🚀 chore (docker): update docker images improving caching and using uv as python package manager
This commit is contained in:
jedzill4
parent
994ce21365
commit
d24805cc18
4 changed files with 178 additions and 113 deletions
13
.dockerignore
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.dockerignore
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.git
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.github
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.venv
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__pycache__
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*.pyc
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.pytest_cache
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.mypy_cache
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.ruff_cache
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.cache
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.tmp
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.secrets
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dist
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build
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124
Dockerfile
124
Dockerfile
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@ -1,86 +1,74 @@
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FROM nvidia/cuda:12.9.1-cudnn-devel-ubuntu24.04
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FROM ghcr.io/astral-sh/uv:0.10.4 AS uvbin
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# --- MARK: Builder Stage
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FROM nvidia/cuda:12.9.1-cudnn-devel-ubuntu24.04 AS builder-gpu
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ENV DEBIAN_FRONTEND=noninteractive
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONUNBUFFERED=1
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WORKDIR /app
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WORKDIR /app
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ARG EXTRAS
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RUN apt-get update && \
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ARG HF_PRECACHE_DIR
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apt-get install -y --no-install-recommends \
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ARG HF_TKN_FILE
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build-essential \
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python3-dev && \
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rm -rf /var/lib/apt/lists/*
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# Install UV and set up the environment
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COPY --from=uvbin /uv /uvx /bin/
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ENV UV_COMPILE_BYTECODE=1 UV_LINK_MODE=copy UV_NO_DEV=1
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ENV UV_PYTHON_PREFERENCE=only-managed
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ENV UV_PYTHON_INSTALL_DIR=/python
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RUN uv python install 3.12
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# Install dependencies first to leverage caching
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ARG EXTRAS=gpu-cu129
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COPY pyproject.toml uv.lock /app/
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RUN set -eux; \
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set --; \
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for extra in $(echo "${EXTRAS:-}" | tr ',' ' '); do \
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set -- "$@" --extra "$extra"; \
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done; \
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uv sync --frozen --no-install-project --no-editable --no-cache "$@"
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# Copy the source code and install the package only
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COPY whisperlivekit /app/whisperlivekit
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RUN set -eux; \
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set --; \
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for extra in $(echo "${EXTRAS:-}" | tr ',' ' '); do \
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set -- "$@" --extra "$extra"; \
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done; \
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uv sync --frozen --no-editable --no-cache "$@"
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# --- MARK: Runtime Stage
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FROM nvidia/cuda:12.9.1-cudnn-devel-ubuntu24.04
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ENV DEBIAN_FRONTEND=noninteractive
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WORKDIR /app
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RUN apt-get update && \
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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apt-get install -y --no-install-recommends \
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python3 \
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ffmpeg &&\
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python3-pip \
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rm -rf /var/lib/apt/lists/*
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python3-venv \
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ffmpeg \
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git \
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build-essential \
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python3-dev \
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ca-certificates && \
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rm -rf /var/lib/apt/lists/*
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RUN python3 -m venv /opt/venv
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# Copy UV binaries
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ENV PATH="/opt/venv/bin:$PATH"
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COPY --from=uvbin /uv /uvx /bin/
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# timeout/retries for large torch wheels
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# Copy the Python version
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RUN pip3 install --upgrade pip setuptools wheel && \
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COPY --from=builder-gpu --chown=python:python /python /python
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pip3 --disable-pip-version-check install --timeout=120 --retries=5 \
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--index-url https://download.pytorch.org/whl/cu129 \
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torch torchaudio \
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|| (echo "Initial install failed — retrying with extended timeout..." && \
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pip3 --disable-pip-version-check install --timeout=300 --retries=3 \
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--index-url https://download.pytorch.org/whl/cu129 \
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torch torchvision torchaudio)
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COPY . .
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# Copy the virtual environment with all dependencies installed
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COPY --from=builder-gpu /app/.venv /app/.venv
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# Install WhisperLiveKit directly, allowing for optional dependencies
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# Example: --build-arg EXTRAS="translation"
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RUN if [ -n "$EXTRAS" ]; then \
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echo "Installing with extras: [$EXTRAS]"; \
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pip install --no-cache-dir "whisperlivekit[$EXTRAS]"; \
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else \
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echo "Installing base package only"; \
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pip install --no-cache-dir whisperlivekit; \
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fi
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# In-container caching for Hugging Face models by:
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# A) Make the cache directory persistent via an anonymous volume.
