perf: prompt

Signed-off-by: 晓杰 <2561589453@qq.com>

.env.template

@@ -1,9 +1,27 @@
-AXIOS_PROXY_HOST=127.0.0.1
-AXIOS_PROXY_PORT_FAST=7890
-AXIOS_PROXY_PORT_NORMAL=7890
-MONGODB_URI=mongodb://username:password@0.0.0.0:27017/?authSource=admin&readPreference=primary&appname=MongoDB%20Compass&ssl=false
-MY_MAIL=11111111@qq.com
-MAILE_CODE=sdasadasfasfad
-TOKEN_KEY=sssssssss
-OPENAIKEY=sk-afadfadfadfsd
-REDIS_URL=redis://default:password@0.0.0.0:8100
+# proxy
+# AXIOS_PROXY_HOST=127.0.0.1
+# AXIOS_PROXY_PORT=7890
+# OPENAI_BASE_URL=https://api.openai.com/v1
+# OPENAI_BASE_URL_AUTH=可选的安全凭证
+# 是否开启队列任务。 1-开启，0-关闭（请求parentUrl去执行任务,单机时直接填1）
+queueTask=1
+parentUrl=https://hostname/api/openapi/startEvents
+# email
+MY_MAIL=xxx@qq.com
+MAILE_CODE=xxx
+# ali ems
+aliAccessKeyId=xxx
+aliAccessKeySecret=xxx
+aliSignName=xxx
+aliTemplateCode=SMS_xxx
+# token
+TOKEN_KEY=xxx
+# openai
+OPENAIKEY=sk-xxx
+# db
+MONGODB_URI=mongodb://username:password@0.0.0.0:27017/test?authSource=admin
+PG_HOST=0.0.0.0
+PG_PORT=8100
+PG_USER=xxx
+PG_PASSWORD=xxx
+PG_DB_NAME=xxx

.github/workflows/release.yml

@@ -0,0 +1,50 @@
+name: Release
+
+on:
+  workflow_dispatch:
+
+  push:
+    branches:
+      - 'main'
+
+jobs:
+  release:
+    runs-on: ubuntu-20.04
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 1
+
+      - name: Install Dependencies
+        run: |
+          sudo apt update && sudo  apt install  -y nodejs npm
+      - # Add support for more platforms with QEMU (optional)
+        # https://github.com/docker/setup-qemu-action
+        name: Set up QEMU
+        uses: docker/setup-qemu-action@v2
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          driver-opts: network=host
+
+      - name: Login to  gitbub
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GH_PAT }}
+      - name: build and publish image
+        env:
+          # fork friendly ^^
+          DOCKER_REPO: ghcr.io/${{ github.repository_owner }}/fast-gpt
+        run: |
+          docker buildx build \
+          --platform linux/amd64,linux/arm64 \
+          --label "org.opencontainers.image.source=https://github.com/${{ github.repository_owner }}/FastGPT" \
+          --label "org.opencontainers.image.description=fast-gpt image" \
+          --label "org.opencontainers.image.licenses=MIT" \
+          --push \
+          -t ${DOCKER_REPO}:latest \
+          -f Dockerfile \
+          .

.gitignore

@@ -34,7 +34,6 @@ yarn-error.log*
 # typescript
 *.tsbuildinfo
 next-env.d.ts
-/public/trainData/
 /.vscode/
 platform.json
 testApi/

Makefile

@@ -34,7 +34,7 @@ run: ## Run a dev service from host.
 
 .PHONY: docker-build
 docker-build: ## Build docker image with the desktop-frontend.
-	docker build -t c121914yu/fast-gpt:latest .
+	docker build -t c121914yu/fast-gpt:latest . --network host  --build-arg HTTP_PROXY=http://127.0.0.1:7890 --build-arg HTTPS_PROXY=http://127.0.0.1:7890
 
 ##@ Deployment
 

README.md

@@ -1,168 +1,136 @@
 # 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。
+Fast GPT 允许你使用自己的 openai API KEY 来快速的调用 openai 接口，目前集成了 gpt35 和 embedding. 可构建自己的知识库。
+
+## 知识库原理
+![KBProcess](docs/imgs/KBProcess.jpg?raw=true "KBProcess")
 
 ## 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
-```
+**配置环境变量**
 ```bash
+# proxy（可选）
+AXIOS_PROXY_HOST=127.0.0.1
+AXIOS_PROXY_PORT=7890
+# openai 中转连接（可选）
+OPENAI_BASE_URL=https://api.openai.com/v1
+OPENAI_BASE_URL_AUTH=可选的安全凭证
+# 是否开启队列任务。 1-开启，0-关闭（请求 parentUrl 去执行任务,单机时直接填1）
+queueTask=1
+parentUrl=https://hostname/api/openapi/startEvents
+# 发送邮箱验证码配置。参考 nodeMail 获取参数，自行百度。
+MY_MAIL=xxx@qq.com
+MAILE_CODE=xxx
+# 阿里短信服务（邮箱和短信至少二选一）
+aliAccessKeyId=xxx
+aliAccessKeySecret=xxx
+aliSignName=xxx
+aliTemplateCode=SMS_xxx
+# token（随便填，作为登录凭证）
+TOKEN_KEY=xxx
+# openai key
+OPENAIKEY=sk-xxx
+# mongo连接地址
+MONGODB_URI=mongodb://username:password@0.0.0.0:27017/test?authSource=admin
+# mongo数据库名称
+MONGODB_NAME=xxx 
+# pg 数据库相关内容，和 docker-compose 对上
+PG_HOST=0.0.0.0 
+PG_PORT=8102
+PG_USER=xxx
+PG_PASSWORD=xxx
+PG_DB_NAME=xxx
+```
+**运行**
+```
 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。
+### 代理环境（国外服务器可忽略）
+1. [clash 方案](./docs/proxy/clash.md) - 仅需一台服务器（需要有 clash）
+2. [nginx 方案](./docs/proxy/nginx.md) - 需要一台国外服务器
+3. [cloudflare 方案](./docs/proxy/cloudflare.md) - 需要有域名（每日免费 10w 次代理请求）
 
-#### 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
+### docker 部署
+#### 1. 安装 docker 和 docker-compose
+这个不同系统略有区别，百度安装下。验证安装成功后进行下一步。下面给出一个例子：
 ```bash
 # 安装docker
-curl -sSL https://get.daocloud.io/docker | sh
+curl -L https://get.daocloud.io/docker | sh
 sudo systemctl start docker
+# 安装 docker-compose
+curl -L https://github.com/docker/compose/releases/download/1.23.2/docker-compose-`uname -s`-`uname -m` -o /usr/local/bin/docker-compose
+sudo chmod +x /usr/local/bin/docker-compose
+# 验证安装
+docker -v
+docker-compose -v
 ```
 
-#### 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 $OLD_PROCESS
-fi
-sleep 2
-cd  **/clash
-rm -f ./nohup.out || true
-rm -f ./cache.db || true
-nohup ./clash-linux-amd64-v1.10.0  -d ./ &
-echo "Restart clash"
+#### 2. 创建3个初始化文件
+手动创建或者直接把 deploy 里内容复制过去
+
+**/root/fast-gpt/pg/init.sql**
+```sql
+set -e
+psql -v ON_ERROR_STOP=1 --username "$POSTGRES_USER" --dbname "$POSTGRES_DB" <<-EOSQL
+
+CREATE EXTENSION vector;
+-- init table
+CREATE TABLE modelData (
+    id BIGSERIAL PRIMARY KEY,
+    vector VECTOR(1536),
+    status VARCHAR(50) NOT NULL,
+    user_id VARCHAR(50) NOT NULL,
+    model_id VARCHAR(50) NOT NULL,
+    q TEXT NOT NULL,
+    a TEXT NOT NULL
+);
+-- create index
+CREATE INDEX modelData_status_index ON modelData USING HASH (status);
+CREATE INDEX modelData_userId_index ON modelData USING HASH (user_id);
+CREATE INDEX modelData_modelId_index ON modelData USING HASH (model_id);
+EOSQL
 ```
 
-#### 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**
-```
+**/root/fast-gpt/nginx/nginx.conf**
+```conf
 user nginx;
 worker_processes auto;
-error_log /var/log/nginx/error.log;
-pid /run/nginx.pid;
+worker_rlimit_nofile 51200;
 
 events {
     worker_connections 1024;
 }
 
 http {
-    include             /etc/nginx/mime.types;
-    default_type        application/octet-stream;
-    include /etc/nginx/conf.d/*.conf;
+    access_log off;
+    server_names_hash_bucket_size 512;
+    client_header_buffer_size 32k;
+    large_client_header_buffers 4 32k;
+    client_max_body_size 50M;
+ 
+    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]\.";
+
+    open_file_cache max=1000 inactive=1d;
+    open_file_cache_valid 30s;
+    open_file_cache_min_uses 8;
+    open_file_cache_errors off;
 
     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]\.";
+        listen 443 ssl;
+        server_name docgpt.ahapocket.cn;
+        ssl_certificate /ssl/docgpt.pem;
+        ssl_certificate_key /ssl/docgpt.key;
+        ssl_session_timeout 5m;
 
         location / {
             proxy_pass http://localhost:3000;
@@ -171,17 +139,90 @@ http {
             proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;        
         }
     }
+    server {
+        listen 80;
+        server_name docgpt.ahapocket.cn;
+        rewrite ^(.*) https://$server_name$1 permanent;
+    }
 }
 ```
 
-#### 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
+**/root/fast-gpt/docker-compose.yml**
+```yml
+version: "3.3"
+services:
+  fast-gpt:
+    image: c121914yu/fast-gpt:latest
+    network_mode: host
+    restart: always
+    container_name: fast-gpt
+    environment:
+      # - AXIOS_PROXY_HOST=127.0.0.1
+      # - AXIOS_PROXY_PORT=7890
+      # - OPENAI_BASE_URL=https://api.openai.com/v1
+      # - OPENAI_BASE_URL_AUTH=可选的安全凭证
+      - MY_MAIL=xxxx@qq.com  
+      - MAILE_CODE=xxxx
+      - aliAccessKeyId=xxxx 
+      - aliAccessKeySecret=xxxx
+      - aliSignName=xxxxx
+      - aliTemplateCode=SMS_xxxx
+      - TOKEN_KEY=xxxx 
+      - queueTask=1
+      - parentUrl=https://hostname/api/openapi/startEvents
+      - MONGODB_URI=mongodb://username:passsword@0.0.0.0:27017/?authSource=admin
+      - MONGODB_NAME=xxx
+      - PG_HOST=0.0.0.0
+      - PG_PORT=8100
+      - PG_USER=xxx
+      - PG_PASSWORD=xxx
+      - PG_DB_NAME=xxx
+      - OPENAIKEY=sk-xxxxx
+  nginx: 
+    image: nginx:alpine3.17
+    container_name: nginx
+    restart: always
+    network_mode: host
+    volumes:
+      - /root/fast-gpt/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+      - /root/fast-gpt/nginx/logs:/var/log/nginx
+      - /root/fast-gpt/nginx/ssl/docgpt.key:/ssl/docgpt.key
+      - /root/fast-gpt/nginx/ssl/docgpt.pem:/ssl/docgpt.pem
+  pg:
+    image: ankane/pgvector
+    container_name: pg
+    restart: always
+    ports:
+      - 8100:5432
+    environment:
+      - POSTGRES_USER=xxx
+      - POSTGRES_PASSWORD=xxx
+      - POSTGRES_DB=xxx
+    volumes:
+      - /root/fast-gpt/pg/data:/var/lib/postgresql/data
+      - /root/fast-gpt/pg/init.sql:/docker-entrypoint-initdb.d/init.sh
+      - /etc/localtime:/etc/localtime:ro
+  mongodb:
+    image: mongo:4.0.1
+    container_name: mongo
+    restart: always
+    ports:
+      - 27017:27017
+    environment:
+      - MONGO_INITDB_ROOT_USERNAME=username
+      - MONGO_INITDB_ROOT_PASSWORD=password
+    volumes:
+      - /root/fast-gpt/mongo/data:/data/db
+      - /root/fast-gpt/mongo/logs:/var/log/mongodb
+      - /etc/localtime:/etc/localtime:ro
 ```
+
+#### 3. 运行 docker-compose
+下面是一个辅助脚本，也可以直接 docker-compose up -d
 **run.sh 运行文件**
 ```bash
 #!/bin/bash
+docker-compose pull
 docker-compose up -d
 
 echo "Docker Compose 重新拉取镜像完成！"
@@ -200,3 +241,16 @@ do
     docker rmi $image_id
 done
 ```
+
+
+## 其他优化点
+### Git Action 自动打包镜像
+.github里拥有一个 git 提交到 main 分支时自动打包 amd64 和 arm64 镜像的 actions。你仅需要提前在 git 配置好 session。  
+
+1. 创建账号 session: 头像 -> settings -> 最底部 Developer settings ->  Personal access tokens -> tokens(classic) -> 创建新 session，把一些看起来需要的权限勾上。
+2. 添加 session 到仓库: 仓库 -> settings -> Secrets and variables -> Actions -> 创建secret
+3. 填写 secret: Name-GH_PAT, Secret-第一步的tokens 
+
+## 其他问题
+### Mac 可能的问题
+> 因为教程有部分镜像不兼容arm64，所以写个文档指导新手如何快速在mac上面搭建fast-gpt[如何在mac上面部署fastgpt](./docs/mac.md)

deploy/docker-compose.yml

@@ -0,0 +1,66 @@
+version: '3.3'
+services:
+  fast-gpt:
+    image: c121914yu/fast-gpt:latest
+    network_mode: host
+    restart: always
+    container_name: fast-gpt
+    environment:
+      # - AXIOS_PROXY_HOST=127.0.0.1
+      # - AXIOS_PROXY_PORT=7890
+      # - OPENAI_BASE_URL=https://api.openai.com/v1
+      # - OPENAI_BASE_URL_AUTH=可选的安全凭证
+      - MY_MAIL=xxxx@qq.com
+      - MAILE_CODE=xxxx
+      - aliAccessKeyId=xxxx
+      - aliAccessKeySecret=xxxx
+      - aliSignName=xxxxx
+      - aliTemplateCode=SMS_xxxx
+      - TOKEN_KEY=xxxx
+      - queueTask=1
+      - parentUrl=https://hostname/api/openapi/startEvents
+      - MONGODB_URI=mongodb://username:passsword@0.0.0.0:27017/?authSource=admin
+      - MONGODB_NAME=xxx
+      - PG_HOST=0.0.0.0
+      - PG_PORT=8100
+      - PG_USER=xxx
+      - PG_PASSWORD=xxx
+      - PG_DB_NAME=xxx
+      - OPENAIKEY=sk-xxxxx
+  nginx:
+    image: nginx:alpine3.17
+    container_name: nginx
+    restart: always
+    network_mode: host
+    volumes:
+      - /root/fast-gpt/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+      - /root/fast-gpt/nginx/logs:/var/log/nginx
+      - /root/fast-gpt/nginx/ssl/docgpt.key:/ssl/docgpt.key
+      - /root/fast-gpt/nginx/ssl/docgpt.pem:/ssl/docgpt.pem
+  pg:
+    image: ankane/pgvector
+    container_name: pg
+    restart: always
+    ports:
+      - 8100:5432
+    environment:
+      - POSTGRES_USER=xxx
+      - POSTGRES_PASSWORD=xxx
+      - POSTGRES_DB=xxx
+    volumes:
+      - /root/fast-gpt/pg/data:/var/lib/postgresql/data
+      - /root/fast-gpt/pg/init.sql:/docker-entrypoint-initdb.d/init.sh
+      - /etc/localtime:/etc/localtime:ro
+  mongodb:
+    image: mongo:4.0.1
+    container_name: mongo
+    restart: always
+    ports:
+      - 27017:27017
+    environment:
+      - MONGO_INITDB_ROOT_USERNAME=username
+      - MONGO_INITDB_ROOT_PASSWORD=password
+    volumes:
+      - /root/fast-gpt/mongo/data:/data/db
+      - /root/fast-gpt/mongo/logs:/var/log/mongodb
+      - /etc/localtime:/etc/localtime:ro

deploy/nginx/nginx.conf

@@ -0,0 +1,49 @@
+user nginx;
+worker_processes auto;
+worker_rlimit_nofile 51200;
+
+events {
+    worker_connections 1024;
+}
+
+http {
+    access_log off;
+    server_names_hash_bucket_size 512;
+    client_header_buffer_size 32k;
+    large_client_header_buffers 4 32k;
+    client_max_body_size 50M;
+ 
+    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]\.";
+
+    open_file_cache max=1000 inactive=1d;
+    open_file_cache_valid 30s;
+    open_file_cache_min_uses 8;
+    open_file_cache_errors off;
+
+    server {
+        listen 443 ssl;
+        server_name docgpt.ahapocket.cn;
+        ssl_certificate /ssl/docgpt.pem;
+        ssl_certificate_key /ssl/docgpt.key;
+        ssl_session_timeout 5m;
+
+        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 $proxy_add_x_forwarded_for;        
+        }
+    }
+    server {
+        listen 80;
+        server_name docgpt.ahapocket.cn;
+        rewrite ^(.*) https://$server_name$1 permanent;
+    }
+}

deploy/pg/init.sql

@@ -0,0 +1,19 @@
+set -e
+psql -v ON_ERROR_STOP=1 --username "$POSTGRES_USER" --dbname "$POSTGRES_DB" <<-EOSQL
+
+CREATE EXTENSION vector;
+-- init table
+CREATE TABLE modelData (
+    id BIGSERIAL PRIMARY KEY,
+    vector VECTOR(1536),
+    status VARCHAR(50) NOT NULL,
+    user_id VARCHAR(50) NOT NULL,
+    model_id VARCHAR(50) NOT NULL,
+    q TEXT NOT NULL,
+    a TEXT NOT NULL
+);
+-- create index
+CREATE INDEX modelData_status_index ON modelData USING HASH (status);
+CREATE INDEX modelData_userId_index ON modelData USING HASH (user_id);
+CREATE INDEX modelData_modelId_index ON modelData USING HASH (model_id);
+EOSQL

deploy/run.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+docker-compose pull
+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

