbaijani (Azerbaijan)", + "code": "az-AZ" + }, + { + "name": "Basque (Spain)", + "code": "eu-ES" + }, + { + "name": "Bengali (Bangladesh)", + "code": "bn-BD" + }, + { + "name": "Bengali (India)", + "code": "bn-IN" + }, + { + "name": "Bosnian (Bosnia and Herzegovina)", + "code": "bs-BA" + }, + { + "name": "Bulgarian (Bulgaria)", + "code": "bg-BG" + }, + { + "name": "Burmese (Myanmar)", + "code": "my-MM" + }, + { + "name": "Catalan (Spain)", + "code": "ca-ES" + }, + { + "name": "Chinese, Cantonese (Traditional Hong Kong)", + "code": "yue-Hant-HK" + }, + { + "name": "Chinese, Mandarin (Simplified, China)", + "code": "zh" + }, + { + "name": "Chinese, Mandarin (Traditional, Taiwan)", + "code": "zh-TW" + }, + { + "name": "Croatian (Croatia)", + "code": "hr-HR" + }, + { + "name": "Czech (Czech Republic)", + "code": "cs-CZ" + }, + { + "name": "Danish (Denmark)", + "code": "da-DK" + }, + { + "name": "Dutch (Belgium)", + "code": "nl-BE" + }, + { + "name": "Dutch (Netherlands)", + "code": "nl-NL" + }, + { + "name": "English (Australia)", + "code": "en-AU" + }, + { + "name": "English (Canada)", + "code": "en-CA" + }, + { + "name": "English (Ghana)", + "code": "en-GH" + }, + { + "name": "English (Hong Kong)", + "code": "en-HK" + }, + { + "name": "English (India)", + "code": "en-IN" + }, + { + "name": "English (Ireland)", + "code": "en-IE" + }, + { + "name": "English (Kenya)", + "code": "en-KE" + }, + { + "name": "English (New Zealand)", + "code": "en-NZ" + }, + { + "name": "English (Nigeria)", + "code": "en-NG" + }, + { + "name": "English (Pakistan)", + "code": "en-PK" + }, + { + "name": "English (Philippines)", + "code": "en-PH" + }, + { + "name": "English (Singapore)", + "code": "en-SG" + }, + { + "name": "English (South Africa)", + "code": "en-ZA" + }, + { + "name": "English (Tanzania)", + "code": "en-TZ" + }, + { + "name": "English (United Kingdom)", + "code": "en-GB" + }, + { + "name": "English (United States)", + "code": "en-US" + }, + { + "name": "Estonian (Estonia)", + "code": "et-EE" + }, + { + "name": "Filipino (Philippines)", + "code": "fil-PH" + }, + { + "name": "Finnish (Finland)", + "code": "fi-FI" + }, + { + "name": "French (Belgium)", + "code": "fr-BE" + }, + { + "name": "French (Canada)", + "code": "fr-CA" + }, + { + "name": "French (France)", + "code": "fr-FR" + }, + { + "name": "French (Switzerland)", + "code": "fr-CH" + }, + { + "name": "Galician (Spain)", + "code": "gl-ES" + }, + { + "name": "Georgian (Georgia)", + "code": "ka-GE" + }, + { + "name": "German (Austria)", + "code": "de-AT" + }, + { + "name": "German (Germany)", + "code": "de-DE" + }, + { + "name": "German (Switzerland)", + "code": "de-CH" + }, + { + "name": "Greek (Greece)", + "code": "el-GR" + }, + { + "name": "Gujarati (India)", + "code": "gu-IN" + }, + { + "name": "Hindi (India)", + "code": "hi-IN" + }, + { + "name": "Hungarian (Hungary)", + "code": "hu-HU" + }, + { + "name": "Icelandic (Iceland)", + "code": "is-IS" + }, + { + "name": "Indonesian (Indonesia)", + "code": "id-ID" + }, + { + "name": "Italian (Italy)", + "code": "it-IT" + }, + { + "name": "Italian (Switzerland)", + "code": "it-CH" + }, + { + "name": "Japanese (Japan)", + "code": "ja-JP" + }, + { + "name": "Javanese (Indonesia)", + "code": "jv-ID" + }, + { + "name": "Kannada (India)", + "code": "kn-IN" + }, + { + "name": "Kazakh (Kazakhstan)", + "code": "kk-KZ" + }, + { + "name": "Khmer (Cambodia)", + "code": "km-KH" + }, + { + "name": "Korean (South Korea)", + "code": "ko-KR" + }, + { + "name": "Lao (Laos)", + "code": "lo-LA" + }, + { + "name": "Latvian (Latvia)", + "code": "lv-LV" + }, + { + "name": "Lithuanian (Lithuania)", + "code": "lt-LT" + }, + { + "name": "Macedonian (North Macedonia)", + "code": "mk-MK" + }, + { + "name": "Malay (Malaysia)", + "code": "ms-MY" + }, + { + "name": "Malayalam (India)", + "code": "ml-IN" + }, + { + "name": "Marathi (India)", + "code": "mr-IN" + }, + { + "name": "Mongolian (Mongolia)", + "code": "mn-MN" + }, + { + "name": "Nepali (Nepal)", + "code": "ne-NP" + }, + { + "name": "Norwegian Bokm\u00e5l (Norway)", + "code": "no-NO" + }, + { + "name": "Persian (Iran)", + "code": "fa-IR" + }, + { + "name": "Polish (Poland)", + "code": "pl-PL" + }, + { + "name": "Portuguese (Brazil)", + "code": "pt-BR" + }, + { + "name": "Portuguese (Portugal)", + "code": "pt-PT" + }, + { + "name": "Punjabi (Gurmukhi India)", + "code": "pa-Guru-IN" + }, + { + "name": "Romanian (Romania)", + "code": "ro-RO" + }, + { + "name": "Russian (Russia)", + "code": "ru-RU" + }, + { + "name": "Serbian (Serbia)", + "code": "sr-RS" + }, + { + "name": "Sinhala (Sri Lanka)", + "code": "si-LK" + }, + { + "name": "Slovak (Slovakia)", + "code": "sk-SK" + }, + { + "name": "Slovenian (Slovenia)", + "code": "sl-SI" + }, + { + "name": "Spanish (Argentina)", + "code": "es-AR" + }, + { + "name": "Spanish (Bolivia)", + "code": "es-BO" + }, + { + "name": "Spanish (Chile)", + "code": "es-CL" + }, + { + "name": "Spanish (Colombia)", + "code": "es-CO" + }, + { + "name": "Spanish (Costa Rica)", + "code": "es-CR" + }, + { + "name": "Spanish (Dominican Republic)", + "code": "es-DO" + }, + { + "name": "Spanish (Ecuador)", + "code": "es-EC" + }, + { + "name": "Spanish (El Salvador)", + "code": "es-SV" + }, + { + "name": "Spanish (Guatemala)", + "code": "es-GT" + }, + { + "name": "Spanish (Honduras)", + "code": "es-HN" + }, + { + "name": "Spanish (Mexico)", + "code": "es-MX" + }, + { + "name": "Spanish (Nicaragua)", + "code": "es-NI" + }, + { + "name": "Spanish (Panama)", + "code": "es-PA" + }, + { + "name": "Spanish (Paraguay)", + "code": "es-PY" + }, + { + "name": "Spanish (Peru)", + "code": "es-PE" + }, + { + "name": "Spanish (Puerto Rico)", + "code": "es-PR" + }, + { + "name": "Spanish (Spain)", + "code": "es-ES" + }, + { + "name": "Spanish (United States)", + "code": "es-US" + }, + { + "name": "Spanish (Uruguay)", + "code": "es-UY" + }, + { + "name": "Spanish (Venezuela)", + "code": "es-VE" + }, + { + "name": "Sundanese (Indonesia)", + "code": "su-ID" + }, + { + "name": "Swahili (Kenya)", + "code": "sw-KE" + }, + { + "name": "Swahili (Tanzania)", + "code": "sw-TZ" + }, + { + "name": "Swedish (Sweden)", + "code": "sv-SE" + }, + { + "name": "Tamil (India)", + "code": "ta-IN" + }, + { + "name": "Tamil (Malaysia)", + "code": "ta-MY" + }, + { + "name": "Tamil (Singapore)", + "code": "ta-SG" + }, + { + "name": "Tamil (Sri Lanka)", + "code": "ta-LK" + }, + { + "name": "Telugu (India)", + "code": "te-IN" + }, + { + "name": "Thai (Thailand)", + "code": "th-TH" + }, + { + "name": "Turkish (Turkey)", + "code": "tr-TR" + }, + { + "name": "Ukrainian (Ukraine)", + "code": "uk-UA" + }, + { + "name": "Urdu (India)", + "code": "ur-IN" + }, + { + "name": "Urdu (Pakistan)", + "code": "ur-PK" + }, + { + "name": "Uzbek (Uzbekistan)", + "code": "uz-UZ" + }, + { + "name": "Vietnamese (Vietnam)", + "code": "vi-VN" + }, + { + "name": "Zulu (South Africa)", + "code": "zu-ZA" + } + ] + }, + "headers": { + "access-control-allow-credentials": "true", + "access-control-allow-origin": "*", + "connection": "keep-alive", + "content-length": "12493", + "content-type": "application/json", + "date": "Sun, 10 Apr 2022 06:26:20 GMT", + "server": "RapidAPI-1.2.8", + "via": "1.1 vegur", + "x-rapidapi-region": "AWS - ap-southeast-1", + "x-rapidapi-version": "1.2.8" + }, + "schema": {} + }, + { + "name": "recognize", + "url": "https://speech-recognition14.p.rapidapi.com/recognize", + "description": "Endpoint for speech recognition process.\nOur service supports audio formats: **mp3**, **wav** and **ogg**", + "method": "POST", + "required_parameters": [ + { + "name": "audio_url", + "type": "STRING", + "description": "Fill in the audio url that will be processed", + "default": "https://firebasestorage.googleapis.com/v0/b/rapid-tts.appspot.com/o/audio-464d3947de1178515a3a937f0d7e2f10.mp3?alt=media" + }, + { + "name": "language_code", + "type": "STRING", + "description": "", + "default": "en-US" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech-recognition14.p.rapidapi.com/recognize\"\nquerystring = {\"audio_url\": audio_url, \"language_code\": language_code}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-recognition14.p.rapidapi.com\"\n}\n\nresponse = requests.post(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode": 200, + "body": { + "status": "success", + "result": "Speech recognition allows you to convert audio to text our service supports many languages with high accuracy and fast processing. Try it now." + }, + "headers": { + "access-control-allow-credentials": "true", + "access-control-allow-origin": "*", + "connection": "keep-alive", + "content-length": "187", + "content-type": "application/json", + "date": "Sun, 10 Apr 2022 06:46:54 GMT", + "server": "RapidAPI-1.2.8", + "via": "1.1 vegur", + "x-rapidapi-region": "AWS - ap-southeast-1", + "x-rapidapi-version": "1.2.8" + }, + "schema": {} + }, + { + "name": "recognize", + "url": "https://speech-recognition14.p.rapidapi.com/recognize", + "description": "Endpoint for speech recognition process.\nOur service supports audio formats: **mp3**, **wav** and **ogg**", + "method": "POST", + "required_parameters": [ + { + "name": "audio_url", + "type": "STRING", + "description": "Fill in the audio url that will be processed", + "default": "https://firebasestorage.googleapis.com/v0/b/rapid-tts.appspot.com/o/audio-464d3947de1178515a3a937f0d7e2f10.mp3?alt=media" + }, + { + "name": "language_code", + "type": "STRING", + "description": "", + "default": "en-US" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech-recognition14.p.rapidapi.com/recognize\"\nquerystring = {\"audio_url\": \"https://firebasestorage.googleapis.com/v0/b/rapid-tts.appspot.com/o/audio-464d3947de1178515a3a937f0d7e2f10.mp3?alt=media\", \"language_code\": \"en-US\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-recognition14.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speech-recognition14.p.rapidapi.com/recognize\"\nquerystring = {\"audio_url\": \"https://firebasestorage.googleapis.com/v0/b/rapid-tts.appspot.com/o/audio-464d3947de1178515a3a937f0d7e2f10.mp3?alt=media\", \"language_code\": \"en-US\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-recognition14.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition/api.py new file mode 100644 index 0000000000000000000000000000000000000000..089513e05af49aa43a94aa319a295455720c6b9c --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_recognition/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def languages(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Get list of supported languages" + + """ + url = f"https://speech-recognition14.p.rapidapi.com/languages" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "speech-recognition14.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_to_text.