56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
import os
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import sys
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import logging
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import asyncio
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from pathlib import Path
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from typing import Optional, Tuple
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logger = logging.getLogger("AGYVoiceTranscriber")
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_whisper_model = None
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def get_whisper_model():
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"""Lazy loader for singleton WhisperModel instance."""
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global _whisper_model
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if _whisper_model is None:
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try:
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from faster_whisper import WhisperModel
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logger.info("Initializing faster-whisper model (base, int8)...")
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_whisper_model = WhisperModel("base", device="cpu", compute_type="int8")
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logger.info("faster-whisper model initialized successfully.")
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except Exception as e:
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logger.error(f"Failed to load faster-whisper model: {e}", exc_info=True)
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_whisper_model = None
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return _whisper_model
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def _transcribe_sync(audio_path: str, language: Optional[str] = None) -> Tuple[bool, str, str]:
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model = get_whisper_model()
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if model is None:
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return False, "", "unknown"
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try:
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# Default to Persian (fa) unless explicitly specified otherwise
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lang = language if (language and language not in ("auto", "none")) else "fa"
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segments, info = model.transcribe(
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audio_path,
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beam_size=5,
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language=lang,
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vad_filter=True,
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initial_prompt="گفتگوی محاورهای و رسمی به زبان فارسی",
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)
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texts = [seg.text.strip() for seg in segments if seg.text.strip()]
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full_text = " ".join(texts).strip()
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detected_lang = getattr(info, "language", "unknown")
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return True, full_text, detected_lang
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except Exception as e:
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logger.error(f"Error transcribing audio {audio_path}: {e}", exc_info=True)
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return False, str(e), "unknown"
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async def transcribe_audio_file(audio_path: str, language: Optional[str] = None) -> Tuple[bool, str, str]:
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"""
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Asynchronously transcribes audio file (OGG, MP3, WAV, M4A, etc.) to text.
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Returns: (success, transcribed_text, detected_language)
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"""
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return await asyncio.to_thread(_transcribe_sync, audio_path, language)
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