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# Note: This only persists for a single, named container. This is
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# only for convenience at de/test stage.
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# For prod, it is better to use a named volume via host mount/k8s.
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VOLUME ["/root/.cache/huggingface/hub"]
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# or
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# B) Conditionally copy a local pre-cache from the build context to the
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# container's cache via the HF_PRECACHE_DIR build-arg.
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# WARNING: This will copy ALL files in the pre-cache location.
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# Conditionally copy a cache directory if provided
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RUN if [ -n "$HF_PRECACHE_DIR" ]; then \
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echo "Copying Hugging Face cache from $HF_PRECACHE_DIR"; \
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mkdir -p /root/.cache/huggingface/hub && \
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cp -r $HF_PRECACHE_DIR/* /root/.cache/huggingface/hub; \
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else \
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echo "No local Hugging Face cache specified, skipping copy"; \
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fi
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# Conditionally copy a Hugging Face token if provided. Useful for Diart backend (pyannote audio models)
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RUN if [ -n "$HF_TKN_FILE" ]; then \
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echo "Copying Hugging Face token from $HF_TKN_FILE"; \
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mkdir -p /root/.cache/huggingface && \
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cp $HF_TKN_FILE /root/.cache/huggingface/token; \
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else \
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echo "No Hugging Face token file specified, skipping token setup"; \
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fi
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EXPOSE 8000
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EXPOSE 8000
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ENV PATH="/app/.venv/bin:$PATH"
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ENV UV_PYTHON_DOWNLOADS=0
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HEALTHCHECK --interval=30s --timeout=5s --start-period=120s --retries=3 \
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HEALTHCHECK --interval=30s --timeout=5s --start-period=120s --retries=3 \
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CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/')" || exit 1
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/')" || exit 1
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ENTRYPOINT ["whisperlivekit-server", "--host", "0.0.0.0"]
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ENTRYPOINT ["whisperlivekit-server", "--host", "0.0.0.0"]
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102
Dockerfile.cpu
102
Dockerfile.cpu
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@ -1,64 +1,76 @@
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FROM python:3.13-slim
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FROM ghcr.io/astral-sh/uv:0.10.4 AS uvbin
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# --- MARK: Builder Stage
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FROM debian:bookworm-slim AS builder-cpu
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ENV DEBIAN_FRONTEND=noninteractive
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONUNBUFFERED=1
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WORKDIR /app
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WORKDIR /app
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ARG EXTRAS
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RUN apt-get update && \
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ARG HF_PRECACHE_DIR
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apt-get install -y --no-install-recommends \
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ARG HF_TKN_FILE
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build-essential \
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python3-dev && \
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rm -rf /var/lib/apt/lists/*
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# Install UV and set up the environment
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COPY --from=uvbin /uv /uvx /bin/
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ENV UV_COMPILE_BYTECODE=1 UV_LINK_MODE=copy UV_NO_DEV=1
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ENV UV_PYTHON_PREFERENCE=only-managed
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ENV UV_PYTHON_INSTALL_DIR=/python
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RUN uv python install 3.12
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# Install dependencies first to leverage caching
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ARG EXTRAS=cpu
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COPY pyproject.toml uv.lock /app/
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RUN set -eux; \
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set --; \
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for extra in $(echo "${EXTRAS:-}" | tr ',' ' '); do \
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set -- "$@" --extra "$extra"; \
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done; \
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uv sync --frozen --no-install-project --no-editable --no-cache "$@"
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# Copy the source code and install the package only
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COPY whisperlivekit /app/whisperlivekit
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RUN set -eux; \
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set --; \
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for extra in $(echo "${EXTRAS:-}" | tr ',' ' '); do \
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set -- "$@" --extra "$extra"; \
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done; \
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uv sync --frozen --no-editable --no-cache "$@"
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# --- MARK: Runtime Stage
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FROM debian:bookworm-slim
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ENV DEBIAN_FRONTEND=noninteractive
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WORKDIR /app
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RUN apt-get update && \
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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apt-get install -y --no-install-recommends \
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ffmpeg \
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ffmpeg &&\
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git \
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rm -rf /var/lib/apt/lists/*
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build-essential \
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python3-dev && \
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rm -rf /var/lib/apt/lists/*
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# Install CPU-only PyTorch
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# Copy UV binaries
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RUN pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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COPY --from=uvbin /uv /uvx /bin/
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COPY . .
