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166 lines
4.2 KiB
Markdown
166 lines
4.2 KiB
Markdown
# Fast GPT
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Fast GPT 允许你使用自己的 openai API KEY 来快速的调用 openai 接口，包括 GPT3 及其微调方法，以及最新的 gpt3.5 接口。
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## 初始化
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复制 .env.template 成 .env.local ，填写核心参数
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```
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AXIOS_PROXY_HOST=axios代理地址，目前 openai 接口都需要走代理，本机的话就填 127.0.0.1
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AXIOS_PROXY_PORT=代理端口
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MONGODB_URI=mongo数据库地址
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MY_MAIL=发送验证码邮箱
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MAILE_CODE=邮箱秘钥（代理里设置的是QQ邮箱，不知道怎么找这个 code 的，可以百度搜"nodemailer发送邮件"）
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TOKEN_KEY=随便填一个，用于生成和校验 token
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OPENAIKEY=openai的key
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REDIS_URL=redis的地址
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```
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```bash
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pnpm dev
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```
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## 部署
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### docker 模式
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请准备好 docker， mongo，代理, 和 nginx。 镜像走本机的代理，所以用 network=host，port 改成代理的端口，clash 一般都是 7890。
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#### docker 打包
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```bash
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docker build -t imageName:tag .
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docker push imageName:tag
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# 或者直接拉镜像，见下方
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```
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#### 服务器拉取镜像和运行
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```yml
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# docker-compose
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version: "3.3"
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services:
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fast-gpt:
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image: c121914yu/fast-gpt:latest
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environment:
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AXIOS_PROXY_HOST: 127.0.0.1
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AXIOS_PROXY_PORT: 7890
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MY_MAIL:
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MAILE_CODE:
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TOKEN_KEY:
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MONGODB_URI:
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OPENAIKEY:
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REDIS_URL:
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network_mode: host
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restart: always
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container_name: fast-gpt
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```
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```bash
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#!/bin/bash
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# 拉取最新镜像
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docker-compose pull
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docker-compose up -d
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echo "Docker Compose 重新拉取镜像完成！"
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# 删除本地旧镜像
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images=$(docker images --format "{{.ID}} {{.Repository}}" | grep fast-gpt)
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# 将镜像 ID 和名称放入数组中
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IFS=$'\n' read -rd '' -a image_array <<<"$images"
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# 遍历数组并删除所有旧的镜像
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for ((i=1; i<${#image_array[@]}; i++))
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do
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image=${image_array[$i]}
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image_id=${image%% *}
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docker rmi $image_id
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done
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```
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#### 软件教程：docker 安装
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```bash
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# 安装docker
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curl -sSL https://get.daocloud.io/docker | sh
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sudo systemctl start docker
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```
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#### 软件教程：mongo 安装
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```bash
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docker pull mongo:6.0.4
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docker stop mongo
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docker rm mongo
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docker run -d --name mongo \
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-e MONGO_INITDB_ROOT_USERNAME= \
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-e MONGO_INITDB_ROOT_PASSWORD= \
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-v /root/service/mongo:/data/db \
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mongo:6.0.4
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# 检查 mongo 运行情况, 有成功的 logs 代表访问成功
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docker logs mongo
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```
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#### 软件教程: clash 代理
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```bash
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# 下载包
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curl https://glados.rocks/tools/clash-linux.zip -o clash.zip
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# 解压
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unzip clash.zip
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# 下载终端配置⽂件（改成自己配置文件路径）
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curl https://update.glados-config.com/clash/98980/8f30944/70870/glados-terminal.yaml > config.yaml
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# 赋予运行权限
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chmod +x ./clash-linux-amd64-v1.10.0
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# 记得配置端口变量：
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export ALL_PROXY=socks5://127.0.0.1:7891
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export http_proxy=http://127.0.0.1:7890
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export https_proxy=http://127.0.0.1:7890
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export HTTP_PROXY=http://127.0.0.1:7890
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export HTTPS_PROXY=http://127.0.0.1:7890
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# 运行脚本: 删除clash - 到 clash 目录 - 删除缓存 - 执行运行
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# 会生成一个 nohup.out 文件，可以看到 clash 的 logs
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OLD_PROCESS=$(pgrep clash)
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if [ ! -z "$OLD_PROCESS" ]; then
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echo "Killing old process: $OLD_PROCESS"
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kill $OLD_PROCESS
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fi
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sleep 2
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cd **/clash
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rm -f ./nohup.out || true
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rm -f ./cache.db || true
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nohup ./clash-linux-amd64-v1.10.0 -d ./ &
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echo "Restart clash"
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```
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#### 软件教程：Nginx
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...没写，这个百度吧。
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#### redis
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安装
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```bash
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#!/bin/bash
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docker pull redis/redis-stack:6.2.6-v6
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docker stop fast-gpt-redis-stack
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docker rm fast-gpt-redis-stack
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docker run -d --name fast-gpt-redis-stack \
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-v /redis/data:/data \
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-v /etc/localtime:/etc/localtime:ro \
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-v /redis.conf:/redis-stack.conf \
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-e REDIS_ARGS="--requirepass 1111111"\
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-p 8102:6379 \
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-p 8103:8001 \
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--restart unless-stopped \
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redis/redis-stack:6.2.6-v6
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```
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```bash
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# /redis.conf
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# 开启aop持久化
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appendonly yes
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#default: 持久化文件
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appendfilename "appendonly.aof"
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#default: 每秒同步一次
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appendfsync everysec
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```
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```bash
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# 添加索引
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FT.CREATE idx:model:data:hash ON HASH PREFIX 1 model:data: SCHEMA modelId TAG userId TAG status TAG q TEXT text TEXT vector VECTOR FLAT 6 DIM 1536 DISTANCE_METRIC COSINE TYPE FLOAT32
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```
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