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- ## ===================================================
- # docker-compose.yml
- ## ===================================================
- # 1. 请在以下方案中选择任意一种,然后删除其他的方案
- # 2. 修改你选择的方案中的environment环境变量,详情请见github wiki或者config.py
- # 3. 选择一种暴露服务端口的方法,并对相应的配置做出修改:
- # 【方法1: 适用于Linux,很方便,可惜windows不支持】与宿主的网络融合为一体,这个是默认配置
- # network_mode: "host"
- # 【方法2: 适用于所有系统包括Windows和MacOS】端口映射,把容器的端口映射到宿主的端口(注意您需要先删除network_mode: "host",再追加以下内容)
- # ports:
- # - "12345:12345" # 注意!12345必须与WEB_PORT环境变量相互对应
- # 4. 最后`docker-compose up`运行
- # 5. 如果希望使用显卡,请关注 LOCAL_MODEL_DEVICE 和 英伟达显卡运行时 选项
- ## ===================================================
- # 1. Please choose one of the following options and delete the others.
- # 2. Modify the environment variables in the selected option, see GitHub wiki or config.py for more details.
- # 3. Choose a method to expose the server port and make the corresponding configuration changes:
- # [Method 1: Suitable for Linux, convenient, but not supported for Windows] Fusion with the host network, this is the default configuration
- # network_mode: "host"
- # [Method 2: Suitable for all systems including Windows and MacOS] Port mapping, mapping the container port to the host port (note that you need to delete network_mode: "host" first, and then add the following content)
- # ports:
- # - "12345: 12345" # Note! 12345 must correspond to the WEB_PORT environment variable.
- # 4. Finally, run `docker-compose up`.
- # 5. If you want to use a graphics card, pay attention to the LOCAL_MODEL_DEVICE and Nvidia GPU runtime options.
- ## ===================================================
- ## ===================================================
- ## 【方案零】 部署项目的全部能力(这个是包含cuda和latex的大型镜像。如果您网速慢、硬盘小或没有显卡,则不推荐使用这个)
- ## ===================================================
- version: '3'
- services:
- gpt_academic_full_capability:
- image: ghcr.io/binary-husky/gpt_academic_with_all_capacity:master
- environment:
- # 请查阅 `config.py`或者 github wiki 以查看所有的配置信息
- API_KEY: ' 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 '
- # USE_PROXY: ' True '
- # proxies: ' { "http": "http://localhost:10881", "https": "http://localhost:10881", } '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "gpt-4", "qianfan", "sparkv2", "spark", "chatglm"] '
- BAIDU_CLOUD_API_KEY : ' bTUtwEAveBrQipEowUvDwYWq '
- BAIDU_CLOUD_SECRET_KEY : ' jqXtLvXiVw6UNdjliATTS61rllG8Iuni '
- XFYUN_APPID: ' 53a8d816 '
- XFYUN_API_SECRET: ' MjMxNDQ4NDE4MzM0OSNlNjQ2NTlhMTkx '
- XFYUN_API_KEY: ' 95ccdec285364869d17b33e75ee96447 '
- ENABLE_AUDIO: ' False '
- DEFAULT_WORKER_NUM: ' 20 '
- WEB_PORT: ' 12345 '
- ADD_WAIFU: ' False '
- ALIYUN_APPKEY: ' RxPlZrM88DnAFkZK '
- THEME: ' Chuanhu-Small-and-Beautiful '
- ALIYUN_ACCESSKEY: ' LTAI5t6BrFUzxRXVGUWnekh1 '
- ALIYUN_SECRET: ' eHmI20SVWIwQZxCiTD2bGQVspP9i68 '
- # LOCAL_MODEL_DEVICE: ' cuda '
- # 加载英伟达显卡运行时
- # runtime: nvidia
- # deploy:
- # resources:
- # reservations:
- # devices:
- # - driver: nvidia
- # count: 1
- # capabilities: [gpu]
- # 【WEB_PORT暴露方法1: 适用于Linux】与宿主的网络融合
- network_mode: "host"
- # 【WEB_PORT暴露方法2: 适用于所有系统】端口映射
- # ports:
- # - "12345:12345" # 12345必须与WEB_PORT相互对应
- # 启动容器后,运行main.py主程序
- command: >
- bash -c "python3 -u main.py"
- ## ===================================================
- ## 【方案一】 如果不需要运行本地模型(仅 chatgpt, azure, 星火, 千帆, claude 等在线大模型服务)
- ## ===================================================
- version: '3'
- services:
- gpt_academic_nolocalllms:
- image: ghcr.io/binary-husky/gpt_academic_nolocal:master # (Auto Built by Dockerfile: docs/GithubAction+NoLocal)
- environment:
- # 请查阅 `config.py` 以查看所有的配置信息
- API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
- USE_PROXY: ' True '
- proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "sparkv2", "qianfan"] '
- WEB_PORT: ' 22303 '
- ADD_WAIFU: ' True '
- # THEME: ' Chuanhu-Small-and-Beautiful '
