47 lines
1.4 KiB
Docker
47 lines
1.4 KiB
Docker
ARG WORKER_CUDA_VERSION=11.8.0
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FROM runpod/worker-vllm:base-0.2.2-cuda${WORKER_CUDA_VERSION} AS vllm-base
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RUN apt-get update -y \
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&& apt-get install -y python3-pip
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# Install Python dependencies
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COPY builder/requirements.txt /requirements.txt
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RUN --mount=type=cache,target=/root/.cache/pip \
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python3 -m pip install --upgrade pip && \
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python3 -m pip install --upgrade -r /requirements.txt
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# Add source files
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COPY src /src
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# Setup for Option 2: Building the Image with the Model included
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ARG MODEL_NAME=""
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ARG TOKENIZER_NAME=""
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ARG BASE_PATH="/runpod-volume"
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ARG QUANTIZATION=""
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ARG MODEL_REVISION="main"
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ARG TOKENIZER_REVISION="main"
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ENV MODEL_NAME=$MODEL_NAME \
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MODEL_REVISION=$REVISION \
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TOKENIZER_NAME=$TOKENIZER_NAME \
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TOKENIZER_REVISION=$TOKENIZER_REVISION \
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BASE_PATH=$BASE_PATH \
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QUANTIZATION=$QUANTIZATION \
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HF_DATASETS_CACHE="${BASE_PATH}/huggingface-cache/datasets" \
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HUGGINGFACE_HUB_CACHE="${BASE_PATH}/huggingface-cache/hub" \
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HF_HOME="${BASE_PATH}/huggingface-cache/hub" \
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HF_TRANSFER=1
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ENV PYTHONPATH="/:/vllm-installation"
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RUN --mount=type=secret,id=HF_TOKEN,required=false \
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if [ -f /run/secrets/HF_TOKEN ]; then \
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export HF_TOKEN=$(cat /run/secrets/HF_TOKEN); \
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fi && \
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if [ -n "$MODEL_NAME" ]; then \
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python3 /src/download_model.py; \
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fi
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# Start the handler
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CMD ["python3", "/src/handler.py"]
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