docs/mac.md

@@ -0,0 +1,100 @@
+## 怎么在mac上面部署fastgpt
+
+### 前置条件
+
+1、可以 curl api.openai.com 
+
+2、有openai key
+
+3、有邮箱MAILE_CODE
+
+4、有docker 
+
+```
+docker -v
+```
+
+5、有pnpm ，可以使用`brew install pnpm`安装
+
+6、需要创建一个放置pg和mongo数据的文件夹，这里创建在`~/fastgpt`目录中,里面有`pg` 和`mongo `两个文件夹
+
+```
+➜  fast-gpt pwd
+/Users/jie/fast-gpt
+➜  fast-gpt ls
+mongo pg
+```
+
+
+
+### docker部署方式
+
+这种方式主要是为了方便调试，可以使用`pnpm dev ` 运行fast-gpt项目
+
+**1、.env.local 文件**
+
+```
+# proxy
+AXIOS_PROXY_HOST=127.0.0.1
+AXIOS_PROXY_PORT_FAST=7890
+AXIOS_PROXY_PORT_NORMAL=7890
+queueTask=1
+# email
+MY_MAIL= {Your Mail}
+MAILE_CODE={Yoir Mail code}
+# ali ems
+aliAccessKeyId=xxx
+aliAccessKeySecret=xxx
+aliSignName=xxx
+aliTemplateCode=SMS_xxx
+# token
+TOKEN_KEY=sswada
+# openai
+OPENAIKEY={Your openapi key}
+# db
+MONGODB_URI=mongodb://username:password@0.0.0.0:27017/test?authSource=admin
+PG_HOST=0.0.0.0
+PG_PORT=8100
+PG_USER=xxx
+PG_PASSWORD=xxx
+PG_DB_NAME=xxx
+```
+
+**2、部署mongo**
+
+```
+docker run --name mongo -p 27017:27017 -e MONGO_INITDB_ROOT_USERNAME=username -e MONGO_INITDB_ROOT_PASSWORD=password -v ~/fast-gpt/mongo/data:/data/db -d mongo:4.0.1
+```
+
+**3、部署pgsql**
+
+```
+docker run -it --name pg -e "POSTGRES_PASSWORD=xxx" -e POSTGRES_USER=xxx -p 8100:5432 -v ~/fast-gpt/pg/data:/var/lib/postgresql/data -d octoberlan/pgvector:v0.4.1
+```
+
+进pgsql容器运行
+
+```
+psql -v ON_ERROR_STOP=1 --username "$POSTGRES_USER" --dbname "$POSTGRES_DB" <<-EOSQL
+
+CREATE EXTENSION vector;
+-- init table
+CREATE TABLE modelData (
+    id BIGSERIAL PRIMARY KEY,
+    vector VECTOR(1536),
+    status VARCHAR(50) NOT NULL,
+    user_id VARCHAR(50) NOT NULL,
+    model_id VARCHAR(50) NOT NULL,
+    q TEXT NOT NULL,
+    a TEXT NOT NULL
+);
+-- create index
+CREATE INDEX modelData_status_index ON modelData (status);
+CREATE INDEX modelData_modelId_index ON modelData (modelId);
+CREATE INDEX modelData_userId_index ON modelData (userId);
+EOSQL
+```
+
+
+
+4、**最后在FASTGPT项目里面运行pnpm dev 运行项目，然后进入localhost:3000 看项目是否跑起来了**

docs/proxy/clash.md

@@ -0,0 +1,68 @@
+# 安装 clash 
+
+clash 会在本机启动代理。对应的，你需要配置项目的两个环境变量：
+
+```
+AXIOS_PROXY_HOST=127.0.0.1
+AXIOS_PROXY_PORT=7890
+```
+
+需要注的是，在你的 config.yaml 文件中，最好仅指定 api.openai.com 走代理，其他请求都直连。
+
+**安装clash**
+```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 
+```
+
+**runClash.sh**
+```sh
+# 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"
+```
+
+**config.yaml配置例子**
+```yaml
+mixed-port: 7890
+allow-lan: false
+bind-address: '*'
+mode: rule
+log-level: warning
+dns:  
+  enable: true  
+  ipv6: false  
+  nameserver:  
+    - 8.8.8.8
+    - 8.8.4.4 
+  cache-size: 400
+proxies:
+    - 
+proxy-groups:
+  - { name: '♻️ 自动选择', type: url-test,  proxies: [香港V01×1.5], url: 'https://api.openai.com', interval: 3600}
+rules:
+  - 'DOMAIN-SUFFIX,api.openai.com,♻️ 自动选择'
+  - 'MATCH,DIRECT'
+```

docs/proxy/cloudflare.md

@@ -0,0 +1,46 @@
+# cloudflare 代理配置
+
+[来自 "不做了睡觉" 教程](https://gravel-twister-d32.notion.site/FastGPT-API-ba7bb261d5fd4fd9bbb2f0607dacdc9e)
+
+**workers 配置文件**
+
+```js
+const TELEGRAPH_URL = 'https://api.openai.com';
+
+addEventListener('fetch', (event) => {
+  event.respondWith(handleRequest(event.request));
+});
+
+async function handleRequest(request) {
+  // 安全校验
+  if (request.headers.get('auth') !== 'auth_code') {
+    return new Response('UnAuthorization', { status: 403 });
+  }
+
+  const url = new URL(request.url);
+  url.host = TELEGRAPH_URL.replace(/^https?:\/\//, '');
+
+  const modifiedRequest = new Request(url.toString(), {
+    headers: request.headers,
+    method: request.method,
+    body: request.body,
+    redirect: 'follow'
+  });
+
+  const response = await fetch(modifiedRequest);
+  const modifiedResponse = new Response(response.body, response);
+
+  // 添加允许跨域访问的响应头
+  modifiedResponse.headers.set('Access-Control-Allow-Origin', '*');
+
+  return modifiedResponse;
+}
+```
+
+**对应的环境变量**
+务必别忘了填 v1
+
+```
+OPENAI_BASE_URL=https://xxxxxx/v1
+OPENAI_BASE_URL_AUTH=auth_code
+```

docs/proxy/nginx.md

@@ -0,0 +1,72 @@
+# nginx 反向代理 openai 接口
+如果你有国外的服务器，可以通过配置 nginx 反向代理，转发 openai 相关的请求，从而让国内的服务器可以通过访问该 nginx 去访问 openai 接口。
+
+```conf
+user nginx;
+worker_processes auto;
+worker_rlimit_nofile 51200;
+
+events {
+    worker_connections 1024;
+}
+
+http {
+    resolver 8.8.8.8;
+    proxy_ssl_server_name on;
+
+    access_log off;
+    server_names_hash_bucket_size 512;
+    client_header_buffer_size 32k;
+    large_client_header_buffers 4 32k;
+    client_max_body_size 50M;
+ 
+    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]\.";
+
+    open_file_cache max=1000 inactive=1d;
+    open_file_cache_valid 30s;
+    open_file_cache_min_uses 8;
+    open_file_cache_errors off;
+
+    server {
+        listen 443 ssl;
+        server_name your_host;
+        ssl_certificate /ssl/your_host.pem;
+        ssl_certificate_key /ssl/your_host.key;
+        ssl_session_timeout 5m;
+
+        location ~ /openai/(.*) {
+            # auth check
+            if ($http_authkey != "xxxxxx") {
+                return 403;
+            }
+            
+            proxy_pass https://api.openai.com/$1$is_args$args;
+            proxy_set_header Host api.openai.com;
+            proxy_set_header X-Real-IP $remote_addr;
+            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+            # 流式响应
+            proxy_set_header Connection '';
+            proxy_http_version 1.1;
+            chunked_transfer_encoding off;
+            proxy_buffering off;
+            proxy_cache off;
+            # 一般响应
+            proxy_buffer_size 128k;
+            proxy_buffers 4 256k;
+            proxy_busy_buffers_size 256k;
+        }
+    }
+    server {
+        listen 80;
+        server_name ai.fastgpt.run;
+        rewrite ^(.*) https://$server_name$1 permanent;
+    }
+}
+```

next.config.js

@@ -1,13 +1,15 @@
 /** @type {import('next').NextConfig} */
 
-const path = require('path');
-const isDev = process.env.NODE_ENV === 'development';
-
 const nextConfig = {
   output: 'standalone',
   reactStrictMode: false,
   compress: true,
+
   webpack(config) {
+    config.experiments = {
+      asyncWebAssembly: true,
+      layers: true
+    };
     config.module.rules = config.module.rules.concat([
       {
         test: /\.svg$/i,

package.json

@@ -11,8 +11,13 @@
     "format": "prettier --config \"./.prettierrc.js\" --write \"./src/**/*.{ts,tsx,scss}\""
   },
   "dependencies": {
+    "@alicloud/dysmsapi20170525": "^2.0.23",
+    "@alicloud/openapi-client": "^0.4.5",
+    "@alicloud/tea-util": "^1.4.5",
     "@chakra-ui/icons": "^2.0.17",
     "@chakra-ui/react": "^2.5.1",
+    "@chakra-ui/system": "^2.5.5",
+    "@dqbd/tiktoken": "^1.0.6",
     "@emotion/react": "^11.10.6",
     "@emotion/styled": "^11.10.6",
     "@next/font": "13.1.6",
@@ -24,7 +29,7 @@
     "eventsource-parser": "^0.1.0",
     "formidable": "^2.1.1",
     "framer-motion": "^9.0.6",
-    "gpt-token-utils": "^1.2.0",
+    "graphemer": "^1.4.0",
     "hyperdown": "^2.4.29",
     "immer": "^9.0.19",
     "jsonwebtoken": "^9.0.0",
@@ -37,6 +42,7 @@
     "nprogress": "^0.2.0",
     "openai": "^3.2.1",
     "papaparse": "^5.4.1",
+    "pg": "^8.10.0",
     "react": "18.2.0",
     "react-dom": "18.2.0",
     "react-hook-form": "^7.43.1",
@@ -60,11 +66,11 @@
     "@types/node": "18.14.0",
     "@types/nodemailer": "^6.4.7",
     "@types/papaparse": "^5.3.7",
+    "@types/pg": "^8.6.6",
     "@types/react": "18.0.28",
     "@types/react-dom": "18.0.11",
     "@types/react-syntax-highlighter": "^15.5.6",
     "@types/tunnel": "^0.0.3",
-    "@types/uuid": "^9.0.1",
     "eslint": "8.34.0",
     "eslint-config-next": "13.1.6",
     "husky": "^8.0.3",

public/docs/chatProblem.md

@@ -1,9 +1,10 @@
-## 常见问题
+### 常见问题
+**请求次数太多了**
+一般是因为自己的 openai 账号异常。请先检查自己的账号是否正常使用。
 **内容长度**
-单次最长 4000 tokens, 上下文最长 8000 tokens, 上下文超长时会被截断。
-
+chatgpt 上下文最长 4096 tokens,  上下文超长时会报错。
 **删除和复制**
-点击对话头像，可以选择复制或删除该条内容。
-
+电脑端：聊天内容右侧有复制和删除的图标。
+移动端：点击对话头像，可以选择复制或删除该条内容。
 **代理出错**
-服务器代理不稳定，可以过一会儿再尝试。 
+服务器代理不稳定，可以过一会儿再尝试。 或者可以访问国外服务器: [FastGpt](https://fastgpt.run/)

public/docs/intro.md

@@ -3,38 +3,41 @@
 [Git 仓库](https://github.com/c121914yu/FastGPT)
 
 ### 交流群/问题反馈
+
 扫码满了，加个小号，定时拉
-wx号: fastgpt123
+wx 号: fastgpt123
 ![](/imgs/wx300.jpg)
 
-
 ### 快速开始
-1. 使用邮箱注册账号。  
-2. 进入账号页面，添加关联账号，目前只有 openai 的账号可以添加，直接去 openai 官网，把 API Key 粘贴过来。  
+
+1. 使用手机号注册账号。
+2. 进入账号页面，添加关联账号，目前只有 openai 的账号可以添加，直接去 openai 官网，把 API Key 粘贴过来。
 3. 如果填写了自己的 openai 账号，使用时会直接用你的账号。如果没有填写，需要付费使用平台的账号。
-4. 进入模型页，创建一个模型，建议直接用 ChatGPT。    
-5. 在模型列表点击【对话】，即可使用 API 进行聊天。  
-
-### 定制 prompt
-
-1. 进入模型编辑页  
-2. 调整温度和提示词  
-3. 使用该模型对话。每次对话时，提示词和温度都会自动注入，方便管理个人的模型。建议把自己日常经常需要使用的 5~10 个方向预设好。
-
-### 知识库
-
-1. 创建模型时选择【知识库】  
-2. 进入模型编辑页  
-3. 导入数据，可以选择手动导入，或者选择文件导入。文件导入会自动调用 chatGPT 理解文件内容，并生成知识库。  
-4. 使用该模型对话。  
-
-注意：使用知识库模型对话时，tokens 消耗会加快。  
+4. 进入模型页，创建一个模型，建议直接用 ChatGPT。
+5. 在模型列表点击【对话】，即可使用 API 进行聊天。
 
 ### 价格表
+
 如果使用了自己的 Api Key，不会计费。可以在账号页，看到详细账单。单纯使用 chatGPT 模型进行对话，只有一个计费项目。使用知识库时，包含**对话**和**索引**生成两个计费项。
 | 计费项 | 价格: 元/ 1K tokens（包含上下文）|
-| --- | --- | 
+| --- | --- |
+| claude - 对话 | 免费 |
 | chatgpt - 对话 | 0.03 |
 | 知识库 - 对话 | 0.03 |
 | 知识库 - 索引 | 0.004 |
 | 文件拆分 | 0.03 |
+
+### 定制 prompt
+
+1. 进入模型编辑页
+2. 调整温度和提示词
+3. 使用该模型对话。每次对话时，提示词和温度都会自动注入，方便管理个人的模型。建议把自己日常经常需要使用的 5~10 个方向预设好。
+
+### 知识库
+
+1. 创建模型时选择【知识库】
+2. 进入模型编辑页
+3. 导入数据，可以选择手动导入，或者选择文件导入。文件导入会自动调用 chatGPT 理解文件内容，并生成知识库。
+4. 使用该模型对话。
+
+注意：使用知识库模型对话时，tokens 消耗会加快。

public/docs/versionIntro.md

@@ -1,3 +1,6 @@
-## Fast GPT V2.7
-* FastGpt Api 允许你将 Fast Gpt 的部分功能通过 api 的形式，将知识库接入到自己的应用中，例如：飞书、企业微信、客服助手.
-* 通过 csv 文件导入和导出你的问答对。你可以将你的 csv 文件放置在飞书文档上，以便团队共享。
+### Fast GPT V3.1
+
+- 优化 - 知识库搜索，会将上一个问题并入搜索范围。
+- 优化 - 模型结构设计，不再区分知识库和对话模型，而是通过开关的形式，手动选择手否需要进行知识库搜索。
+- 新增 - 模型共享市场，可以使用其他用户分享的模型。
+- 新增 - 邀请好友注册功能。

public/js/pdf.js

@@ -406,12 +406,12 @@ function getVerbosityLevel() {
 }
 function info(msg) {
   if (verbosity >= VerbosityLevel.INFOS) {
-    console.log(`Info: ${msg}`);
+    // console.log(`Info: ${msg}`);
   }
 }
 function warn(msg) {
   if (verbosity >= VerbosityLevel.WARNINGS) {
-    console.log(`Warning: ${msg}`);
+    // console.log(`Warning: ${msg}`);
   }
 }
 function unreachable(msg) {
@@ -4206,7 +4206,7 @@ function loadScript(src, removeScriptElement = false) {
   });
 }
 function deprecated(details) {
-  console.log("Deprecated API usage: " + details);
+  // console.log("Deprecated API usage: " + details);
 }
 let pdfDateStringRegex;
 class PDFDateString {

public/js/pdf.worker.js

@@ -1008,12 +1008,12 @@ function getVerbosityLevel() {
 }
 function info(msg) {
   if (verbosity >= VerbosityLevel.INFOS) {
-    console.log(`Info: ${msg}`);
+    // console.log(`Info: ${msg}`);
   }
 }
 function warn(msg) {
   if (verbosity >= VerbosityLevel.WARNINGS) {
-    console.log(`Warning: ${msg}`);
+    // console.log(`Warning: ${msg}`);
   }
 }
 function unreachable(msg) {

src/api/chat.ts

@@ -1,44 +1,36 @@
 import { GET, POST, DELETE } from './request';
-import type { ChatItemType, ChatSiteItemType } from '@/types/chat';
+import type { ChatItemType } from '@/types/chat';
 import type { InitChatResponse } from './response/chat';
 
-/**
- * 获取一个聊天框的ID
- */
-export const getChatSiteId = (modelId: string) => GET<string>(`/chat/generate?modelId=${modelId}`);
-
 /**
  * 获取初始化聊天内容
  */
-export const getInitChatSiteInfo = (chatId: string) =>
-  GET<InitChatResponse>(`/chat/init?chatId=${chatId}`);
+export const getInitChatSiteInfo = (modelId: string, chatId: '' | string) =>
+  GET<InitChatResponse>(`/chat/init?modelId=${modelId}&chatId=${chatId}`);
 
 /**
- * 发送 GPT3 prompt
+ * 获取历史记录
  */
-export const postGPT3SendPrompt = ({
-  chatId,
-  prompt
-}: {
-  prompt: ChatSiteItemType[];
-  chatId: string;
-}) =>
-  POST<string>(`/chat/gpt3`, {
-    chatId,
-    prompt: prompt.map((item) => ({
-      obj: item.obj,
-      value: item.value
-    }))
-  });
+export const getChatHistory = () =>
+  GET<{ _id: string; title: string; modelId: string }[]>('/chat/getHistory');
+
+/**
+ * 删除一条历史记录
+ */
+export const delChatHistoryById = (id: string) => GET(`/chat/removeHistory?id=${id}`);
 
 /**
  * 存储一轮对话
  */
-export const postSaveChat = (data: { chatId: string; prompts: ChatItemType[] }) =>
-  POST('/chat/saveChat', data);
+export const postSaveChat = (data: {
+  modelId: string;
+  newChatId: '' | string;
+  chatId: '' | string;
+  prompts: ChatItemType[];
+}) => POST<string>('/chat/saveChat', data);
 
 /**
  * 删除一句对话
  */
-export const delChatRecordByIndex = (chatId: string, index: number) =>
-  DELETE(`/chat/delChatRecordByIndex?chatId=${chatId}&index=${index}`);
+export const delChatRecordByIndex = (chatId: string, contentId: string) =>
+  DELETE(`/chat/delChatRecordByContentId?chatId=${chatId}&contentId=${contentId}`);

src/api/data.ts

@@ -1,25 +0,0 @@
-import { GET, POST, DELETE, PUT } from './request';
-import { RequestPaging } from '../types/index';
-import { Obj2Query } from '@/utils/tools';
-import type { DataListItem } from '@/types/data';
-import type { PagingData } from '../types/index';
-import type { DataItemSchema } from '@/types/mongoSchema';
-import type { CreateDataProps } from '@/pages/data/components/CreateDataModal';
-
-export const getDataList = () => GET<DataListItem[]>(`/data/getDataList`);
-
-export const postData = (data: CreateDataProps) => POST<string>(`/data/postData`, data);
-
-export const postSplitData = (dataId: string, text: string) =>
-  POST(`/data/splitData`, { dataId, text });
-
-export const updateDataName = (dataId: string, name: string) =>
-  PUT(`/data/putDataName?dataId=${dataId}&name=${name}`);
-
-export const delData = (dataId: string) => DELETE(`/data/delData?dataId=${dataId}`);
-
-type GetDataItemsProps = RequestPaging & {
-  dataId: string;
-};
-export const getDataItems = (data: GetDataItemsProps) =>
-  GET<PagingData<DataItemSchema>>(`/data/getDataItems?${Obj2Query(data)}`);

src/api/fetch.ts

@@ -1,4 +1,6 @@
 import { getToken } from '../utils/user';
+import { SYSTEM_PROMPT_HEADER, NEW_CHATID_HEADER } from '@/constants/chat';
+
 interface StreamFetchProps {
   url: string;
   data: any;
@@ -6,46 +8,56 @@ interface StreamFetchProps {
   abortSignal: AbortController;
 }
 export const streamFetch = ({ url, data, onMessage, abortSignal }: StreamFetchProps) =>
-  new Promise(async (resolve, reject) => {
-    try {
-      const res = await fetch(url, {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-          Authorization: getToken() || ''
-        },
-        body: JSON.stringify(data),
-        signal: abortSignal.signal
-      });
-      const reader = res.body?.getReader();
-      if (!reader) return;
-      const decoder = new TextDecoder();
-      let responseText = '';
+  new Promise<{ responseText: string; systemPrompt: string; newChatId: string }>(
+    async (resolve, reject) => {
+      try {
+        const res = await fetch(url, {
+          method: 'POST',
+          headers: {
+            'Content-Type': 'application/json',
+            Authorization: getToken() || ''
+          },
+          body: JSON.stringify(data),
+          signal: abortSignal.signal
+        });
+        const reader = res.body?.getReader();
+        if (!reader) return;
 
