feat: 微信自动化客服(wechatauto-replica) 干净历史导入 - AI 自动回复/语音收发/朋友圈发布

voice2text.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""微信语音转文字模块（silk 解码 + faster-whisper ASR）。
+
+链路：.silk → silk_v3_decoder.exe 解码为 .pcm → 加 wav 头 → faster-whisper 转文字。
+
+用法：
+    from voice2text import VoiceToText
+    v2t = VoiceToText()
+    text = v2t.transcribe_silk("/path/to/xxx.silk")   # 返回文字，失败返回 None
+    text = v2t.transcribe_voice(username, local_id, db)  # 直接从微信库提取并转文字
+
+说明：
+    - whisper 模型懒加载（首次调用才加载，约几十秒；之后常驻内存）。
+    - 中文识别，small 模型在 CPU 上平衡速度与准确率。
+"""
+from __future__ import annotations
+
+import os
+import subprocess
+import threading
+import wave
+
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+DECODER_EXE = os.path.join(
+    BASE_DIR, "third_party", "silk-v3-decoder", "silk_v3_decoder.exe"
+)
+WHISPER_MODEL = os.environ.get("V2T_MODEL", "small")
+SAMPLE_RATE = 24000  # silk_v3_decoder 默认输出采样率
+
+_model = None
+_model_lock = threading.Lock()
+_hf_ready = False
+
+
+def _ensure_hf_env():
+    """国内环境用 hf-mirror 下载模型，并禁用 xet（避免 401）。"""
+    global _hf_ready
+    if _hf_ready:
+        return
+    os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")
+    os.environ.setdefault("HF_HUB_DISABLE_XET", "1")
+    _hf_ready = True
+
+
+def _get_model():
+    global _model
+    with _model_lock:
+        if _model is None:
+            _ensure_hf_env()
+            from faster_whisper import WhisperModel
+            _model = WhisperModel(WHISPER_MODEL, device="cpu", compute_type="int8")
+        return _model
+
+
+def _silk_to_pcm(silk_path: str, pcm_path: str) -> bool:
+    if not os.path.exists(DECODER_EXE):
+        return False
+    try:
+        r = subprocess.run(
+            [DECODER_EXE, silk_path, pcm_path, "-quiet"],
+            capture_output=True, timeout=60,
+        )
+        return r.returncode == 0 and os.path.exists(pcm_path) and os.path.getsize(pcm_path) > 0
+    except Exception:
+        return False
+
+
+def _pcm_to_wav(pcm_path: str, wav_path: str, sample_rate: int = SAMPLE_RATE):
+    with open(pcm_path, "rb") as f:
+        data = f.read()
+    with wave.open(wav_path, "wb") as w:
+        w.setnchannels(1)
+        w.setsampwidth(2)
+        w.setframerate(sample_rate)
+        w.writeframes(data)
+
+
+def transcribe_silk(silk_path: str, sample_rate: int = SAMPLE_RATE):
+    """把 .silk 语音文件转成文字；失败返回 None。"""
+    if not silk_path or not os.path.exists(silk_path):
+        return None
+    pcm_path = silk_path + ".pcm"
+    wav_path = silk_path + ".wav"
+    try:
+        if not _silk_to_pcm(silk_path, pcm_path):
+            return None
+        _pcm_to_wav(pcm_path, wav_path, sample_rate)
+        segments, _info = _get_model().transcribe(
+            wav_path, language="zh", beam_size=5,
+        )
+        text = "".join(s.text for s in segments).strip()
+        return text or None
+    except Exception:
+        return None
+    finally:
+        for p in (pcm_path, wav_path):
+            try:
+                if os.path.exists(p):
+                    os.remove(p)
+            except OSError:
+                pass
+
+
+def transcribe_voice(username: str, local_id: int, db, save_dir: str = None):
+    """从微信库提取语音并转文字：db 为 WeChatDB 实例。"""
+    try:
+        from wechatauto.media import MediaDownloader
+        md = MediaDownloader(db, save_dir=save_dir)
+        silk = md.download_voice(username, local_id, save_dir=save_dir)
+        if not silk:
+            return None
+        return transcribe_silk(silk)
+    except Exception:
+        return None
+
+
+class VoiceToText:
+    """可复用的语音转文字器（模型懒加载、线程安全）。"""
+
+    def __init__(self, model: str = None):
+        global WHISPER_MODEL
+        if model:
+            WHISPER_MODEL = model
+
+    def transcribe_silk(self, silk_path: str):
+        return transcribe_silk(silk_path)
+
+    def transcribe_voice(self, username: str, local_id: int, db, save_dir: str = None):
+        return transcribe_voice(username, local_id, db, save_dir)
+
+
+if __name__ == "__main__":
+    import sys
+    if len(sys.argv) < 2:
+        print("用法: python voice2text.py <xxx.silk>")
+        sys.exit(1)
+    print(transcribe_silk(sys.argv[1]))