- Switch default TTS engine from Piper to Qwen3-TTS (1.7B params) - Upgrade to Python 3.12 - Add docker-compose.cpu.yml for CPU-only deployments - Improve GPU configuration with NVIDIA environment variables - Comment out optional engines (Piper, XTTS, Silero, Kokoro) in requirements - Update Makefile with local/local-cpu targets and venv support - Simplify voice_to_speaker.default.yaml for Qwen3-TTS voices - Update docs/MODELS.md with Qwen3-TTS documentation - Add git commit guidelines to CLAUDE.md
45 lines
1.3 KiB
Docker
45 lines
1.3 KiB
Docker
FROM python:3.12-slim
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RUN --mount=type=cache,target=/root/.cache/pip pip install -U pip
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ARG TARGETPLATFORM
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RUN <<EOF
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apt-get update
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apt-get install --no-install-recommends -y curl ffmpeg git
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if [ "$TARGETPLATFORM" != "linux/amd64" ]; then
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apt-get install --no-install-recommends -y build-essential
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curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
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fi
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# for deepspeed support - image +7.5GB, over the 10GB ghcr.io limit, and no noticable gain in speed or VRAM usage?
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#curl -O https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.1-1_all.deb
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#dpkg -i cuda-keyring_1.1-1_all.deb
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#rm cuda-keyring_1.1-1_all.deb
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#apt-get install --no-install-recommends -y libaio-dev build-essential cuda-toolkit
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apt-get clean
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rm -rf /var/lib/apt/lists/*
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EOF
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#ENV CUDA_HOME=/usr/local/cuda
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ENV PATH="/root/.cargo/bin:${PATH}"
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WORKDIR /app
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RUN mkdir -p voices config
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ARG USE_ROCM
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ENV USE_ROCM=${USE_ROCM}
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COPY requirements*.txt /app/
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RUN if [ "${USE_ROCM}" = "1" ]; then mv /app/requirements-rocm.txt /app/requirements.txt; fi
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RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt
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COPY *.py *.sh *.default.yaml README.md LICENSE /app/
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COPY scripts/ /app/scripts/
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ARG PRELOAD_MODEL
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ENV PRELOAD_MODEL=${PRELOAD_MODEL}
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ENV TTS_HOME=voices
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ENV HF_HOME=voices
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ENV COQUI_TOS_AGREED=1
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CMD bash startup.sh
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