-      const read = async () => {
-        const { done, value } = await reader?.read();
-        if (done) {
-          if (res.status === 200) {
-            resolve(responseText);
-          } else {
-            try {
-              const parseError = JSON.parse(responseText);
-              reject(parseError?.message || '请求异常');
-            } catch (err) {
-              reject('请求异常');
+        const decoder = new TextDecoder();
+
+        const systemPrompt = decodeURIComponent(res.headers.get(SYSTEM_PROMPT_HEADER) || '');
+        const newChatId = decodeURIComponent(res.headers.get(NEW_CHATID_HEADER) || '');
+
+        let responseText = '';
+
+        const read = async () => {
+          try {
+            const { done, value } = await reader?.read();
+            if (done) {
+              if (res.status === 200) {
+                resolve({ responseText, systemPrompt, newChatId });
+              } else {
+                const parseError = JSON.parse(responseText);
+                reject(parseError?.message || '请求异常');
+              }
+
+              return;
             }
+            const text = decoder.decode(value).replace(/<br\/>/g, '\n');
+            responseText += text;
+            onMessage(text);
+            read();
+          } catch (err: any) {
+            if (err?.message === 'The user aborted a request.') {
+              return resolve({ responseText, systemPrompt, newChatId });
+            }
+            reject(typeof err === 'string' ? err : err?.message || '请求异常');
           }
-
-          return;
-        }
-        const text = decoder.decode(value).replace(/<br\/>/g, '\n');
-        res.status === 200 && onMessage(text);
-        responseText += text;
+        };
         read();
-      };
-      read();
-    } catch (err: any) {
-      console.log(err, '====');
-      reject(typeof err === 'string' ? err : err?.message || '请求异常');
+      } catch (err: any) {
+        console.log(err, '====');
+        reject(typeof err === 'string' ? err : err?.message || '请求异常');
+      }
     }
-  });
+  );

src/api/model.ts

@@ -1,7 +1,6 @@
 import { GET, POST, DELETE, PUT } from './request';
-import type { ModelSchema, ModelDataSchema, ModelSplitDataSchema } from '@/types/mongoSchema';
-import { ModelUpdateParams } from '@/types/model';
-import { TrainingItemType } from '../types/training';
+import type { ModelSchema, ModelDataSchema } from '@/types/mongoSchema';
+import { ModelUpdateParams, ShareModelItem } from '@/types/model';
 import { RequestPaging } from '../types/index';
 import { Obj2Query } from '@/utils/tools';
 
@@ -13,8 +12,7 @@ export const getMyModels = () => GET<ModelSchema[]>('/model/list');
 /**
  * 创建一个模型
  */
-export const postCreateModel = (data: { name: string; serviceModelName: string }) =>
-  POST<ModelSchema>('/model/create', data);
+export const postCreateModel = (data: { name: string }) => POST<string>('/model/create', data);
 
 /**
  * 根据 ID 删除模型
@@ -32,23 +30,10 @@ export const getModelById = (id: string) => GET<ModelSchema>(`/model/detail?mode
 export const putModelById = (id: string, data: ModelUpdateParams) =>
   PUT(`/model/update?modelId=${id}`, data);
 
-export const postTrainModel = (id: string, form: FormData) =>
-  POST(`/model/train/train?modelId=${id}`, form, {
-    headers: {
-      'content-type': 'multipart/form-data'
-    }
-  });
-
-export const putModelTrainingStatus = (id: string) =>
-  PUT(`/model/train/putTrainStatus?modelId=${id}`);
-
-export const getModelTrainings = (id: string) =>
-  GET<TrainingItemType[]>(`/model/train/getTrainings?modelId=${id}`);
-
 /* 模型 data */
-
 type GetModelDataListProps = RequestPaging & {
   modelId: string;
+  searchText: string;
 };
 /**
  * 获取模型的知识库数据
@@ -78,14 +63,18 @@ export const getWebContent = (url: string) => POST<string>(`/model/data/fetching
  */
 export const postModelDataInput = (data: {
   modelId: string;
-  data: { text: ModelDataSchema['text']; q: ModelDataSchema['q'] }[];
+  data: { a: ModelDataSchema['a']; q: ModelDataSchema['q'] }[];
 }) => POST<number>(`/model/data/pushModelDataInput`, data);
 
 /**
  * 拆分数据
  */
-export const postModelDataSplitData = (data: { modelId: string; text: string; prompt: string }) =>
-  POST(`/model/data/splitData`, data);
+export const postModelDataSplitData = (data: {
+  modelId: string;
+  chunks: string[];
+  prompt: string;
+  mode: 'qa' | 'subsection';
+}) => POST(`/model/data/splitData`, data);
 
 /**
  * json导入数据
@@ -96,10 +85,26 @@ export const postModelDataCsvData = (modelId: string, data: string[][]) =>
 /**
  * 更新模型数据
  */
-export const putModelDataById = (data: { dataId: string; text: string; q?: string }) =>
+export const putModelDataById = (data: { dataId: string; a: string; q?: string }) =>
   PUT('/model/data/putModelData', data);
 /**
  * 删除一条模型数据
  */
 export const delOneModelData = (dataId: string) =>
   DELETE(`/model/data/delModelDataById?dataId=${dataId}`);
+
+/* 共享市场 */
+/**
+ * 获取共享市场模型
+ */
+export const getShareModelList = (data: { searchText?: string } & RequestPaging) =>
+  POST(`/model/share/getModels`, data);
+/**
+ * 获取收藏的模型
+ */
+export const getCollectionModels = () => GET<ShareModelItem[]>(`/model/share/getCollection`);
+/**
+ * 收藏/取消收藏模型
+ */
+export const triggerModelCollection = (modelId: string) =>
+  POST<number>(`/model/share/collection?modelId=${modelId}`);

src/api/request.ts

@@ -1,6 +1,6 @@
 import axios, { Method, InternalAxiosRequestConfig, AxiosResponse } from 'axios';
 import { getToken, clearToken } from '@/utils/user';
-import { TOKEN_ERROR_CODE } from '@/constants/responseCode';
+import { TOKEN_ERROR_CODE } from '@/service/errorCode';
 
 interface ConfigType {
   headers?: { [key: string]: string };

src/api/response/chat.d.ts

@@ -7,7 +7,6 @@ export type InitChatResponse = {
   name: string;
   avatar: string;
   intro: string;
-  chatModel: ModelSchema.service.chatModel; // 对话模型名
-  modelName: ModelSchema.service.modelName; // 底层模型
+  chatModel: ModelSchema['chat']['chatModel']; // 对话模型名
   history: ChatItemType[];
 };

src/api/response/user.d.ts

@@ -1,5 +1,13 @@
 import type { UserType } from '@/types/user';
+import type { PromotionRecordSchema } from '@/types/mongoSchema';
 export interface ResLogin {
   token: string;
   user: UserType;
 }
+
+export interface PromotionRecordType {
+  _id: PromotionRecordSchema['_id'];
+  type: PromotionRecordSchema['type'];
+  createTime: PromotionRecordSchema['createTime'];
+  amount: PromotionRecordSchema['amount'];
+}

src/api/user.ts

@@ -1,50 +1,66 @@
 import { GET, POST, PUT } from './request';
 import { createHashPassword, Obj2Query } from '@/utils/tools';
-import { ResLogin } from './response/user';
-import { EmailTypeEnum } from '@/constants/common';
+import { ResLogin, PromotionRecordType } from './response/user';
+import { UserAuthTypeEnum } from '@/constants/common';
 import { UserType, UserUpdateParams } from '@/types/user';
 import type { PagingData, RequestPaging } from '@/types';
 import { BillSchema, PaySchema } from '@/types/mongoSchema';
 import { adaptBill } from '@/utils/adapt';
 
-export const sendCodeToEmail = ({ email, type }: { email: string; type: `${EmailTypeEnum}` }) =>
-  GET('/user/sendEmail', { email, type });
+export const sendAuthCode = ({
+  username,
+  type
+}: {
+  username: string;
+  type: `${UserAuthTypeEnum}`;
+}) => GET('/user/sendAuthCode', { username, type });
 
 export const getTokenLogin = () => GET<UserType>('/user/tokenLogin');
 
+/* get promotion init data */
+export const getPromotionInitData = () =>
+  GET<{
+    invitedAmount: number;
+    historyAmount: number;
+    residueAmount: number;
+  }>('/user/promotion/getPromotionData');
+
 export const postRegister = ({
-  email,
+  username,
   password,
-  code
+  code,
+  inviterId
 }: {
-  email: string;
+  username: string;
   code: string;
   password: string;
+  inviterId: string;
 }) =>
   POST<ResLogin>('/user/register', {
-    email,
+    username,
     code,
+    inviterId,
     password: createHashPassword(password)
   });
 
 export const postFindPassword = ({
-  email,
+  username,
   code,
   password
 }: {
-  email: string;
+  username: string;
   code: string;
   password: string;
 }) =>
   POST<ResLogin>('/user/updatePasswordByCode', {
-    email,
+    username,
     code,
     password: createHashPassword(password)
   });
 
-export const postLogin = ({ email, password }: { email: string; password: string }) =>
+export const postLogin = ({ username, password }: { username: string; password: string }) =>
   POST<ResLogin>('/user/loginByPassword', {
-    email,
+    username,
     password: createHashPassword(password)
   });
 
@@ -65,3 +81,7 @@ export const getPayCode = (amount: number) =>
   }>(`/user/getPayCode?amount=${amount}`);
 
 export const checkPayResult = (payId: string) => GET<number>(`/user/checkPayResult?payId=${payId}`);
+
+/* promotion records */
+export const getPromotionRecords = (data: RequestPaging) =>
+  GET<PromotionRecordType>(`/user/promotion/getPromotions?${Obj2Query(data)}`);

src/components/Icon/icons/chatting.svg

@@ -1,19 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" style="margin: auto; background: none; display: block; shape-rendering: auto;" width="204px" height="204px" viewBox="0 0 100 100" preserveAspectRatio="xMidYMid">
-<circle cx="84" cy="50" r="10" fill="#e15b64">
-    <animate attributeName="r" repeatCount="indefinite" dur="0.5681818181818182s" calcMode="spline" keyTimes="0;1" values="15;0" keySplines="0 0.5 0.5 1" begin="0s"></animate>
-    <animate attributeName="fill" repeatCount="indefinite" dur="2.272727272727273s" calcMode="discrete" keyTimes="0;0.25;0.5;0.75;1" values="#e15b64;#abbd81;#f8b26a;#f47e60;#e15b64" begin="0s"></animate>
-</circle><circle cx="16" cy="50" r="10" fill="#e15b64">
-  <animate attributeName="r" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="0;0;15;15;15" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="0s"></animate>
-  <animate attributeName="cx" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="16;16;16;50;84" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="0s"></animate>
-</circle><circle cx="50" cy="50" r="10" fill="#f47e60">
-  <animate attributeName="r" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="0;0;15;15;15" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-0.5681818181818182s"></animate>
-  <animate attributeName="cx" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="16;16;16;50;84" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-0.5681818181818182s"></animate>
-</circle><circle cx="84" cy="50" r="10" fill="#f8b26a">
-  <animate attributeName="r" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="0;0;15;15;15" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-1.1363636363636365s"></animate>
-  <animate attributeName="cx" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="16;16;16;50;84" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-1.1363636363636365s"></animate>
-</circle><circle cx="16" cy="50" r="10" fill="#abbd81">
-  <animate attributeName="r" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="0;0;15;15;15" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-1.7045454545454546s"></animate>
-  <animate attributeName="cx" repeatCount="indefinite" dur="2.272727272727273s" calcMode="spline" keyTimes="0;0.25;0.5;0.75;1" values="16;16;16;50;84" keySplines="0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1;0 0.5 0.5 1" begin="-1.7045454545454546s"></animate>
-</circle>
-<!-- [ldio] generated by https://loading.io/ --></svg>

src/components/Icon/icons/collectionLight.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682602070818" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2479" xmlns:xlink="http://www.w3.org/1999/xlink" width="128" height="128"><path d="M509.606998 143.114488c9.082866 0 17.327644 4.840238 20.996197 12.331863l97.262184 197.441814c5.613858 11.403724 16.663518 19.358907 29.438473 21.216207l223.738737 32.552393c8.420787 1.215688 15.604396 6.851035 18.23327 14.254655 2.520403 7.18361 0.595564 15.062044-5.084808 20.586874L730.253304 601.611947c-8.949836 8.751315-12.994965 21.171182-10.916631 33.370015l38.011732 222.060515c1.325182 7.737218-2.165316 15.426341-8.905834 19.978007-4.088108 2.741437-8.861832 4.155646-13.812587 4.155646-4.022617 0-7.999185-0.972141-11.425214-2.740414L528.149307 775.671215c-5.768377-3.006474-12.155854-4.552689-18.542308-4.552689-6.364965 0-12.727882 1.547239-18.518772 4.552689L296.254819 878.348736c-3.559059 1.855254-7.602142 2.828418-11.668761 2.828418-4.861728 0-9.723455-1.459235-13.546527-4.022617-6.961552-4.684696-10.475586-12.419867-9.127891-20.155039l38.011732-222.016513c2.078335-12.198833-1.988284-24.619724-10.939143-33.370015L125.02397 441.443038c-5.635347-5.492084-7.55814-13.348006-5.061272-20.453844 2.63092-7.481392 9.812483-13.116739 18.298761-14.332427l223.674269-32.552393c12.839423-1.857301 23.867594-9.813506 29.481452-21.216207l97.194646-197.396789C492.325403 147.965983 500.590648 143.114488 509.606998 143.114488M509.606998 104.904235c-24.043602 0-45.922912 13.226233-56.177464 33.95637L356.189863 336.302419l-223.674269 32.54216c-22.983457 3.304256-42.100864 18.718317-49.481971 39.659255-7.381108 21.048385-1.812275 44.23241 14.431687 60.033281l163.916257 160.125931-38.011732 222.016513c-3.868097 22.408359 6.03239 44.819788 25.458835 57.94676 10.69662 7.116071 23.204491 10.784624 35.757388 10.784624 10.298554 0 20.663622-2.475378 30.055526-7.337105l194.987926-102.7205L704.662463 912.072815c9.369392 4.861728 19.712971 7.337105 29.990035 7.337105 12.57541 0 25.082258-3.668553 35.778878-10.784624 19.426445-13.126972 29.305443-35.538401 25.460882-57.94676l-38.012755-222.016513 163.937746-160.125931c16.22145-15.812127 21.810748-38.984896 14.408151-60.033281-7.402597-20.940938-26.51898-36.353976-49.503461-39.659255L663.04767 336.302419l-97.240695-197.441814C555.619962 118.131491 533.695626 104.904235 509.606998 104.904235L509.606998 104.904235z"  p-id="2480"></path></svg>

src/components/Icon/icons/collectionSolid.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682602068431" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2339" xmlns:xlink="http://www.w3.org/1999/xlink" width="128" height="128"><path d="M335.008 916.629333c-35.914667 22.314667-82.88 10.773333-104.693333-25.557333a77.333333 77.333333 0 0 1-8.96-57.429333l46.485333-198.24a13.141333 13.141333 0 0 0-4.021333-12.864l-152.16-132.586667c-31.605333-27.52-35.253333-75.648-8.234667-107.733333a75.68 75.68 0 0 1 51.733333-26.752L354.848 339.2c4.352-0.362667 8.245333-3.232 10.026667-7.594667l76.938666-188.170666c16.032-39.2 60.618667-57.92 99.52-41.461334a76.309333 76.309333 0 0 1 40.832 41.461334l76.938667 188.16c1.781333 4.373333 5.674667 7.253333 10.026667 7.605333l199.712 16.277333c41.877333 3.413333 72.885333 40.458667 69.568 82.517334a76.938667 76.938667 0 0 1-26.08 51.978666l-152.16 132.586667c-3.541333 3.082667-5.141333 8.074667-4.021334 12.853333l46.485334 198.24c9.621333 41.013333-15.36 82.336-56.138667 92.224a75.285333 75.285333 0 0 1-57.525333-9.237333l-170.976-106.24a11.296 11.296 0 0 0-12.010667 0l-170.986667 106.24z" p-id="2340"></path></svg>

src/components/Icon/icons/dbModel.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682232349111" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="7070" xmlns:xlink="http://www.w3.org/1999/xlink" width="28" height="28"><path d="M512 102.6c110.7 0 215 12.3 293.9 34.7 35.8 10.2 65 22.1 84.5 34.7 18.6 12 21.3 19.7 21.6 20.6-0.2 0.9-3 8.6-21.6 20.6-19.5 12.5-48.7 24.5-84.5 34.7-78.9 22.3-183.2 34.7-293.9 34.7s-215-12.3-293.9-34.7c-35.8-10.2-65-22.1-84.5-34.7-18.6-12-21.3-19.7-21.6-20.6 0.2-0.9 3-8.6 21.6-20.6 19.5-12.5 48.7-24.5 84.5-34.7 78.9-22.4 183.2-34.7 293.9-34.7m0-40c-243 0-440 58.2-440 130s197 130 440 130 440-58.2 440-130-197-130-440-130zM112 190.4H72v641h40v-641z m840-0.3h-40v641h40v-641zM912 831v0.5c-0.2 0.9-3 8.6-21.6 20.6-19.5 12.5-48.7 24.5-84.5 34.7-78.9 22.3-183.2 34.6-293.9 34.6s-215-12.3-293.9-34.7c-35.8-10.2-65-22.1-84.5-34.7-18.6-12-21.3-19.7-21.6-20.6v-0.3l-40 0.3v0.1c0 71.8 197 130 440 130s440-58.2 440-130v-0.4l-40-0.1z m0-210.5v0.5c-0.2 0.9-3 8.6-21.6 20.6-19.5 12.5-48.7 24.5-84.5 34.7C727 698.6 622.7 711 512 711s-215-12.3-293.9-34.7c-35.8-10.2-65-22.1-84.5-34.7-18.6-12-21.3-19.7-21.6-20.6v-0.3l-40 0.3v0.1c0 71.8 197 130 440 130s440-58.2 440-130v-0.4l-40-0.2z m0-221.5v0.5c-0.2 0.9-3 8.6-21.6 20.6-19.5 12.5-48.7 24.5-84.5 34.7-78.9 22.3-183.2 34.7-293.9 34.7s-215-12.3-293.9-34.7c-35.8-10.2-65-22.1-84.5-34.7-18.6-12-21.3-19.7-21.6-20.6v-0.3l-40 0.3v0.1c0 71.8 197 130 440 130s440-58.2 440-130v-0.4l-40-0.2z" fill="" p-id="7071"></path></svg>

