63 lines
2.0 KiB
Docker
63 lines
2.0 KiB
Docker
FROM nvidia/cuda:12.9.1-base-ubuntu22.04
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RUN apt-get update -y \
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&& apt-get install -y python3-pip
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RUN ldconfig /usr/local/cuda-12.9/compat/
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ENV RAY_METRICS_EXPORT_ENABLED=0 \
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RAY_DISABLE_USAGE_STATS=1 \
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TOKENIZERS_PARALLELISM=false \
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RAYON_NUM_THREADS=4
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# Install vLLM first to avoid PyTorch version conflicts
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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 "vllm[flashinfer]==0.15.0" --extra-index-url https://download.pytorch.org/whl/cu129
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# Install remaining 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 -r /requirements.txt
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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=""
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ARG TOKENIZER_REVISION=""
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ARG VLLM_NIGHTLY="false"
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ENV MODEL_NAME=$MODEL_NAME \
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MODEL_REVISION=$MODEL_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="${BASE_PATH}/huggingface-cache/hub" \
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HF_HUB_ENABLE_HF_TRANSFER=0
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ENV PYTHONPATH="/:/vllm-workspace"
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RUN if [ -n "${VLLM_NIGHTLY}" ]; then \
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pip install -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly && \
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apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/* && \
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pip install git+https://github.com/huggingface/transformers.git; \
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fi
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COPY src /src
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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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