Spaces:
Sleeping
Sleeping
File size: 15,039 Bytes
971ac20 17d0a32 971ac20 17d0a32 971ac20 17d0a32 971ac20 7875741 5c0a088 7875741 8a5e8bc 7875741 624d203 7875741 5c0a088 7875741 a1fe67d 624d203 7875741 624d203 7875741 a1fe67d 7875741 8a5e8bc 7875741 a1fe67d 7875741 a1fe67d 7875741 624d203 59a4bca 47289f8 59a4bca 624d203 59a4bca a1fe67d 17d0a32 a1fe67d 59a4bca 8a5e8bc 59a4bca 1bb45d4 59a4bca 478f3a7 59a4bca 478f3a7 7875741 47289f8 7875741 8a5e8bc 9f9848c 8a5e8bc 9f9848c 8a5e8bc 9f9848c 8a5e8bc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 |
## ===================================================
# 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"
|