Этап 7: Локальное распознавание речи
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mirivlad
parent
b50388063a
commit
0a294e89fc
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@ -1,15 +1,18 @@
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import asyncio
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import logging
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import os
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import tempfile
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from telegram import Update
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from telegram.ext import (
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Application, CommandHandler, MessageHandler, filters,
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ContextTypes, CallbackQueryHandler
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ContextTypes, CallbackQueryHandler, VoiceHandler
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)
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from telegram import InlineKeyboardButton, InlineKeyboardMarkup
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from config.config import get_settings
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from src.tools.orchestrator import Orchestrator
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from src.bot.states import chat_state, ChatMode
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from src.scheduler.scheduler import SchedulerManager
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from src.speech.speech import SpeechRecognizer
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logging.basicConfig(
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
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@ -20,6 +23,7 @@ logger = logging.getLogger(__name__)
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settings = get_settings()
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orchestrator = Orchestrator()
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scheduler_manager = None
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speech_recognizer = SpeechRecognizer()
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async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
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@ -32,6 +36,7 @@ async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
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async def help_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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mode = chat_state.get_mode(update.effective_chat.id)
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current_tool = orchestrator.get_default_tool()
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stt_status = "включено" if speech_recognizer.is_enabled() else "отключено"
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help_text = (
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f"Я {settings.bot_name}, ваш ИИ-ассистент.\n\n"
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"Доступные команды:\n"
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@ -44,9 +49,11 @@ async def help_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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"/qwen <текст> - Задать вопрос qwen-code\n"
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"/open <текст> - Задать вопрос opencode\n"
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"/forget - Очистить историю чата\n"
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"/remind <текст> <время> - Создать напоминание\n\n"
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"/remind <текст> <время> - Создать напоминание\n"
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"/stt on|off - Включить/выключить распознавание речи\n\n"
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f"Текущий режим: {'с подтверждением' if mode == ChatMode.CONFIRM else 'автономный'}\n"
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f"Инструмент по умолчанию: {current_tool}"
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f"Инструмент по умолчанию: {current_tool}\n"
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f"Распознавание речи: {stt_status}"
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)
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await update.message.reply_text(help_text)
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@ -99,6 +106,23 @@ async def cancel_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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await update.message.reply_text("Нет активных задач для отмены.")
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async def stt_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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if not context.args:
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status = "включено" if speech_recognizer.is_enabled() else "отключено"
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await update.message.reply_text(f"Распознавание речи: {status}")
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return
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arg = context.args[0].lower()
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if arg == "on":
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speech_recognizer.toggle(True)
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await update.message.reply_text("Распознавание речи включено.")
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elif arg == "off":
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speech_recognizer.toggle(False)
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await update.message.reply_text("Распознавание речи отключено.")
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else:
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await update.message.reply_text("Использование: /stt on | off")
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async def confirm_callback(update: Update, context: ContextTypes.DEFAULT_TYPE):
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query = update.callback_query
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await query.answer()
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@ -239,7 +263,6 @@ async def remind_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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minutes = int(match.group(1)) * value
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break
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from datetime import datetime
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run_at = datetime.now() + timedelta(minutes=minutes)
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scheduler_manager.add_reminder(chat_id, text, run_at)
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@ -248,8 +271,31 @@ async def remind_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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)
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async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
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prompt = update.message.text
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async def handle_voice(update: Update, context: ContextTypes.DEFAULT_TYPE):
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if not speech_recognizer.is_enabled():
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await update.message.reply_text("Распознавание речи отключено.")
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return
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await update.message.reply_text("Распознаю голос...")
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voice = update.message.voice
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file = await context.bot.get_file(voice.file_id)
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with tempfile.NamedTemporaryFile(delete=False, suffix=".ogg") as tmp:
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await file.download_to_drive(tmp.name)
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audio_path = tmp.name
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text = await speech_recognizer.recognize(audio_path)
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if text:
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await update.message.reply_text(f"Распознано: {text}")
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await handle_message(update, context, text)
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else:
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await update.message.reply_text("Не удалось распознать речь.")
