# Fast GPT 

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。

## 开发
复制 .env.template 成 .env.local ，填写核心参数  

```
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
AXIOS_PROXY_PORT_FAST=代理端口1,clash默认为7890
AXIOS_PROXY_PORT_NORMAL=代理端口2
MONGODB_URI=mongo数据库地址
MY_MAIL=发送验证码邮箱
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"）
TOKEN_KEY=随便填一个，用于生成和校验 token
OPENAIKEY=openai的key
REDIS_URL=redis的地址
```
```bash
pnpm dev
```

## 部署

### docker 模式
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。

#### docker 打包
```bash
docker build -t imageName:tag .
docker push imageName:tag
# 或者直接拉镜像，见下方
```

#### 软件教程：docker 安装
```bash
# 安装docker
curl -sSL https://get.daocloud.io/docker | sh
sudo systemctl start docker
```

#### 软件教程: clash 代理
```bash
# 下载包
curl https://glados.rocks/tools/clash-linux.zip -o clash.zip 
# 解压
unzip clash.zip
# 下载终端配置⽂件（改成自己配置文件路径）
curl https://update.glados-config.com/clash/98980/8f30944/70870/glados-terminal.yaml > config.yaml
# 赋予运行权限
chmod +x ./clash-linux-amd64-v1.10.0 
# 记得配置端口变量：
export ALL_PROXY=socks5://127.0.0.1:7891
export http_proxy=http://127.0.0.1:7890
export https_proxy=http://127.0.0.1:7890
export HTTP_PROXY=http://127.0.0.1:7890
export HTTPS_PROXY=http://127.0.0.1:7890

# 运行脚本: 删除clash - 到 clash 目录 - 删除缓存 - 执行运行. 会生成一个 nohup.out 文件，可以看到 clash 的 logs
OLD_PROCESS=$(pgrep clash)
if [ ! -z "$OLD_PROCESS" ]; then
  echo "Killing old process: $OLD_PROCESS"
  kill $OLD_PROCESS
fi
sleep 2
cd  **/clash
rm -f ./nohup.out || true
rm -f ./cache.db || true
nohup ./clash-linux-amd64-v1.10.0  -d ./ &
echo "Restart clash"
```

#### 文件创建
**yml文件**
```yml
version: "3.3"
services:
  fast-gpt:
    image: c121914yu/fast-gpt:latest
    environment:
      AXIOS_PROXY_HOST: 127.0.0.1
      AXIOS_PROXY_PORT: 7890
      MY_MAIL: 11111111@qq.com
      MAILE_CODE: sdasadasfasfad
      TOKEN_KEY: sssssssss
      MONGODB_URI: mongodb://username:password@0.0.0.0:27017/?authSource=admin&readPreference=primary&appname=MongoDB%20Compass&ssl=false
      OPENAIKEY: sk-afadfadfadfsd
      REDIS_URL: redis://default:password@0.0.0.0:8100
    network_mode: host
    restart: always
    container_name: fast-gpt
  mongodb:
    image: mongo:6.0.4
    container_name: mongo
    restart: always
    environment:
      - MONGO_INITDB_ROOT_USERNAME=root
      - MONGO_INITDB_ROOT_PASSWORD=ROOT_1234
      - MONGO_DATA_DIR=/data/db
      - MONGO_LOG_DIR=/data/logs
    volumes:
      - /root/fastgpt/mongo/data:/data/db
      - /root/fastgpt/mongo/logs:/data/logs
    ports:
      - 27017:27017
  nginx: 
    image: nginx:alpine3.17
    container_name: nginx
    restart: always
    network_mode: host
    ports:
      - "80:80"
    volumes:
      - /root/fastgpt/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
  redis-stack:
    image: redis/redis-stack:6.2.6-v6
    container_name: redis-stack
    restart: unless-stopped
    ports:
      - "8100:6379"
      - "8101:8001"
    environment:
      - REDIS_ARGS=--requirepass psw1234
    volumes:
      - /etc/localtime:/etc/localtime:ro
      - /root/fastgpt/redis/redis.conf:/redis.conf
      - /root/fastgpt/redis/data:/data
```
**redis.conf**
```
## 开启aop持久化
appendonly yes
#default: 持久化文件
appendfilename "appendonly.aof"
#default: 每秒同步一次
appendfsync everysec
```
**nginx.conf**
```
user nginx;
worker_processes auto;
error_log /var/log/nginx/error.log;
pid /run/nginx.pid;

events {
    worker_connections 1024;
}

http {
    include             /etc/nginx/mime.types;
    default_type        application/octet-stream;
    include /etc/nginx/conf.d/*.conf;

    server {
        listen 80;
        server_name test.com;
        
        gzip  on;
        gzip_min_length   1k;
        gzip_buffers  4 8k;
        gzip_http_version 1.1;
        gzip_comp_level 6;
        gzip_vary on;
        gzip_types  text/plain application/x-javascript text/css application/javascript application/json application/xml;
        gzip_disable "MSIE [1-6]\.";

        location / {
            proxy_pass http://localhost:3000;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;        
        }
    }
}
```

#### 运行脚本
**redis创建索引**
```bash
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
```
**run.sh 运行文件**
```bash
#!/bin/bash
docker-compose up -d

echo "Docker Compose 重新拉取镜像完成！"

# 删除本地旧镜像
images=$(docker images --format "{{.ID}} {{.Repository}}" | grep fast-gpt)

# 将镜像 ID 和名称放入数组中
IFS=$'\n' read -rd '' -a image_array <<<"$images"

# 遍历数组并删除所有旧的镜像
for ((i=1; i<${#image_array[@]}; i++))
do
    image=${image_array[$i]}
    image_id=${image%% *}
    docker rmi $image_id
done
```