镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-05 22:16:49 +00:00
update dockerfiles
这个提交包含在：
binary-husky
44
.github/workflows/build-with-chatglm.yml
vendored
44
.github/workflows/build-with-chatglm.yml
vendored
@@ -1,44 +0,0 @@
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# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
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name: build-with-chatglm
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on:
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push:
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branches:
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- 'master'
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env:
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}_chatglm_moss
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jobs:
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build-and-push-image:
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runs-on: ubuntu-latest
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permissions:
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contents: read
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packages: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v3
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- name: Log in to the Container registry
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uses: docker/login-action@v2
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Extract metadata (tags, labels) for Docker
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id: meta
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uses: docker/metadata-action@v4
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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- name: Build and push Docker image
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uses: docker/build-push-action@v4
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with:
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context: .
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push: true
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file: docs/GithubAction+ChatGLM+Moss
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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@@ -1 +0,0 @@
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# 此Dockerfile不再维护，请前往docs/GithubAction+ChatGLM+Moss
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@@ -1 +0,0 @@
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# 此Dockerfile不再维护，请前往docs/GithubAction+NoLocal+Latex
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@@ -1,24 +1,37 @@
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# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
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# 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal .
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# 如何运行: docker run --rm -it --net=host gpt-academic-nolocal
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FROM python:3.11
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FROM ghcr.io/astral-sh/uv:python3.12-bookworm
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# 指定路径
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# 非必要步骤，更换pip源 （以下三行，可以删除）
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RUN echo '[global]' > /etc/pip.conf && \
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echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
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echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
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# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除）
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RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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apt-get update
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RUN apt-get install ffmpeg -y
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RUN apt-get clean
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# 进入工作路径（必要）
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WORKDIR /gpt
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# 装载项目文件
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# 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
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COPY requirements.txt ./
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RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
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ENV PATH="/gpt/.venv/bin:$PATH"
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RUN python -c 'import loguru'
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# 装载项目文件，安装剩余依赖（必要）
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COPY . .
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RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
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# 安装依赖
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RUN pip3 install -r requirements.txt
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# # 非必要步骤，用于预热模块（可以删除）
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RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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# edge-tts需要的依赖
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RUN apt update && apt install ffmpeg -y
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ENV CGO_ENABLED=0
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# 可选步骤，用于预热模块
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RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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RUN python3 -m pip cache purge && apt-get clean
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# 启动
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CMD ["python3", "-u", "main.py"]
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# 启动（必要）
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CMD ["bash", "-c", "python main.py"]
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@@ -1,25 +1,44 @@
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# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
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# 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal .
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# 如何运行: docker run --rm -it --net=host gpt-academic-nolocal
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FROM python:3.11
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# 此Dockerfile适用于“无本地模型”的迷你运行环境构建
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# 如果需要使用chatglm等本地模型或者latex运行依赖，请参考 docker-compose.yml
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# - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
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# - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
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# - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
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# 指定路径
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FROM ghcr.io/astral-sh/uv:python3.12-bookworm
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# 非必要步骤，更换pip源 （以下三行，可以删除）
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RUN echo '[global]' > /etc/pip.conf && \
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echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
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echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
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# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除）
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RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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apt-get update
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RUN apt-get install ffmpeg -y
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RUN apt-get clean
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# 进入工作路径（必要）
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WORKDIR /gpt
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# 装载项目文件
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# 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
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COPY requirements.txt ./
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RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
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RUN uv venv --python=3.12 && uv pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
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ENV PATH="/gpt/.venv/bin:$PATH"
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RUN python -c 'import loguru'
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# 装载项目文件，安装剩余依赖（必要）
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COPY . .
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RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
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# 安装依赖
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RUN pip3 install -r requirements.txt
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# # 非必要步骤，用于预热模块（可以删除）
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RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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# 安装语音插件的额外依赖
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RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
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ENV CGO_ENABLED=0
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# edge-tts需要的依赖
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RUN apt update && apt install ffmpeg -y
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# 可选步骤，用于预热模块
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RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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# 启动（必要）
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CMD ["bash", "-c", "python main.py"]
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# 启动
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CMD ["python3", "-u", "main.py"]
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@@ -1,31 +1,47 @@
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# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
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# 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal-vs -f docs/GithubAction+NoLocal+Vectordb .
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# 如何运行: docker run --rm -it --net=host gpt-academic-nolocal-vs
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FROM python:3.11
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# 此Dockerfile适用于“无本地模型”的迷你运行环境构建
|
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# 如果需要使用chatglm等本地模型或者latex运行依赖，请参考 docker-compose.yml
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# - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
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# - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
|
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# - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
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# 指定路径
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FROM ghcr.io/astral-sh/uv:python3.12-bookworm
|
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|
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# 非必要步骤，更换pip源 （以下三行，可以删除）
|
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RUN echo '[global]' > /etc/pip.conf && \
|
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echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
|
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echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
|
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|
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# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除）
|
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RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
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apt-get update
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RUN apt-get install ffmpeg -y
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RUN apt-get clean
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# 进入工作路径（必要）
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WORKDIR /gpt
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# 装载项目文件
|
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# 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
|
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COPY requirements.txt ./
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RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
|
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RUN uv venv --python=3.12 && uv pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
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RUN uv venv --python=3.12 && uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
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RUN uv venv --python=3.12 && uv pip install transformers protobuf langchain sentence-transformers faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
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RUN uv venv --python=3.12 && uv pip install unstructured[all-docs] --upgrade
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ENV PATH="/gpt/.venv/bin:$PATH"
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RUN python -c 'import loguru'
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# 装载项目文件，安装剩余依赖（必要）
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COPY . .
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RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
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|
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# 安装依赖
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RUN pip3 install -r requirements.txt
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# # 非必要步骤，用于预热模块（可以删除）
|
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RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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# 安装知识库插件的额外依赖
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RUN apt-get update && apt-get install libgl1 -y
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RUN pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu
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RUN pip3 install transformers protobuf langchain sentence-transformers faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
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RUN pip3 install unstructured[all-docs] --upgrade
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RUN python3 -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'
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|
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# edge-tts需要的依赖
|
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RUN apt update && apt install ffmpeg -y
|
||||
|
||||
# 可选步骤，用于预热模块
|
||||
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
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RUN python3 -m pip cache purge && apt-get clean
|
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ENV CGO_ENABLED=0
|
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|
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# 启动（必要）
|
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CMD ["bash", "-c", "python main.py"]
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|
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# 启动
|
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CMD ["python3", "-u", "main.py"]
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|
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