| import gradio as gr |
| import requests |
| import pandas as pd |
| import ast |
|
|
| def image_classifier(grand_topics,topics, sub_topics, difficulty, count): |
| url = "https://d5cdtgvt04.execute-api.ap-south-1.amazonaws.com/test/q_gen" |
| params = { |
| "grand_topic_ids": "16595,898,746", |
| "topic_ids": "59559,59564,59565,59563", |
| "sub_topic_ids": "54345,31152,4011", |
| "count":"10", |
| "difficulty":"8" |
| |
| } |
| try: |
| response = requests.get(url, params=params) |
| response.raise_for_status() |
| |
| |
| content = response.text |
| |
| except requests.exceptions.RequestException as e: |
| print("Error occurred:", e) |
| return pd.DataFrame(ast.literal_eval(content)) |
|
|
| demo = gr.Interface(fn=image_classifier, inputs=["text", "text","text", ], outputs="dataframe") |
| demo.launch(share=True) |
