import os
import gradio as gr
import requests
import pandas as pd
from rag_agent import BasicAgent

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

def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    username = profile.username if profile else None
    if not username:
        return "Please log in to Hugging Face.", None

    agent = BasicAgent()
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"

    try:
        response = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
        response.raise_for_status()
        questions_data = response.json()
    except Exception as e:
        return f"Error fetching questions: {e}", None

    answers_payload, results_log = [], []
    for item in questions_data:
        task_id = item.get("task_id")
        question = item.get("question")
        if not task_id or not question:
            continue
        try:
            answer = agent(question)
        except Exception as e:
            answer = f"ERROR: {e}"
        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
        results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})

    submission_data = {
        "username": username,
        "agent_code": agent_code,
        "answers": answers_payload
    }

    try:
        res = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data, timeout=60)
        res.raise_for_status()
        result = res.json()
        status = f"✅ Submitted! Score: {result.get('score')}% - {result.get('message')}"
        return status, pd.DataFrame(results_log)
    except Exception as e:
        return f"Submission error: {e}", pd.DataFrame(results_log)

with gr.Blocks() as demo:
    gr.Markdown("# 🧠 RAG Agent: Wikipedia + arXiv")
    gr.Markdown("Login with Hugging Face and click below to evaluate your agent.")
    gr.LoginButton()
    run_button = gr.Button("Run Evaluation & Submit All Answers")
    status = gr.Textbox(label="Status", lines=4)
    table = gr.DataFrame(label="Results")

    run_button.click(fn=run_and_submit_all, outputs=[status, table])

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