import aiohttp
import logging
from app.settings_cache import SettingsCache

logger = logging.getLogger(__name__)


async def categorize_with_gpt(text: str) -> str:
    gpt_key = SettingsCache.get("yandex_gpt_key")
    folder_id = SettingsCache.get("yandex_folder_id")
    if not gpt_key or not folder_id:
        return ""

    prompt = (
        "Определи категорию обращения клиента из списка: "
        "Видеонаблюдение, СКУД, Пожарная сигнализация, IT-инфраструктура, "
        "Обслуживание, Консультация, Другое. "
        "Ответь только названием категории, без пояснений. "
        f"Текст обращения: {text}"
    )

    url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
    headers = {
        "Authorization": f"Api-Key {gpt_key}",
        "Content-Type": "application/json",
        "x-folder-id": folder_id,
    }
    body = {
        "modelUri": f"gpt://{folder_id}/yandexgpt-lite/latest",
        "completionOptions": {"stream": False, "temperature": 0.1, "maxTokens": 50},
        "messages": [{"role": "user", "text": prompt}],
    }

    try:
        async with aiohttp.ClientSession() as session:
            async with session.post(url, headers=headers, json=body) as resp:
                if resp.status == 200:
                    data = await resp.json()
                    return data.get("result", {}).get("alternatives", [{}])[0].get("message", {}).get("text", "").strip()
                logger.warning(f"GPT categorize returned {resp.status}")
    except Exception as e:
        logger.error(f"GPT categorize error: {e}")
    return ""


async def analyze_emotion_with_gpt(text: str) -> str:
    gpt_key = SettingsCache.get("yandex_gpt_key")
    folder_id = SettingsCache.get("yandex_folder_id")
    if not gpt_key or not folder_id:
        return "neutral"

    prompt = (
        "Определи эмоциональную окраску текста клиента. "
        "Варианты: positive, neutral, negative. "
        "Ответь только одним словом. "
        f"Текст: {text}"
    )

    url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
    headers = {
        "Authorization": f"Api-Key {gpt_key}",
        "Content-Type": "application/json",
        "x-folder-id": folder_id,
    }
    body = {
        "modelUri": f"gpt://{folder_id}/yandexgpt-lite/latest",
        "completionOptions": {"stream": False, "temperature": 0.1, "maxTokens": 10},
        "messages": [{"role": "user", "text": prompt}],
    }

    try:
        async with aiohttp.ClientSession() as session:
            async with session.post(url, headers=headers, json=body) as resp:
                if resp.status == 200:
                    data = await resp.json()
                    return data.get("result", {}).get("alternatives", [{}])[0].get("message", {}).get("text", "").strip().lower()
                logger.warning(f"GPT emotion analysis returned {resp.status}")
    except Exception as e:
        logger.error(f"GPT emotion analysis error: {e}")
    return "neutral"