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_to_text.json new file mode 100644 index 0000000000000000000000000000000000000000..d4a5110a8fc71bafcd182e4f0e71404cd0164845 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speech_to_text.json @@ -0,0 +1,43 @@ +{ + "product_id": "api_0b1b213d-1c31-4969-8adf-18bcbe2faa2c", + "tool_description": "Transcribe 28 languages from 376 file formats, including video, with over 50GB of training data ensuring precision. User-friendly and powerful.", + "home_url": "https://rapidapi.com/talk2txt/api/speech-to-text20/", + "name": "Speech To Text", + "title": "Speech To Text", + "pricing": "FREEMIUM", + "tool_name": "Speech To Text", + "score": { + "avgServiceLevel": 0, + "avgLatency": 124810, + "avgSuccessRate": 0, + "popularityScore": 0.1, + "__typename": "Score" + }, + "host": "speech-to-text20.p.rapidapi.com", + "api_list": [ + { + "name": "Transcribe", + "url": "https://speech-to-text20.p.rapidapi.com/", + "description": "Upload an audio file and transcribe to text.\nlanguage option:\nEnglish = en-us\nEnglish India = en-in\nChinese = cn\nRussian = ru\nFrench = fr\nGerman = de\nSpanish = es\nPortuguese/Brazilian = pt\nGreek = el-gr\nTurkish = tr\nVietnamese = vn\nItalian = it\nDutch = nl\nCatalan = ca\nArabic = ar\nFarsi = fa\nFilipino = ph\nUkrainian = uk\nKazakh = kz\nSwedish = sv\nJapanese = ja\nEsperanto = eo\nHindi = hi\nCzech = cs\nPolish = pl\nUzbek = uz\nKorean = ko\nBreton = br", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + }, + { + "name": "language", + "type": "STRING", + "description": "", + "default": "en-us" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speech-to-text20.p.rapidapi.com/\"\nquerystring = {\"file\": \"\", \"language\": \"en-us\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-to-text20.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speech-to-text20.p.rapidapi.com/\"\nquerystring = {\"file\": \"\", \"language\": \"en-us\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speech-to-text20.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speechy.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speechy.json new file mode 100644 index 0000000000000000000000000000000000000000..5bcbb9998f3a94b25ead954d9e29b2a8a5ca305d --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/speechy.json @@ -0,0 +1,57 @@ +{ + "product_id": "api_66a397e7-9333-43a7-b62f-63c700d883bb", + "tool_description": "Speech to text in 20+ languages, support files up to 1 hours long. Convert audio or video to text. Voice to text.", + "home_url": "https://rapidapi.com/onipot/api/speechy/", + "name": "Speechy", + "title": "Speechy", + "pricing": "FREEMIUM", + "tool_name": "Speechy", + "score": { + "avgServiceLevel": 0, + "avgLatency": 72731, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "speechy.p.rapidapi.com", + "api_list": [ + { + "name": "Convert Video/Audio To Text [ACCURATE]", + "url": "https://speechy.p.rapidapi.com/media-to-text-accurate", + "description": "Convert any audio or video file to text with our most accurate model. \nResponse time benchmarks:\n- 5min audio -> 20 seconds\n- 20min audio -> 2.5 minutes", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speechy.p.rapidapi.com/media-to-text-accurate\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speechy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speechy.p.rapidapi.com/media-to-text-accurate\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speechy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Convert Video/Audio To Text [FASTER]", + "url": "https://speechy.p.rapidapi.com/media-to-text-faster", + "description": "Convert any audio or video file to text. It uses a lighter model, so it is faster.\nUse this when:\n- audio is crisp\n- you want faster responses", + "method": "POST", + "required_parameters": [ + { + "name": "file", + "type": "BINARY", + "description": "", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://speechy.p.rapidapi.com/media-to-text-faster\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speechy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://speechy.p.rapidapi.com/media-to-text-faster\"\nquerystring = {\"file\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"speechy.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spinmenot.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spinmenot.json new file mode 100644 index 0000000000000000000000000000000000000000..1dad3baf0c7ce7dc31c243f0eb0b618be4b179a7 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/spinmenot.json @@ -0,0 +1,44 @@ +{ + "product_id": "api_f61424f9-a193-4521-bfaf-97c013b0b5e8", + "tool_description": "Detects spun content and AI-generated text.", + "home_url": "https://rapidapi.com/grammarbot/api/spinmenot/", + "name": "SpinMeNot", + "title": "SpinMeNot", + "pricing": "PAID", + "tool_name": "SpinMeNot", + "score": { + "avgServiceLevel": 100, + "avgLatency": 379, + "avgSuccessRate": 100, + "popularityScore": 8.4, + "__typename": "Score" + }, + "host": "spinmenot.p.rapidapi.com", + "api_list": [ + { + "name": "detect", + "url": "https://spinmenot.p.rapidapi.com/detect_www", + "description": "Detect spun content", + "method": "POST", + "required_parameters": [ + { + "name": "text", + "type": "STRING", + "description": "", + "default": "I went to the store today and got a few basic foods." + } + ], + "optional_parameters": [ + { + "name": "fmt", + "type": "STRING", + "description": "Value can be \"dict\" or \"list\". Default value is \"dict\". This determines whether the word scores are formatted as an associative array (dict) or an array of objects (list).", + "default": "dict" + } + ], + "code": "import requests\n\nurl = \"https://spinmenot.p.rapidapi.com/detect_www\"\nquerystring = {\"fmt\": \"dict\", \"text\": \"I went to the store today and got a few basic foods.\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spinmenot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://spinmenot.p.rapidapi.com/detect_www\"\nquerystring = {\"fmt\": \"dict\", \"text\": \"I went to the store today and got a few basic foods.\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"spinmenot.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stability_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stability_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..642c83983ce6f9cd010ceda1f5f144e1382bdebd --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stability_ai.json @@ -0,0 +1,41 @@ +{ + "product_id": "api_54269fab-b858-44a6-8e6e-158a23686614", + "tool_description": "A text-to-image generative AI model that creates beautiful 1024x1024 images", + "home_url": "https://rapidapi.com/ankatechllc/api/stability-ai5/", + "name": "Stability AI", + "title": "Stability AI", + "pricing": "FREEMIUM", + "tool_name": "Stability AI", + "score": { + "avgServiceLevel": 95, + "avgLatency": 6726, + "avgSuccessRate": 95, + "popularityScore": 9.3, + "__typename": "Score" + }, + "host": "stability-ai5.p.rapidapi.com", + "api_list": [ + { + "name": "Generate Images Syncronously", + "url": "https://stability-ai5.p.rapidapi.com/v1/images", + "description": "Generate Images Syncronously", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stability-ai5.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stability-ai5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stability-ai5.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stability-ai5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "Generate Images Asyncronously", + "url": "https://stability-ai5.p.rapidapi.com/v1/images", + "description": "Generate Images Asyncronously", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stability-ai5.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stability-ai5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stability-ai5.p.rapidapi.com/v1/images\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stability-ai5.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_sdxl.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_sdxl.json new file mode 100644 index 0000000000000000000000000000000000000000..b6e8e8638f51d88f31eae4bd7dd2bf1c722acbb6 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_sdxl.json @@ -0,0 +1,48 @@ +{ + "product_id": "api_59bf1af3-dcb4-45fe-926b-955d66d7f58a", + "tool_description": "Stable Diffusion XL (SDXL 1.0 Base + Refiner) endpoints make you able to generate quality photos using the following params: \n\n- prompt text\n- negative prompt text \n- width\n- height\n- number of inference steps", + "home_url": "https://rapidapi.com/growthmkt-growthmkt-default/api/stable-diffusion-sdxl/", + "name": "Stable Diffusion SDXL ", + "title": "Stable Diffusion SDXL ", + "pricing": "PAID", + "tool_name": "Stable Diffusion SDXL ", + "score": null, + "host": "stable-diffusion-sdxl.p.rapidapi.com", + "api_list": [ + { + "name": "Generate new photo (Base + Refiner)", + "url": "https://stable-diffusion-sdxl.p.rapidapi.com/generate", + "description": "It generates a new photo using Stable Diffusion model XL 1.0 returning a base 64 image encoded. This endpoint inference uses the Base model and Refiner to provide much better resolutions and details.\n\n**It usually takes 10 seconds on average**\n\n**We strongly recommend to use a long timeout (max 1 min) due to timing to generate the image on our servers**", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stable-diffusion-sdxl.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-sdxl.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stable-diffusion-sdxl.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-sdxl.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "image": { + "type": "array", + "items": { + "type": "string" + } + }, + "message": { + "type": "string" + }, + "run_id": { + "type": "string" + }, + "run_time": { + "type": "number" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2.json new file mode 100644 index 0000000000000000000000000000000000000000..ebb004cd3c4fe819cadb045eca2a3767fd8c9518 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2.json @@ -0,0 +1,38 @@ +{ + "product_id": "api_4128a415-938a-4605-bf00-5469e6679028", + "tool_description": "Generate high-quality images with the latest Stable Diffusion v2.1 model.", + "home_url": "https://rapidapi.com/apis-world-apis-world-default/api/stable-diffusion-v2/", + "name": "Stable Diffusion v2", + "title": "Stable Diffusion v2", + "pricing": "FREEMIUM", + "tool_name": "Stable Diffusion v2", + "score": { + "avgServiceLevel": 100, + "avgLatency": 2109, + "avgSuccessRate": 100, + "popularityScore": 9, + "__typename": "Score" + }, + "host": "stable-diffusion-v2.p.rapidapi.com", + "api_list": [ + { + "name": "Generate Image", + "url": "https://stable-diffusion-v2.p.rapidapi.com/stable-diffusion", + "description": "Generate an image with stable diffusion", + "method": "GET", + "required_parameters": [ + { + "name": "description", + "type": "STRING", + "description": "", + "default": "cat" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stable-diffusion-v2.p.rapidapi.com/stable-diffusion\"\nquerystring = {\"description\": \"cat\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-v2.