import os
import logging
from faster_whisper import WhisperModel
import sqlite3
from datetime import datetime
from pydub import AudioSegment

logger = logging.getLogger(__name__)

class VoiceService:
    def __init__(self, db_path: str, model_size: str = "small"):
        self.db_path = db_path
        self.model_size = model_size
        # CPU-only optimization: int8 is fast on standard CPUs
        self.model = WhisperModel(model_size, device="cpu", compute_type="int8")
        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:
        try:
            start_time = datetime.now()
            
            # Convert to wav if needed (Telegram uses .oga/.ogg)
            wav_path = file_path.rsplit('.', 1)[0] + ".wav"
            audio = AudioSegment.from_file(file_path)
            duration = int(len(audio) / 1000)
            audio.export(wav_path, format="wav")

            segments, info = self.model.transcribe(wav_path, beam_size=5)
            text = " ".join([segment.text for segment in segments]).strip()

            # Clean up temp files
            if os.path.exists(wav_path): os.remove(wav_path)
            
            # Log to DB
            self._log_to_db(user_id, username, msg_type, duration, text)
            
            return text
        except Exception as e:
            logger.error(f"Transcription error: {e}")
            return f"[Ошибка распознавания]: {e}"

    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}")

# Global instance will be initialized in main.py or handlers