- # DEFAULT_WORKER_NUM: ' 10 '
- # AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
- # 与宿主的网络融合
- network_mode: "host"
- # 不使用代理网络拉取最新代码
- command: >
- bash -c "python3 -u main.py"
- ### ===================================================
- ### 【方案二】 如果需要运行ChatGLM + Qwen + MOSS等本地模型
- ### ===================================================
- version: '3'
- services:
- gpt_academic_with_chatglm:
- image: ghcr.io/binary-husky/gpt_academic_chatglm_moss:master # (Auto Built by Dockerfile: docs/Dockerfile+ChatGLM)
- environment:
- # 请查阅 `config.py` 以查看所有的配置信息
- API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
- USE_PROXY: ' True '
- proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["chatglm", "qwen", "moss", "gpt-3.5-turbo", "gpt-4", "newbing"] '
- LOCAL_MODEL_DEVICE: ' cuda '
- DEFAULT_WORKER_NUM: ' 10 '
- WEB_PORT: ' 12303 '
- ADD_WAIFU: ' True '
- # AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
- # 显卡的使用,nvidia0指第0个GPU
- runtime: nvidia
- devices:
- - /dev/nvidia0:/dev/nvidia0
- # 与宿主的网络融合
- network_mode: "host"
- command: >
- bash -c "python3 -u main.py"
- # P.S. 通过对 command 进行微调,可以便捷地安装额外的依赖
- # command: >
- # bash -c "pip install -r request_llms/requirements_qwen.txt && python3 -u main.py"
- ### ===================================================
- ### 【方案三】 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
- ### ===================================================
- version: '3'
- services:
- gpt_academic_with_rwkv:
- image: ghcr.io/binary-husky/gpt_academic_jittorllms:master
- environment:
- # 请查阅 `config.py` 以查看所有的配置信息
- API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
- USE_PROXY: ' True '
- proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "newbing", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"] '
- LOCAL_MODEL_DEVICE: ' cuda '
- DEFAULT_WORKER_NUM: ' 10 '
- WEB_PORT: ' 12305 '
- ADD_WAIFU: ' True '
- # AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
- # 显卡的使用,nvidia0指第0个GPU
- runtime: nvidia
- devices:
- - /dev/nvidia0:/dev/nvidia0
- # 与宿主的网络融合
- network_mode: "host"
- # 不使用代理网络拉取最新代码
- command: >
- python3 -u main.py
- ## ===================================================
- ## 【方案四】 ChatGPT + Latex
- ## ===================================================
- version: '3'
- services:
- gpt_academic_with_latex:
- image: ghcr.io/binary-husky/gpt_academic_with_latex:master # (Auto Built by Dockerfile: docs/GithubAction+NoLocal+Latex)
- environment:
- # 请查阅 `config.py` 以查看所有的配置信息
- API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
- USE_PROXY: ' True '
- proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "gpt-4"] '
- LOCAL_MODEL_DEVICE: ' cuda '
- DEFAULT_WORKER_NUM: ' 10 '
- WEB_PORT: ' 12303 '
- # 与宿主的网络融合
- network_mode: "host"
- # 不使用代理网络拉取最新代码
- command: >
- bash -c "python3 -u main.py"
- ## ===================================================
- ## 【方案五】 ChatGPT + 语音助手 (请先阅读 docs/use_audio.md)
- ## ===================================================
- version: '3'
- services:
- gpt_academic_with_audio:
- image: ghcr.io/binary-husky/gpt_academic_audio_assistant:master
- environment:
- # 请查阅 `config.py` 以查看所有的配置信息
- API_KEY: ' fk195831-IdP0Pb3W6DCMUIbQwVX6MsSiyxwqybyS '
- USE_PROXY: ' False '
- proxies: ' None '
- LLM_MODEL: ' gpt-3.5-turbo '
- AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "gpt-4"] '
- ENABLE_AUDIO: ' True '
- LOCAL_MODEL_DEVICE: ' cuda '
- DEFAULT_WORKER_NUM: ' 20 '
- WEB_PORT: ' 12343 '
- ADD_WAIFU: ' True '
- THEME: ' Chuanhu-Small-and-Beautiful '
- ALIYUN_APPKEY: ' RoP1ZrM84DnAFkZK '
- ALIYUN_TOKEN: ' f37f30e0f9934c34a992f6f64f7eba4f '
- # (无需填写) ALIYUN_ACCESSKEY: ' LTAI5q6BrFUzoRXVGUWnekh1 '
- # (无需填写) ALIYUN_SECRET: ' eHmI20AVWIaQZ0CiTD2bGQVsaP9i68 '
- # 与宿主的网络融合
- network_mode: "host"
- # 不使用代理网络拉取最新代码
- command: >
- bash -c "python3 -u main.py"
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