zikai
00e2a95fb7
- 音频/视频转双语(英/中)SRT 字幕，Docker 容器化，CPU 开发/GPU 生产同一份代码 - faster-whisper ASR(词级时间戳) + 断句时间戳重算 + NLLB 翻译(模型不共驻) - 分片上传(断点续传) + SQLite 持久化 + 主页/历史/日志页面 - 历史页文件名搜索；缓存定时清理(默认保留7天，可配置) - 双 Dockerfile(cpu/gpu) + setup/start/stop 脚本
64 lines
2.6 KiB
Docker
64 lines
2.6 KiB
Docker
# audio2text — 一份 Dockerfile，CPU(dev) / GPU(prod) 双形态。
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# docker build --build-arg VARIANT=cpu -t audio2text:cpu .
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# docker build --build-arg VARIANT=gpu -t audio2text:gpu .
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# 区别仅在基础镜像与 torch 轮子；Python 依赖列表完全一致。
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ARG VARIANT=cpu
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FROM python:3.12-slim AS base-cpu
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# GPU 基础镜像带 CUDA 运行时，torch 可装 CUDA 轮子
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FROM nvidia/cuda:12.1.0-runtime-ubuntu22.04 AS base-gpu
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RUN apt-get update -y && apt-get install -y --no-install-recommends \
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python3.12 python3.12-venv python3.12-dev python3-pip \
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&& rm -rf /var/lib/apt/lists/* \
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&& ln -sf /usr/bin/python3.12 /usr/local/bin/python3 \
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&& ln -sf /usr/bin/python3.12 /usr/local/bin/python
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FROM base-${VARIANT} AS final
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ARG VARIANT
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ENV VARIANT=${VARIANT} \
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PYTHONUNBUFFERED=1 \
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PIP_NO_CACHE_DIR=1 \
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HF_HOME=/models/huggingface \
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CT2_CACHE=/models/ctranslate2
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# ffmpeg 是核心系统依赖，必须装
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RUN apt-get update -y && apt-get install -y --no-install-recommends \
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ffmpeg ca-certificates patchelf \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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COPY requirements.txt /app/requirements.txt
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# CPU 装 CPU 版 torch；GPU 走默认 index（带 CUDA 的轮子）
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RUN if [ "$VARIANT" = "cpu" ]; then \
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pip install --upgrade pip && \
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pip install torch --index-url https://download.pytorch.org/whl/cpu ; \
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else \
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pip install --upgrade pip && \
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pip install torch ; \
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fi
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RUN pip install -r /app/requirements.txt
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# ctranslate2 的 .so 带可执行栈标志（PT_GNU_STACK X），在某些内核 + Docker 组合下
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# 会触发 "cannot enable executable stack as shared object requires"。用 patchelf
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# 清掉该标志（改为 RW），无需放宽容器安全策略。
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# 注意：库在 ctranslate2.libs/ 隐藏目录（pip wheel 拆分产物），不在 ctranslate2/ 包目录。
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RUN for d in /usr/local/lib/python3.12/site-packages/ctranslate2.libs \
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/usr/local/lib/python3.12/site-packages/ctranslate2; do \
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[ -d "$d" ] && find "$d" -name '*.so*' \
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-exec patchelf --clear-execstack {} \; 2>/dev/null || true; \
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done; \
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python -c "import ctranslate2; print('ctranslate2 stack fix verified', ctranslate2.__version__)"
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COPY app /app/app
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COPY config.example.yaml /app/config.example.yaml
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# 运行时数据：上传 / 中间产物 / 输出字幕 / 模型缓存
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# 全部走 volume，镜像本身无状态、无敏感数据
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VOLUME ["/data", "/models"]
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ENV CONFIG_PATH=/app/config.yaml
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EXPOSE 8000
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CMD ["python", "-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
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