src/components/Icon/icons/delete.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1681997838051" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4520" xmlns:xlink="http://www.w3.org/1999/xlink" width="48" height="48"><path d="M898 178.7H665.3c4.3-9.8 6.7-20.6 6.7-32 0-44-36-80-80-80H432c-44 0-80 36-80 80 0 11.4 2.4 22.2 6.7 32H126c-13.2 0-24 10.8-24 24s10.8 24 24 24h772c13.2 0 24-10.8 24-24s-10.8-24-24-24z m-466 0c-8.5 0-16.5-3.4-22.6-9.4-6.1-6.1-9.4-14.1-9.4-22.6s3.4-16.5 9.4-22.6c6.1-6.1 14.1-9.4 22.6-9.4h160c8.5 0 16.5 3.4 22.6 9.4 6.1 6.1 9.4 14.1 9.4 22.6 0 8.5-3.4 16.5-9.4 22.6-6.1 6.1-14.1 9.4-22.6 9.4H432zM513 774.7c18.1 0 33-14.8 33-33v-334c0-18.1-14.9-33-33-33h-2c-18.1 0-33 14.8-33 33v334c0 18.2 14.8 33 33 33h2zM363 774.7c18.1 0 33-14.8 33-33v-334c0-18.1-14.9-33-33-33h-2c-18.1 0-33 14.8-33 33v334c0 18.2 14.8 33 33 33h2zM663 774.7c18.1 0 33-14.8 33-33v-334c0-18.1-14.9-33-33-33h-2c-18.1 0-33 14.8-33 33v334c0 18.2 14.8 33 33 33h2z" p-id="4521"></path><path d="M812 280.7c-13.3 0-24 10.7-24 24v530c0 41.9-34.1 76-76 76H312c-41.9 0-76-34.1-76-76v-530c0-13.3-10.7-24-24-24s-24 10.7-24 24v530c0 68.4 55.6 124 124 124h400c68.4 0 124-55.6 124-124v-530c0-13.2-10.7-24-24-24z" p-id="4522"></path></svg>

src/components/Icon/icons/export.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682957006954" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2644" xmlns:xlink="http://www.w3.org/1999/xlink" width="48" height="48"><path d="M942.1 593.9c-22.6 0-41 18.3-41 41v204.8c0 22.6-18.4 41-41 41H163.8c-22.6 0-41-18.4-41-41V634.9c0-22.6-18.3-41-41-41s-41 18.3-41 41v204.8c0 67.8 55.1 122.9 122.9 122.9H860c67.8 0 122.9-55.1 122.9-122.9V634.9c0.1-22.6-18.2-41-40.8-41z" p-id="2645"></path><path d="M309.3 363L471 201.3v515.5c0 22.5 18.4 41 41 41 22.5 0 41-18.4 41-41V201.3L714.7 363c15.9 15.9 42 15.9 57.9 0 15.9-15.9 15.9-42 0-57.9L541.5 73.9c-0.2-0.2-0.3-0.4-0.4-0.5-5.7-5.7-12.7-9.3-20.1-10.9-0.2-0.1-0.5-0.2-0.7-0.2-2.7-0.5-5.4-0.8-8.1-0.8-2.7 0-5.5 0.3-8.1 0.8-0.3 0.1-0.5 0.2-0.7 0.2-7.4 1.6-14.4 5.2-20.1 10.9-0.2 0.2-0.3 0.4-0.4 0.5L251.4 305.1c-15.9 15.9-15.9 42 0 57.9 15.9 15.9 42 15.9 57.9 0z" p-id="2646"></path></svg>

src/components/Icon/icons/history.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682232686576" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="8959" xmlns:xlink="http://www.w3.org/1999/xlink" width="28" height="28"><path d="M762.805186 140.938939c-14.335497-9.66922-33.725102-5.887081-43.373857 8.398274-9.648754 14.295588-5.897314 33.714869 8.398274 43.373857 106.369609 71.852468 169.864736 191.267185 169.864736 319.445496 0 212.414831-172.802648 385.217479-385.217479 385.217479S127.259382 724.571397 127.259382 512.156566c0-128.178311 63.494103-247.593028 169.864736-319.445496 14.295588-9.658987 18.047028-29.078269 8.398274-43.373857-9.658987-14.285355-29.088502-18.067494-43.373857-8.398274C138.575102 224.432539 64.791655 363.206162 64.791655 512.156566c0 246.851131 200.834074 447.685205 447.685205 447.685205S960.162066 759.007697 960.162066 512.156566C960.162066 363.206162 886.377596 224.432539 762.805186 140.938939z"  p-id="8960"></path><path d="M401.003 64.47136c-17.253966 0-31.234375 13.980409-31.234375 31.233352l0 30.470989c0 17.253966 13.980409 31.234375 31.234375 31.234375s31.234375-13.980409 31.234375-31.234375L432.237375 95.704712C432.236352 78.450746 418.256966 64.47136 401.003 64.47136z" p-id="8961"></path><path d="M623.950721 64.47136c-17.253966 0-31.233352 13.980409-31.233352 31.233352l0 30.470989c0 17.253966 13.980409 31.234375 31.233352 31.234375s31.234375-13.980409 31.234375-31.234375L655.185097 95.704712C655.184073 78.450746 641.204687 64.47136 623.950721 64.47136z"  p-id="8962"></path><path d="M426.012603 227.493248c11.214413 18.047028 41.970904 48.589648 86.157265 48.589648 43.963281 0 75.105558-30.318516 86.574774-48.223305 9.222035-14.396895 5.03262-33.358759-9.242502-42.763966-14.304797-9.405207-33.593096-5.398964-43.159986 8.764618-0.132006 0.193405-13.614066 19.754926-34.172287 19.754926-19.989263 0-32.423457-18.098193-33.267685-19.36914-9.160637-14.427594-28.264741-18.799158-42.834574-9.770528C421.416935 193.584973 416.912341 212.841549 426.012603 227.493248z"  p-id="8963"></path><path d="M510.781242 335.164502c-17.253966 0-31.233352 13.980409-31.233352 31.233352l0 208.225415c0 0.63445 0.149403 1.227967 0.187265 1.853208 0.067538 1.115404 0.148379 2.217505 0.333598 3.314489 0.168846 1.00898 0.416486 1.978051 0.679475 2.951215 0.258896 0.954745 0.529049 1.895163 0.87595 2.821255 0.36839 0.981351 0.801249 1.916653 1.26276 2.847861 0.431835 0.876973 0.880043 1.734504 1.393743 2.569522 0.532119 0.860601 1.115404 1.670036 1.727341 2.472308 0.610914 0.805342 1.235131 1.588171 1.926886 2.336208 0.688685 0.74292 1.424442 1.420349 2.181689 2.093684 0.741897 0.659009 1.484817 1.303692 2.298346 1.89721 0.899486 0.657986 1.850138 1.222851 2.819209 1.783623 0.544399 0.314155 1.00898 0.714268 1.577938 0.998747l208.225415 104.113219c4.484128 2.236947 9.252735 3.304256 13.94971 3.304256 11.44875 0 22.479991-6.334265 27.959795-17.274432 7.706519-15.433504 1.454118-34.192753-13.970176-41.909505l-190.961216-95.480608L542.015617 366.397854C542.015617 349.143888 528.035208 335.164502 510.781242 335.164502z"  p-id="8964"></path></svg>

src/components/Icon/icons/promotion.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682078370900" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="3577" xmlns:xlink="http://www.w3.org/1999/xlink" width="32" height="32"><path d="M941.312 888.704H628.032a32 32 0 0 1 0-64h313.28a32 32 0 0 1 0 64zM519.808 576.768c-158.976 0-288.384-129.344-288.384-288.384S360.832 0 519.808 0s288.384 129.344 288.384 288.384-129.408 288.384-288.384 288.384z m0-512.768C396.096 64 295.424 164.672 295.424 288.384s100.672 224.384 224.384 224.384c123.776 0 224.384-100.672 224.384-224.384S643.584 64 519.808 64z" p-id="3578"></path><path d="M763.264 606.528a31.552 31.552 0 0 1-16.96-4.864 427.2 427.2 0 0 0-100.544-45.952 32 32 0 0 1-21.184-40 31.744 31.744 0 0 1 39.936-21.184 492.16 492.16 0 0 1 115.712 52.864 32 32 0 0 1-16.96 59.136zM59.776 996.928a32 32 0 0 1-32-32 489.6 489.6 0 0 1 347.328-470.464 32 32 0 1 1 18.816 61.184 425.856 425.856 0 0 0-302.144 409.28 32 32 0 0 1-32 32zM964.224 879.68a32.128 32.128 0 0 1-24.32-11.2l-108.224-126.336a32 32 0 1 1 48.64-41.6l108.224 126.336a32 32 0 0 1-24.32 52.8z" p-id="3579"></path><path d="M856 1024a32 32 0 0 1-25.664-51.2l108.224-144.32a32.064 32.064 0 0 1 51.264 38.336L881.6 1011.2a32 32 0 0 1-25.6 12.8z" p-id="3580"></path></svg>

src/components/Icon/icons/shareMarket.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682599933100" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="5707" xmlns:xlink="http://www.w3.org/1999/xlink" width="128" height="128"><path d="M750.592 668.7232a159.6416 159.6416 0 0 0-128.4608 64.9216l-269.568-138.24a159.3344 159.3344 0 0 0 17.0496-128.6656l261.12-136.704a159.4368 159.4368 0 1 0-31.1296-53.0432L341.1456 412.3648a159.7952 159.7952 0 1 0-32.256 229.7856l286.72 146.9952a159.7952 159.7952 0 1 0 154.88-120.4224z m0-542.72a98.3552 98.3552 0 1 1-98.3552 98.3552 98.4576 98.4576 0 0 1 98.3552-98.304z m-534.2208 484.352A98.3552 98.3552 0 1 1 314.7264 512a98.4576 98.4576 0 0 1-98.3552 98.3552zM750.592 926.72a98.3552 98.3552 0 1 1 98.3552-98.3552A98.4576 98.4576 0 0 1 750.592 926.72z" p-id="5708"></path></svg>

src/components/Icon/icons/stop.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682424901088" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="3662" xmlns:xlink="http://www.w3.org/1999/xlink" width="32" height="32"><path d="M885.333333 85.333333H138.666667a53.393333 53.393333 0 0 0-53.333334 53.333334v746.666666a53.393333 53.393333 0 0 0 53.333334 53.333334h746.666666a53.393333 53.393333 0 0 0 53.333334-53.333334V138.666667a53.393333 53.393333 0 0 0-53.333334-53.333334z m-160 602.666667a37.373333 37.373333 0 0 1-37.333333 37.333333H336a37.373333 37.373333 0 0 1-37.333333-37.333333V336a37.373333 37.373333 0 0 1 37.333333-37.333333h352a37.373333 37.373333 0 0 1 37.333333 37.333333z"  p-id="3663"></path></svg>

src/components/Icon/icons/withdraw.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682079057126" class="icon" viewBox="0 0 1322 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2677" xmlns:xlink="http://www.w3.org/1999/xlink" width="36.1484375" height="28"><path d="M952.04654459 837.88839531H336.95615443A113.52706888 113.52706888 0 0 1 223.61160468 724.54384556v-419.79462838h728.43493991a113.52706888 113.52706888 0 0 1 113.34454973 113.34454975V724.54384556a113.52706888 113.52706888 0 0 1-113.34454973 113.34454975zM278.36742569 359.13999928v365.03880736a58.77124787 58.77124787 0 0 0 58.58872873 58.58872874h615.09039016a58.77124787 58.77124787 0 0 0 58.58872874-58.58872874V417.72872802a58.77124787 58.77124787 0 0 0-58.58872874-58.58872874z" p-id="2678"></path><path d="M278.36742569 350.37906772H223.61160468V297.44844068A111.51935577 111.51935577 0 0 1 334.94844068 186.11160469h334.01050924a111.51935577 111.51935577 0 0 1 111.33683598 111.33683599v49.09771996h-54.75582101V297.44844068A56.76353475 56.76353475 0 0 0 668.95894991 240.8674257H334.94844068A56.76353475 56.76353475 0 0 0 278.36742569 297.44844068zM1038.19570329 704.83175018H825.92563707A131.59649008 131.59649008 0 0 1 825.92563707 441.63877003h208.43715913v54.75582103H825.92563707a76.84066906 76.84066906 0 0 0 0 153.86385725h212.27006621z" p-id="2679"></path><path d="M889.80742792 600.43065117h-65.34194654a27.37791082 27.37791082 0 0 1 0-54.75582103h65.34194654a27.37791082 27.37791082 0 0 1-1e-8 54.75582103z" p-id="2680"></path></svg>

src/components/Icon/index.tsx

@@ -13,14 +13,31 @@ const map = {
   board: require('./icons/board.svg').default,
   develop: require('./icons/develop.svg').default,
   user: require('./icons/user.svg').default,
-  chatting: require('./icons/chatting.svg').default
+  promotion: require('./icons/promotion.svg').default,
+  delete: require('./icons/delete.svg').default,
+  withdraw: require('./icons/withdraw.svg').default,
+  dbModel: require('./icons/dbModel.svg').default,
+  history: require('./icons/history.svg').default,
+  stop: require('./icons/stop.svg').default,
+  shareMarket: require('./icons/shareMarket.svg').default,
+  collectionLight: require('./icons/collectionLight.svg').default,
+  collectionSolid: require('./icons/collectionSolid.svg').default,
+  export: require('./icons/export.svg').default
 };
 
 export type IconName = keyof typeof map;
 
 const MyIcon = ({ name, w = 'auto', h = 'auto', ...props }: { name: IconName } & IconProps) => {
   return map[name] ? (
-    <Icon as={map[name]} w={w} h={h} boxSizing={'content-box'} verticalAlign={'top'} {...props} />
+    <Icon
+      as={map[name]}
+      w={w}
+      h={h}
+      boxSizing={'content-box'}
+      verticalAlign={'top'}
+      fill={'currentcolor'}
+      {...props}
+    />
   ) : null;
 };
 

src/components/Layout/auth.tsx

@@ -7,7 +7,8 @@ import { useQuery } from '@tanstack/react-query';
 
 const unAuthPage: { [key: string]: boolean } = {
   '/': true,
-  '/login': true
+  '/login': true,
+  '/model/share': true
 };
 
 const Auth = ({ children }: { children: JSX.Element }) => {
@@ -33,7 +34,9 @@ const Auth = ({ children }: { children: JSX.Element }) => {
     {
       onError(error) {
         console.log('error->', error);
-        router.push('/login');
+        router.replace(
+          `/login?lastRoute=${encodeURIComponent(location.pathname + location.search)}`
+        );
         toast();
       },
       onSettled() {

src/components/Layout/index.tsx

@@ -20,18 +20,31 @@ const navbarList = [
     link: '/',
     activeLink: ['/']
   },
+  {
+    label: '共享',
+    icon: 'shareMarket',
+    link: '/model/share',
+    activeLink: ['/model/share']
+  },
   {
     label: '模型',
     icon: 'model',
     link: '/model/list',
     activeLink: ['/model/list', '/model/detail']
   },
+
   {
     label: '账号',
     icon: 'user',
     link: '/number/setting',
     activeLink: ['/number/setting']
   },
+  {
+    label: '邀请',
+    icon: 'promotion',
+    link: '/promotion',
+    activeLink: ['/promotion']
+  },
   {
     label: '开发',
     icon: 'develop',

src/components/Layout/navbarPhone.tsx

@@ -39,7 +39,7 @@ const NavbarPhone = ({
         px={7}
       >
         <Box onClick={onOpen}>
-          <MyIcon name="menu" width={'20px'} height={'20px'} color={'blackAlpha.600'}></MyIcon>
+          <MyIcon name="menu" width={'20px'} height={'20px'} color={'blackAlpha.700'}></MyIcon>
         </Box>
       </Flex>
       <Drawer isOpen={isOpen} placement="left" size={'xs'} onClose={onClose}>

src/components/Markdown/index.tsx

@@ -1,4 +1,4 @@
-import React, { memo, useMemo } from 'react';
+import React, { memo } from 'react';
 import ReactMarkdown from 'react-markdown';
 import { Prism as SyntaxHighlighter } from 'react-syntax-highlighter';
 import { Box, Flex, useColorModeValue } from '@chakra-ui/react';
@@ -13,12 +13,11 @@ import styles from './index.module.scss';
 import { codeLight } from './codeLight';
 
 const Markdown = ({ source, isChatting = false }: { source: string; isChatting?: boolean }) => {
-  const formatSource = useMemo(() => source, [source]);
   const { copyData } = useCopyData();
 
   return (
     <ReactMarkdown
-      className={`${styles.markdown} ${
+      className={`markdown ${styles.markdown} ${
         isChatting ? (source === '' ? styles.waitingAnimation : styles.animation) : ''
       }`}
       remarkPlugins={[remarkMath]}
@@ -32,6 +31,7 @@ const Markdown = ({ source, isChatting = false }: { source: string; isChatting?:
           return !inline || match ? (
             <Box my={3} borderRadius={'md'} overflow={'hidden'} backgroundColor={'#222'}>
               <Flex
+                className="code-header"
                 py={2}
                 px={5}
                 backgroundColor={useColorModeValue('#323641', 'gray.600')}
@@ -63,7 +63,7 @@ const Markdown = ({ source, isChatting = false }: { source: string; isChatting?:
       }}
       linkTarget="_blank"
     >
-      {formatSource}
+      {source}
     </ReactMarkdown>
   );
 };

src/components/Radio/index.tsx

@@ -0,0 +1,52 @@
+import React from 'react';
+import { Stack, Box, Flex, useTheme } from '@chakra-ui/react';
+import type { StackProps } from '@chakra-ui/react';
+
+// @ts-ignore
+interface Props extends StackProps {
+  list: { label: string; value: string | number }[];
+  value: string | number;
+  onChange: (e: string | number) => void;
+}
+
+const Radio = ({ list, value, onChange, ...props }: Props) => {
+  return (
+    <Stack {...props} spacing={5} direction={'row'}>
+      {list.map((item) => (
+        <Flex
+          key={item.value}
+          alignItems={'center'}
+          cursor={'pointer'}
+          userSelect={'none'}
+          _before={{
+            content: '""',
+            w: '16px',
+            h: '16px',
+            mr: 1,
+            borderRadius: '16px',
+            transition: '0.2s',
+            ...(value === item.value
+              ? {
+                  border: '5px solid',
+                  borderColor: 'blue.500'
+                }
+              : {
+                  border: '2px solid',
+                  borderColor: 'gray.200'
+                })
+          }}
+          _hover={{
+            _before: {
+              borderColor: 'blue.400'
+            }
+          }}
+          onClick={() => onChange(item.value)}
+        >
+          {item.label}
+        </Flex>
+      ))}
+    </Stack>
+  );
+};
+
+export default Radio;

src/constants/common.ts

@@ -1,6 +1,826 @@
-export enum EmailTypeEnum {
+export enum UserAuthTypeEnum {
   register = 'register',
   findPassword = 'findPassword'
 }
 