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async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE, override_text: str = None):
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prompt = override_text or update.message.text
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chat_id = update.effective_chat.id
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mode = chat_state.get_mode(chat_id)
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@ -281,6 +327,8 @@ async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
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def main():
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global scheduler_manager
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speech_recognizer.load_model()
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builder = Application.builder()
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builder.token(settings.telegram_bot_token)
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@ -298,11 +346,13 @@ def main():
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application.add_handler(CommandHandler("mode", mode_command))
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application.add_handler(CommandHandler("use", use_command))
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application.add_handler(CommandHandler("cancel", cancel_command))
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application.add_handler(CommandHandler("stt", stt_command))
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application.add_handler(CommandHandler("qwen", qwen_command))
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application.add_handler(CommandHandler("open", open_command))
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application.add_handler(CommandHandler("forget", forget_command))
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application.add_handler(CommandHandler("remind", remind_command))
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application.add_handler(CallbackQueryHandler(confirm_callback))
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application.add_handler(VoiceHandler(handle_voice))
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application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
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logger.info("Бот запущен")
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@ -0,0 +1,118 @@
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import asyncio
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import logging
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import os
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import aiofiles
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from typing import Optional
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from pathlib import Path
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from config.config import get_settings
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logger = logging.getLogger(__name__)
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settings = get_settings()
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class SpeechRecognizer:
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def __init__(self):
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self.enabled = settings.stt_enabled
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self.model_name = settings.stt_model
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self.model = None
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self.recognizer = None
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def load_model(self):
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if not self.enabled:
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logger.info("Распознавание речи отключено")
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return
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try:
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if self.model_name == "vosk":
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from vosk import Model, KaldiRecognizer
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import json
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model_path = os.path.expanduser("~/.vosk/models/vosk-model-ru")
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if not os.path.exists(model_path):
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logger.warning(f"Модель Vosk не найдена по пути {model_path}")
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return
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self.model = Model(model_path)
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logger.info("Модель Vosk загружена")
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elif self.model_name == "whisper":
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from faster_whisper import WhisperModel
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self.model = WhisperModel("small", device="cpu", compute_type="int8")
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logger.info("Модель Whisper загружена")
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except Exception as e:
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logger.error(f"Ошибка загрузки модели распознавания: {e}")
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self.enabled = False
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async def download_and_convert(self, bot, file_id: str, output_path: str) -> Optional[str]:
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try:
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file = await bot.get_file(file_id)
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await file.download_to_drive(output_path)
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if output_path.endswith(".ogg"):
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wav_path = output_path.replace(".ogg", ".wav")
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process = await asyncio.create_subprocess_exec(
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"ffmpeg", "-i", output_path, "-ar", "16000", "-ac", "1", wav_path,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE
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)
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await process.communicate()
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os.remove(output_path)
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return wav_path
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return output_path
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except Exception as e:
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logger.error(f"Ошибка скачивания/конвертации: {e}")
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return None
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async def recognize(self, audio_path: str) -> Optional[str]:
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if not self.enabled or not self.model:
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return None
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try:
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if self.model_name == "vosk":
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return await self._recognize_vosk(audio_path)
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elif self.model_name == "whisper":
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return await self._recognize_whisper(audio_path)
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except Exception as e:
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logger.error(f"Ошибка распознавания: {e}")
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return None
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finally:
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if os.path.exists(audio_path):
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os.remove(audio_path)
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async def _recognize_vosk(self, audio_path: str) -> Optional[str]:
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import json
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from vosk import KaldiRecognizer
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rec = KaldiRecognizer(self.model, 16000)
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async with aiofiles.open(audio_path, "rb") as f:
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while True:
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data = await f.read(4000)
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if not data:
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break
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rec.AcceptWaveform(data)
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result = json.loads(rec.FinalResult())
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return result.get("text", "")
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async def _recognize_whisper(self, audio_path: str) -> Optional[str]:
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segments, info = self.model.transcribe(audio_path, language="ru")
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text_parts = []
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async for segment in segments:
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text_parts.append(segment.text)
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return " ".join(text_parts)
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def toggle(self, enabled: bool):
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self.enabled = enabled
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logger.info(f"Распознавание речи: {'включено' if enabled else 'отключено'}")
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def is_enabled(self) -> bool:
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return self.enabled
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