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02e3e1d
1 Parent(s): a9e9e79

fix dockerfile

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  1. docs/Dockerfile+ChatGLM +11 -11
docs/Dockerfile+ChatGLM CHANGED
@@ -1,6 +1,6 @@
1
  # How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
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- # How to run | 如何运行 (1) 直接运行: docker run --rm -it --net=host --gpus=all gpt-academic
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- # How to run | 如何运行 (2) 我想运行之前进容器做一些调整: docker run --rm -it --net=host --gpus=all gpt-academic bash
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  # 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
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  FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
@@ -11,11 +11,11 @@ RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
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  # 配置代理网络(构建Docker镜像时使用)
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  # # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
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- # RUN $useProxyNetwork curl cip.cc
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- # RUN sed -i '$ d' /etc/proxychains.conf
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- # RUN sed -i '$ d' /etc/proxychains.conf
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- # RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
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- # ARG useProxyNetwork=proxychains
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  # # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
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@@ -24,7 +24,7 @@ RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
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  # 下载分支
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  WORKDIR /gpt
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- RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git -b v3.1
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  WORKDIR /gpt/chatgpt_academic
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  RUN $useProxyNetwork python3 -m pip install -r requirements.txt
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  RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
@@ -45,14 +45,14 @@ RUN $useProxyNetwork git pull
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  RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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  # 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
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- # 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey1,fkxxxx-api2dkey2"
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  # LLM_MODEL 是选择初始的模型
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  # LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
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  RUN echo ' \n\
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- API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
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  USE_PROXY = True \n\
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  LLM_MODEL = "chatglm" \n\
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- LOCAL_MODEL_DEVICE = "cpu" \n\
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  proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
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  # 启动
 
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  # How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
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+ # How to run | 如何运行 (1) 直接运行(选择0号GPU): docker run --rm -it --net=host --gpus="0" gpt-academic
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+ # How to run | 如何运行 (2) 我想运行之前进容器做一些调整: docker run --rm -it --net=host --gpus="0" gpt-academic bash
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  # 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
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  FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
 
11
 
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  # 配置代理网络(构建Docker镜像时使用)
13
  # # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
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+ RUN $useProxyNetwork curl cip.cc
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+ RUN sed -i '$ d' /etc/proxychains.conf
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+ RUN sed -i '$ d' /etc/proxychains.conf
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+ RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
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+ ARG useProxyNetwork=proxychains
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  # # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
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  # 下载分支
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  WORKDIR /gpt
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+ RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git
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  WORKDIR /gpt/chatgpt_academic
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  RUN $useProxyNetwork python3 -m pip install -r requirements.txt
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  RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
 
45
  RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
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  # 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
48
+ # 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
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  # LLM_MODEL 是选择初始的模型
50
  # LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
51
  RUN echo ' \n\
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+ API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
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  USE_PROXY = True \n\
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  LLM_MODEL = "chatglm" \n\
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+ LOCAL_MODEL_DEVICE = "cuda" \n\
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  proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
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  # 启动