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avoid silent failure of pip/uv install in Dockerfile (#22598)

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Jan Kessler
2026-03-11 15:40:54 -05:00
committed by GitHub
parent 4a8f995c3f
commit 1b1abdd30c
1 changed files with 11 additions and 10 deletions
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@@ -135,29 +135,30 @@ RUN apt-get update && \
# install python dependencies # install python dependencies
COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt
RUN pip3 install --no-cache-dir uv && \ RUN set -e; \
pip3 install --no-cache-dir uv; \
if [ "$USE_CUDA" = "true" ]; then \ if [ "$USE_CUDA" = "true" ]; then \
# If you use CUDA the whisper and embedding model will be downloaded on first use # If you use CUDA the whisper and embedding model will be downloaded on first use
# fix: pin torch<=2.9.1 - torch 2.10.0 aarch64 wheels cause SIGILL on ARM devices (RPi 4 Cortex-A72) #21349 # fix: pin torch<=2.9.1 - torch 2.10.0 aarch64 wheels cause SIGILL on ARM devices (RPi 4 Cortex-A72) #21349
pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \ pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir; \
uv pip install --system -r requirements.txt --no-cache-dir && \ uv pip install --system -r requirements.txt --no-cache-dir; \
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \ python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')" && \ python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')"; \
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 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; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \ python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
python -c "import nltk; nltk.download('punkt_tab')"; \ python -c "import nltk; nltk.download('punkt_tab')"; \
else \ else \
pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \ pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir; \
uv pip install --system -r requirements.txt --no-cache-dir && \ uv pip install --system -r requirements.txt --no-cache-dir; \
if [ "$USE_SLIM" != "true" ]; then \ if [ "$USE_SLIM" != "true" ]; then \
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \ python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \
python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')" && \ python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')"; \
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 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; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \ python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
python -c "import nltk; nltk.download('punkt_tab')"; \ python -c "import nltk; nltk.download('punkt_tab')"; \
fi; \ fi; \
fi; \ fi; \
mkdir -p /app/backend/data && chown -R $UID:$GID /app/backend/data/ && \ mkdir -p /app/backend/data; chown -R $UID:$GID /app/backend/data/; \
rm -rf /var/lib/apt/lists/*; rm -rf /var/lib/apt/lists/*;
# Install Ollama if requested # Install Ollama if requested