app.py

import os
import gradio as gr
import requests
import pandas as pd
from smolagents import CodeAgent, DuckDuckGoSearchTool, LiteLLMModel

# API URL for submission
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# My agent class
class BasicAgent:
    def __init__(self):
        print("Starting agent...")
        
        # Get my HF token
        token = os.getenv("hf_token")  # ← Changed to lowercase!
        
        if not token:
            raise Exception("Token not found! Check secrets.")
        
        # Create the model
        self.model = LiteLLMModel(
            model_id="huggingface/meta-llama/Llama-3.2-3B-Instruct",
            api_key=token
        )
        
        # Add web search
        self.search_tool = DuckDuckGoSearchTool()
        
        # Create agent
        self.agent = CodeAgent(
            tools=[self.search_tool],
            model=self.model,
            additional_authorized_imports=["requests", "pandas", "numpy", "openpyxl", "xlrd"]
        )
        
        print("Agent ready!")
    
    def __call__(self, question: str) -> str:
        print(f"Question: {question[:50]}...")
        try:
            answer = self.agent.run(question)
            return str(answer)
        except Exception as e:
            return f"Error: {str(e)}"


def run_and_submit_all(profile: gr.OAuthProfile | None):
    """Main function to run the evaluation"""
    
    space_id = os.getenv("SPACE_ID")
    
    # Check if logged in
    if profile:
        username = profile.username
        print(f"Logged in as: {username}")
    else:
        return "Please login first!", None
    
    # URLs
    questions_url = f"{DEFAULT_API_URL}/questions"
    submit_url = f"{DEFAULT_API_URL}/submit"
    
    # Initialize agent
    print("Creating agent...")
    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Error creating agent: {e}", None
    
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    
    # Get questions
    print("Getting questions...")
    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions = response.json()
        print(f"Got {len(questions)} questions")
    except Exception as e:
        return f"Error getting questions: {e}", None
    
    # Answer questions
    print("Answering questions...")
    results = []
    answers = []
    
    for i, item in enumerate(questions):
        task_id = item.get("task_id")
        question = item.get("question")
        
        if not task_id or not question:
            continue
        
        print(f"Question {i+1}/{len(questions)}")
        
        try:
            answer = agent(question)
            answers.append({"task_id": task_id, "submitted_answer": answer})
            results.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
        except Exception as e:
            print(f"Error on question {i+1}: {e}")
            results.append({"Task ID": task_id, "Question": question, "Submitted Answer": f"Error: {e}"})
    
    if not answers:
        return "No answers generated", pd.DataFrame(results)
    
    # Submit
    print(f"Submitting {len(answers)} answers...")
    submission = {
        "username": username,
        "agent_code": agent_code,
        "answers": answers
    }
    
    try:
        response = requests.post(submit_url, json=submission, timeout=60)
        response.raise_for_status()
        result = response.json()
        
        status = (
            f"Submission successful!\n"
            f"User: {result.get('username')}\n"
            f"Score: {result.get('score')}%\n"
            f"Correct: {result.get('correct_count')}/{result.get('total_attempted')}\n"
            f"Message: {result.get('message')}"
        )
        
        return status, pd.DataFrame(results)
    
    except Exception as e:
        return f"Submission failed: {e}", pd.DataFrame(results)


# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# My Agent Evaluation")
    gr.Markdown("Login and click the button to run the evaluation.")
    
    gr.LoginButton()
    
    run_btn = gr.Button("Run Evaluation & Submit")
    
    status = gr.Textbox(label="Status", lines=5)
    table = gr.DataFrame(label="Results", wrap=True)
    
    run_btn.click(fn=run_and_submit_all, outputs=[status, table])

if __name__ == "__main__":
    print("Starting app...")
    demo.launch()