 export const PRICE_SCALE = 100000;
+
+export const htmlTemplate = `<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta http-equiv="X-UA-Compatible" content="IE=edge" />
+    <meta name="viewport" content="width=device-width initial-scale=1.0" />
+    <title>FastGpt</title>
+  </head>
+  <style>
+    .markdown > :first-child {
+      margin-top: 0 !important;
+    }
+    .markdown > :last-child {
+      margin-bottom: 0 !important;
+    }
+    .markdown a.absent {
+      color: #cc0000;
+    }
+    .markdown a.anchor {
+      bottom: 0;
+      cursor: pointer;
+      display: block;
+      left: 0;
+      margin-left: -30px;
+      padding-left: 30px;
+      position: absolute;
+      top: 0;
+    }
+    .markdown h1,
+    .markdown h2,
+    .markdown h3,
+    .markdown h4,
+    .markdown h5,
+    .markdown h6 {
+      cursor: text;
+      font-weight: bold;
+      margin: 10px 0;
+      padding: 0;
+      position: relative;
+    }
+    .markdown h1 .mini-icon-link,
+    .markdown h2 .mini-icon-link,
+    .markdown h3 .mini-icon-link,
+    .markdown h4 .mini-icon-link,
+    .markdown h5 .mini-icon-link,
+    .markdown h6 .mini-icon-link {
+      display: none;
+    }
+    .markdown h1:hover a.anchor,
+    .markdown h2:hover a.anchor,
+    .markdown h3:hover a.anchor,
+    .markdown h4:hover a.anchor,
+    .markdown h5:hover a.anchor,
+    .markdown h6:hover a.anchor {
+      line-height: 1;
+      margin-left: -22px;
+      padding-left: 0;
+      text-decoration: none;
+      top: 15%;
+    }
+    .markdown h1:hover a.anchor .mini-icon-link,
+    .markdown h2:hover a.anchor .mini-icon-link,
+    .markdown h3:hover a.anchor .mini-icon-link,
+    .markdown h4:hover a.anchor .mini-icon-link,
+    .markdown h5:hover a.anchor .mini-icon-link,
+    .markdown h6:hover a.anchor .mini-icon-link {
+      display: inline-block;
+    }
+    .markdown h1 tt,
+    .markdown h1 code,
+    .markdown h2 tt,
+    .markdown h2 code,
+    .markdown h3 tt,
+    .markdown h3 code,
+    .markdown h4 tt,
+    .markdown h4 code,
+    .markdown h5 tt,
+    .markdown h5 code,
+    .markdown h6 tt,
+    .markdown h6 code {
+      font-size: inherit;
+    }
+    .markdown h1 {
+      font-size: 28px;
+    }
+    .markdown h2 {
+      font-size: 24px;
+    }
+    .markdown h3 {
+      font-size: 18px;
+    }
+    .markdown h4 {
+      font-size: 16px;
+    }
+    .markdown h5 {
+      font-size: 14px;
+    }
+    .markdown h6 {
+      font-size: 12px;
+    }
+    .markdown p,
+    .markdown blockquote,
+    .markdown ul,
+    .markdown ol,
+    .markdown dl,
+    .markdown table,
+    .markdown pre {
+      margin: 10px 0;
+    }
+    .markdown > h2:first-child,
+    .markdown > h1:first-child,
+    .markdown > h1:first-child + h2,
+    .markdown > h3:first-child,
+    .markdown > h4:first-child,
+    .markdown > h5:first-child,
+    .markdown > h6:first-child {
+      margin-top: 0;
+      padding-top: 0;
+    }
+    .markdown a:first-child,
+    .markdown > h1,
+    .markdown a:first-child,
+    .markdown > h2,
+    .markdown a:first-child,
+    .markdown > h3,
+    .markdown a:first-child,
+    .markdown > h4,
+    .markdown a:first-child,
+    .markdown > h5,
+    .markdown a:first-child,
+    .markdown > h6 {
+      margin-top: 0;
+      padding-top: 0;
+    }
+    .markdown h1 + p,
+    .markdown h2 + p,
+    .markdown h3 + p,
+    .markdown h4 + p,
+    .markdown h5 + p,
+    .markdown h6 + p {
+      margin-top: 0;
+    }
+    .markdown li p.first {
+      display: inline-block;
+    }
+    .markdown ul,
+    .markdown ol {
+      padding-left: 2em;
+    }
+    .markdown ul.no-list,
+    .markdown ol.no-list {
+      list-style-type: none;
+      padding: 0;
+    }
+    .markdown ul li > :first-child,
+    .markdown ol li > :first-child {
+      margin-top: 0;
+    }
+    .markdown ul ul,
+    .markdown ul ol,
+    .markdown ol ol,
+    .markdown ol ul {
+      margin-bottom: 0;
+    }
+    .markdown dl {
+      padding: 0;
+    }
+    .markdown dl dt {
+      font-size: 14px;
+      font-style: italic;
+      font-weight: bold;
+      margin: 15px 0 5px;
+      padding: 0;
+    }
+    .markdown dl dt:first-child {
+      padding: 0;
+    }
+    .markdown dl dt > :first-child {
+      margin-top: 0;
+    }
+    .markdown dl dt > :last-child {
+      margin-bottom: 0;
+    }
+    .markdown dl dd {
+      margin: 0 0 15px;
+      padding: 0 15px;
+    }
+    .markdown dl dd > *:first-child {
+      margin-top: 0;
+    }
+    .markdown dl dd > *last-child {
+      margin-bottom: none;
+    }
+
+    .markdown blockquote {
+      border-left: solid 4px #dddddd;
+      color: #777777;
+      padding-left: 15px;
+    }
+
+    .markdown blockquote > * :first-child {
+      margin-top: 0;
+    }
+
+    .markdown blockquote > * :last-child {
+      margin-bottom: 0;
+    }
+
+    .markdown table th {
+      font-weight: bold;
+    }
+    .markdown table th,
+    .markdown table td {
+      padding: 6px 13px;
+    }
+    .markdown table tr {
+      background-color: #ffffff;
+    }
+    .markdown table tr:nth-child(2n) {
+      background-color: #f0f0f0;
+    }
+    .markdown img {
+      max-width: 100%;
+    }
+    .markdown span.frame {
+      display: block;
+      overflow: hidden;
+    }
+    .markdown span.frame > span {
+      border: 1px solid #dddddd;
+      display: block;
+      float: left;
+      margin: 13px 0 0;
+      overflow: hidden;
+      padding: 7px;
+      width: auto;
+    }
+    .markdown span.frame span img {
+      display: block;
+      float: left;
+    }
+    .markdown span.frame span span {
+      clear: both;
+      color: #333333;
+      display: block;
+      padding: 5px;
+    }
+
+    .markdown span.align-center {
+      clear: both;
+      display: block;
+      overflow: hidden;
+      text-align: center;
+    }
+
+    .markdown span.align-center > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+    }
+
+    .markdown span.align-center span img {
+      margin: 0 auto;
+      text-align: center;
+    }
+
+    .markdown span.align-right {
+      clear: both;
+      display: block;
+      overflow: hidden;
+    }
+
+    .markdown span.align-right > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+      text-align: right;
+    }
+
+    .markdown span.align-right img {
+      margin: 0;
+      text-align: right;
+    }
+
+    .markdown span.float-left {
+      display: block;
+      float: left;
+      margin-right: 13px;
+      overflow: hidden;
+    }
+
+    .markdown span.float-left > span {
+      margin: 13px auto;
+    }
+
+    .markdown span.float-right {
+      display: block;
+      float: right;
+      margin-left: 13px;
+      overflow: hidden;
+    }
+
+    .markdown span.float-right > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+      text-align: right;
+    }
+
+    .markdown code,
+    .markdown tt {
+      border: 1px solid #eaeaea;
+      border-radius: 3px;
+      margin: 0 2px;
+      padding: 0 5px;
+    }
+    .markdown pre > code {
+      background-color: transparent;
+      border: none;
+      margin: 0;
+      padding: 0;
+      white-space: pre;
+    }
+    .markdown .highlight pre,
+    .markdown pre {
+      border: 1px solid #ccc;
+      border-radius: 3px;
+      font-size: max(0.9em, 14px);
+      line-height: 19px;
+      overflow: auto;
+      padding: 6px 10px;
+    }
+
+    .markdown pre code,
+    .markdown pre tt {
+      background-color: #f8f8f8;
+      border: none;
+    }
+
+    .markdown {
+      text-align: justify;
+      overflow-y: hidden;
+      tab-size: 4;
+      word-spacing: normal;
+      word-break: break-all;
+    }
+    .markdown pre {
+      display: block;
+      width: 100%;
+      padding: 15px;
+      margin: 0;
+      border: none;
+      border-radius: none;
+      background-color: #222 !important;
+      overflow-x: auto;
+      color: #fff;
+    }
+    .markdown pre code {
+      background-color: #222 !important;
+      width: 100%;
+    }
+    .markdown a {
+      text-decoration: underline;
+      color: var(--chakra-colors-blue-600);
+    }
+    .markdown table {
+      border-collapse: separate;
+      border-spacing: 0;
+      color: #718096;
+    }
+    .markdown table thead tr:first-child th {
+      border-bottom-width: 1px;
+      border-left-width: 1px;
+      border-top-width: 1px;
+      border-color: #ccc;
+      background-color: #edf2f7;
+      overflow: hidden;
+    }
+    .markdown table thead tr:first-child th:first-child {
+      border-top-left-radius: 0.375rem;
+    }
+    .markdown table thead tr:first-child th:last-child {
+      border-right-width: 1px;
+      border-top-right-radius: 0.375rem;
+    }
+    .markdown td {
+      border-bottom-width: 1px;
+      border-left-width: 1px;
+      border-color: #ccc;
+    }
+    .markdown td:last-of-type {
+      border-right-width: 1px;
+    }
+    .markdown tbody tr:last-child {
+      overflow: hidden;
+    }
+    .markdown tbody tr:last-child td:first-child {
+      border-bottom-left-radius: 0.375rem;
+    }
+    .markdown tbody tr:last-child td:last-child {
+      border-bottom-right-radius: 0.375rem;
+    }
+    .markdown p {
+      text-align: justify;
+      white-space: pre-wrap;
+    }
+    code[class*='language-'] {
+      color: #d4d4d4;
+      text-shadow: none;
+      direction: ltr;
+      text-align: left;
+      white-space: pre;
+      word-spacing: normal;
+      word-break: normal;
+      line-height: 1.5;
+      -moz-tab-size: 4;
+      -o-tab-size: 4;
+      tab-size: 4;
+      -webkit-hyphens: none;
+      -moz-hyphens: none;
+      hyphens: none;
+    }
+
+    pre[class*='language-'] {
+      color: #d4d4d4;
+      text-shadow: none;
+      direction: ltr;
+      text-align: left;
+      white-space: pre;
+      word-spacing: normal;
+      word-break: normal;
+      line-height: 1.5;
+      -moz-tab-size: 4;
+      -o-tab-size: 4;
+      tab-size: 4;
+      -webkit-hyphens: none;
+      -moz-hyphens: none;
+      hyphens: none;
+      padding: 1em;
+      margin: 0.5em0;
+      overflow: auto;
+      background: #1e1e1e;
+    }
+
+    code[class*='language-'] ::selection,
+    code[class*='language-']::selection,
+    pre[class*='language-'] ::selection,
+    pre[class*='language-']::selection {
+      text-shadow: none;
+      background: #264f78;
+    }
+
+    :not(pre) > code[class*='language-'] {
+      padding: 0.1em 0.3em;
+      border-radius: 0.3em;
+      color: #db4c69;
+      background: #1e1e1e;
+    }
+
+    .namespace {
+      opacity: 0.7;
+    }
+
+    .doctype.doctype-tag {
+      color: #569cd6;
+    }
+
+    .doctype.name {
+      color: #9cdcfe;
+    }
+
+    comment {
+      color: #6a9955;
+    }
+
+    prolog {
+      color: #6a9955;
+    }
+
+    .language-html .language-css .token.punctuation,
+    .language-html .language-javascript .token.punctuation {
+      color: #d4d4d4;
+    }
+
+    punctuation {
+      color: #d4d4d4;
+    }
+
+    boolean {
+      color: #569cd6;
+    }
+
+    constant {
+      color: #9cdcfe;
+    }
+
+    inserted {
+      color: #b5cea8;
+    }
+
+    number {
+      color: #b5cea8;
+    }
+
+    property {
+      color: #9cdcfe;
+    }
+
+    symbol {
+      color: #b5cea8;
+    }
+
+    tag {
+      color: #569cd6;
+    }
+
+    unit {
+      color: #b5cea8;
+    }
+
+    attr-name {
+      color: #9cdcfe;
+    }
+
+    builtin {
+      color: #ce9178;
+    }
+
+    char {
+      color: #ce9178;
+    }
+
+    deleted {
+      color: #ce9178;
+    }
+
+    selector {
+      color: #d7ba7d;
+    }
+
+    string {
+      color: #ce9178;
+    }
+
+    .language-css .token.string.url {
+      text-decoration: underline;
+    }
+
+    entity {
+      color: #569cd6;
+    }
+
+    operator {
+      color: #d4d4d4;
+    }
+
+    operator.arrow {
+      color: #569cd6;
+    }
+
+    atrule {
+      color: #ce9178;
+    }
+
+    atrule.rule {
+      color: #c586c0;
+    }
+
+    atrule.url {
+      color: #9cdcfe;
+    }
+
+    atrule.url.function {
+      color: #dcdcaa;
+    }
+
+    atrule.url.punctuation {
+      color: #d4d4d4;
+    }
+    keyword {
+      color: #569cd6;
+    }
+
+    keyword.control-flow {
+      color: #c586c0;
+    }
+
+    keyword.module {
+      color: #c586c0;
+    }
+
+    function {
+      color: #dcdcaa;
+    }
+
+    function.maybe-class-name {
+      color: #dcdcaa;
+    }
+
+    regex {
+      color: #d16969;
+    }
+
+    important {
+      color: #569cd6;
+    }
+
+    italic {
+      font-style: italic;
+    }
+
+    class-name {
+      color: #4ec9b0;
+    }
+
+    maybe-class-name {
+      color: #4ec9b0;
+    }
+
+    console {
+      color: #9cdcfe;
+    }
+
+    parameter {
+      color: #9cdcfe;
+    }
+
+    interpolation {
+      color: #9cdcfe;
+    }
+    punctuation.interpolation-punctuation {
+      color: #569cd6;
+    }
+    exports.maybe-class-name {
+      color: #9cdcfe;
+    }
+    imports.maybe-class-name {
+      color: #9cdcfe;
+    }
+    variable {
+      color: #9cdcfe;
+    }
+    escape {
+      color: #d7ba7d;
+    }
+    tag.punctuation {
+      color: grey;
+    }
+    cdata {
+      color: grey;
+    }
+    attr-value {
+      color: #ce9178;
+    }
+    attr-value.punctuation {
+      color: #ce9178;
+    }
+    attr-value.punctuation.attr-equals {
+      color: #d4d4d4;
+    }
+    namespace {
+      color: #4ec9b0;
+    }
+    code[class*='language-javascript'],
+    code[class*='language-jsx'],
+    code[class*='language-tsx'],
+    code[class*='language-typescript'] {
+      color: #9cdcfe;
+    }
+
+    pre[class*='language-javascript'],
+    pre[class*='language-jsx'],
+    pre[class*='language-tsx'],
+    pre[class*='language-typescript'] {
+      color: #9cdcfe;
+    }
+
+    code[class*='language-css'] {
+      color: #ce9178;
+    }
+
+    pre[class*='language-css'] {
+      color: #ce9178;
+    }
+
+    code[class*='language-html'] {
+      color: #d4d4d4;
+    }
+
+    pre[class*='language-html'] {
+      color: #d4d4d4;
+    }
+
+    .language-regex .token.anchor {
+      color: #dcdcaa;
+    }
+
+    .language-html .token.punctuation {
+      color: grey;
+    }
+
+    pre[class*='language-'] > code[class*='language-'] {
+      position: relative;
+      z-index: 1;
+    }
+
+    .line-highlight.line-highlight {
+      background: #f7ebc6;
+      box-shadow: inset 5px 0 0 #f7d87c;
+      z-index: 0;
+    }
+    * {
+      box-sizing: border-box;
+    }
+    body,
+    h1,
+    h2,
+    h3,
+    h4,
+    hr,
+    p,
+    blockquote,
+    dl,
+    dt,
+    dd,
+    ul,
+    ol,
+    li,
+    pre,
+    form,
+    fieldset,
+    legend,
+    button,
+    input,
+    textarea,
+    th,
+    td,
+    svg  {
+      margin: 0;
+    }
+    body,
+    html {
+      font-size: 16px;
+      background-color: #fff;
+      color: rgba(0, 0, 0, 0.64);
+      font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif,
+        'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol';
+    }
+    pre,
+    code,
+    kbd,
+    samp {
+      font-family: SFMono-Regular, Menlo, Monaco, Consolas, monospace;
+      font-size: 1em;
+    }
+    ::-webkit-scrollbar,
+    ::-webkit-scrollbar {
+      width: 10px;
+      height: 10px;
+    }
+    ::-webkit-scrollbar-track,
+    ::-webkit-scrollbar-track {
+      background: transparent;
+      border-radius: 2px;
+    }
+    ::-webkit-scrollbar-thumb,
+    ::-webkit-scrollbar-thumb {
+      background: #bfbfbf;
+      border-radius: 10px;
+    }
+    ::-webkit-scrollbar-thumb:hover,
+    ::-webkit-scrollbar-thumb:hover {
+      background: #999;
+    }
+  </style>
+  <style>
+    .chat-item {
+      display: flex;
+      align-items: flex-start;
+      padding: 20px 16px;
+      border-bottom: 1px solid rgba(0, 0, 0, 0.1);
+      justify-content: center;
+    }
+    .chat-item img {
+      width: 30px;
+      max-height: 50px;
+      object-fit: contain;
+      margin-right: 10px;
+    }
+    .chat-item:nth-child(even) {
+      background-color: #f6f6f6;
+    }
+    .chat-item:nth-child(odd) {
+      background-color: #ffffff;
+    }
+    .markdown {
+      overflow-x: hidden;
+      max-width: 800px;
+      width: 100%;
+    }
+    @media (max-width: 900px) {
+      html {
+        font-size: 14px;
+      }
+      ::-webkit-scrollbar,
+      ::-webkit-scrollbar {
+        width: 2px;
+        height: 2px;
+      }
+      .chat-item img {
+        width: 20px;
+        max-height: 40px;
+        margin-right: 4px;
+      }
+    }
+  </style>
+  <body>{{CHAT_CONTENT}}</body>
+</html>
+`;

src/constants/data.ts

@@ -1,6 +0,0 @@
-import type { DataType } from '@/types/data';
-
-export const DataTypeTextMap: Record<DataType, string> = {
-  QA: '问答拆分',
-  abstract: '摘要总结'
-};

src/constants/model.ts

@@ -1,58 +1,67 @@
-import type { ServiceName, ModelDataType, ModelSchema } from '@/types/mongoSchema';
-import type { RedisModelDataItemType } from '@/types/redis';
+import type { ModelSchema } from '@/types/mongoSchema';
 
-export enum ChatModelNameEnum {
-  GPT35 = 'gpt-3.5-turbo',
-  VECTOR_GPT = 'VECTOR_GPT',
-  VECTOR = 'text-embedding-ada-002'
+export const embeddingModel = 'text-embedding-ada-002';
+export type EmbeddingModelType = 'text-embedding-ada-002';
+
+export enum OpenAiChatEnum {
+  'GPT35' = 'gpt-3.5-turbo',
+  'GPT4' = 'gpt-4',
+  'GPT432k' = 'gpt-4-32k'
+}
+export enum ClaudeEnum {
+  'Claude' = 'Claude'
 }
 
