41 lines
1.6 KiB
Docker
41 lines
1.6 KiB
Docker
FROM python:3.12-slim AS base
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# uv binary, pinned via digest-less tag (see astral-sh/uv releases)
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /usr/local/bin/
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WORKDIR /app
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ENV UV_COMPILE_BYTECODE=1 \
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UV_LINK_MODE=copy \
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PYTHONUNBUFFERED=1
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# Экстра-группа `gpu` (ADR-004: cuBLAS/cuDNN9 для FasterWhisperGPU,
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# `core/plugins/faster_whisper.py`) — ставится ТОЛЬКО в GPU-образе воркера
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# транскрибации (deploy/docker-compose.yml, сервис `worker-transcriber-gpu`,
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# `build.args.WITH_GPU_EXTRA: "true"`, профиль `transcribe-gpu`); базовый
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# CPU-образ backend/worker/worker-transcriber собирается с дефолтом "false"
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# — не тянет нативные CUDA-библиотеки туда, где GPU нет.
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ARG WITH_GPU_EXTRA=false
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# Install dependencies first (better layer caching), then copy source.
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COPY pyproject.toml uv.lock ./
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RUN if [ "$WITH_GPU_EXTRA" = "true" ]; then \
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uv sync --frozen --no-dev --no-install-project --extra gpu; \
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else \
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uv sync --frozen --no-dev --no-install-project; \
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fi
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COPY . .
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RUN if [ "$WITH_GPU_EXTRA" = "true" ]; then \
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uv sync --frozen --no-dev --extra gpu; \
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else \
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uv sync --frozen --no-dev; \
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fi
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EXPOSE 8000
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HEALTHCHECK --interval=10s --timeout=5s --retries=10 --start-period=15s \
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/api/health')" || exit 1
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CMD ["uv", "run", "uvicorn", "main:create_app", "--factory", "--host", "0.0.0.0", "--port", "8000"]
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