fix: add cloud local asr fallback

api/main.py

@@ -61,8 +61,12 @@ LLM_API_KEY = os.getenv("LLM_API_KEY", "").strip()
 ASR_BASE_URL = os.getenv("ASR_BASE_URL", LLM_BASE_URL).strip()
 ASR_API_KEY = (os.getenv("ASR_API_KEY") or LLM_API_KEY).strip()
 ASR_MODEL = os.getenv("ASR_MODEL", "whisper-1")
+ASR_REMOTE_ENABLED = os.getenv("ASR_REMOTE_ENABLED", "true").strip().lower() not in {"0", "false", "no", "off"}
 ASR_FALLBACK_MODEL = os.getenv("ASR_FALLBACK_MODEL", "gemini-2.5-flash").strip() or "gemini-2.5-flash"
 ASR_TIMEOUT_SECONDS = max(15, int(os.getenv("ASR_TIMEOUT_SECONDS", "45")))
+FASTER_WHISPER_MODEL = os.getenv("FASTER_WHISPER_MODEL", "tiny.en").strip() or "tiny.en"
+FASTER_WHISPER_DEVICE = os.getenv("FASTER_WHISPER_DEVICE", "cpu").strip() or "cpu"
+FASTER_WHISPER_COMPUTE_TYPE = os.getenv("FASTER_WHISPER_COMPUTE_TYPE", "int8").strip() or "int8"
 LOCAL_ASR_BIN = os.getenv("LOCAL_ASR_BIN", "").strip()
 LOCAL_ASR_MODEL = os.getenv("LOCAL_ASR_MODEL", "mlx-community/whisper-tiny").strip() or "mlx-community/whisper-tiny"
 LOCAL_ASR_TIMEOUT_SECONDS = max(30, int(os.getenv("LOCAL_ASR_TIMEOUT_SECONDS", "180")))
@@ -2794,6 +2798,32 @@ def _transcribe_mlx_sync(wav: Path) -> list[dict]:
     return _validate_asr_segments(segments, duration, "mlx_whisper")
 
 
+def _transcribe_faster_whisper_sync(wav: Path) -> list[dict]:
+    try:
+        from faster_whisper import WhisperModel
+    except Exception as e:
+        raise TranscriptionUnavailable(f"faster-whisper 不可用：{e}") from e
+    duration = media_duration(wav)
+    model = WhisperModel(
+        FASTER_WHISPER_MODEL,
+        device=FASTER_WHISPER_DEVICE,
+        compute_type=FASTER_WHISPER_COMPUTE_TYPE,
+    )
+    raw_segments, _info = model.transcribe(
+        str(wav.resolve()),
+        language="en",
+        beam_size=1,
+        vad_filter=True,
+        condition_on_previous_text=False,
+    )
+    segments = [
+        {"start": float(seg.start), "end": float(seg.end), "text": str(seg.text or "").strip()}
+        for seg in raw_segments
+        if str(seg.text or "").strip()
+    ]
+    return _validate_asr_segments(segments, duration, f"faster-whisper:{FASTER_WHISPER_MODEL}")
+
+
 def _transcribe_gemini_sync(wav: Path) -> list[dict]:
     duration = media_duration(wav)
     audio_b64 = base64.b64encode(wav.read_bytes()).decode("ascii")
@@ -2828,22 +2858,29 @@ def _transcribe_sync(wav: Path) -> list[dict]:
     """Remote ASR first, local mlx_whisper second. Gemini fallback is guarded against fake timelines."""
     errors: list[str] = []
     duration = media_duration(wav)
+    if ASR_REMOTE_ENABLED:
+        try:
+            with wav.open("rb") as f:
+                resp = asr_llm().with_options(timeout=ASR_TIMEOUT_SECONDS).audio.transcriptions.create(
+                    file=(wav.name, f, "audio/wav"),
+                    model=ASR_MODEL,
+                    response_format="verbose_json",
+                    timestamp_granularities=["segment"],
+                )
+            raw = resp.model_dump() if hasattr(resp, "model_dump") else resp
+            segments = raw.get("segments") or []
+            # 兜底：网关如果不返回 segments，把全文当一段
+            if not segments and raw.get("text"):
+                segments = [{"start": 0.0, "end": float(raw.get("duration", 0) or 0), "text": raw["text"]}]
+            return _validate_asr_segments(segments, duration, ASR_MODEL)
+        except Exception as e:
+            errors.append(f"{ASR_MODEL}: {e}")
+    else:
+        errors.append(f"{ASR_MODEL}: remote disabled")
     try:
-        with wav.open("rb") as f:
-            resp = asr_llm().with_options(timeout=ASR_TIMEOUT_SECONDS).audio.transcriptions.create(
-                file=(wav.name, f, "audio/wav"),
-                model=ASR_MODEL,
-                response_format="verbose_json",
-                timestamp_granularities=["segment"],
-            )
-        raw = resp.model_dump() if hasattr(resp, "model_dump") else resp
-        segments = raw.get("segments") or []
-        # 兜底：网关如果不返回 segments，把全文当一段
-        if not segments and raw.get("text"):
-            segments = [{"start": 0.0, "end": float(raw.get("duration", 0) or 0), "text": raw["text"]}]
-        return _validate_asr_segments(segments, duration, ASR_MODEL)
+        return _transcribe_faster_whisper_sync(wav)
     except Exception as e:
-        errors.append(f"{ASR_MODEL}: {e}")
+        errors.append(f"faster-whisper: {e}")
     try:
         return _transcribe_mlx_sync(wav)
     except Exception as e:
@@ -3956,6 +3993,8 @@ def health() -> dict:
         "models": {
             "asr": ASR_MODEL,
             "asr_base_url": ASR_BASE_URL or LLM_BASE_URL or "openai-default",
+            "asr_remote_enabled": ASR_REMOTE_ENABLED,
+            "faster_whisper": FASTER_WHISPER_MODEL,
             "local_asr": LOCAL_ASR_MODEL,
             "asr_fallback": ASR_FALLBACK_MODEL,
             "translate": TRANSLATE_MODEL,

api/requirements.txt

@@ -9,3 +9,4 @@ httpx==0.27.2
 imagehash==4.3.1
 Pillow>=11.0
 numpy>=2.0
+faster-whisper==1.1.1