-export const ChatModelNameMap = {
-  [ChatModelNameEnum.GPT35]: 'gpt-3.5-turbo',
-  [ChatModelNameEnum.VECTOR_GPT]: 'gpt-3.5-turbo',
-  [ChatModelNameEnum.VECTOR]: 'text-embedding-ada-002'
-};
+export type ChatModelType = `${OpenAiChatEnum}` | `${ClaudeEnum}`;
 
-export type ModelConstantsData = {
-  serviceCompany: `${ServiceName}`;
+export type ChatModelItemType = {
+  chatModel: ChatModelType;
   name: string;
-  model: `${ChatModelNameEnum}`;
-  trainName: string; // 空字符串代表不能训练
-  maxToken: number;
   contextMaxToken: number;
+  systemMaxToken: number;
   maxTemperature: number;
-  price: number; // 多少钱 / 1token，单位: 0.00001元
+  price: number;
 };
 
-export const modelList: ModelConstantsData[] = [
-  {
-    serviceCompany: 'openai',
-    name: 'chatGPT',
-    model: ChatModelNameEnum.GPT35,
-    trainName: '',
-    maxToken: 4000,
-    contextMaxToken: 7500,
+export const ChatModelMap = {
+  [OpenAiChatEnum.GPT35]: {
+    chatModel: OpenAiChatEnum.GPT35,
+    name: 'ChatGpt',
+    contextMaxToken: 4096,
+    systemMaxToken: 3000,
     maxTemperature: 1.5,
     price: 3
   },
-  {
-    serviceCompany: 'openai',
-    name: '知识库',
-    model: ChatModelNameEnum.VECTOR_GPT,
-    trainName: 'vector',
-    maxToken: 4000,
-    contextMaxToken: 7000,
+  [OpenAiChatEnum.GPT4]: {
+    chatModel: OpenAiChatEnum.GPT4,
+    name: 'Gpt4',
+    contextMaxToken: 8000,
+    systemMaxToken: 4000,
+    maxTemperature: 1.5,
+    price: 30
+  },
+  [OpenAiChatEnum.GPT432k]: {
+    chatModel: OpenAiChatEnum.GPT432k,
+    name: 'Gpt4-32k',
+    contextMaxToken: 32000,
+    systemMaxToken: 4000,
+    maxTemperature: 1.5,
+    price: 30
+  },
+  [ClaudeEnum.Claude]: {
+    chatModel: ClaudeEnum.Claude,
+    name: 'Claude(免费体验)',
+    contextMaxToken: 9000,
+    systemMaxToken: 2500,
     maxTemperature: 1,
-    price: 3
+    price: 0
   }
-];
+};
 
-export enum TrainingStatusEnum {
-  pending = 'pending',
-  succeed = 'succeed',
-  errored = 'errored',
-  canceled = 'canceled'
-}
+export const chatModelList: ChatModelItemType[] = [
+  ChatModelMap[OpenAiChatEnum.GPT35],
+  ChatModelMap[ClaudeEnum.Claude]
+];
 
 export enum ModelStatusEnum {
   running = 'running',
@@ -80,7 +89,12 @@ export const formatModelStatus = {
   }
 };
 
-export const ModelDataStatusMap: Record<RedisModelDataItemType['status'], string> = {
+export enum ModelDataStatusEnum {
+  ready = 'ready',
+  waiting = 'waiting'
+}
+
+export const ModelDataStatusMap: Record<`${ModelDataStatusEnum}`, string> = {
   ready: '训练完成',
   waiting: '训练中'
 };
@@ -114,24 +128,24 @@ export const ModelVectorSearchModeMap: Record<
 };
 
 export const defaultModel: ModelSchema = {
-  _id: '',
-  userId: '',
-  name: '',
-  avatar: '',
+  _id: 'modelId',
+  userId: 'userId',
+  name: '模型名称',
+  avatar: '/icon/logo.png',
   status: ModelStatusEnum.pending,
   updateTime: Date.now(),
-  trainingTimes: 0,
-  systemPrompt: '',
-  intro: '',
-  temperature: 5,
-  search: {
-    mode: ModelVectorSearchModeEnum.hightSimilarity
+  chat: {
+    useKb: false,
+    searchMode: ModelVectorSearchModeEnum.hightSimilarity,
+    systemPrompt: '',
+    temperature: 0,
+    chatModel: OpenAiChatEnum.GPT35
   },
-  service: {
-    company: 'openai',
-    trainId: '',
-    chatModel: ChatModelNameEnum.GPT35,
-    modelName: ChatModelNameEnum.GPT35
+  share: {
+    isShare: false,
+    isShareDetail: false,
+    intro: '',
+    collection: 0
   },
   security: {
     domain: ['*'],

src/constants/redis.ts

@@ -1,6 +0,0 @@
-export const VecModelDataPrefix = 'model:data';
-export const VecModelDataIdx = `idx:${VecModelDataPrefix}:hash`;
-export enum ModelDataStatusEnum {
-  ready = 'ready',
-  waiting = 'waiting'
-}

src/constants/responseCode.ts

@@ -1,20 +0,0 @@
-export const ERROR_CODE: { [key: number]: string } = {
-  400: '请求失败',
-  401: '无权访问',
-  403: '紧张访问',
-  404: '请求不存在',
-  405: '请求方法错误',
-  406: '请求的格式错误',
-  410: '资源已删除',
-  422: '验证错误',
-  500: '服务器发生错误',
-  502: '网关错误',
-  503: '服务器暂时过载或维护',
-  504: '网关超时'
-};
-
-export const TOKEN_ERROR_CODE: { [key: number]: string } = {
-  506: '请先登录',
-  507: '请重新登录',
-  508: '登录已过期'
-};

src/constants/user.ts

@@ -20,3 +20,15 @@ export const BillTypeMap: Record<`${BillTypeEnum}`, string> = {
   [BillTypeEnum.vector]: '索引生成',
   [BillTypeEnum.return]: '退款'
 };
+
+export enum PromotionEnum {
+  invite = 'invite',
+  shareModel = 'shareModel',
+  withdraw = 'withdraw'
+}
+
+export const PromotionTypeMap = {
+  [PromotionEnum.invite]: '好友充值',
+  [PromotionEnum.shareModel]: '模型分享',
+  [PromotionEnum.withdraw]: '提现'
+};

src/hooks/usePagination.tsx

@@ -18,7 +18,7 @@ export const usePagination = <T = any,>({
   const [pageNum, setPageNum] = useState(1);
   const [total, setTotal] = useState(0);
   const [data, setData] = useState<T[]>([]);
-  const maxPage = useMemo(() => Math.ceil(total / pageSize), [pageSize, total]);
+  const maxPage = useMemo(() => Math.ceil(total / pageSize) || 1, [pageSize, total]);
 
   const { mutate, isLoading } = useMutation({
     mutationFn: async (num: number = pageNum) => {
@@ -41,10 +41,6 @@ export const usePagination = <T = any,>({
     }
   });
 
-  useEffect(() => {
-    mutate(1);
-  }, []);
-
   const Pagination = useCallback(() => {
     return (
       <Flex alignItems={'center'} justifyContent={'end'}>
@@ -93,6 +89,10 @@ export const usePagination = <T = any,>({
     );
   }, [maxPage, mutate, pageNum]);
 
+  useEffect(() => {
+    mutate(1);
+  }, []);
+
   return {
     pageNum,
     pageSize,

src/hooks/useSendCode.ts

@@ -1,6 +1,6 @@
 import { useState, useMemo, useCallback } from 'react';
-import { sendCodeToEmail } from '@/api/user';
-import { EmailTypeEnum } from '@/constants/common';
+import { sendAuthCode } from '@/api/user';
+import { UserAuthTypeEnum } from '@/constants/common';
 let timer: any;
 import { useToast } from './useToast';
 
@@ -19,11 +19,11 @@ export const useSendCode = () => {
   }, [codeCountDown]);
 
   const sendCode = useCallback(
-    async ({ email, type }: { email: string; type: `${EmailTypeEnum}` }) => {
+    async ({ username, type }: { username: string; type: `${UserAuthTypeEnum}` }) => {
       setCodeSending(true);
       try {
-        await sendCodeToEmail({
-          email,
+        await sendAuthCode({
+          username,
           type
         });
         setCodeCountDown(60);

src/pages/_app.tsx

@@ -51,8 +51,9 @@ export default function App({ Component, pageProps }: AppProps) {
         />
         <link rel="icon" href="/favicon.ico" />
       </Head>
-      <Script src="/js/qrcode.min.js" strategy="afterInteractive"></Script>
-      <Script src="/js/pdf.js" strategy="afterInteractive"></Script>
+      <Script src="/js/qrcode.min.js" strategy="lazyOnload"></Script>
+      <Script src="/js/pdf.js" strategy="lazyOnload"></Script>
+      <Script src="/js/html2pdf.bundle.min.js" strategy="lazyOnload"></Script>
       <QueryClientProvider client={queryClient}>
         <ChakraProvider theme={theme}>
           <ColorModeScript initialColorMode={theme.config.initialColorMode} />

src/pages/_error.tsx

@@ -0,0 +1,15 @@
+function Error({ statusCode }: { statusCode: number }) {
+  return (
+    <p>
+      {statusCode ? `An error ${statusCode} occurred on server` : 'An error occurred on client'}
+    </p>
+  );
+}
+
+Error.getInitialProps = ({ res, err }: { res: any; err: any }) => {
+  const statusCode = res ? res.statusCode : err ? err.statusCode : 404;
+  console.log(err);
+  return { statusCode };
+};
+
+export default Error;

src/pages/api/chat/chat.ts

@@ -0,0 +1,133 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { connectToDatabase } from '@/service/mongo';
+import { authChat } from '@/service/utils/auth';
+import { modelServiceToolMap } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
+import { jsonRes } from '@/service/response';
+import { PassThrough } from 'stream';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
+import { pushChatBill } from '@/service/events/pushBill';
+import { resStreamResponse } from '@/service/utils/chat';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
+
+/* 发送提示词 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  let step = 0; // step=1时，表示开始了流响应
+  const stream = new PassThrough();
+  stream.on('error', () => {
+    console.log('error: ', 'stream error');
+    stream.destroy();
+  });
+  res.on('close', () => {
+    stream.destroy();
+  });
+  res.on('error', () => {
+    console.log('error: ', 'request error');
+    stream.destroy();
+  });
+
+  try {
+    const { chatId, prompt, modelId } = req.body as {
+      prompt: ChatItemSimpleType;
+      modelId: string;
+      chatId: '' | string;
+    };
+
+    const { authorization } = req.headers;
+    if (!modelId || !prompt) {
+      throw new Error('缺少参数');
+    }
+
+    await connectToDatabase();
+    let startTime = Date.now();
+
+    const { model, showModelDetail, content, userOpenAiKey, systemAuthKey, userId } =
+      await authChat({
+        modelId,
+        chatId,
+        authorization
+      });
+
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
+    // 读取对话内容
+    const prompts = [...content, prompt];
+
+    // 使用了知识库搜索
+    if (model.chat.useKb) {
+      const { code, searchPrompt } = await searchKb({
+        userOpenAiKey,
+        prompts,
+        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
+        model,
+        userId
+      });
+
+      // search result is empty
+      if (code === 201) {
+        return res.send(searchPrompt?.value);
+      }
+
+      searchPrompt && prompts.unshift(searchPrompt);
+    } else {
+      // 没有用知识库搜索，仅用系统提示词
+      model.chat.systemPrompt &&
+        prompts.unshift({
+          obj: ChatRoleEnum.System,
+          value: model.chat.systemPrompt
+        });
+    }
+
+    // 计算温度
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
+    );
+
+    // 发出请求
+    const { streamResponse } = await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+      apiKey: userOpenAiKey || systemAuthKey,
+      temperature: +temperature,
+      messages: prompts,
+      stream: true,
+      res,
+      chatId
+    });
+
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
+
+    step = 1;
+
+    const { totalTokens, finishMessages } = await resStreamResponse({
+      model: model.chat.chatModel,
+      res,
+      stream,
+      chatResponse: streamResponse,
+      prompts,
+      systemPrompt:
+        showModelDetail && prompts[0].obj === ChatRoleEnum.System ? prompts[0].value : ''
+    });
+
+    // 只有使用平台的 key 才计费
+    pushChatBill({
+      isPay: !userOpenAiKey,
+      chatModel: model.chat.chatModel,
+      userId,
+      chatId,
+      textLen: finishMessages.map((item) => item.value).join('').length,
+      tokens: totalTokens
+    });
+  } catch (err: any) {
+    if (step === 1) {
+      // 直接结束流
+      console.log('error，结束');
+      stream.destroy();
+    } else {
+      res.status(500);
+      jsonRes(res, {
+        code: 500,
+        error: err
+      });
+    }
+  }
+}

src/pages/api/chat/chatGpt.ts

@@ -1,135 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase } from '@/service/mongo';
-import { getOpenAIApi, authChat } from '@/service/utils/chat';
-import { httpsAgent, openaiChatFilter } from '@/service/utils/tools';
-import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import type { ModelSchema } from '@/types/mongoSchema';
-import { PassThrough } from 'stream';
-import { modelList } from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { gpt35StreamResponse } from '@/service/utils/openai';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const { chatId, prompt } = req.body as {
-      prompt: ChatItemType;
-      chatId: string;
-    };
-
-    const { authorization } = req.headers;
-    if (!chatId || !prompt) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-    let startTime = Date.now();
-
-    const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
-
-    const model: ModelSchema = chat.modelId;
-    const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
-
-    // 读取对话内容
-    const prompts = [...chat.content, prompt];
-
-    // 如果有系统提示词，自动插入
-    if (model.systemPrompt) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
-
-    // 格式化文本内容成 chatgpt 格式
-    const map = {
-      Human: ChatCompletionRequestMessageRoleEnum.User,
-      AI: ChatCompletionRequestMessageRoleEnum.Assistant,
-      SYSTEM: ChatCompletionRequestMessageRoleEnum.System
-    };
-    const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
-      (item: ChatItemType) => ({
-        role: map[item.obj],
-        content: item.value
-      })
-    );
-    // console.log(formatPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 获取 chatAPI
-    const chatAPI = getOpenAIApi(userApiKey || systemKey);
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature: temperature,
-        // max_tokens: modelConstantsData.maxToken,
-        messages: formatPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: true,
-        stop: ['.!?。']
-      },
-      {
-        timeout: 40000,
-        responseType: 'stream',
-        httpsAgent: httpsAgent(!userApiKey)
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    step = 1;
-
-    const { responseContent } = await gpt35StreamResponse({
-      res,
-      stream,
-      chatResponse
-    });
-    const promptsContent = formatPrompts.map((item) => item.content).join('');
-
-    // 只有使用平台的 key 才计费
-    pushChatBill({
-      isPay: !userApiKey,
-      modelName: model.service.modelName,
-      userId,
-      chatId,
-      text: promptsContent + responseContent
-    });
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/chat/delChatRecordByContentId.ts

@@ -1,17 +1,17 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Chat } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
-    const { chatId, index } = req.query as { chatId: string; index: string };
+    const { chatId, contentId } = req.query as { chatId: string; contentId: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
       throw new Error('无权操作');
     }
-    if (!chatId || !index) {
+    if (!chatId || !contentId) {
       throw new Error('缺少参数');
     }
 
@@ -26,30 +26,13 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('找不到对话');
     }
 
-    // 重新计算 index，跳过已经被删除的内容
-    let unDeleteIndex = +index;
-    let deletedIndex = 0;
-    for (deletedIndex = 0; deletedIndex < chatRecord.content.length; deletedIndex++) {
-      if (!chatRecord.content[deletedIndex].deleted) {
-        unDeleteIndex--;
-        if (unDeleteIndex < 0) {
-          break;
-        }
-      }
-    }
-
-    // 删除最一条数据库记录, 也就是预发送的那一条
+    // 删除一条数据库记录
     await Chat.updateOne(
       {
         _id: chatId,
         userId
       },
-      {
-        $set: {
-          [`content.${deletedIndex}.deleted`]: true,
-          updateTime: Date.now()
-        }
-      }
+      { $pull: { content: { _id: contentId } } }
     );
 
     jsonRes(res);

src/pages/api/chat/generate.ts

@@ -1,54 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Model, Chat } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import type { ModelSchema } from '@/types/mongoSchema';
-
-/* 获取我的模型 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
-  try {
-    const { modelId } = req.query as {
-      modelId: string;
-    };
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('无权生成对话');
-    }
-
-    if (!modelId) {
-      throw new Error('缺少参数');
-    }
-
-    // 凭证校验
-    const userId = await authToken(authorization);
-
-    await connectToDatabase();
-
-    // 校验是否为用户的模型
-    const model = await Model.findOne<ModelSchema>({
-      _id: modelId,
-      userId
-    });
-
-    if (!model) {
-      throw new Error('无权使用该模型');
-    }
-
-    // 创建 chat 数据
-    const response = await Chat.create({
-      userId,
-      modelId,
-      content: []
-    });
-
-    jsonRes(res, {
-      data: response._id // 即聊天框的 ID
-    });
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/chat/getHistory.ts

@@ -0,0 +1,31 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { connectToDatabase, Chat } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+
+/* 获取历史记录 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  try {
+    const userId = await authToken(req.headers.authorization);
+
+    await connectToDatabase();
+
+    const data = await Chat.find(
+      {
+        userId
+      },
+      '_id title modelId'
+    )
+      .sort({ updateTime: -1 })
+      .limit(20);
+
+    jsonRes(res, {
+      data
+    });
+  } catch (err) {
+    jsonRes(res, {
+      code: 500,
+      error: err
+    });
+  }
+}

src/pages/api/chat/init.ts

@@ -1,9 +1,11 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Chat } from '@/service/mongo';
-import type { ChatPopulate } from '@/types/mongoSchema';
 import type { InitChatResponse } from '@/api/response/chat';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
+import { ChatItemType } from '@/types/chat';
+import { authModel } from '@/service/utils/auth';
+import mongoose from 'mongoose';
 
 /* 初始化我的聊天框，需要身份验证 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -11,43 +13,57 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     const { authorization } = req.headers;
     const userId = await authToken(authorization);
 
-    const { chatId } = req.query as { chatId: string };
+    const { modelId, chatId } = req.query as { modelId: string; chatId: '' | string };
 
-    if (!chatId) {
+    if (!modelId) {
       throw new Error('缺少参数');
     }
 
     await connectToDatabase();
 
-    // 获取 chat 数据
-    const chat = await Chat.findOne<ChatPopulate>({
-      _id: chatId,
-      userId
-    }).populate({
-      path: 'modelId',
-      options: {
-        strictPopulate: false
-      }
-    });
+    // 获取 model 数据
+    const { model } = await authModel({ modelId, userId, authUser: false, authOwner: false });
 
-    if (!chat) {
-      throw new Error('聊天框不存在');
+    // 历史记录
+    let history: ChatItemType[] = [];
+
+    if (chatId) {
+      // 获取 chat.content 数据
+      history = await Chat.aggregate([
+        {
+          $match: {
+            _id: new mongoose.Types.ObjectId(chatId),
+            userId: new mongoose.Types.ObjectId(userId)
+          }
+        },
+        {
+          $project: {
+            content: {
+              $slice: ['$content', -50] // 返回 content 数组的最后50个元素
+            }
+          }
+        },
+        { $unwind: '$content' },
+        {
+          $project: {
+            _id: '$content._id',
+            obj: '$content.obj',
+            value: '$content.value',
+            systemPrompt: '$content.systemPrompt'
+          }
+        }
+      ]);
     }
 
