app.py

import os
import requests
import pandas as pd
import gradio as gr
from crew import run_crew          # ← your multi-agent logic

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


# ─── AGENT WRAPPER ──────────────────────────────────────────────────────────────
class CrewAgent:
    def __call__(self, question: str) -> str:
        return run_crew(question, file_path="")   # It MUST use your real crew logic!

agent = CrewAgent()


# ─── MAIN HANDLER ───────────────────────────────────────────────────────────────
def evaluate_and_submit(username: str):
    """Runs the agent on benchmark questions and submits answers, with debug logging."""
    username = username.strip()
    if not username:
        return "❌  Please enter your Hugging Face username.", None

    space_id   = os.getenv("SPACE_ID", "")
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""

    # 1) Fetch questions
    try:
        questions = requests.get(f"{API_URL}/questions", timeout=30).json()
    except Exception as e:
        return f"❌  Failed to fetch questions: {e}", None

    # 2) Answer questions, logging every result
    answers, log = [], []
    for item in questions:
        qid, qtxt = item["task_id"], item["question"]
        try:
            ans = agent(qtxt)
            # Debug print:
            print(f"QID: {qid} | Q: {qtxt[:60]}... | Agent Answer: {ans}")
            # Add warning if placeholder detected
            if ans.strip().lower() in ["this is a default answer.", "", "n/a"]:
                print(f"⚠️ Warning: Agent returned a default/empty answer for QID {qid}.")
        except Exception as e:
            ans = f"AGENT ERROR: {e}"
            print(f"⚠️ Agent error on QID {qid}: {e}")
        answers.append({"task_id": qid, "submitted_answer": ans})
        log.append({"Task ID": qid, "Question": qtxt, "Answer": ans})

    # Show part of the DataFrame in the console for debugging
    try:
        df = pd.DataFrame(log)
        print("=== First 5 results ===")
        print(df.head())
    except Exception as e:
        print(f"DataFrame print error: {e}")

    if not answers:
        return "⚠️  No answers generated.", pd.DataFrame(log)

    # 3) Submit
    try:
        resp = requests.post(
            f"{API_URL}/submit",
            json={"username": username, "agent_code": agent_code, "answers": answers},
            timeout=60,
        )
        resp.raise_for_status()
        data = resp.json()
        status = (
            "✅  Submission successful!\n"
            f"Score: {data.get('score')} % "
            f"({data.get('correct_count')}/{data.get('total_attempted')})\n"
            f"Message: {data.get('message')}"
        )
    except Exception as e:
        status = f"❌  Submission failed: {e}"

    return status, pd.DataFrame(log)



# ─── GRADIO UI ──────────────────────────────────────────────────────────────────
demo = gr.Interface(
    fn=evaluate_and_submit,
    inputs=gr.Textbox(label="Hugging Face username", placeholder="e.g. john-doe"),
    outputs=[
        gr.Textbox(label="Status", lines=6),
        gr.DataFrame(label="Submitted Answers"),
    ],
    title="GAIA Agent Submission",
    description=(
        "Enter your Hugging Face username and click **Run Evaluation & Submit**. "
        "The app will run your agent on all benchmark questions and send the answers."
    ),
)

if __name__ == "__main__":
    demo.launch()