app.py

import gradio as gr
import requests
import pandas as pd
from BasicAgent import BasicAgent  # Import BasicAgent class

DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

def run_and_submit_all(profile: gr.OAuthProfile | None):
    # Your logic for fetching and submitting data here
    agent = BasicAgent()
    question = "What is the meaning of life?"  # Example question, you can modify this
    answer = agent(question)  # Get answer from BasicAgent
    
    # Mocking data as if agent has answered some questions
    data = [{"Task ID": f"task_{i+1}", "Answer": f"Answer to question {i+1}"} for i in range(5)]
    
    # You can modify the status and table as per your needs
    return "Results submitted successfully!", pd.DataFrame(data)

# Initialize Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")
    gr.LoginButton()
    
    # Add run button and result output fields
    run_button = gr.Button("Run Evaluation & Submit All Answers")
    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
    
    # Hook up button click to function
    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])

if __name__ == "__main__":
    demo.launch(debug=True, share=False)