import os
import gradio as gr
import requests
import openai

# Gunakan OpenAI GPT untuk menjawab pertanyaan
class GPTAgent:
    def __init__(self):
        self.api_key = os.getenv("OPENAI_API_KEY")
        openai.api_key = self.api_key
        self.model = "gpt-4o"  # atau "gpt-3.5-turbo" jika tidak punya akses

    def __call__(self, question: str) -> str:
        try:
            response = openai.chat.completions.create(
                model=self.model,
                messages=[
                    {"role": "system", "content": "You are a helpful assistant."},
                    {"role": "user", "content": question},
                ]
            )
            return response.choices[0].message.content.strip()
        except Exception as e:
            return f"ERROR: {e}"

# Fungsi utama untuk evaluasi & submit
def run_and_submit_all(user_profile):
    username = user_profile if user_profile else "anonymous"
    agent = GPTAgent()

    questions_url = "https://agents-course-unit4-scoring.hf.space/questions"
    submit_url = "https://agents-course-unit4-scoring.hf.space/submit"

    try:
        questions = requests.get(questions_url, timeout=10).json()
    except Exception as e:
        return f"❌ Error fetching questions: {e}", []

    answers = []
    results = []

    for q in questions:
        task_id = q["task_id"]
        question_text = q["question"]
        answer = agent(question_text)
        answers.append({"task_id": task_id, "answer": answer})
        results.append([task_id, question_text, answer])

    payload = {
        "user": username,
        "answers": answers
    }

    try:
        res = requests.post(submit_url, json=payload, timeout=10)
        res.raise_for_status()
        score = res.json().get("score", 0.0)
        correct = res.json().get("correct", 0)
        total = res.json().get("total", len(questions))
        status = f"✅ User: {username}\nScore: {score:.1f}%\nCorrect: {correct}/{total}"
        return status, results
    except Exception as e:
        return f"❌ Error submitting answers: {e}", results

# UI Gradio
with gr.Blocks() as demo:
    gr.Markdown("# GAIA Benchmark Agent with GPT-4o")
    gr.Markdown(
        """
        1. Login using your Hugging Face account below.<br>
        2. Click 'Run Evaluation & Submit' to start.<br>
        3. Wait for your agent to answer all questions and submit.<br>
        """
    )

    login = gr.LoginButton()
    run_btn = gr.Button("Run Evaluation & Submit")
    status = gr.Textbox(label="Status", interactive=False, lines=4)
    results = gr.DataFrame(headers=["Task ID", "Question", "Answer"])

    run_btn.click(fn=run_and_submit_all, inputs=[login], outputs=[status, results])

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