-    // filter 掉被 deleted 的内容
-    chat.content = chat.content.filter((item) => item.deleted !== true);
-
-    const model = chat.modelId;
     jsonRes<InitChatResponse>(res, {
       data: {
-        chatId: chat._id,
-        modelId: model._id,
+        chatId: chatId || '',
+        modelId: modelId,
         name: model.name,
         avatar: model.avatar,
-        intro: model.intro,
-        modelName: model.service.modelName,
-        chatModel: model.service.chatModel,
-        history: chat.content
+        intro: model.share.intro,
+        chatModel: model.chat.chatModel,
+        history
       }
     });
   } catch (err) {

src/pages/api/chat/removeHistory.ts

@@ -0,0 +1,27 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { ChatItemType } from '@/types/chat';
+import { connectToDatabase, Chat } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+
+/* 获取历史记录 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  try {
+    const { id } = req.query;
+    const userId = await authToken(req.headers.authorization);
+
+    await connectToDatabase();
+
+    await Chat.findOneAndRemove({
+      _id: id,
+      userId
+    });
+
+    jsonRes(res);
+  } catch (err) {
+    jsonRes(res, {
+      code: 500,
+      error: err
+    });
+  }
+}

src/pages/api/chat/saveChat.ts

@@ -2,34 +2,60 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { ChatItemType } from '@/types/chat';
 import { connectToDatabase, Chat } from '@/service/mongo';
+import { authModel } from '@/service/utils/auth';
+import { authToken } from '@/service/utils/auth';
+import mongoose from 'mongoose';
 
 /* 聊天内容存存储 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
-    const { chatId, prompts } = req.body as {
-      chatId: string;
+    const { chatId, modelId, prompts, newChatId } = req.body as {
+      newChatId: '' | string;
+      chatId: '' | string;
+      modelId: string;
       prompts: ChatItemType[];
     };
 
-    if (!chatId || !prompts) {
+    if (!prompts) {
       throw new Error('缺少参数');
     }
 
+    const userId = await authToken(req.headers.authorization);
+
     await connectToDatabase();
 
-    // 存入库
-    await Chat.findByIdAndUpdate(chatId, {
-      $push: {
-        content: {
-          $each: prompts.map((item) => ({
-            obj: item.obj,
-            value: item.value
-          }))
-        }
-      },
-      updateTime: new Date()
-    });
+    const content = prompts.map((item) => ({
+      _id: new mongoose.Types.ObjectId(item._id),
+      obj: item.obj,
+      value: item.value,
+      systemPrompt: item.systemPrompt
+    }));
 
+    await authModel({ modelId, userId, authOwner: false });
+
+    // 没有 chatId, 创建一个对话
+    if (!chatId) {
+      const { _id } = await Chat.create({
+        _id: newChatId ? new mongoose.Types.ObjectId(newChatId) : undefined,
+        userId,
+        modelId,
+        content,
+        title: content[0].value.slice(0, 20)
+      });
+      return jsonRes(res, {
+        data: _id
+      });
+    } else {
+      // 已经有记录，追加入库
+      await Chat.findByIdAndUpdate(chatId, {
+        $push: {
+          content: {
+            $each: content
+          }
+        },
+        updateTime: new Date()
+      });
+    }
     jsonRes(res);
   } catch (err) {
     jsonRes(res, {

src/pages/api/chat/vectorGpt.ts

@@ -1,200 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase } from '@/service/mongo';
-import { authChat } from '@/service/utils/chat';
-import { httpsAgent, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
-import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import type { ModelSchema } from '@/types/mongoSchema';
-import { PassThrough } from 'stream';
-import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
-import dayjs from 'dayjs';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const { chatId, prompt } = req.body as {
-      prompt: ChatItemType;
-      chatId: string;
-    };
-
-    const { authorization } = req.headers;
-    if (!chatId || !prompt) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-    const redis = await connectRedis();
-    let startTime = Date.now();
-
-    const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
-
-    const model: ModelSchema = chat.modelId;
-    const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
-
-    // 读取对话内容
-    const prompts = [...chat.content, prompt];
-
-    // 获取提示词的向量
-    const { vector: promptVector, chatAPI } = await openaiCreateEmbedding({
-      isPay: !userApiKey,
-      apiKey: userApiKey || systemKey,
-      userId,
-      text: prompt.value
-    });
-
-    const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${String(
-        chat.modelId._id
-      )}} @vector:[VECTOR_RANGE ${similarity} $blob]=>{$YIELD_DISTANCE_AS: score}`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'LIMIT',
-      '0',
-      '30',
-      'DIALECT',
-      '2'
-    ]);
-
-    const formatRedisPrompt: string[] = [];
-    // 格式化响应值，获取 qa
-    for (let i = 2; i < 61; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
-
-    /* 高相似度+退出，无法匹配时直接退出 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
-    ) {
-      return res.send('对不起，你的问题不在知识库中。');
-    }
-    /* 高相似度+无上下文，不添加额外知识 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.noContext
-    ) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    } else {
-      // 有匹配情况下，添加知识库内容。
-      // 系统提示词过滤，最多 2800 tokens
-      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
-
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
-          'YYYY/MM/DD HH:mm:ss'
-        )} ${systemPrompt}"`
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
-
-    // 格式化文本内容成 chatgpt 格式
-    const map = {
-      Human: ChatCompletionRequestMessageRoleEnum.User,
-      AI: ChatCompletionRequestMessageRoleEnum.Assistant,
-      SYSTEM: ChatCompletionRequestMessageRoleEnum.System
-    };
-    const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
-      (item: ChatItemType) => ({
-        role: map[item.obj],
-        content: item.value
-      })
-    );
-    // console.log(formatPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature: temperature,
-        // max_tokens: modelConstantsData.maxToken,
-        messages: formatPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: true
-      },
-      {
-        timeout: 40000,
-        responseType: 'stream',
-        httpsAgent: httpsAgent(!userApiKey)
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    step = 1;
-
-    const { responseContent } = await gpt35StreamResponse({
-      res,
-      stream,
-      chatResponse
-    });
-
-    const promptsContent = formatPrompts.map((item) => item.content).join('');
-    // 只有使用平台的 key 才计费
-    pushChatBill({
-      isPay: !userApiKey,
-      modelName: model.service.modelName,
-      userId,
-      chatId,
-      text: promptsContent + responseContent
-    });
-    // jsonRes(res);
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/data/delData.ts

@@ -1,47 +0,0 @@
-// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Data, DataItem } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import type { DataListItem } from '@/types/data';
-import type { PagingData } from '@/types';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('缺少登录凭证');
-    }
-
-    await authToken(authorization);
-
-    const { dataId } = req.query as { dataId: string };
-    if (!dataId) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-
-    await Data.findByIdAndUpdate(dataId, {
-      isDeleted: true
-    });
-
-    // 改变 dataItem 状态为 0
-    await DataItem.updateMany(
-      {
-        dataId
-      },
-      {
-        status: 0
-      }
-    );
-
-    jsonRes<PagingData<DataListItem>>(res);
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/data/getDataItems.ts

@@ -1,48 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, DataItem } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    let {
-      dataId,
-      pageNum = 1,
-      pageSize = 10
-    } = req.query as { dataId: string; pageNum: string; pageSize: string };
-    pageNum = +pageNum;
-    pageSize = +pageSize;
-
-    if (!dataId) {
-      throw new Error('参数错误');
-    }
-    await connectToDatabase();
-
-    const { authorization } = req.headers;
-
-    await authToken(authorization);
-
-    const dataItems = await DataItem.find({
-      dataId
-    })
-      .sort({ _id: -1 }) // 按照创建时间倒序排列
-      .skip((pageNum - 1) * pageSize)
-      .limit(pageSize);
-
-    jsonRes(res, {
-      data: {
-        pageNum,
-        pageSize,
-        data: dataItems,
-        total: await DataItem.countDocuments({
-          dataId
-        })
-      }
-    });
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/data/getDataList.ts

@@ -1,71 +0,0 @@
-// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Data, DataItem } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import type { DataListItem } from '@/types/data';
-import mongoose from 'mongoose';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('缺少登录凭证');
-    }
-
-    const userId = await authToken(authorization);
-
-    await connectToDatabase();
-
-    const datalist = await Data.aggregate<DataListItem>([
-      {
-        $match: {
-          userId: new mongoose.Types.ObjectId(userId),
-          isDeleted: false
-        }
-      },
-      {
-        $sort: { createTime: -1 } // 按照创建时间倒序排列
-      },
-      {
-        $lookup: {
-          from: 'dataitems',
-          localField: '_id',
-          foreignField: 'dataId',
-          as: 'items'
-        }
-      },
-      {
-        $addFields: {
-          totalData: {
-            $size: '$items' // 统计dataItem的总数
-          },
-          trainingData: {
-            $size: {
-              $filter: {
-                input: '$items',
-                as: 'item',
-                cond: { $ne: ['$$item.status', 0] } // 统计 status 不为0的数量
-              }
-            }
-          }
-        }
-      },
-      {
-        $project: {
-          items: 0 // 不返回 items 字段
-        }
-      }
-    ]);
-
-    jsonRes(res, {
-      data: datalist
-    });
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/data/postData.ts

@@ -1,35 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Data } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import type { DataType } from '@/types/data';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    let { name, type } = req.body as { name: string; type: DataType };
-    if (!name || !type) {
-      throw new Error('参数错误');
-    }
-    await connectToDatabase();
-
-    const { authorization } = req.headers;
-
-    const userId = await authToken(authorization);
-
-    // 生成 data 集合
-    const data = await Data.create({
-      userId,
-      name,
-      type
-    });
-
-    jsonRes(res, {
-      data: data._id
-    });
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/data/putDataName.ts

@@ -1,37 +0,0 @@
-// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Data } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import type { DataListItem } from '@/types/data';
-import type { PagingData } from '@/types';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('缺少登录凭证');
-    }
-
-    await authToken(authorization);
-
-    const { dataId, name } = req.query as { dataId: string; name: string };
-    if (!dataId || !name) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-
-    await Data.findByIdAndUpdate(dataId, {
-      name
-    });
-
-    jsonRes<PagingData<DataListItem>>(res);
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/data/splitData.ts

@@ -1,69 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, DataItem, Data } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { generateQA } from '@/service/events/generateQA';
-import { generateAbstract } from '@/service/events/generateAbstract';
-import { encode } from 'gpt-token-utils';
-
-/* 拆分数据成QA */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { text, dataId } = req.body as { text: string; dataId: string };
-    if (!text || !dataId) {
-      throw new Error('参数错误');
-    }
-    await connectToDatabase();
-
-    const { authorization } = req.headers;
-
-    const userId = await authToken(authorization);
-
-    const DataRecord = await Data.findById(dataId);
-
-    if (!DataRecord) {
-      throw new Error('找不到数据集');
-    }
-    const replaceText = text.replace(/[\\n]+/g, ' ');
-
-    // 文本拆分成 chunk
-    let chunks = replaceText.match(/[^!?.。]+[!?.。]/g) || [];
-
-    const dataItems: any[] = [];
-    let splitText = '';
-
-    chunks.forEach((chunk) => {
-      splitText += chunk;
-      const tokens = encode(splitText).length;
-      if (tokens >= 780) {
-        dataItems.push({
-          userId,
-          dataId,
-          type: DataRecord.type,
-          text: splitText,
-          status: 1
-        });
-        splitText = '';
-      }
-    });
-
-    // 批量插入数据
-    await DataItem.insertMany(dataItems);
-
-    try {
-      generateQA();
-      generateAbstract();
-    } catch (error) {
-      error;
-    }
-
-    jsonRes(res, {
-      data: { chunks, replaceText }
-    });
-  } catch (err) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/model/create.ts

@@ -2,15 +2,14 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { ModelStatusEnum, modelList, ChatModelNameEnum, ChatModelNameMap } from '@/constants/model';
+import { authToken } from '@/service/utils/auth';
+import { ModelStatusEnum } from '@/constants/model';
 import { Model } from '@/service/models/model';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { name, serviceModelName } = req.body as {
+    const { name } = req.body as {
       name: string;
-      serviceModelName: `${ChatModelNameEnum}`;
     };
     const { authorization } = req.headers;
 
@@ -18,47 +17,32 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       throw new Error('无权操作');
     }
 
-    if (!name || !serviceModelName) {
+    if (!name) {
       throw new Error('缺少参数');
     }
 
     // 凭证校验
     const userId = await authToken(authorization);
 
-    const modelItem = modelList.find((item) => item.model === serviceModelName);
-
-    if (!modelItem) {
-      throw new Error('模型不存在');
-    }
-
     await connectToDatabase();
 
     // 上限校验
     const authCount = await Model.countDocuments({
       userId
     });
-    if (authCount >= 20) {
-      throw new Error('上限 20 个模型');
+    if (authCount >= 30) {
+      throw new Error('上限 30 个模型');
     }
 
     // 创建模型
     const response = await Model.create({
       name,
       userId,
-      status: ModelStatusEnum.running,
-      service: {
-        company: modelItem.serviceCompany,
-        trainId: '',
-        chatModel: ChatModelNameMap[modelItem.model], // 聊天时用的模型
-        modelName: modelItem.model // 最底层的模型，不会变，用于计费等核心操作
-      }
+      status: ModelStatusEnum.running
     });
 
-    // 根据 id 获取模型信息
-    const model = await Model.findById(response._id);
-
     jsonRes(res, {
-      data: model
+      data: response._id
     });
   } catch (err) {
     jsonRes(res, {

src/pages/api/model/data/delModelDataById.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
+import { authToken } from '@/service/utils/auth';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
@@ -21,15 +21,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     // 凭证校验
     const userId = await authToken(authorization);
 
-    const redis = await connectRedis();
+    await PgClient.delete('modelData', {
+      where: [['user_id', userId], 'AND', ['id', dataId]]
+    });
 
-    // 校验是否为该用户的数据
-    const dataItemUserId = await redis.hGet(dataId, 'userId');
-    if (dataItemUserId !== userId) {
-      throw new Error('无权操作');
-    }
-    // 删除
-    await redis.del(dataId);
     jsonRes(res);
   } catch (err) {
     console.log(err);

src/pages/api/model/data/exportModelData.ts

@@ -1,9 +1,8 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataIdx } from '@/constants/redis';
+import { authToken } from '@/service/utils/auth';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
@@ -25,28 +24,23 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
-    // 从 redis 中获取数据
-    const searchRes = await redis.ft.search(
-      VecModelDataIdx,
-      `@modelId:{${modelId}} @userId:{${userId}}`,
-      {
-        RETURN: ['q', 'text'],
-        LIMIT: {
-          from: 0,
-          size: 10000
-        }
-      }
-    );
-
-    const data: [string, string][] = [];
-
-    searchRes.documents.forEach((item: any) => {
-      if (item.value.q && item.value.text) {
-        data.push([item.value.q.replace(/\n/g, '\\n'), item.value.text.replace(/\n/g, '\\n')]);
-      }
+    // 统计数据
+    const count = await PgClient.count('modelData', {
+      where: [['model_id', modelId], 'AND', ['user_id', userId]]
     });
+    // 从 pg 中获取所有数据
+    const pgData = await PgClient.select<{ q: string; a: string }>('modelData', {
+      where: [['model_id', modelId], 'AND', ['user_id', userId]],
+      fields: ['q', 'a'],
+      order: [{ field: 'id', mode: 'DESC' }],
+      limit: count
+    });
+
+    const data: [string, string][] = pgData.rows.map((item) => [
+      item.q.replace(/\n/g, '\\n'),
+      item.a.replace(/\n/g, '\\n')
+    ]);
 
     jsonRes(res, {
       data

src/pages/api/model/data/fetchingUrlData.ts

@@ -1,9 +1,9 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import axios from 'axios';
-import { httpsAgent } from '@/service/utils/tools';
+import { axiosConfig } from '@/service/utils/tools';
 
 /**
  * 读取网站的内容
@@ -22,7 +22,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     const data = await axios
       .get(url, {
-        httpsAgent: httpsAgent(false)
+        httpsAgent: axiosConfig().httpsAgent
       })
       .then((res) => res.data as string);
 

src/pages/api/model/data/getModelData.ts

@@ -1,23 +1,24 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataIdx } from '@/constants/redis';
-import { SearchOptions } from 'redis';
+import { authToken } from '@/service/utils/auth';
+import { PgClient } from '@/service/pg';
+import type { PgModelDataItemType } from '@/types/pg';
+import { authModel } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
     let {
       modelId,
       pageNum = 1,
-      pageSize = 10
+      pageSize = 10,
+      searchText = ''
     } = req.query as {
       modelId: string;
       pageNum: string;
       pageSize: string;
+      searchText: string;
     };
-
     const { authorization } = req.headers;
 
     pageNum = +pageNum;
@@ -35,34 +36,35 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
-    // 从 redis 中获取数据
-    const searchRes = await redis.ft.search(
-      VecModelDataIdx,
-      `@modelId:{${modelId}} @userId:{${userId}}`,
-      {
-        RETURN: ['q', 'text', 'status'],
-        LIMIT: {
-          from: (pageNum - 1) * pageSize,
-          size: pageSize
-        },
-        SORTBY: {
-          BY: 'modelId',
-          DIRECTION: 'DESC'
-        }
-      }
-    );
+    const { model } = await authModel({
+      userId,
+      modelId,
+      authOwner: false
+    });
+
+    const where: any = [
+      ...(model.share.isShareDetail ? [] : [['user_id', userId], 'AND']),
+      ['model_id', modelId],
+      ...(searchText ? ['AND', `(q LIKE '%${searchText}%' OR a LIKE '%${searchText}%')`] : [])
+    ];
+
+    const searchRes = await PgClient.select<PgModelDataItemType>('modelData', {
+      fields: ['id', 'q', 'a', 'status'],
+      where,
+      order: [{ field: 'id', mode: 'DESC' }],
+      limit: pageSize,
+      offset: pageSize * (pageNum - 1)
+    });
 
     jsonRes(res, {
       data: {
         pageNum,
         pageSize,
-        data: searchRes.documents.map((item) => ({
-          id: item.id,
-          ...item.value
-        })),
-        total: searchRes.total
+        data: searchRes.rows,
+        total: await PgClient.count('modelData', {
+          where
+        })
       }
     });
   } catch (err) {

src/pages/api/model/data/getSplitData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, SplitData, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 /* 拆分数据成QA */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/model/data/pushModelDataCsv.ts

@@ -1,13 +1,11 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { connectToDatabase, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { connectToDatabase } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
 import { generateVector } from '@/service/events/generateVector';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix, ModelDataStatusEnum } from '@/constants/redis';
-import { VecModelDataIdx } from '@/constants/redis';
-import { customAlphabet } from 'nanoid';
-const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890', 12);
+import { ModelDataStatusEnum } from '@/constants/model';
+import { PgClient } from '@/service/pg';
+import { authModel } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
@@ -29,28 +27,34 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
     // 验证是否是该用户的 model
-    const model = await Model.findOne({
-      _id: modelId,
-      userId
+    await authModel({
+      userId,
+      modelId
     });
 
