122 lines
7.5 KiB
YAML
122 lines
7.5 KiB
YAML
【请修改完参数后，删除此行】请在以下方案中选择一种，然后删除其他的方案，最后docker-compose up运行 | Please choose from one of these options below, delete other options as well as This Line
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## ===================================================
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## 【方案一】 如果不需要运行本地模型（仅chatgpt类远程服务）
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## ===================================================
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version: '3'
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services:
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gpt_academic_nolocalllms:
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image: fuqingxu/gpt_academic:no-local-llms
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environment:
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# 请查阅 `config.py` 以查看所有的配置信息
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API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
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USE_PROXY: ' True '
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proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
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LLM_MODEL: ' gpt-3.5-turbo '
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AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4"] '
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DEFAULT_WORKER_NUM: ' 10 '
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WEB_PORT: ' 22303 '
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ADD_WAIFU: ' True '
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AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
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# 与宿主的网络融合
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network_mode: "host"
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# 不使用代理网络拉取最新代码
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command: >
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bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
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git checkout master --force &&
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git remote set-url origin https://github.com/binary-husky/chatgpt_academic.git &&
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git pull &&
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python3 -u main.py"
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### ===================================================
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### 【方案二】 如果需要运行ChatGLM本地模型
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### ===================================================
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version: '3'
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services:
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gpt_academic_with_chatglm:
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image: fuqingxu/gpt_academic:chatgpt-chatglm-newbing # [option 2] 如果需要运行ChatGLM本地模型
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environment:
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# 请查阅 `config.py` 以查看所有的配置信息
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API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
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USE_PROXY: ' True '
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proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
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LLM_MODEL: ' gpt-3.5-turbo '
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AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4", "chatglm"] '
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LOCAL_MODEL_DEVICE: ' cuda '
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DEFAULT_WORKER_NUM: ' 10 '
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WEB_PORT: ' 12303 '
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ADD_WAIFU: ' True '
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AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
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# 显卡的使用，nvidia0指第0个GPU
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runtime: nvidia
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devices:
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- /dev/nvidia0:/dev/nvidia0
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# 与宿主的网络融合
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network_mode: "host"
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# 使用代理网络拉取最新代码
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# command: >
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# bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
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# truncate -s -1 /etc/proxychains.conf &&
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# echo \"socks5 127.0.0.1 10880\" >> /etc/proxychains.conf &&
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# proxychains git pull &&
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# python3 -u main.py "
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# 不使用代理网络拉取最新代码
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command: >
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bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
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git pull &&
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python3 -u main.py"
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### ===================================================
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### 【方案三】 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
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### ===================================================
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version: '3'
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services:
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gpt_academic_with_rwkv:
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image: fuqingxu/gpt_academic:jittorllms # [option 2] 如果需要运行ChatGLM本地模型
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environment:
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# 请查阅 `config.py` 以查看所有的配置信息
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API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
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USE_PROXY: ' True '
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proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
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LLM_MODEL: ' gpt-3.5-turbo '
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AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4", "jittorllms_rwkv"] '
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LOCAL_MODEL_DEVICE: ' cuda '
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DEFAULT_WORKER_NUM: ' 10 '
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WEB_PORT: ' 12305 '
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ADD_WAIFU: ' True '
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# AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
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# 显卡的使用，nvidia0指第0个GPU
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runtime: nvidia
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devices:
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- /dev/nvidia0:/dev/nvidia0
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# 与宿主的网络融合
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network_mode: "host"
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# 使用代理网络拉取最新代码
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# command: >
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# bash -c " truncate -s -1 /etc/proxychains.conf &&
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# echo \"socks5 127.0.0.1 10880\" >> /etc/proxychains.conf &&
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# echo '[gpt-academic] 正在从github拉取最新代码...' &&
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# proxychains git pull &&
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# echo '[jittorllms] 正在从github拉取最新代码...' &&
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# proxychains git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
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# python3 -u main.py"
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# 不使用代理网络拉取最新代码
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command: >
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bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
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git pull &&
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echo '[jittorllms] 正在从github拉取最新代码...' &&
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git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
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python3 -u main.py"
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