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stable-diffusion-v2.p.rapidapi.com/stable-diffusion\"\nquerystring = {\"description\": \"cat\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-v2.p.rapidapi.com\"\n }\n\nresponse = requests.get(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "https://dbuzz-assets.s3.amazonaws.com/api_image/sd/image-642564938567.jpg" + } + ], + "standardized_name": "stable_diffusion_v2" +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2/api.py new file mode 100644 index 0000000000000000000000000000000000000000..253ab5193d335864c4bcb3fe0314c8456d2f7842 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def generate_image(description: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Generate an image with stable diffusion" + + """ + url = f"https://stable-diffusion-v2.p.rapidapi.com/stable-diffusion" + querystring = {'description': description, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stable-diffusion-v2.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2_1.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2_1.json new file mode 100644 index 0000000000000000000000000000000000000000..247e57eebafd92cc358a9565de15b08046ae6b59 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stable_diffusion_v2_1.json @@ -0,0 +1,48 @@ +{ + "product_id": "api_b8a3b5fd-2346-459c-97fd-b52a673c661e", + "tool_description": "Stable Diffusion 2.1 model version endpoints enable you to generate quality photos using simple text prompts and filling in the other params to create a stunning photo, as you can see below.", + "home_url": "https://rapidapi.com/growthmkt-growthmkt-default/api/stable-diffusion-v2-11/", + "name": "Stable Diffusion V2.1", + "title": "Stable Diffusion V2.1", + "pricing": "PAID", + "tool_name": "Stable Diffusion V2.1", + "score": null, + "host": "stable-diffusion-v2-11.p.rapidapi.com", + "api_list": [ + { + "name": "Generate", + "url": "https://stable-diffusion-v2-11.p.rapidapi.com/generate", + "description": "It generates a new photo using Stable Diffusion model 2.1 returning a base 64 image encoded. \n\n**We strongly recommend to use a long timeout (max 1 min) due to timing to generate the image on our servers**", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stable-diffusion-v2-11.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-v2-11.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stable-diffusion-v2-11.p.rapidapi.com/generate\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stable-diffusion-v2-11.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "statusCode": { + "type": "integer" + }, + "image": { + "type": "array", + "items": { + "type": "string" + } + }, + "message": { + "type": "string" + }, + "run_id": { + "type": "string" + }, + "run_time": { + "type": "number" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor.json new file mode 100644 index 0000000000000000000000000000000000000000..6675ea6919762858f61a5024ae246dec1a272e31 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor.json @@ -0,0 +1,37 @@ +{ + "tool_name":"StarPredictAI - AI-powered Text Review Star Predictor", + "tool_description":"🌟 Want to know how many stars your product review deserves? Look no further than StarPredictAI! Our AI model is fine-tuned for sentiment analysis on product reviews and can predict star ratings from 0 to 5 with high accuracy. With support for over 140 languages, StarPredictAI can help you gain valuable insights into your product's customer satisfaction. 🚀", + "title":"StarPredictAI - AI-powered Text Review Star Predictor", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":100, + "avgLatency":2101, + "avgSuccessRate":100, + "popularityScore":8.1, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/IntelligenzaArtificiale/api/starpredictai-ai-powered-text-review-star-predictor/", + "host":"starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com", + "api_list":[ + { + "name":"StarPredictAI API 🌟", + "url":"https://starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com/reviewStar", + "description":"🌟 Our API can analyze text in over 140 languages", + "method":"GET", + "required_parameters":[ + { + "name":"text", + "type":"STRING", + "description":"", + "default":"Support over 140 languages, try it now :)" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com/reviewStar\"\nquerystring = {\"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor/api.py new file mode 100644 index 0000000000000000000000000000000000000000..19a13808fb7bd40bca4ba229a8e517dd1cf1edcb --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/starpredictai_ai_powered_text_review_star_predictor/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def starpredictai_api(text: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "🌟 Our API can analyze text in over 140 languages" + + """ + url = f"https://starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com/reviewstar" + querystring = {'text': text, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "starpredictai-ai-powered-text-review-star-predictor.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stileschat_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stileschat_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..dd2b0277f5fa9be7a345ab5326a025509bbbc0d6 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stileschat_ai.json @@ -0,0 +1,30 @@ +{ + "product_id": "api_97fa23d5-3245-4821-9d19-6252de6196db", + "tool_description": "The API accepts user input in the form of a question or query and processes it using advanced NLP algorithms. It handles various question types, including factual, descriptive, and inferential questions. Contextual Understanding: The API is designed to understand the context of the question by analyzing the provided query along with any accompanying information or context. This enables it to generate accurate answers that are contextually relevant.", + "home_url": "https://rapidapi.com/dastilesforever-FjcvEn-J9dL/api/stileschat-ai/", + "name": "stilesChat AI", + "title": "stilesChat AI", + "pricing": "FREE", + "tool_name": "stilesChat AI", + "score": { + "avgServiceLevel": 25, + "avgLatency": 504, + "avgSuccessRate": 25, + "popularityScore": 1.9, + "__typename": "Score" + }, + "host": "stileschat-ai.p.rapidapi.com", + "api_list": [ + { + "name": "chat", + "url": "https://stileschat-ai.p.rapidapi.com/api", + "description": "chat with an ai", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://stileschat-ai.p.rapidapi.com/api\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stileschat-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://stileschat-ai.p.rapidapi.com/api\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stileschat-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database.json new file mode 100644 index 0000000000000000000000000000000000000000..7109ead5c425476c7ab35e67723952ddb1465db1 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database.json @@ -0,0 +1,2955 @@ +{ + "tool_name":"Stock, Ticker, Security and Company Search database", + "tool_description":"Lookup active tickers using fuzzy Security name search from exchanges worldwide.\nGet the Security name from the ticker.\nCheck if a company is in the S&P 500 or get a list of all SP500 companies.\nGet the historical Price and Volume of security.\nGet the sentiment of companies mentioned in an article. ", + "title":"Stock, Ticker, Security and Company Search database", + "pricing":"FREEMIUM", + "score":{ + "avgServiceLevel":100, + "avgLatency":461, + "avgSuccessRate":100, + "popularityScore":9.4, + "__typename":"Score" + }, + "home_url":"https://rapidapi.com/logicione/api/stock-ticker-security-and-company-search-database/", + "host":"stock-ticker-security-and-company-search-database.p.rapidapi.com", + "api_list":[ + { + "name":"/security_price_volume", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/security_price_volume", + "description":"Returns end of day Price and Volume for a security", + "method":"GET", + "required_parameters":[ + { + "name":"date", + "type":"STRING", + "description":"It needs a date from which the historical price and volume will be provided.\nIf on that date there is an exchange holiday or data is not available, then it will return previous days data", + "default":"20230718" + }, + { + "name":"ticker", + "type":"STRING", + "description":"The ticker should having following pattern:\n:", + "default":"NASDAQ:AAPL" + } + ], + "optional_parameters":[ + { + "name":"past_days", + "type":"STRING", + "description":"", + "default":"2" + } + ], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/security_price_volume\"\nquerystring = {\"date\": date, \"past_days\": past_days, \"ticker\": ticker}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":[ + { + "Exchange":"NASDAQ", + "Ticker":"AAPL", + "Closing_Date":20230718, + "Open_Price":193.35, + "High_Price":194.33, + "Low_Price":192.415, + "Close_Price":193.73, + "Volume":48353700 + }, + { + "Exchange":"NASDAQ", + "Ticker":"AAPL", + "Closing_Date":20230717, + "Open_Price":191.9, + "High_Price":194.32, + "Low_Price":191.81, + "Close_Price":193.99, + "Volume":50520100 + } + ], + "headers":{ + "access-control-allow-credentials":"true", + "access-control-allow-origin":"*", + "content-length":"502", + "content-security-policy":"upgrade-insecure-requests", + "content-type":"application/json", + "date":"Wed, 19 Jul 2023 08:36:58 GMT", + "server":"RapidAPI-1.2.8", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.2.8" + }, + "schema":{} + }, + { + "name":"/sp500_active_list", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_active_list", + "description":"List all the SP500 active companies", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_active_list\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":200, + "body":[ + { + "ticker":"ATVI", + "company_name":"Activision Blizzard", + "sector":"Communication Services" + }, + { + "ticker":"ADBE", + "company_name":"Adobe Inc.", + "sector":"Information Technology" + }, + { + "ticker":"AAP", + "company_name":"Advance Auto Parts", + "sector":"Consumer Discretionary" + }, + { + "ticker":"ARE", + "company_name":"Alexandria Real Estate Equities", + "sector":"Real Estate" + }, + { + "ticker":"ALGN", + "company_name":"Align Technology", + "sector":"Health Care" + }, + { + "ticker":"ALLE", + "company_name":"Allegion", + "sector":"Industrials" + }, + { + "ticker":"GOOGL", + "company_name":"Alphabet Inc. (Class A)", + "sector":"Communication Services" + }, + { + "ticker":"GOOG", + "company_name":"Alphabet Inc. (Class C)", + "sector":"Communication Services" + }, + { + "ticker":"AAL", + "company_name":"American Airlines Group", + "sector":"Industrials" + }, + { + "ticker":"AEP", + "company_name":"American Electric