Adding GPU support for transcription

app/worker.py

@@ -162,13 +162,33 @@ def get_model():
     global _model
     if _model is None:
         print(f"[whisper] loading model='{MODEL_NAME}' device='{WHISPER_DEVICE}' idx={WHISPER_DEVICE_INDEX} compute='{COMPUTE}' threads={WHISPER_CPU_THREADS}", flush=True)
-        _model = WhisperModel(
-            MODEL_NAME,
-            device=WHISPER_DEVICE,
-            device_index=WHISPER_DEVICE_INDEX,
-            compute_type=COMPUTE,
-            cpu_threads=WHISPER_CPU_THREADS,
-        )
+        try:
+            _model = WhisperModel(
+                MODEL_NAME,
+                device=WHISPER_DEVICE,
+                device_index=WHISPER_DEVICE_INDEX,
+                compute_type=COMPUTE,
+                cpu_threads=WHISPER_CPU_THREADS,
+            )
+        except Exception as e:
+            # If GPU is selected/auto-selected but not available, some environments try to load
+            # CUDA/cuDNN and fail. Fall back to CPU automatically.
+            msg = str(e).lower()
+            gpu_markers = [
+                "cuda", "cublas", "cudnn", "hip", "rocm", "nvrtc", "gpu",
+                "unable to load any of {libcudnn", "cannot load symbol cudnncreatetensordescriptor",
+            ]
+            if WHISPER_DEVICE.lower() != "cpu" and any(m in msg for m in gpu_markers):
+                print(f"[whisper] model init failed on device '{WHISPER_DEVICE}': {e}. Falling back to CPU…", flush=True)
+                _model = WhisperModel(
+                    MODEL_NAME,
+                    device="cpu",
+                    device_index=0,
+                    compute_type=COMPUTE,
+                    cpu_threads=WHISPER_CPU_THREADS,
+                )
+            else:
+                raise
     return _model
 
 # --- Helper: Reset model with new device and device_index ---
@@ -191,8 +211,8 @@ def run_transcribe_with_fallback(wav_path: Path, lang):
     Try to transcribe with current model; on GPU/CUDA/HIP/ROCm/OOM errors, reset to CPU and retry once.
     Returns (segments, info) or raises exception.
     """
-    model = get_model()
     try:
+        model = get_model()
         return model.transcribe(str(wav_path), vad_filter=True, language=lang)
     except Exception as e:
         msg = str(e)