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# Copy the Python version
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COPY --from=builder-cpu --chown=python:python /python /python
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# Install WhisperLiveKit directly, allowing for optional dependencies
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# Copy the virtual environment with all dependencies installed
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RUN if [ -n "$EXTRAS" ]; then \
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COPY --from=builder-cpu /app/.venv /app/.venv
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echo "Installing with extras: [$EXTRAS]"; \
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pip install --no-cache-dir whisperlivekit[$EXTRAS]; \
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else \
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echo "Installing base package only"; \
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pip install --no-cache-dir whisperlivekit; \
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fi
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# Enable in-container caching for Hugging Face models
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VOLUME ["/root/.cache/huggingface/hub"]
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# Conditionally copy a local pre-cache from the build context
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RUN if [ -n "$HF_PRECACHE_DIR" ]; then \
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echo "Copying Hugging Face cache from $HF_PRECACHE_DIR"; \
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mkdir -p /root/.cache/huggingface/hub && \
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cp -r $HF_PRECACHE_DIR/* /root/.cache/huggingface/hub; \
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else \
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echo "No local Hugging Face cache specified, skipping copy"; \
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fi
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# Conditionally copy a Hugging Face token if provided
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RUN if [ -n "$HF_TKN_FILE" ]; then \
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echo "Copying Hugging Face token from $HF_TKN_FILE"; \
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mkdir -p /root/.cache/huggingface && \
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cp $HF_TKN_FILE /root/.cache/huggingface/token; \
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else \
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echo "No Hugging Face token file specified, skipping token setup"; \
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fi
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# Expose port for the transcription server
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EXPOSE 8000
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EXPOSE 8000
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ENV PATH="/app/.venv/bin:$PATH"
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ENV UV_PYTHON_DOWNLOADS=0
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HEALTHCHECK --interval=30s --timeout=5s --start-period=120s --retries=3 \
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HEALTHCHECK --interval=30s --timeout=5s --start-period=120s --retries=3 \
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CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/')" || exit 1
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/')" || exit 1
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ENTRYPOINT ["whisperlivekit-server", "--host", "0.0.0.0"]
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ENTRYPOINT ["whisperlivekit-server", "--host", "0.0.0.0"]
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# Default args - you might want to use a smaller model for CPU
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# Default args - you might want to use a smaller model for CPU
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CMD ["--model", "tiny"]
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CMD ["--model", "tiny"]
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52
compose.yml
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52
compose.yml
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services:
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wlk-gpu-sortformer:
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build:
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context: .
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dockerfile: Dockerfile
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args:
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EXTRAS: ${GPU_SORTFORMER_EXTRAS:-gpu-cu129,diarization-sortformer}
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image: wlk:gpu-sortformer
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gpus: all
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ports:
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- "8000:8000"
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volumes:
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- hf-cache:/root/.cache/huggingface/hub
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# - ${HF_TKN_FILE:-./token}:/root/.cache/huggingface/token:ro
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environment:
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- HF_TOKEN
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command: ["--model", "medium", "--diarization", "--pcm-input"]
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wlk-gpu-voxtral:
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build:
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context: .
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dockerfile: Dockerfile
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args:
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EXTRAS: ${GPU_VOXTRAL_EXTRAS:-gpu-cu129,voxtral-hf,translation}
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image: wlk:gpu-voxtral
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gpus: all
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ports:
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- "8001:8000"
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volumes:
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- hf-cache:/root/.cache/huggingface/hub
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# - ${HF_TKN_FILE:-./token}:/root/.cache/huggingface/token:ro
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environment:
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- HF_TOKEN
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command: ["--backend", "voxtral", "--pcm-input"]
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wlk-cpu:
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build:
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context: .
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dockerfile: Dockerfile.cpu
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args:
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EXTRAS: ${CPU_EXTRAS:-cpu,diarization-diart,translation}
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image: wlk:cpu
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ports:
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- "8000:8000"
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volumes:
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- hf-cache:/root/.cache/huggingface/hub
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# - ${HF_TKN_FILE:-./token}:/root/.cache/huggingface/token:ro
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environment:
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- HF_TOKEN
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volumes:
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hf-cache:
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