import os
import time
import requests
import gradio as gr
import pandas as pd

GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
GEMINI_MODEL = "gemini-2.5-flash"
GEMINI_API_URL = f"https://generativelanguage.googleapis.com/v1/models/{GEMINI_MODEL}:generateContent"
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

class GeminiAgent:
    def __init__(self):
        if not GEMINI_API_KEY:
            raise ValueError("❌ Переменная окружения GEMINI_API_KEY не установлена.")

    def __call__(self, question: str) -> str:
        headers = {"Content-Type": "application/json"}
        params = {"key": GEMINI_API_KEY}
        payload = {
            "contents": [{"parts": [{"text": question}]}]
        }

        for attempt in range(3):
            try:
                response = requests.post(GEMINI_API_URL, headers=headers, params=params, json=payload)
                if response.status_code == 429:
                    print(f"⚠️  Попытка {attempt+1}: Превышен лимит. Ждём 5 сек.")
                    time.sleep(5)
                    continue
                response.raise_for_status()
                return response.json()["candidates"][0]["content"]["parts"][0]["text"].strip()
            except Exception as e:
                print(f"❌ Ошибка: {e}")
                time.sleep(5)
        return "Ошибка при получении ответа от Gemini API"

def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    if not profile:
        return "Пожалуйста, войдите в Hugging Face", None

    username = profile.username
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    print(f"Пользователь: {username}")

    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"❌ Ошибка при загрузке вопросов: {e}", None

    agent = GeminiAgent()
    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
        answer = agent(question_text)
        results_log.append({"Task ID": task_id, "Question": question_text, "Answer": answer})
        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
        time.sleep(3)  # ⏳ Задержка между запросами

    try:
        submission_data = {
            "username": username,
            "agent_code": agent_code,
            "answers": answers_payload
        }
        submit_response = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data)
        submit_response.raise_for_status()
        result = submit_response.json()
        score = result.get("score", "N/A")
        return f"✅ Отправка завершена! Ваш результат: {score}%", pd.DataFrame(results_log)
    except Exception as e:
        return f"❌ Ошибка при отправке ответов: {e}", pd.DataFrame(results_log)

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## Gemini 2.5 Agent 🤖")
    gr.Markdown("Войдите в Hugging Face и нажмите кнопку для запуска агента.")
    gr.LoginButton()
    run_btn = gr.Button("▶️ Запустить агента")
    status = gr.Textbox(label="Статус")
    table = gr.DataFrame(label="Результаты")
    run_btn.click(fn=run_and_submit_all, outputs=[status, table])

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