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handler.py

@@ -242,8 +242,9 @@ class AudioFeatureExtractorEndpoint:
 # FastAPI handler for deployment (HF Spaces / Cloud Run / Lambda)
 # ──────────────────────────────────────────────────────────────────────── #
 
-from fastapi import FastAPI, File, UploadFile, Form
+from fastapi import FastAPI, File, UploadFile, Form, Request
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
 from pydantic import BaseModel
 from typing import Optional
 import base64
@@ -256,6 +257,17 @@ app.add_middleware(
     allow_methods=["*"], allow_headers=["*"],
 )
 
+
+@app.exception_handler(Exception)
+async def global_exception_handler(request: Request, exc: Exception):
+    """Catch any unhandled exceptions and return defaults instead of 500."""
+    print(f"[GLOBAL ERROR] {request.url}: {exc}")
+    traceback.print_exc()
+    return JSONResponse(
+        status_code=200,
+        content={**DEFAULT_AUDIO_FEATURES, "_error": str(exc), "_handler": "global"},
+    )
+
 extractor = AudioFeatureExtractorEndpoint()
 
 DEFAULT_AUDIO_FEATURES = {
@@ -331,8 +343,9 @@ async def extract_audio_features_base64(data: AudioBase64Request):
             print(f"[WARN] soundfile failed ({sf_err}), trying librosa...")
             y, sr = librosa.load(io.BytesIO(audio_bytes), sr=16000, mono=True)
 
-        if len(y.shape) > 1:
+        if hasattr(y, 'shape') and len(y.shape) > 1:
             y = np.mean(y, axis=1)
+        y = np.asarray(y, dtype=np.float32)
         if sr != 16000:
             y = librosa.resample(y, orig_sr=sr, target_sr=16000)
         y = y.astype(np.float32)