Power", + "sector":"Utilities" + }, + { + "ticker":"AIG", + "company_name":"American International Group", + "sector":"Financials" + }, + { + "ticker":"AMP", + "company_name":"Ameriprise Financial", + "sector":"Financials" + }, + { + "ticker":"ANSS", + "company_name":"ANSYS", + "sector":"Information Technology" + }, + { + "ticker":"AAPL", + "company_name":"Apple Inc.", + "sector":"Information Technology" + }, + { + "ticker":"ANET", + "company_name":"Arista Networks", + "sector":"Information Technology" + }, + { + "ticker":"AJG", + "company_name":"Arthur J. Gallagher & Co.", + "sector":"Financials" + }, + { + "ticker":"AIZ", + "company_name":"Assurant", + "sector":"Financials" + }, + { + "ticker":"ATO", + "company_name":"Atmos Energy", + "sector":"Utilities" + }, + { + "ticker":"AVB", + "company_name":"AvalonBay Communities", + "sector":"Real Estate" + }, + { + "ticker":"BDX", + "company_name":"Becton Dickinson", + "sector":"Health Care" + }, + { + "ticker":"BRK.B", + "company_name":"Berkshire Hathaway", + "sector":"Financials" + }, + { + "ticker":"BLK", + "company_name":"BlackRock", + "sector":"Financials" + }, + { + "ticker":"BWA", + "company_name":"BorgWarner", + "sector":"Consumer Discretionary" + }, + { + "ticker":"BXP", + "company_name":"Boston Properties", + "sector":"Real Estate" + }, + { + "ticker":"BSX", + "company_name":"Boston Scientific", + "sector":"Health Care" + }, + { + "ticker":"AVGO", + "company_name":"Broadcom Inc.", + "sector":"Information Technology" + }, + { + "ticker":"BR", + "company_name":"Broadridge Financial Solutions", + "sector":"Industrials" + }, + { + "ticker":"CDNS", + "company_name":"Cadence Design Systems", + "sector":"Information Technology" + }, + { + "ticker":"CARR", + "company_name":"Carrier Global", + "sector":"Industrials" + }, + { + "ticker":"CAT", + "company_name":"Caterpillar Inc.", + "sector":"Industrials" + }, + { + "ticker":"CBOE", + "company_name":"Cboe Global Markets", + "sector":"Financials" + }, + { + "ticker":"CBRE", + "company_name":"CBRE Group", + "sector":"Real Estate" + }, + { + "ticker":"CDW", + "company_name":"CDW", + "sector":"Information Technology" + }, + { + "ticker":"CE", + "company_name":"Celanese", + "sector":"Materials" + }, + { + "ticker":"CNC", + "company_name":"Centene Corporation", + "sector":"Health Care" + }, + { + "ticker":"CNP", + "company_name":"CenterPoint Energy", + "sector":"Utilities" + }, + { + "ticker":"SCHW", + "company_name":"Charles Schwab Corporation", + "sector":"Financials" + }, + { + "ticker":"CHTR", + "company_name":"Charter Communications", + "sector":"Communication Services" + }, + { + "ticker":"CMG", + "company_name":"Chipotle Mexican Grill", + "sector":"Consumer Discretionary" + }, + { + "ticker":"CB", + "company_name":"Chubb Limited", + "sector":"Financials" + }, + { + "ticker":"CHD", + "company_name":"Church & Dwight", + "sector":"Consumer Staples" + }, + { + "ticker":"CINF", + "company_name":"Cincinnati Financial", + "sector":"Financials" + }, + { + "ticker":"CFG", + "company_name":"Citizens Financial Group", + "sector":"Financials" + }, + { + "ticker":"CMS", + "company_name":"CMS Energy", + "sector":"Utilities" + }, + { + "ticker":"CL", + "company_name":"Colgate-Palmolive", + "sector":"Consumer Staples" + }, + { + "ticker":"CAG", + "company_name":"Conagra Brands", + "sector":"Consumer Staples" + }, + { + "ticker":"COP", + "company_name":"ConocoPhillips", + "sector":"Energy" + }, + { + "ticker":"ED", + "company_name":"Consolidated Edison", + "sector":"Utilities" + }, + { + "ticker":"STZ", + "company_name":"Constellation Brands", + "sector":"Consumer Staples" + }, + { + "ticker":"GLW", + "company_name":"Corning Inc.", + "sector":"Information Technology" + }, + { + "ticker":"CTVA", + "company_name":"Corteva", + "sector":"Materials" + }, + { + "ticker":"CVS", + "company_name":"CVS Health", + "sector":"Health Care" + }, + { + "ticker":"DRI", + "company_name":"Darden Restaurants", + "sector":"Consumer Discretionary" + }, + { + "ticker":"DVA", + "company_name":"DaVita Inc.", + "sector":"Health Care" + }, + { + "ticker":"XRAY", + "company_name":"Dentsply Sirona", + "sector":"Health Care" + }, + { + "ticker":"DVN", + "company_name":"Devon Energy", + "sector":"Energy" + }, + { + "ticker":"DXCM", + "company_name":"DexCom", + "sector":"Health Care" + }, + { + "ticker":"FANG", + "company_name":"Diamondback Energy", + "sector":"Energy" + }, + { + "ticker":"DISH", + "company_name":"Dish Network", + "sector":"Communication Services" + }, + { + "ticker":"DG", + "company_name":"Dollar General", + "sector":"Consumer Staples" + }, + { + "ticker":"DLTR", + "company_name":"Dollar Tree", + "sector":"Consumer Staples" + }, + { + "ticker":"D", + "company_name":"Dominion Energy", + "sector":"Utilities" + }, + { + "ticker":"DOV", + "company_name":"Dover Corporation", + "sector":"Industrials" + }, + { + "ticker":"DOW", + "company_name":"Dow Inc.", + "sector":"Materials" + }, + { + "ticker":"DUK", + "company_name":"Duke Energy", + "sector":"Utilities" + }, + { + "ticker":"DXC", + "company_name":"DXC Technology", + "sector":"Information Technology" + }, + { + "ticker":"ETN", + "company_name":"Eaton Corporation", + "sector":"Industrials" + }, + { + "ticker":"EW", + "company_name":"Edwards Lifesciences", + "sector":"Health Care" + }, + { + "ticker":"EA", + "company_name":"Electronic Arts", + "sector":"Communication Services" + }, + { + "ticker":"EOG", + "company_name":"EOG Resources", + "sector":"Energy" + }, + { + "ticker":"EQIX", + "company_name":"Equinix", + "sector":"Real 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"company_name":"Marathon Oil", + "sector":"Energy" + }, + { + "ticker":"MAS", + "company_name":"Masco", + "sector":"Industrials" + }, + { + "ticker":"MA", + "company_name":"Mastercard", + "sector":"Financials" + }, + { + "ticker":"MKC", + "company_name":"McCormick & Company", + "sector":"Consumer Staples" + }, + { + "ticker":"MCD", + "company_name":"McDonald's", + "sector":"Consumer Discretionary" + }, + { + "ticker":"MDT", + "company_name":"Medtronic", + "sector":"Health Care" + }, + { + "ticker":"MET", + "company_name":"MetLife", + "sector":"Financials" + }, + { + "ticker":"MSFT", + "company_name":"Microsoft", + "sector":"Information Technology" + }, + { + "ticker":"MCO", + "company_name":"Moody's Corporation", + "sector":"Financials" + }, + { + "ticker":"MSI", + "company_name":"Motorola Solutions", + "sector":"Information Technology" + }, + { + "ticker":"MSCI", + "company_name":"MSCI", + "sector":"Financials" + }, + { + "ticker":"NFLX", + "company_name":"Netflix", + "sector":"Communication Services" + }, + { + "ticker":"NEM", + "company_name":"Newmont", + "sector":"Materials" + }, + { + "ticker":"NI", + "company_name":"NiSource", + "sector":"Utilities" + }, + { + "ticker":"NTRS", + "company_name":"Northern Trust", + "sector":"Financials" + }, + { + "ticker":"NUE", + "company_name":"Nucor", + "sector":"Materials" + }, + { + "ticker":"NVDA", + "company_name":"Nvidia", + "sector":"Information Technology" + }, + { + "ticker":"PAYX", + "company_name":"Paychex", + "sector":"Industrials" + }, + { + "ticker":"PNR", + "company_name":"Pentair", + "sector":"Industrials" + }, + { + "ticker":"PEP", + "company_name":"PepsiCo", + "sector":"Consumer Staples" + }, + { + "ticker":"PFE", + "company_name":"Pfizer", + "sector":"Health Care" + }, + { + "ticker":"PGR", + "company_name":"Progressive Corporation", + "sector":"Financials" + }, + { + "ticker":"PTC", + "company_name":"PTC", + "sector":"Information Technology" + }, + { + "ticker":"PEG", + "company_name":"Public Service Enterprise Group", + "sector":"Utilities" + }, + { + "ticker":"PWR", + "company_name":"Quanta Services", + "sector":"Industrials" + }, + { + "ticker":"REG", + "company_name":"Regency Centers", + "sector":"Real Estate" + }, + { + "ticker":"RF", + "company_name":"Regions Financial Corporation", + "sector":"Financials" + }, + { + "ticker":"RSG", + "company_name":"Republic Services", + "sector":"Industrials" + }, + { + "ticker":"ROK", + "company_name":"Rockwell Automation", + "sector":"Industrials" + }, + { + "ticker":"SPGI", + "company_name":"S&P Global", + "sector":"Financials" + }, + { + "ticker":"CRM", + "company_name":"Salesforce", + "sector":"Information Technology" + }, + { + "ticker":"SLB", + "company_name":"Schlumberger", + "sector":"Energy" + }, + { + "ticker":"SPG", + "company_name":"Simon Property Group", + "sector":"Real Estate" + }, + { + "ticker":"SBUX", + "company_name":"Starbucks", + "sector":"Consumer Discretionary" + }, + { + "ticker":"STT", + "company_name":"State Street Corporation", + "sector":"Financials" + }, + { + "ticker":"SYK", + "company_name":"Stryker Corporation", + "sector":"Health Care" + }, + { + "ticker":"SNPS", + "company_name":"Synopsys", + "sector":"Information Technology" + }, + { + "ticker":"SYY", + "company_name":"Sysco", + "sector":"Consumer Staples" + }, + { + "ticker":"TROW", + "company_name":"T. Rowe Price", + "sector":"Financials" + }, + { + "ticker":"TGT", + "company_name":"Target Corporation", + "sector":"Consumer Staples" + }, + { + "ticker":"TEL", + "company_name":"TE Connectivity", + "sector":"Information Technology" + }, + { + "ticker":"TXT", + "company_name":"Textron", + "sector":"Industrials" + }, + { + "ticker":"TJX", + "company_name":"TJX Companies", + "sector":"Consumer Discretionary" + }, + { + "ticker":"TT", + "company_name":"Trane Technologies", + "sector":"Industrials" + }, + { + "ticker":"UNH", + "company_name":"UnitedHealth Group", + "sector":"Health Care" + }, + { + "ticker":"URI", + "company_name":"United Rentals", + "sector":"Industrials" + }, + { + "ticker":"VTR", + "company_name":"Ventas", + "sector":"Real Estate" + }, + { + "ticker":"VRSN", + "company_name":"Verisign", + "sector":"Information Technology" + }, + { + "ticker":"VRTX", + "company_name":"Vertex Pharmaceuticals", + "sector":"Health Care" + }, + { + "ticker":"WAB", + "company_name":"Wabtec", + "sector":"Industrials" + }, + { + "ticker":"WM", + "company_name":"Waste Management", + "sector":"Industrials" + }, + { + "ticker":"WELL", + "company_name":"Welltower", + "sector":"Real Estate" + }, + { + "ticker":"WHR", + "company_name":"Whirlpool Corporation", + "sector":"Consumer Discretionary" + }, + { + "ticker":"WYNN", + "company_name":"Wynn Resorts", + "sector":"Consumer Discretionary" + }, + { + "ticker":"XEL", + "company_name":"Xcel Energy", + "sector":"Utilities" + }, + { + "ticker":"YUM", + "company_name":"Yum! Brands", + "sector":"Consumer Discretionary" + }, + { + "ticker":"AMCR", + "company_name":"Amcor", + "sector":"Materials" + }, + { + "ticker":"AOS", + "company_name":"A. O. Smith", + "sector":"Industrials" + }, + { + "ticker":"BF.B", + "company_name":"Brown–Forman", + "sector":"Consumer Staples" + }, + { + "ticker":"GWW", + "company_name":"W. W. Grainger", + "sector":"Industrials" + }, + { + "ticker":"MRNA", + "company_name":"Moderna", + "sector":"Health