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	# How to build \| 如何构建: docker build -t gpt-academic-jittor --network=host -f Dockerfile+ChatGLM .
	# How to run \| (1) 我想直接一键运行（选择0号GPU）: docker run --rm -it --net=host --gpus \"device=0\" gpt-academic-jittor bash
	# How to run \| (2) 我想运行之前进容器做一些调整（选择1号GPU）: docker run --rm -it --net=host --gpus \"device=1\" gpt-academic-jittor bash

	# 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）
	FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
	ARG useProxyNetwork=''
	RUN apt-get update
	RUN apt-get install -y curl proxychains curl g++
	RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing

	# 配置代理网络（构建Docker镜像时使用）
	# # comment out below if you do not need proxy network \| 如果不需要翻墙 - 从此行向下删除
	RUN $useProxyNetwork curl cip.cc
	RUN sed -i '$ d' /etc/proxychains.conf
	RUN sed -i '$ d' /etc/proxychains.conf
	# 在这里填写主机的代理协议（用于从github拉取代码）
	RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
	ARG useProxyNetwork=proxychains
	# # comment out above if you do not need proxy network \| 如果不需要翻墙 - 从此行向上删除


	# use python3 as the system default python
	RUN curl -sS https://bootstrap.pypa.io/get-pip.py \| python3.8
	# 下载pytorch
	RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
	# 下载分支
	WORKDIR /gpt
	RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git -b jittor
	WORKDIR /gpt/chatgpt_academic
	RUN $useProxyNetwork python3 -m pip install -r requirements.txt
	RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
	RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
	RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I

	# 下载JittorLLMs
	RUN $useProxyNetwork git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llm/jittorllms

	# 禁用缓存，确保更新代码
	ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
	RUN $useProxyNetwork git pull

	# 预热Tiktoken模块
	RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'

	# 为chatgpt-academic配置代理和API-KEY （非必要可选步骤）
	# 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,........"
	# LLM_MODEL 是选择初始的模型
	# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备，可选 cpu 和 cuda
	# [说明: 以下内容与`config.py`一一对应，请查阅config.py来完成一下配置的填写]
	RUN echo ' \n\
	API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
	USE_PROXY = True \n\
	LLM_MODEL = "chatglm" \n\
	LOCAL_MODEL_DEVICE = "cuda" \n\
	proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py

	# 启动
	CMD ["python3", "-u", "main.py"]