app.py

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

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

class BasicAgent:
    def __init__(self):
        print("Initializing agent via OpenRouter...")
        # Uses OpenRouter — free $1 credit, no HF credit consumption
 self.agent = CodeAgent(
    tools=[DuckDuckGoSearchTool()],
    model=OpenAIServerModel(
        model_id="llama-3.3-70b-versatile",
        api_base="https://api.groq.com/openai/v1",
        api_key=os.environ["GROQ_API_KEY"],
    ),
    max_steps=4,
    verbosity_level=0,
)
        print("Agent ready.")

    def __call__(self, question: str) -> str:
        print(f"Q: {question[:80]}...")
        try:
            result = self.agent.run(question)
            answer = str(result).strip()
            print(f"A: {answer[:100]}")
            return answer
        except Exception as e:
            print(f"Error: {e}")
            return "I don't know."


def run_and_submit_all(profile: gr.OAuthProfile | None):
    if not profile:
        return "Please login with your Hugging Face account first.", None

    username = profile.username
    space_id = os.getenv("SPACE_ID", "unknown/space")
    api_url = DEFAULT_API_URL
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"

    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Agent init failed: {e}", None

    try:
        resp = requests.get(f"{api_url}/questions", timeout=15)
        resp.raise_for_status()
        questions_data = resp.json()
        print(f"Fetched {len(questions_data)} questions.")
    except Exception as e:
        return f"Failed to fetch questions: {e}", None

    results_log = []
    answers_payload = []

    for item in questions_data:
        task_id = item.get("task_id")
        question_text = item.get("question")
        if not task_id or question_text is None:
            continue
        try:
            answer = agent(question_text)
        except Exception as e:
            answer = "I don't know."
        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
        results_log.append({"Task ID": task_id, "Question": question_text, "Answer": answer})

    if not answers_payload:
        return "No answers produced.", pd.DataFrame(results_log)

    submission = {
        "username": username.strip(),
        "agent_code": agent_code,
        "answers": answers_payload
    }

    try:
        resp = requests.post(f"{api_url}/submit", json=submission, timeout=120)
        resp.raise_for_status()
        r = resp.json()
        status = (
            f"✅ Submitted!\n"
            f"User: {r.get('username')}\n"
            f"Score: {r.get('score', 'N/A')}% "
            f"({r.get('correct_count', '?')}/{r.get('total_attempted', '?')} correct)\n"
            f"Message: {r.get('message', '')}"
        )
        return status, pd.DataFrame(results_log)
    except Exception as e:
        return f"Submission failed: {e}", pd.DataFrame(results_log)


with gr.Blocks() as demo:
    gr.Markdown("# 🤖 HF Agents Course — Final Assignment")
    gr.Markdown("""
1. Login with your HF account below
2. Click **Run Evaluation** and wait ~3–5 min
3. Results and score appear below
    """)
    gr.LoginButton()
    run_btn = gr.Button("🚀 Run Evaluation & Submit All Answers")
    status_out = gr.Textbox(label="Result", lines=6, interactive=False)
    results_table = gr.DataFrame(label="Answers", wrap=True)
    run_btn.click(fn=run_and_submit_all, outputs=[status_out, results_table])

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