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59 lines
1.7 KiB
Docker
59 lines
1.7 KiB
Docker
# Base ML Image - Contains all heavy ML dependencies
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# This image is built once and reused by all ML services (svc-ocr, svc-rag-indexer, svc-rag-retriever)
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#
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# Build: docker build -t gitea.harkon.co.uk/harkon/base-ml:v1.0.1 -f infra/docker/base-ml.Dockerfile .
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# Push: docker push gitea.harkon.co.uk/harkon/base-ml:v1.0.1
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FROM python:3.12-slim as builder
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# Install build dependencies
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RUN apt-get update && apt-get install -y \
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build-essential \
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curl \
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git \
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&& rm -rf /var/lib/apt/lists/*
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# Create virtual environment
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RUN python -m venv /opt/venv
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ENV PATH="/opt/venv/bin:$PATH"
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# Copy requirements files
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COPY libs/requirements-base.txt /tmp/requirements-base.txt
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COPY libs/requirements-ml.txt /tmp/requirements-ml.txt
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# Install all dependencies (base + ML)
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RUN pip install --no-cache-dir --upgrade pip && \
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pip install --no-cache-dir -r /tmp/requirements-base.txt && \
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pip install --no-cache-dir -r /tmp/requirements-ml.txt
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# Final stage - Runtime image
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FROM python:3.12-slim
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# Install runtime dependencies
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RUN apt-get update && apt-get install -y \
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curl \
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&& rm -rf /var/lib/apt/lists/* \
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&& groupadd -r appuser \
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&& useradd -r -g appuser appuser
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# Copy virtual environment from builder
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COPY --from=builder /opt/venv /opt/venv
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# Set environment variables
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ENV PATH="/opt/venv/bin:$PATH" \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD python -c "import sentence_transformers; import transformers; print('ML base image healthy')"
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# Default user
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USER appuser
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# Label
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LABEL maintainer="AI Tax Agent Team" \
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description="Base ML image with sentence-transformers, PyTorch, and ML dependencies" \
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version="1.0.1"
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