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app.py
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import
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import
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from fastapi import Body
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HF_TOKEN = os.environ.get("HF_TOKEN")
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DB_HF_TOKEN = os.environ.get("DB_Write_Token")
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#
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FEEDBACK_API_URL = "https://rr19tech-plnb-demo.hf.space/add_user_comment"
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'''
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def call_private_api(user_input):
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# Pass the token in the Authorization header
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headers = {
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"Authorization": f"Bearer {HF_TOKEN}",
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#"Content-Type": "text/plain"
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"Content-Type": "application/json"
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}
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try:
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response = requests.get(
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PRIVATE_API_URL,
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headers=headers,
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params={"text": user_input},
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timeout=300,
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)
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content_type = response.headers.get("content-type")
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print(f"DEBUG: Status {response.status_code} | Content-Type: {content_type}")
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if response.status_code == 200:
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#return response.json()
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return response.text # workaround
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else:
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return {"error": f"Status {response.status_code}", "detail": response.text}
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except Exception as e:
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return {"error": f"Connection failed: {str(e)}"}
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#
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'''
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#changing this to a server method
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from gradio import Server
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#from fastapi.middleware.cors import CORSMiddleware
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# Initialize the server
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app = Server()
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'''
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app.add_middleware(
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CORSMiddleware,
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# Replace with the EXACT domain where your JS code is running (include http/https)
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# DO NOT USE ["*"] here, as browsers block credentials paired with wildcards
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allow_origins=["http://localhost:8000", "https://your-frontend-app.com"],
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allow_credentials=True, # Matches the incoming JS request flag
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allow_methods=["*"],
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allow_headers=["*"],
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)
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'''
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# Define Method 1: Triggers when client calls /gradio_api/call/update_data
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#@app.api(name="call_private_api")
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@app.post("/call_private_api")
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async def call_private_api(user_input: str) -> dict:
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#def call_private_api(user_input: str = Body(..., embed=True)) -> dict:
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headers = {
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"Authorization": f"Bearer {HF_TOKEN}",
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#"Content-Type": "text/plain"
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"Content-Type": "application/json"
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}
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print(f"User input is: {user_input}")
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# We take that string and put it into a GET request
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try:
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response = requests.get(
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PRIVATE_API_URL,
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headers=headers,
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params={"text": user_input},
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timeout=300,
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)
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content_type = response.headers.get("content-type")
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print(f"DEBUG: Status {response.status_code} | Content-Type: {content_type}")
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if response.status_code == 200:
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return response.json()
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#return response.text # workaround
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else:
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return {"error": f"Status {response.status_code}", "detail": response.text}
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except Exception as e:
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return {"error": f"Connection failed: {str(e)}"}
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# Define Method 2: User feedback
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#@app.api(name="user_feedback")
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@app.post("/user_feedback")
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async def process_user_feedback(user_input: str) -> dict:
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headers = {
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"Authorization": f"Bearer {DB_HF_TOKEN}",
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#"Content-Type": "text/plain"
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"Content-Type": "application/json"
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}
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print(f"User feedback input is : {user_input}")
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try:
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response = requests.get(
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FEEDBACK_API_URL,
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headers=headers,
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params={"text": user_input},
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timeout=300,
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)
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content_type = response.headers.get("content-type")
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print(f"DEBUG: Status {response.status_code} | Content-Type: {content_type}")
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if response.status_code == 200:
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return response.json()
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#return response.text # workaround
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else:
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return {"error": f"Status {response.status_code}", "detail": response.text}
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except Exception as e:
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return {"error": f"Connection failed: {str(e)}"}
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app.launch()
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from fastapi import FastAPI
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import gradio as gr
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from pydantic import BaseModel
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app = FastAPI()
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# 1. Define the incoming JSON structure
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class ApiInput(BaseModel):
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user_string: str # The key name you want to use in your JSON payload
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# 2. Setup your POST route
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@app.post("/call_private_api")
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def call_private_api(payload: ApiInput):
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# Extract the string value from the request
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input_text = payload.user_string
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# Run your custom processing logic here
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processed_result = f"Received and processed: {input_text}"
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return {"result": processed_result}
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# 3. Mount your standard Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# My Space Interface")
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app = gr.mount_gradio_app(app, demo, path="/")
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