Care" + }, + { + "ticker":"BBWI", + "company_name":"Bath & Body Works, Inc.", + "sector":"Consumer Discretionary" + }, + { + "ticker":"TECH", + "company_name":"Bio-Techne", + "sector":"Health Care" + }, + { + "ticker":"BA", + "company_name":"Boeing", + "sector":"Industrials" + }, + { + "ticker":"BMY", + "company_name":"Bristol Myers Squibb", + "sector":"Health Care" + }, + { + "ticker":"BRO", + "company_name":"Brown & Brown", + "sector":"Financials" + }, + { + "ticker":"CDAY", + "company_name":"Ceridian", + "sector":"Information Technology" + }, + { + "ticker":"MTCH", + "company_name":"Match Group", + "sector":"Communication Services" + }, + { + "ticker":"CTRA", + "company_name":"Coterra", + "sector":"Energy" + }, + { + "ticker":"APH", + "company_name":"Amphenol", + "sector":"Information Technology" + }, + { + "ticker":"COF", + "company_name":"Capital One", + "sector":"Financials" + }, + { + "ticker":"EMR", + "company_name":"Emerson Electric", + "sector":"Industrials" + }, + { + "ticker":"EPAM", + "company_name":"EPAM Systems", + "sector":"Information Technology" + }, + { + "ticker":"FDS", + "company_name":"FactSet", + "sector":"Financials" + }, + { + "ticker":"SEDG", + "company_name":"SolarEdge", + "sector":"Information Technology" + }, + { + "ticker":"ABT", + "company_name":"Abbott", + "sector":"Health Care" + }, + { + "ticker":"AKAM", + "company_name":"Akamai", + "sector":"Information Technology" + }, + { + "ticker":"ALL", + "company_name":"Allstate", + "sector":"Financials" + }, + { + "ticker":"MO", + "company_name":"Altria", + "sector":"Consumer Staples" + }, + { + "ticker":"AMD", + "company_name":"AMD", + "sector":"Information Technology" + }, + { + "ticker":"AEE", + "company_name":"Ameren", + "sector":"Utilities" + }, + { + "ticker":"BIO", + "company_name":"Bio-Rad", + "sector":"Health Care" + }, + { + "ticker":"CTAS", + "company_name":"Cintas", + "sector":"Industrials" + }, + { + "ticker":"CSCO", + "company_name":"Cisco", + "sector":"Information Technology" + }, + { + "ticker":"WTW", + "company_name":"Willis Towers Watson", + "sector":"Financials" + }, + { + "ticker":"DLR", + "company_name":"Digital Realty", + "sector":"Real Estate" + }, + { + "ticker":"COO", + "company_name":"CooperCompanies", + "sector":"Health Care" + }, + { + "ticker":"ADP", + "company_name":"ADP", + "sector":"Industrials" + }, + { + "ticker":"CTSH", + "company_name":"Cognizant", + "sector":"Information Technology" + }, + { + "ticker":"DPZ", + "company_name":"Domino's", + "sector":"Consumer Discretionary" + }, + { + "ticker":"ENPH", + "company_name":"Enphase", + "sector":"Information Technology" + }, + { + "ticker":"ES", + "company_name":"Eversource", + "sector":"Utilities" + }, + { + "ticker":"FRT", + "company_name":"Federal Realty", + "sector":"Real Estate" + }, + { + "ticker":"FIS", + "company_name":"FIS", + "sector":"Financials" + }, + { + "ticker":"GNRC", + "company_name":"Generac", + "sector":"Industrials" + }, + { + "ticker":"CEG", + "company_name":"Constellation Energy", + "sector":"Utilities" + }, + { + "ticker":"MGM", + "company_name":"MGM Resorts", + "sector":"Consumer Discretionary" + }, + { + "ticker":"PARA", + "company_name":"Paramount Global", + "sector":"Communication Services" + }, + { + "ticker":"CHRW", + "company_name":"C.H. Robinson", + "sector":"Industrials" + }, + { + "ticker":"CCL", + "company_name":"Carnival", + "sector":"Consumer Discretionary" + }, + { + "ticker":"DIS", + "company_name":"Disney", + "sector":"Communication Services" + }, + { + "ticker":"HSY", + "company_name":"Hershey's", + "sector":"Consumer Staples" + }, + { + "ticker":"WRB", + "company_name":"Berkley", + "sector":"Financials" + }, + { + "ticker":"DHI", + "company_name":"D.R. Horton", + "sector":"Consumer Discretionary" + }, + { + "ticker":"FITB", + "company_name":"Fifth Third Bank", + "sector":"Financials" + }, + { + "ticker":"HIG", + "company_name":"Hartford (The)", + "sector":"Financials" + }, + { + "ticker":"JBHT", + "company_name":"J.B. Hunt", + "sector":"Industrials" + }, + { + "ticker":"BEN", + "company_name":"Franklin Templeton", + "sector":"Financials" + }, + { + "ticker":"PEAK", + "company_name":"Healthpeak", + "sector":"Real Estate" + }, + { + "ticker":"KEYS", + "company_name":"Keysight", + "sector":"Information Technology" + }, + { + "ticker":"LHX", + "company_name":"L3Harris", + "sector":"Industrials" + }, + { + "ticker":"LNC", + "company_name":"Lincoln Financial", + "sector":"Financials" + }, + { + "ticker":"MCK", + "company_name":"McKesson", + "sector":"Health Care" + }, + { + "ticker":"ODFL", + "company_name":"Old Dominion", + "sector":"Industrials" + }, + { + "ticker":"PNW", + "company_name":"Pinnacle West", + "sector":"Utilities" + }, + { + "ticker":"RJF", + "company_name":"Raymond James", + "sector":"Financials" + }, + { + "ticker":"O", + "company_name":"Realty Income", + "sector":"Real Estate" + }, + { + "ticker":"REGN", + "company_name":"Regeneron", + "sector":"Health Care" + }, + { + "ticker":"RHI", + "company_name":"Robert Half", + "sector":"Industrials" + }, + { + "ticker":"TSCO", + "company_name":"Tractor Supply", + "sector":"Consumer Discretionary" + }, + { + "ticker":"TFC", + "company_name":"Truist", + "sector":"Financials" + }, + { + "ticker":"USB", + "company_name":"U.S. Bank", + "sector":"Financials" + }, + { + "ticker":"VRSK", + "company_name":"Verisk", + "sector":"Industrials" + }, + { + "ticker":"VZ", + "company_name":"Verizon", + "sector":"Communication Services" + }, + { + "ticker":"MOH", + "company_name":"Molina Healthcare", + "sector":"Health Care" + }, + { + "ticker":"APD", + "company_name":"Air Products and Chemicals", + "sector":"Materials" + }, + { + "ticker":"WBD", + "company_name":"Warner Bros. Discovery", + "sector":"Communication Services" + }, + { + "ticker":"AES", + "company_name":"AES Corporation", + "sector":"Utilities" + }, + { + "ticker":"BALL", + "company_name":"Ball Corporation", + "sector":"Materials" + }, + { + "ticker":"CPT", + "company_name":"Camden Property Trust", + "sector":"Real Estate" + }, + { + "ticker":"DE", + "company_name":"John Deere", + "sector":"Industrials" + }, + { + "ticker":"DFS", + "company_name":"Discover Financial", + "sector":"Financials" + }, + { + "ticker":"EMN", + "company_name":"Eastman Chemical Company", + "sector":"Materials" + }, + { + "ticker":"LLY", + "company_name":"Eli Lilly and Company", + "sector":"Health Care" + }, + { + "ticker":"EXPD", + "company_name":"Expeditors International", + "sector":"Industrials" + }, + { + "ticker":"FFIV", + "company_name":"F5, Inc.", + "sector":"Information Technology" + }, + { + "ticker":"GPC", + "company_name":"Genuine Parts Company", + "sector":"Consumer Discretionary" + }, + { + "ticker":"MMC", + "company_name":"Marsh McLennan", + "sector":"Financials" + }, + { + "ticker":"META", + "company_name":"Meta Platforms", + "sector":"Communication Services" + }, + { + "ticker":"MAA", + "company_name":"Mid-America Apartment Communities", + "sector":"Real Estate" + }, + { + "ticker":"NSC", + "company_name":"Norfolk Southern Railway", + "sector":"Industrials" + }, + { + "ticker":"ORLY", + "company_name":"O'Reilly Auto Parts", + "sector":"Consumer Discretionary" + }, + { + "ticker":"ORCL", + "company_name":"Oracle Corporation", + "sector":"Information Technology" + }, + { + "ticker":"PH", + "company_name":"Parker Hannifin", + "sector":"Industrials" + }, + { + "ticker":"PPL", + "company_name":"PPL Corporation", + "sector":"Utilities" + }, + { + "ticker":"UNP", + "company_name":"Union Pacific Corporation", + "sector":"Industrials" + }, + { + "ticker":"VICI", + "company_name":"Vici Properties", + "sector":"Real Estate" + }, + { + "ticker":"VMC", + "company_name":"Vulcan Materials Company", + "sector":"Materials" + }, + { + "ticker":"ZION", + "company_name":"Zions Bancorporation", + "sector":"Financials" + }, + { + "ticker":"CPB", + "company_name":"Campbell Soup Company", + "sector":"Consumer Staples" + }, + { + "ticker":"KDP", + "company_name":"Keurig Dr Pepper", + "sector":"Consumer Staples" + }, + { + "ticker":"ON", + "company_name":"ON Semiconductor", + "sector":"Information Technology" + }, + { + "ticker":"HRL", + "company_name":"Hormel Foods", + "sector":"Consumer Staples" + }, + { + "ticker":"NDSN", + "company_name":"Nordson Corporation", + "sector":"Industrials" + }, + { + "ticker":"ELV", + "company_name":"Elevance Health", + "sector":"Health Care" + }, + { + "ticker":"J", + "company_name":"Jacobs Solutions", + "sector":"Industrials" + }, + { + "ticker":"CSGP", + "company_name":"CoStar Group", + "sector":"Industrials" + }, + { + "ticker":"INVH", + "company_name":"Invitation Homes", + "sector":"Real Estate" + }, + { + "ticker":"EQT", + "company_name":"EQT", + "sector":"Energy" + }, + { + "ticker":"TRGP", + "company_name":"Targa Resources", + "sector":"Energy" + }, + { + "ticker":"ACGL", + "company_name":"Arch Capital Group", + "sector":"Financials" + }, + { + "ticker":"GEN", + "company_name":"Gen Digital", + "sector":"Information Technology" + }, + { + "ticker":"PCG", + "company_name":"PG&E Corporation", + "sector":"Utilities" + }, + { + "ticker":"FSLR", + "company_name":"First Solar", + "sector":"Information Technology" + }, + { + "ticker":"STLD", + "company_name":"Steel Dynamics", + "sector":"Materials" + }, + { + "ticker":"GEHC", + "company_name":"GE HealthCare", + "sector":"Health Care" + }, + { + "ticker":"HD", + "company_name":"Home Depot (The)", + "sector":"Consumer Discretionary" + }, + { + "ticker":"KO", + "company_name":"Coca-Cola Company (The)", + "sector":"Consumer Staples" + }, + { + "ticker":"EL", + "company_name":"Estée Lauder Companies (The)", + "sector":"Consumer Staples" + }, + { + "ticker":"IPG", + "company_name":"Interpublic Group of Companies (The)", + "sector":"Communication Services" + }, + { + "ticker":"MOS", + "company_name":"Mosaic Company (The)", + "sector":"Materials" + }, + { + "ticker":"SJM", + "company_name":"J.M. Smucker Company (The)", + "sector":"Consumer Staples" + }, + { + "ticker":"TRV", + "company_name":"Travelers Companies (The)", + "sector":"Financials" + }, + { + "ticker":"BG", + "company_name":"Bunge Limited", + "sector":"Consumer Staples" + }, + { + "ticker":"PODD", + "company_name":"Insulet", + "sector":"Health Care" + }, + { + "ticker":"FICO", + "company_name":"Fair Isaac", + "sector":"Information Technology" + }, + { + "ticker":"AXON", + "company_name":"Axon Enterprise", + "sector":"Industrials" + } + ], + "headers":{ + "access-control-allow-credentials":"true", + "access-control-allow-origin":"*", + "content-length":"40615", + "content-security-policy":"upgrade-insecure-requests", + "content-type":"application/json", + "date":"Mon, 15 May 2023 12:21:48 GMT", + "server":"RapidAPI-1.2.8", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.2.8" + }, + "schema":{} + }, + { + "name":"/all_search get result by ticker or security_term", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search", + "description":"In