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()  # Raise an exception if the request was not successful
    
        # Access the response content
        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)