import json
import os
import gradio as gr
import requests
from agent import API, fetch, make_agent, solve


def owner(profile):
    if not profile or profile.username != os.getenv("OWNER_USERNAME", "bestdive"):
        raise gr.Error("Please sign in as the Space owner.")


def smoke(profile: gr.OAuthProfile | None):
    owner(profile)
    try:
        answer = make_agent().run("Use calculate to compute (19 * 7) + 4. Return only the number.")
        return "Smoke test: " + str(answer)
    except Exception as exc:
        return "Model connection failed (" + type(exc).__name__ + "). Check Space Secrets, model availability and provider quota."


def evaluate(profile: gr.OAuthProfile | None):
    owner(profile)
    make_agent()  # Fail before running if credentials are absent.
    questions = json.loads(fetch(API + "/questions")[0])
    rows = []
    yield "Starting evaluation...", rows, None
    for i, question in enumerate(questions):
        try:
            answer = solve(question)
            status = "generated"
        except Exception as exc:
            answer, status = "", "error:" + type(exc).__name__
        rows.append({"task_id": question["task_id"], "question": question["question"],
                     "submitted_answer": answer, "status": status})
        yield f"Completed {i + 1}/{len(questions)}", rows, None
    yield "Evaluation complete. Review answers before submission.", rows, rows


def submit(rows, profile: gr.OAuthProfile | None):
    owner(profile)
    if not rows:
        raise gr.Error("Run an evaluation first.")
    space = os.getenv("SPACE_ID", "")
    if not space.startswith(profile.username + "/"):
        raise gr.Error("Publish this app in your own public Space before submission.")
    payload = {"username": profile.username, "agent_code": f"https://huggingface.co/spaces/{space}/tree/main",
               "answers": [{"task_id": r["task_id"], "submitted_answer": r["submitted_answer"]} for r in rows]}
    response = requests.post(API + "/submit", json=payload, timeout=90)
    response.raise_for_status()
    return json.dumps(response.json(), ensure_ascii=False, indent=2)


with gr.Blocks() as demo:
    gr.Markdown("# Bestdive Research Agent\nSign in, test the model connection, run the official questions, then submit.")
    gr.LoginButton()
    with gr.Row():
        test_button = gr.Button("1. Test model connection")
        run_button = gr.Button("2. Run official evaluation")
        submit_button = gr.Button("3. Submit generated answers")
    status = gr.Textbox(label="Status", lines=5)
    results = gr.JSON(label="Generated answers")
    state = gr.State(None)
    test_button.click(smoke, outputs=status, concurrency_limit=1)
    run_button.click(evaluate, outputs=[status, results, state], concurrency_limit=1)
    submit_button.click(submit, inputs=state, outputs=status, concurrency_limit=1)

if __name__ == "__main__":
    demo.queue(default_concurrency_limit=1).launch()