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

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

# Basic Agent
class BasicAgent:
    def __init__(self):
        OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
        if not OPENAI_API_KEY:
            raise ValueError(
                "OPENAI_API_KEY not set. Add it in HF → Settings → Secrets."
            )

        model = OpenAIServerModel(
            model_id="gpt-4o-mini",
            api_key=OPENAI_API_KEY
        )

        search_tool = DuckDuckGoSearchTool()

        self.agent = CodeAgent(
            model=model,
            tools=[search_tool],
            max_steps=3  # prevents infinite loops
        )

    def __call__(self, question: str) -> str:
        return self.agent.run(question)

# Run + Submit
def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    if not profile:
        return "Please login first.", None
    username = profile.username

    questions_url = f"{DEFAULT_API_URL}/questions"
    submit_url = f"{DEFAULT_API_URL}/submit"

    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Error initializing agent: {e}", None

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

    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions_data = response.json()
    except Exception as e:
        return f"Error fetching 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 not question_text:
            continue
        try:
            answer = agent(question_text)
        except Exception as e:
            answer = f"AGENT ERROR: {e}"
        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
        results_log.append({
            "Task ID": task_id,
            "Question": question_text,
            "Submitted Answer": answer
        })

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

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

    try:
        response = requests.post(submit_url, json=submission_data, timeout=60)
        response.raise_for_status()
        result = response.json()
        final_status = (
            f"Submission Successful!\n"
            f"User: {result.get('username')}\n"
            f"Score: {result.get('score', 'N/A')}% "
            f"({result.get('correct_count', '?')}/"
            f"{result.get('total_attempted', '?')})\n"
            f"Message: {result.get('message', '')}"
        )
        return final_status, pd.DataFrame(results_log)
    except Exception as e:
        return f"Submission failed: {e}", pd.DataFrame(results_log)

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# 🤖 Basic Agent Evaluation Runner")
    gr.Markdown("""
    **Instructions**
    1. Login with your Hugging Face account.
    2. Click **Run Evaluation & Submit All Answers**.
    3. Wait for the agent to finish.

    **Requirements**
    - Uses **OpenAI (gpt-4o-mini)**
    - Requires `OPENAI_API_KEY` in HF Space Secrets
    - Agent is **step-limited** (max 3 steps)
    """)

    gr.LoginButton()
    run_button = gr.Button("Run Evaluation & Submit All Answers")
    status_output = gr.Textbox(label="Run Status / Submission Result", lines=6, interactive=False)
    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)

    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])

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