a single call search by ticker OR security_term", + "method":"GET", + "required_parameters":[], + "optional_parameters":[ + { + "name":"security", + "type":"STRING", + "description":"", + "default":"Apple Inc" + }, + { + "name":"ticker", + "type":"STRING", + "description":"", + "default":"AAPL_sdfs" + } + ], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search\"\nquerystring = {\"security\": security, \"ticker\": ticker}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":[ + { + "exchange":"NASDAQ", + "ticker":"AAPL", + "security_name":"Apple Inc. - Common Stock", + "is_etf":"N", + "last_updated":"2021-04-05", + "search_type":"FUZZY_MATCH", + "similarity_score":0.5 + }, + { + "exchange":"LSE", + "ticker":"0JQ4", + "security_name":"APPLE INC COM STK NPV", + "last_updated":"2021-04-07", + "search_type":"FUZZY_MATCH", + "similarity_score":0.4 + } + ], + "headers":{ + "access-control-allow-credentials":"true", + "access-control-allow-origin":"*", + "content-length":"354", + "content-security-policy":"upgrade-insecure-requests", + "content-type":"application/json", + "date":"Mon, 15 May 2023 11:42:35 GMT", + "server":"RapidAPI-1.2.8", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.2.8" + }, + "schema":{} + }, + { + "name":"/company_sentiment", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/company_sentiment", + "description":"Extract securities and sentiment towards those securities from a free form text using an advanced AI", + "method":"GET", + "required_parameters":[ + { + "name":"text", + "type":"STRING", + "description":"", + "default":"Tesla gave investors a few reasons to be bullish last week. News broke on Thursday that CEO Elon Musk had hired someone to take over his position as CEO at privately held social network Twitter. The move will likely free up more of Musk's time, which was already split between Tesla, SpaceX, Twitter, and some smaller ventures like The Boring Company." + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/company_sentiment\"\nquerystring = {\"text\": text}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "Tesla":"positive", + "SpaceX":"positive", + "Twitter":"neutral", + "The Boring Company":"neutral" + }, + "headers":{ + "access-control-allow-credentials":"true", + "access-control-allow-origin":"*", + "content-length":"98", + "content-security-policy":"upgrade-insecure-requests", + "content-type":"application/json", + "date":"Mon, 15 May 2023 11:37:48 GMT", + "server":"RapidAPI-1.2.8", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.2.8" + }, + "schema":{} + }, + { + "name":"/sp500_search by Ticker", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search", + "description":"Check if security is currently listed in the S&P 500 by Ticker (or Symbol)", + "method":"GET", + "required_parameters":[ + { + "name":"ticker", + "type":"STRING", + "description":"", + "default":"AAPL" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search\"\nquerystring = {\"ticker\": ticker}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":[ + { + "cik":"0000320193", + "company_name":"Apple Inc.", + "date_first_added":"1982-11-30", + "founded_year":"1977", + "gics_sector":"Information Technology", + "gics_sub_industry":"Technology Hardware, Storage & Peripherals", + "hq_location":"Cupertino, California", + "ticker":"AAPL" + } + ], + "headers":{ + "content-type":"application/json", + "date":"Mon, 16 Nov 2020 00:39:07 GMT", + "server":"RapidAPI-1.2.6", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.2.6", + "content-length":"277", + "connection":"Close" + }, + "schema":{ + "items":{ + "properties":{ + "exchange":{ + "type":"string" + }, + "financial_status":{ + "type":"string" + }, + "is_etf":{ + "type":"string" + }, + "last_updated":{ + "type":"string" + }, + "removed_date":{ + "type":"null" + }, + "security_name":{ + "type":"string" + }, + "ticker":{ + "type":"string" + } + }, + "type":"object" + }, + "type":"array" + } + }, + { + "name":"/all_search by Ticker", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search", + "description":"Search security by ticker\n\nYou can also input different exchanges, for example:\n\n```\nticker=NASDAQ:AAPL\nticker=NYSE:BA\n```", + "method":"GET", + "required_parameters":[ + { + "name":"ticker", + "type":"STRING", + "description":"", + "default":"AAPL" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search\"\nquerystring = {\"ticker\": ticker}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":[ + { + "exchange":"NASDAQ", + "financial_status":"Normal", + "is_etf":"N", + "last_updated":"May 04 2020", + "removed_date":null, + "security_name":"Apple Inc. - Common Stock", + "ticker":"AAPL" + } + ], + "headers":{ + "content-type":"application/json", + "date":"Thu, 06 Aug 2020 08:44:41 GMT", + "server":"RapidAPI-1.1.24", + "via":"1.1 vegur", + "x-rapidapi-region":"AWS - us-west-2", + "x-rapidapi-version":"1.1.24", + "content-length":"186", + "connection":"Close" + }, + "schema":{ + "items":{ + "properties":{ + "exchange":{ + "type":"string" + }, + "financial_status":{ + "type":"string" + }, + "is_etf":{ + "type":"string" + }, + "last_updated":{ + "type":"string" + }, + "removed_date":{ + "type":"null" + }, + "security_name":{ + "type":"string" + }, + "ticker":{ + "type":"string" + } + }, + "type":"object" + }, + "type":"array" + } + }, + { + "name":"/sp500_search by Security Term", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search", + "description":"Search security by providing the first few words for the security or the company name", + "method":"GET", + "required_parameters":[ + { + "name":"security", + "type":"STRING", + "description":"", + "default":"apple" + } + ], + "optional_parameters":[ + { + "name":"exchange", + "type":"STRING", + "description":"", + "default":"NASDAQ" + } + ], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search\"\nquerystring = {\"exchange\": exchange, \"security\": security}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"/all_search by Exchange and Ticker", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search", + "description":"Search security by ticker\n\nYou can also input different exchanges, for example:\n\n```\nticker=NASDAQ:AAPL\nticker=NYSE:BA\n```", + "method":"GET", + "required_parameters":[ + { + "name":"ticker", + "type":"STRING", + "description":"", + "default":"SGX:1D5" + } + ], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search\"\nquerystring = {\"ticker\": ticker}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"/all_search by Security Term", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search", + "description":"Search security by providing the first few words for the security or the company name", + "method":"GET", + "required_parameters":[ + { + "name":"security", + "type":"STRING", + "description":"", + "default":"apple" + } + ], + "optional_parameters":[ + { + "name":"exchange", + "type":"STRING", + "description":"", + "default":"NASDAQ" + } + ], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search\"\nquerystring = {\"security\": security, \"exchange\": exchange}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + }, + { + "name":"/all_search get single security by term search", + "url":"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search", + "description":"Search security by providing the first few words for the security or the company name\n\nUse optional query param \n`result_type=short`, which will return the top-most similar only one security, which matches your search term.\nOtherwise, it will return all the security, which starts with the term you provided.", + "method":"GET", + "required_parameters":[ + { + "name":"security", + "type":"STRING", + "description":"", + "default":"apple" + } + ], + "optional_parameters":[ + { + "name":"result_type", + "type":"STRING", + "description":"", + "default":"short" + }, + { + "name":"exchange", + "type":"STRING", + "description":"", + "default":"NASDAQ" + } + ], + "code":"import requests\n\nurl = \"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search\"\nquerystring = {\"result_type\": result_type, \"security\": security, \"exchange\": exchange}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"stock-ticker-security-and-company-search-database.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database/api.py new file mode 100644 index 0000000000000000000000000000000000000000..511b6c6cbea070b611aa2bfe22e3d0ec8d419756 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/stock_ticker_security_and_company_search_database/api.py @@ -0,0 +1,254 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def security_price_volume(date: str, ticker: str, past_days: str='2', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Returns end of day Price and Volume for a security" + date: It needs a date from which the historical price and volume will be provided. +If on that date there is an exchange holiday or data is not available, then it will return previous days data + ticker: The ticker should having following pattern: +: + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/security_price_volume" + querystring = {'date': date, 'ticker': ticker, } + if past_days: + querystring['past_days'] = past_days + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def sp500_active_list(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "List all the SP500 active companies" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_active_list" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def all_search_get_result_by_ticker_or_security_term(security: str='Apple Inc', ticker: str='AAPL_sdfs', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "In a single call search by ticker OR security_term" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search" + querystring = {} + if security: + querystring['security'] = security + if ticker: + querystring['ticker'] = ticker + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def company_sentiment(text: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Extract securities and sentiment towards those securities from a free form text using an advanced AI" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/company_sentiment" + querystring = {'text': text, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def sp500_search_by_ticker(ticker: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Check if security is currently listed in the S&P 500 by Ticker (or Symbol)" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search" + querystring = {'ticker': ticker, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def all_search_by_ticker(ticker: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search security by ticker + + You can also input different exchanges, for example: + + ``` + ticker=NASDAQ:AAPL + ticker=NYSE:BA + ```" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search" + querystring = {'ticker': ticker, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def sp500_search_by_security_term(security: str, exchange: str='NASDAQ', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search security by providing the first few words for the security or the company name" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/sp500_search" + querystring = {'security': security, } + if exchange: + querystring['exchange'] = exchange + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def all_search_by_exchange_and_ticker(ticker: str, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search security by ticker + + You can also input different exchanges, for example: + + ``` + ticker=NASDAQ:AAPL + ticker=NYSE:BA + ```" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search" + querystring = {'ticker': ticker, } + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def all_search_by_security_term(security: str, exchange: str='NASDAQ', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search security by providing the first few words for the security or the company name" + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search" + querystring = {'security': security, } + if exchange: + querystring['exchange'] = exchange + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + +def all_search_get_single_security_by_term_search(security: str, result_type: str='short', exchange: str='NASDAQ', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Search security by providing the first few words for the security or the company name + + Use optional query param + `result_type=short`, which will return the top-most similar only one security, which matches your search term. + Otherwise, it will return all the security, which starts with the term you provided." + + """ + url = f"https://stock-ticker-security-and-company-search-database.p.rapidapi.com/all_search" + querystring = {'security': security, } + if result_type: + querystring['result_type'] = result_type + if exchange: + querystring['exchange'] = exchange + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "stock-ticker-security-and-company-search-database.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summandsend.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summandsend.json new file mode 100644 index 0000000000000000000000000000000000000000..ab28543405ee676e4ec728f4e9d07f58fefa6d8a --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summandsend.json @@ -0,0 +1,32 @@ +{ + "product_id": "api_a8b5b140-bc85-450a-9cec-8b3811d6b9cc", + "tool_description": "Summarize any YouTube video in any language and get only the essential content delivered to your inbox.", + "home_url": "https://rapidapi.com/odlica-odlica-default/api/summandsend1/", + "name": "Summandsend", + "title": "Summandsend", + "pricing": "FREEMIUM", + "tool_name": "Summandsend", + "score": { + "avgServiceLevel": 100, + "avgLatency": 189, + "avgSuccessRate": 67, + "popularityScore": 8.7, + "__typename": "Score" + }, + "host": "summandsend1.p.rapidapi.com", + "api_list": [ + { + "name": "video", + "url": "https://summandsend1.p.rapidapi.com/video", + "description": "This endpoint is specifically designed for video summarization and utilizes callbacks due to the time-consuming nature of video processing. To facilitate testing, you can easily set up a callback server using Google Colab. For detailed instructions, please refer to the provided tutorial for more information.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://summandsend1.p.rapidapi.com/video\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"summandsend1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://summandsend1.p.rapidapi.com/video\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"summandsend1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 1, + "schema": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it.json new file mode 100644 index 0000000000000000000000000000000000000000..7fb9a10791c49969d7d989530c9a3a0ecc941f77 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it.json @@ -0,0 +1,47 @@ +{ + "tool_name":"Summate.it", + "tool_description":"Quickly summarize web articles with OpenAI", + "title":"Summate.it", + "pricing":"FREEMIUM", + "score":null, + "home_url":"https://rapidapi.com/fivefilters/api/summate-it/", + "host":"summate-it.p.rapidapi.com", + "api_list":[ + { + "name":"Summarize", + "url":"https://summate-it.p.rapidapi.com/summarize", + "description":"Pass in a web article URL and get a summary of the article back. Optionally you can pass in a language code you'd like the summary to be translated to.", + "method":"GET", + "required_parameters":[ + { + "name":"url", + "type":"STRING", + "description":"The URL of the web article to be summarized", + "default":"https://www.medialens.org/2023/arguments-against-despair/" + } + ], + "optional_parameters":[ + { + "name":"type", + "type":"ENUM", + "description":"Determined if a shorter (default) or longer summary should returned. To return a slightly longer summary, pass 'expand' here.", + "default":"" + }, + { + "name":"lang", + "type":"STRING", + "description":"Language the summary should be translated to. Leave blank to keep the summary in the same language as the article.", + "default":"en" + } + ], + "code":"import requests\n\nurl = \"https://summate-it.p.rapidapi.com/summarize\"\nquerystring = {\"url\": url, \"lang\": lang}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"summate-it.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers, params=querystring)\n\nprint(response.json())\n", + "statuscode":200, + "body":{ + "key1":"value", + "key2":"value" + }, + "headers":{}, + "schema":{} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it/api.py new file mode 100644 index 0000000000000000000000000000000000000000..b6eebda5db34e6a0a9bf1c4242f7028bf56ab288 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/summate_it/api.py @@ -0,0 +1,36 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def summarize(url: str, type: str=None, lang: str='en', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "Pass in a web article URL and get a summary of the article back. Optionally you can pass in a language code you'd like the summary to be translated to." + url: The URL of the web article to be summarized + type: Determined if a shorter (default) or longer summary should returned. To return a slightly longer summary, pass 'expand' here. + lang: Language the summary should be translated to. Leave blank to keep the summary in the same language as the article. + + """ + url = f"https://summate-it.p.rapidapi.com/summarize" + querystring = {'url': url, } + if type: + querystring['type'] = type + if lang: + querystring['lang'] = lang + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "summate-it.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/superai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/superai.json new file mode 100644 index 0000000000000000000000000000000000000000..16c91865d7faaaa575a52fc6647b894279e01195 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/superai.json @@ -0,0 +1,201 @@ +{ + "product_id": "api_6600d822-f9a0-462f-a6f0-6729b5f755ea", + "tool_description": "SuperAI GPT-3 ChatGPT API, help you implement a chatGPT-like conversation app.", + "home_url": "https://rapidapi.com/guyskk/api/superai1/", + "name": "superai", + "title": "superai", + "pricing": "PAID", + "tool_name": "superai", + "score": { + "avgServiceLevel": 0, + "avgLatency": 61995, + "avgSuccessRate": 0, + "popularityScore": 0, + "__typename": "Score" + }, + "host": "superai1.p.rapidapi.com", + "api_list": [ + { + "name": "chat.list", + "url": "https://superai1.p.rapidapi.com/api/v4/chat.list", + "description": "List all chat sessions of a user.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.list\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.list\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "item_s": { + "type": "array", + "items": { + "type": "object", + "properties": { + "id": { + "type": "integer" + }, + "user_id": { + "type": "string" + }, + "question": { + "type": "object", + "properties": { + "text": { + "type": "string" + } + } + }, + "dt_created": { + "type": "string" + }, + "dt_updated": { + "type": "string" + }, + "message_s": { + "type": "null" + } + } + } + } + } + } + }, + { + "name": "chat.get", + "url": "https://superai1.p.rapidapi.com/api/v4/chat.get", + "description": "Get all messages in a chat session.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.get\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.get\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "id": { + "type": "integer" + }, + "user_id": { + "type": "string" + }, + "question": { + "type": "string" + }, + "dt_created": { + "type": "string" + }, + "dt_updated": { + "type": "string" + }, + "message_s": { + "type": "array", + "items": { + "type": "object", + "properties": { + "id": { + "type": "integer" + }, + "user_id": { + "type": "string" + }, + "chat_id": { + "type": "integer" + }, + "question": { + "type": "object", + "properties": { + "text": { + "type": "string" + } + } + }, + "answer": { + "type": "object", + "properties": { + "text": { + "type": "string" + } + } + }, + "answer_cost_ms": { + "type": "integer" + }, + "dt_created": { + "type": "string" + } + } + } + } + } + } + }, + { + "name": "chat.ask", + "url": "https://superai1.p.rapidapi.com/api/v4/chat.ask", + "description": "Begin chat session or ask question in chat session.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.ask\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "id": { + "type": "integer" + }, + "user_id": { + "type": "string" + }, + "chat_id": { + "type": "integer" + }, + "question": { + "type": "string" + }, + "answer": { + "type": "object", + "properties": { + "text": { + "type": "string" + } + } + }, + "answer_cost_ms": { + "type": "integer" + }, + "dt_created": { + "type": "string" + } + } + } + }, + { + "name": "chat.delete", + "url": "https://superai1.p.rapidapi.com/api/v4/chat.delete", + "description": "Delete a chat session.", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://superai1.p.rapidapi.com/api/v4/chat.delete\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"superai1.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": { + "type": "object", + "properties": { + "message": { + "type": "string" + } + } + } + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/synthia_ai.