Fix: Use openai-whisper library for model loading instead of torch.hub

Dockerfile

@@ -19,7 +19,7 @@ RUN pip install --no-cache-dir -r requirements.txt
 COPY . .
 
 # Pre-descargar el modelo durante la construcción
-RUN python -c "import torch; torch.hub.load('openai/whisper', 'large-v3')"
+RUN python -c "import whisper; whisper.load_model('large-v3')" || echo "Model download skipped, will download at runtime"
 
 EXPOSE 7860
 

requirements.txt

@@ -10,3 +10,4 @@ torchaudio>=2.0.0
 tqdm
 tiktoken
 triton>=2.0.0,<3;platform_machine=="x86_64" and sys_platform=="linux" or sys_platform=="linux2"
+openai-whisper>=20230314

server_wrapper.py

@@ -17,13 +17,25 @@ _online = None
 def _get_model_path():
     """Get the path to the Whisper model. Download if needed."""
     import os
-    model_dir = os.path.expanduser('~/.cache/torch/hub/checkpoints')
+    model_dir = os.path.expanduser('~/.cache/whisper')
+    
+    # Create model directory if it doesn't exist
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir, exist_ok=True)
+    
     model_path = os.path.join(model_dir, 'large-v3.pt')
     
     if not os.path.exists(model_path):
         print(f"Model not found at {model_path}. Downloading...")
-        import torch
-        torch.hub.load('openai/whisper', 'large-v3')
+        try:
+            import whisper
+            whisper.load_model('large-v3')
+            print(f"Model downloaded to {model_path}")
+        except Exception as e:
+            print(f"Warning: Could not download model: {e}")
+            # Fallback to trying current directory
+            if os.path.exists('./large-v3.pt'):
+                return './large-v3.pt'
     
     return model_path