mirror of
				https://github.com/open-webui/open-webui
				synced 2025-06-26 18:26:48 +00:00 
			
		
		
		
	Replace pip3 with uv
				
					
				
			This commit is contained in:
		
							parent
							
								
									ac7bb03cb3
								
							
						
					
					
						commit
						748a930a5f
					
				| @ -93,15 +93,16 @@ RUN if [ "$USE_OLLAMA" = "true" ]; then \ | ||||
| # install python dependencies | ||||
| COPY ./backend/requirements.txt ./requirements.txt | ||||
| 
 | ||||
| RUN if [ "$USE_CUDA" = "true" ]; then \ | ||||
| RUN pip3 install uv && \ | ||||
|     if [ "$USE_CUDA" = "true" ]; then \ | ||||
|         # If you use CUDA the whisper and embedding model will be downloaded on first use | ||||
|         pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \ | ||||
|         pip3 install -r requirements.txt --no-cache-dir && \ | ||||
|         uv pip install --system -r requirements.txt --no-cache-dir && \ | ||||
|         python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])" && \ | ||||
|         python -c "import os; from chromadb.utils import embedding_functions; sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \ | ||||
|     else \ | ||||
|         pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \ | ||||
|         pip3 install -r requirements.txt --no-cache-dir && \ | ||||
|         uv pip install --system -r requirements.txt --no-cache-dir && \ | ||||
|         python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])" && \ | ||||
|         python -c "import os; from chromadb.utils import embedding_functions; sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \ | ||||
|     fi | ||||
|  | ||||
		Loading…
	
		Reference in New Issue
	
	Block a user