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/synthia_ai.json new file mode 100644 index 0000000000000000000000000000000000000000..ddf12a3fe84dfbd919867e453fae0afa5b229575 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/synthia_ai.json @@ -0,0 +1,85 @@ +{ + "product_id": "api_06319c4f-c0e3-43d8-accc-9f08a1fcfa69", + "tool_description": "Synthia AI", + "home_url": "https://rapidapi.com/komodo-ai-komodo-ai-default/api/synthia-ai/", + "name": "Synthia AI", + "title": "Synthia AI", + "pricing": "FREEMIUM", + "tool_name": "Synthia AI", + "score": { + "avgServiceLevel": 98, + "avgLatency": 2494, + "avgSuccessRate": 98, + "popularityScore": 8.8, + "__typename": "Score" + }, + "host": "synthia-ai.p.rapidapi.com", + "api_list": [ + { + "name": "/query_company_data_direct", + "url": "https://synthia-ai.p.rapidapi.com/query_company_data_direct", + "description": "/query_company_data_direct", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/query_company_data_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/query_company_data_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/query_industry_data_direct", + "url": "https://synthia-ai.p.rapidapi.com/query_industry_data_direct", + "description": "/query_industry_data_direct", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/query_industry_data_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/query_industry_data_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/llm_responser_direct", + "url": "https://synthia-ai.p.rapidapi.com/llm_responser_direct", + "description": "/llm_responser_direct", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/llm_responser_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/llm_responser_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/company_profile_direct", + "url": "https://synthia-ai.p.rapidapi.com/company_profile_direct", + "description": "/company_profile_direct", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/company_profile_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/company_profile_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/user_profile_direct", + "url": "https://synthia-ai.p.rapidapi.com/user_profile_direct", + "description": "user_profile_direct", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/user_profile_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/user_profile_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/prompt_enhancer_direct", + "url": "https://synthia-ai.p.rapidapi.com/prompt_enhancer_direct", + "description": "Enhance the prompt", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/prompt_enhancer_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://synthia-ai.p.rapidapi.com/prompt_enhancer_direct\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"synthia-ai.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test.json new file mode 100644 index 0000000000000000000000000000000000000000..29fd65bd283085d7a9bc1925f20c0a0ec46af557 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test.json @@ -0,0 +1,24 @@ +{ + "tool_name":"test", + "tool_description":"testjoo", + "title":"test", + "pricing":"FREE", + "score":null, + "home_url":"https://rapidapi.com/rxrxrx913/api/test15380/", + "host":"test15380.p.rapidapi.com", + "api_list":[ + { + "name":"qwetre", + "url":"https://test15380.p.rapidapi.com/wrty", + "description":"qweytr", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://test15380.p.rapidapi.com/wrty\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"test15380.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test/api.py new file mode 100644 index 0000000000000000000000000000000000000000..8a283e9460ebc8f650a2382d40604f8c1b0261fe --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def qwetre(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "qweytr" + + """ + url = f"https://test15380.p.rapidapi.com/wrty" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "test15380.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test_api.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test_api.json new file mode 100644 index 0000000000000000000000000000000000000000..b87cfc94a5bcda480f786581b04ba51ca29cb3de --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/test_api.json @@ -0,0 +1,24 @@ +{ + "product_id": "api_a933e501-a8c9-4ea6-9022-5b89d8dc8623", + "tool_description": "test_API_Daniel_Fiuza", + "home_url": "https://rapidapi.com/daniel-dnIFESCC-/api/test_api126/", + "name": "Test_API", + "title": "Test_API", + "pricing": "PAID", + "tool_name": "Test_API", + "score": null, + "host": "test_api126.p.rapidapi.com", + "api_list": [ + { + "name": "endpoint_test", + "url": "https://test_api126.p.rapidapi.com/", + "description": "test api with original url at:\nhttps://qwz2nb9yt9.execute-api.us-east-1.amazonaws.com/dev", + "method": "POST", + "required_parameters": [], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://test_api126.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"test_api126.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://test_api126.p.rapidapi.com/\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"test_api126.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers)\nprint(response.json())\n", + "test_endpoint": "" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste.json new file mode 100644 index 0000000000000000000000000000000000000000..00ed1bf47fd25ee569999e5a943bc042ae6455e8 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste.json @@ -0,0 +1,24 @@ +{ + "tool_name":"teste", + "tool_description":"teste", + "title":"teste", + "pricing":"FREE", + "score":null, + "home_url":"https://rapidapi.com/rubenfilipesoareslascasas-d0HF_S-F8L9/api/teste890/", + "host":"teste890.p.rapidapi.com", + "api_list":[ + { + "name":"teste", + "url":"https://teste890.p.rapidapi.com/teste", + "description":"teste", + "method":"GET", + "required_parameters":[], + "optional_parameters":[], + "code":"import requests\n\nurl = \"https://teste890.p.rapidapi.com/teste\"\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"teste890.p.rapidapi.com\"\n}\n\nresponse = requests.get(url, headers=headers)\n\nprint(response.json())\n", + "statuscode":111, + "body":"", + "headers":"", + "schema":"" + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste/api.py new file mode 100644 index 0000000000000000000000000000000000000000..ab7b68c565f88a79af9b519eaa5e650da30a0e3e --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/teste/api.py @@ -0,0 +1,29 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def teste(toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "teste" + + """ + url = f"https://teste890.p.rapidapi.com/teste" + querystring = {} + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "teste890.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation + diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/texel_virtual_try_on.json b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/texel_virtual_try_on.json new file mode 100644 index 0000000000000000000000000000000000000000..6037423e2e1ff2054ca98701ef653dc31ae8c156 --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/texel_virtual_try_on.json @@ -0,0 +1,69 @@ +{ + "product_id": "api_686101e5-5fe8-43ea-99b4-7fb1e1a70243", + "tool_description": "A cutting edge Virtual Try-On solution to integrate with your fashion e-commerce that allows customers to try-on clothing by uploading their own photos.", + "home_url": "https://rapidapi.com/texel-inc-texel-inc-default/api/texel-virtual-try-on/", + "name": "Texel Virtual Try-On", + "title": "Texel Virtual Try-On", + "pricing": "FREEMIUM", + "tool_name": "Texel Virtual Try-On", + "score": { + "avgServiceLevel": 99, + "avgLatency": 3291, + "avgSuccessRate": 44, + "popularityScore": 9.4, + "__typename": "Score" + }, + "host": "texel-virtual-try-on.p.rapidapi.com", + "api_list": [ + { + "name": "/try-on-file", + "url": "https://texel-virtual-try-on.p.rapidapi.com/try-on-file", + "description": "Transfer clothing from the clothing image to the avatar image.", + "method": "POST", + "required_parameters": [ + { + "name": "avatar_image", + "type": "BINARY", + "description": "Image file with user's avatar (JPEG, PNG or WEBP)", + "default": "" + }, + { + "name": "clothing_image", + "type": "BINARY", + "description": "Image file with clothing on a person in frontal pose (JPEG, PNG or WEBP)", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://texel-virtual-try-on.p.rapidapi.com/try-on-file\"\nquerystring = {\"avatar_image\": \"\", \"clothing_image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"texel-virtual-try-on.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://texel-virtual-try-on.p.rapidapi.com/try-on-file\"\nquerystring = {\"avatar_image\": \"\", \"clothing_image\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"texel-virtual-try-on.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "" + }, + { + "name": "/try-on-url", + "url": "https://texel-virtual-try-on.p.rapidapi.com/try-on-url", + "description": "Transfer clothing from the clothing image to the avatar image passed by URLs", + "method": "POST", + "required_parameters": [ + { + "name": "clothing_image_url", + "type": "STRING", + "description": "URL of an image of clothing on a person in frontal pose (JPEG, PNG or WEBP)", + "default": "" + }, + { + "name": "avatar_image_url", + "type": "STRING", + "description": "URL of an image with user's avatar (JPEG, PNG or WEBP)", + "default": "" + } + ], + "optional_parameters": [], + "code": "import requests\n\nurl = \"https://texel-virtual-try-on.p.rapidapi.com/try-on-url\"\nquerystring = {\"clothing_image_url\": \"\", \"avatar_image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"texel-virtual-try-on.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "convert_code": "import requests\n\nurl = \"https://texel-virtual-try-on.p.rapidapi.com/try-on-url\"\nquerystring = {\"clothing_image_url\": \"\", \"avatar_image_url\": \"\"}\n\nheaders = {\n \"X-RapidAPI-Key\": \"SIGN-UP-FOR-KEY\",\n \"X-RapidAPI-Host\": \"texel-virtual-try-on.p.rapidapi.com\"\n }\n\nresponse = requests.post(url, headers=headers, params=querystring)\nprint(response.json())\n", + "test_endpoint": "", + "statuscode": 200, + "schema": {} + } + ] +} \ No newline at end of file diff --git a/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/text2speech/api.py b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/text2speech/api.py new file mode 100644 index 0000000000000000000000000000000000000000..777d7cea185a7858dd489f6fec0ec05a5489b1de --- /dev/null +++ b/toolbench/toolenv/tools/Artificial_Intelligence_Machine_Learning/text2speech/api.py @@ -0,0 +1,33 @@ +import requests +import json +from datetime import date, datetime, timedelta +import os + +from typing import Optional, Dict, Union, List + + +def text2speech_endpoint(text: str, lang: str=None, slow: bool=None, toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): + """ + "/tts" + + """ + url = f"https://text2speech3.p.rapidapi.com/tts" + querystring = {'text': text, } + if lang: + querystring['lang'] = lang + if slow: + querystring['slow'] = slow + + headers = { + "X-RapidAPI-Key": toolbench_rapidapi_key, + "X-RapidAPI-Host": "text2speech3.p.rapidapi.com" + } + + + response = requests.get(url, headers=headers, params=querystring) + try: + observation = response.json() + except: + observation = response.text + return observation +