import os
import logging
import requests
import sqlite3
from datetime import datetime
from pydub import AudioSegment
from pathlib import Path

logger = logging.getLogger(__name__)

# Настройки внешнего Whisper-сервиса на MacMini
WHISPER_API_URL = "http://192.168.10.168:9001/transcribe"

class VoiceService:
    def __init__(self, db_path: str, model_size: str = "large-v3"):
        self.db_path = db_path
        self.model_size = model_size
        logger.info(f"🎙️ Использование внешнего Whisper-сервиса ({model_size}) на MacMini")
        self._init_db()

    def _init_db(self):
        conn = sqlite3.connect(self.db_path)
        cursor = conn.cursor()
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS voice_recognition_logs (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                user_id INTEGER,
                username TEXT,
                message_type TEXT,
                duration INTEGER,
                text TEXT,
                created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
            )
        ''')
        conn.commit()
        conn.close()

    def transcribe(self, file_path: str, user_id: int, username: str, msg_type: str) -> str:
        f_path = Path(file_path)
        if not f_path.exists():
            raise FileNotFoundError(f"Файл не найден: {file_path}")

        try:
            logger.info(f"🧠 Отправка {f_path.name} на MacMini M4...")
            
            # Определяем длительность (локально через pydub)
            audio = AudioSegment.from_file(str(f_path))
            duration = int(len(audio) / 1000)

            # Отправляем файл в API
            with open(str(f_path), 'rb') as f:
                files = {'file': (f_path.name, f, 'audio/mpeg')}
                response = requests.post(WHISPER_API_URL, files=files, timeout=300)
                
            if response.status_code != 200:
                raise Exception(f"API Error: {response.text}")

            result = response.json()
            text = result.get("text", "").strip()

            logger.info(f"✅ Распознано успешно ({duration}с)")
            
            self._log_to_db(user_id, username, msg_type, duration, text)
            return text
        except Exception as e:
            logger.error(f"❌ Ошибка внешней транскрибации: {e}")
            return "Не удалось распознать голос (ошибка связи с M4-сервером)."

    def _log_to_db(self, user_id, username, msg_type, duration, text):
        try:
            conn = sqlite3.connect(self.db_path)
            cursor = conn.cursor()
            cursor.execute('''
                INSERT INTO voice_recognition_logs (user_id, username, message_type, duration, text)
                VALUES (?, ?, ?, ?, ?)
            ''', (user_id, username, msg_type, duration, text))
            conn.commit()
            conn.close()
        except Exception as e:
            logger.error(f"DB Log error: {e}")