-    if (!model) {
-      throw new Error('无权操作该模型');
-    }
-
     // 去重
     const searchRes = await Promise.allSettled(
       data.map(async ([q, a]) => {
+        if (!q || !a) {
+          return Promise.reject('q/a为空');
+        }
         try {
           q = q.replace(/\\n/g, '\n');
           a = a.replace(/\\n/g, '\n');
-          const redisSearch = await redis.ft.search(VecModelDataIdx, `@q:${q} @text:${a}`, {
-            RETURN: ['q', 'text']
+          const count = await PgClient.count('modelData', {
+            where: [
+              ['user_id', userId],
+              'AND',
+              ['model_id', modelId],
+              'AND',
+              ['q', q],
+              'AND',
+              ['a', a]
+            ]
           });
-          if (redisSearch.total > 0) {
+          if (count > 0) {
             return Promise.reject('已经存在');
           }
         } catch (error) {
@@ -62,35 +66,26 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
         });
       })
     );
-
+    // 过滤重复的内容
     const filterData = searchRes
       .filter((item) => item.status === 'fulfilled')
       .map<{ q: string; a: string }>((item: any) => item.value);
 
-    // 插入 redis
-    const insertRedisRes = await Promise.allSettled(
-      filterData.map((item) => {
-        return redis.sendCommand([
-          'HMSET',
-          `${VecModelDataPrefix}:${nanoid()}`,
-          'userId',
-          userId,
-          'modelId',
-          String(modelId),
-          'q',
-          item.q,
-          'text',
-          item.a,
-          'status',
-          ModelDataStatusEnum.waiting
-        ]);
-      })
-    );
+    // 插入 pg
+    const insertRes = await PgClient.insert('modelData', {
+      values: filterData.map((item) => [
+        { key: 'user_id', value: userId },
+        { key: 'model_id', value: modelId },
+        { key: 'q', value: item.q },
+        { key: 'a', value: item.a },
+        { key: 'status', value: ModelDataStatusEnum.waiting }
+      ])
+    });
 
     generateVector();
 
     jsonRes(res, {
-      data: insertRedisRes.filter((item) => item.status === 'fulfilled').length
+      data: insertRes.rowCount
     });
   } catch (err) {
     jsonRes(res, {

src/pages/api/model/data/pushModelDataInput.ts

@@ -1,17 +1,17 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { connectToDatabase, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { connectToDatabase } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
 import { ModelDataSchema } from '@/types/mongoSchema';
 import { generateVector } from '@/service/events/generateVector';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix, ModelDataStatusEnum } from '@/constants/redis';
+import { PgClient } from '@/service/pg';
+import { authModel } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
     const { modelId, data } = req.body as {
       modelId: string;
-      data: { text: ModelDataSchema['text']; q: ModelDataSchema['q'] }[];
+      data: { a: ModelDataSchema['a']; q: ModelDataSchema['q'] }[];
     };
     const { authorization } = req.headers;
 
@@ -27,41 +27,28 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
     // 验证是否是该用户的 model
-    const model = await Model.findOne({
-      _id: modelId,
-      userId
+    await authModel({
+      userId,
+      modelId
     });
 
-    if (!model) {
-      throw new Error('无权操作该模型');
-    }
-
-    const insertRes = await Promise.allSettled(
-      data.map((item) => {
-        return redis.sendCommand([
-          'HMSET',
-          `${VecModelDataPrefix}:${item.q.id}`,
-          'userId',
-          userId,
-          'modelId',
-          modelId,
-          'q',
-          item.q.text,
-          'text',
-          item.text,
-          'status',
-          ModelDataStatusEnum.waiting
-        ]);
-      })
-    );
+    // 插入记录
+    await PgClient.insert('modelData', {
+      values: data.map((item) => [
+        { key: 'user_id', value: userId },
+        { key: 'model_id', value: modelId },
+        { key: 'q', value: item.q },
+        { key: 'a', value: item.a },
+        { key: 'status', value: 'waiting' }
+      ])
+    });
 
     generateVector();
 
     jsonRes(res, {
-      data: insertRes.filter((item) => item.status === 'rejected').length
+      data: 0
     });
   } catch (err) {
     jsonRes(res, {

src/pages/api/model/data/putModelData.ts

@@ -1,13 +1,13 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { ModelDataStatusEnum } from '@/constants/redis';
+import { authToken } from '@/service/utils/auth';
+import { ModelDataStatusEnum } from '@/constants/model';
 import { generateVector } from '@/service/events/generateVector';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { dataId, text, q } = req.body as { dataId: string; text: string; q?: string };
+    const { dataId, a, q } = req.body as { dataId: string; a: string; q?: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
@@ -21,26 +21,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     // 凭证校验
     const userId = await authToken(authorization);
 
-    const redis = await connectRedis();
+    // 更新 pg 内容
+    await PgClient.update('modelData', {
+      where: [['id', dataId], 'AND', ['user_id', userId]],
+      values: [
+        { key: 'a', value: a },
+        ...(q
+          ? [
+              { key: 'q', value: q },
+              { key: 'status', value: ModelDataStatusEnum.waiting }
+            ]
+          : [])
+      ]
+    });
 
-    // 校验是否为该用户的数据
-    const dataItemUserId = await redis.hGet(dataId, 'userId');
-    if (dataItemUserId !== userId) {
-      throw new Error('无权操作');
-    }
-
-    // 更新
-    await redis.sendCommand([
-      'HMSET',
-      dataId,
-      ...(q ? ['q', q, 'status', ModelDataStatusEnum.waiting] : []),
-      'text',
-      text
-    ]);
-
-    if (q) {
-      generateVector();
-    }
+    q && generateVector();
 
     jsonRes(res);
   } catch (err) {

src/pages/api/model/data/splitData.ts

@@ -1,15 +1,21 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, SplitData, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
+import { generateVector } from '@/service/events/generateVector';
 import { generateQA } from '@/service/events/generateQA';
-import { encode } from 'gpt-token-utils';
+import { PgClient } from '@/service/pg';
 
 /* 拆分数据成QA */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
-    const { text, modelId, prompt } = req.body as { text: string; modelId: string; prompt: string };
-    if (!text || !modelId || !prompt) {
+    const { chunks, modelId, prompt, mode } = req.body as {
+      modelId: string;
+      chunks: string[];
+      prompt: string;
+      mode: 'qa' | 'subsection';
+    };
+    if (!chunks || !modelId || !prompt) {
       throw new Error('参数错误');
     }
     await connectToDatabase();
@@ -28,46 +34,31 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('无权操作该模型');
     }
 
-    const replaceText = text.replace(/(\\n|\n)+/g, ' ');
+    if (mode === 'qa') {
+      // 批量QA拆分插入数据
+      await SplitData.create({
+        userId,
+        modelId,
+        textList: chunks,
+        prompt
+      });
 
-    // 文本拆分成 chunk
-    const chunks = replaceText.match(/[^!?.。]+[!?.。]/g) || [];
+      generateQA();
+    } else if (mode === 'subsection') {
+      // 插入记录
+      await PgClient.insert('modelData', {
+        values: chunks.map((item) => [
+          { key: 'user_id', value: userId },
+          { key: 'model_id', value: modelId },
+          { key: 'q', value: item },
+          { key: 'a', value: '' },
+          { key: 'status', value: 'waiting' }
+        ])
+      });
 
-    const textList: string[] = [];
-    let splitText = '';
-
-    /* 取 3k ~ 4K tokens 内容 */
-    chunks.forEach((chunk) => {
-      const tokens = encode(splitText + chunk).length;
-      if (tokens >= 4000) {
-        // 超过 4000，不要这块内容
-        textList.push(splitText);
-        splitText = chunk;
-      } else if (tokens >= 3000) {
-        // 超过 3000，取内容
-        textList.push(splitText + chunk);
-        splitText = '';
-      } else {
-        //没超过 3000，继续添加
-        splitText += chunk;
-      }
-    });
-
-    if (splitText) {
-      textList.push(splitText);
+      generateVector();
     }
 
-    // 批量插入数据
-    await SplitData.create({
-      userId,
-      modelId,
-      rawText: text,
-      textList,
-      prompt
-    });
-
-    generateQA();
-
     jsonRes(res);
   } catch (err) {
     jsonRes(res, {

src/pages/api/model/del.ts

@@ -1,18 +1,14 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { Chat, Model, Training, connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { getUserApiOpenai } from '@/service/utils/openai';
-import { TrainingStatusEnum } from '@/constants/model';
-import { TrainingItemType } from '@/types/training';
-import { httpsAgent } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataIdx } from '@/constants/redis';
+import { Chat, Model, connectToDatabase } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+import { PgClient } from '@/service/pg';
+import { authModel } from '@/service/utils/auth';
 
 /* 获取我的模型 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { modelId } = req.query;
+    const { modelId } = req.query as { modelId: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
@@ -26,63 +22,24 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     // 凭证校验
     const userId = await authToken(authorization);
 
+    await connectToDatabase();
+
     // 验证是否是该用户的 model
-    const model = await Model.findOne({
-      _id: modelId,
+    await authModel({
+      modelId,
       userId
     });
 
-    if (!model) {
-      throw new Error('无权操作该模型');
-    }
-
-    await connectToDatabase();
-    const redis = await connectRedis();
-
-    // 获取 redis 中模型关联的所有数据
-    const searchRes = await redis.ft.search(
-      VecModelDataIdx,
-      `@modelId:{${modelId}} @userId:{${userId}}`,
-      {
-        LIMIT: {
-          from: 0,
-          size: 10000
-        }
-      }
-    );
-    // 删除 redis 内容
-    await Promise.all(searchRes.documents.map((item) => redis.del(item.id)));
+    // 删除 pg 中所有该模型的数据
+    await PgClient.delete('modelData', {
+      where: [['user_id', userId], 'AND', ['model_id', modelId]]
+    });
 
     // 删除对应的聊天
     await Chat.deleteMany({
       modelId
     });
 
-    // 查看是否正在训练
-    const training: TrainingItemType | null = await Training.findOne({
-      modelId,
-      status: TrainingStatusEnum.pending
-    });
-
-    // 如果正在训练，需要删除openai上的相关信息
-    if (training) {
-      const { openai } = await getUserApiOpenai(userId);
-      // 获取训练记录
-      const tuneRecord = await openai.retrieveFineTune(training.tuneId, {
-        httpsAgent: httpsAgent(false)
-      });
-
-      // 删除训练文件
-      openai.deleteFile(tuneRecord.data.training_files[0].id, { httpsAgent: httpsAgent(false) });
-      // 取消训练
-      openai.cancelFineTune(training.tuneId, { httpsAgent: httpsAgent(false) });
-    }
-
-    // 删除对应训练记录
-    await Training.deleteMany({
-      modelId
-    });
-
     // 删除模型
     await Model.deleteOne({
       _id: modelId,

src/pages/api/model/detail.tsx

@@ -1,9 +1,8 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { Model } from '@/service/models/model';
-import type { ModelSchema } from '@/types/mongoSchema';
+import { authToken } from '@/service/utils/auth';
+import { authModel } from '@/service/utils/auth';
 
 /* 获取我的模型 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
@@ -14,7 +13,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       throw new Error('无权操作');
     }
 
-    const { modelId } = req.query;
+    const { modelId } = req.query as { modelId: string };
 
     if (!modelId) {
       throw new Error('参数错误');
@@ -25,16 +24,12 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
 
     await connectToDatabase();
 
-    // 根据 userId 获取模型信息
-    const model = await Model.findOne<ModelSchema>({
+    const { model } = await authModel({
+      modelId,
       userId,
-      _id: modelId
+      authOwner: false
     });
 
-    if (!model) {
-      throw new Error('模型不存在');
-    }
-
     jsonRes(res, {
       data: model
     });

src/pages/api/model/list.ts

@@ -1,10 +1,10 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { Model } from '@/service/models/model';
 
-/* 获取我的模型 */
+/* 获取模型列表 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
     const { authorization } = req.headers;

src/pages/api/model/share/collection.ts

@@ -0,0 +1,44 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { connectToDatabase, Collection, Model } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+
+/* 模型收藏切换 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
+  try {
+    const { modelId } = req.query as { modelId: string };
+
+    if (!modelId) {
+      throw new Error('缺少参数');
+    }
+    // 凭证校验
+    const userId = await authToken(req.headers.authorization);
+
+    await connectToDatabase();
+
+    const collectionRecord = await Collection.findOne({
+      userId,
+      modelId
+    });
+
+    if (collectionRecord) {
+      await Collection.findByIdAndRemove(collectionRecord._id);
+    } else {
+      await Collection.create({
+        userId,
+        modelId
+      });
+    }
+
+    await Model.findByIdAndUpdate(modelId, {
+      'share.collection': await Collection.countDocuments({ modelId })
+    });
+
+    jsonRes(res);
+  } catch (err) {
+    jsonRes(res, {
+      code: 500,
+      error: err
+    });
+  }
+}

src/pages/api/model/share/getCollection.ts

@@ -0,0 +1,37 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { connectToDatabase, Collection } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+import type { ShareModelItem } from '@/types/model';
+
+/* 获取模型列表 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
+  try {
+    // 凭证校验
+    const userId = await authToken(req.headers.authorization);
+
+    await connectToDatabase();
+
+    // get my collections
+    const collections = await Collection.find({
+      userId
+    }).populate('modelId', '_id avatar name userId share');
+
+    jsonRes<ShareModelItem[]>(res, {
+      data: collections
+        .map((item: any) => ({
+          _id: item.modelId?._id,
+          avatar: item.modelId?.avatar || '/icon/logo.png',
+          name: item.modelId?.name || '',
+          userId: item.modelId?.userId || '',
+          share: item.modelId?.share || {},
+          isCollection: true
+        }))
+        .filter((item) => item.share.isShare)
+    });
+  } catch (err) {
+    jsonRes(res, {
+      data: []
+    });
+  }
+}

src/pages/api/model/share/getModels.ts

@@ -0,0 +1,60 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { connectToDatabase, Collection, Model } from '@/service/mongo';
+import { authToken } from '@/service/utils/auth';
+import type { PagingData } from '@/types';
+import type { ShareModelItem } from '@/types/model';
+
+/* 获取模型列表 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
+  try {
+    const {
+      searchText = '',
+      pageNum = 1,
+      pageSize = 20
+    } = req.body as { searchText: string; pageNum: number; pageSize: number };
+
+    await connectToDatabase();
+
+    const regex = new RegExp(searchText, 'i');
+
+    const where = {
+      $and: [
+        { 'share.isShare': true },
+        { $or: [{ name: { $regex: regex } }, { 'share.intro': { $regex: regex } }] }
+      ]
+    };
+
+    // 获取被分享的模型
+    const [models, total] = await Promise.all([
+      Model.find(where, '_id avatar name userId share')
+        .sort({
+          'share.collection': -1
+        })
+        .limit(pageSize)
+        .skip((pageNum - 1) * pageSize),
+      Model.countDocuments(where)
+    ]);
+
+    jsonRes<PagingData<ShareModelItem>>(res, {
+      data: {
+        pageNum,
+        pageSize,
+        data: models.map((item) => ({
+          _id: item._id,
+          avatar: item.avatar || '/icon/logo.png',
+          name: item.name,
+          userId: item.userId,
+          share: item.share,
+          isCollection: false
+        })),
+        total
+      }
+    });
+  } catch (err) {
+    jsonRes(res, {
+      code: 500,
+      error: err
+    });
+  }
+}

src/pages/api/model/train/getTrainings.ts

@@ -1,52 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Training } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-
-// 关闭next默认的bodyParser处理方式
-export const config = {
-  api: {
-    bodyParser: false
-  }
-};
-
-/* 获取模型训练记录 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('无权操作');
-    }
-    const { modelId } = req.query;
-    if (!modelId) {
-      throw new Error('参数错误');
-    }
-    await authToken(authorization);
-
-    await connectToDatabase();
-
-    /* 获取 modelId 下的 training 记录 */
-    const records = await Training.find({
-      modelId
-    });
-
-    jsonRes(res, {
-      data: records
-    });
-  } catch (err: any) {
-    /* 清除上传的文件，关闭训练记录 */
-    // @ts-ignore
-    if (openai) {
-      // @ts-ignore
-      uploadFileId && openai.deleteFile(uploadFileId);
-      // @ts-ignore
-      trainId && openai.cancelFineTune(trainId);
-    }
-
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/model/train/putTrainStatus.ts

@@ -1,106 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Model, Training } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { getUserApiOpenai } from '@/service/utils/openai';
-import type { ModelSchema } from '@/types/mongoSchema';
-import { TrainingItemType } from '@/types/training';
-import { ModelStatusEnum, TrainingStatusEnum } from '@/constants/model';
-import { OpenAiTuneStatusEnum } from '@/service/constants/training';
-import { httpsAgent } from '@/service/utils/tools';
-
-/* 更新训练状态 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('无权操作');
-    }
-    const { modelId } = req.query as { modelId: string };
-    if (!modelId) {
-      throw new Error('参数错误');
-    }
-    const userId = await authToken(authorization);
-
-    await connectToDatabase();
-
-    // 获取模型
-    const model = await Model.findById<ModelSchema>(modelId);
-
-    if (!model || model.status !== 'training') {
-      throw new Error('模型不在训练中');
-    }
-
-    // 查询正在训练中的训练记录
-    const training: TrainingItemType | null = await Training.findOne({
-      modelId,
-      status: 'pending'
-    });
-
-    if (!training) {
-      throw new Error('找不到训练记录');
-    }
-
-    // 用户的 openai 实例
-    const { openai } = await getUserApiOpenai(userId);
-
-    // 获取 openai 的训练情况
-    const { data } = await openai.retrieveFineTune(training.tuneId, {
-      httpsAgent: httpsAgent(false)
-    });
-    // console.log(data);
-    if (data.status === OpenAiTuneStatusEnum.succeeded) {
-      // 删除训练文件
-      openai.deleteFile(data.training_files[0].id, { httpsAgent: httpsAgent(false) });
-
-      // 更新模型状态和模型内容
-      await Model.findByIdAndUpdate(modelId, {
-        status: ModelStatusEnum.running,
-        updateTime: new Date(),
-        service: {
-          ...model.service,
-          trainId: data.fine_tuned_model, // 训练完后，再次训练和对话使用的 model 是一样的
-          chatModel: data.fine_tuned_model
-        }
-      });
-      // 更新训练数据
-      await Training.findByIdAndUpdate(training._id, {
-        status: TrainingStatusEnum.succeed
-      });
-
-      return jsonRes(res, {
-        data: '模型微调完成'
-      });
-    }
-
-    /* 取消微调 */
-    if (data.status === OpenAiTuneStatusEnum.cancelled) {
-      // 删除训练文件
-      openai.deleteFile(data.training_files[0].id, { httpsAgent: httpsAgent(false) });
-
-      // 更新模型
-      await Model.findByIdAndUpdate(modelId, {
-        status: ModelStatusEnum.running,
-        updateTime: new Date()
-      });
-      // 更新训练数据
-      await Training.findByIdAndUpdate(training._id, {
-        status: TrainingStatusEnum.canceled
-      });
-
-      return jsonRes(res, {
-        data: '模型微调已取消'
-      });
-    }
-
-    jsonRes(res, {
-      data: '模型还在训练中'
-    });
-  } catch (err: any) {
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/model/train/train.ts

@@ -1,130 +0,0 @@
-// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { connectToDatabase, Model, Training } from '@/service/mongo';
-import formidable from 'formidable';
-import { authToken } from '@/service/utils/tools';
-import { getUserApiOpenai } from '@/service/utils/openai';
-import { join } from 'path';
-import fs from 'fs';
-import type { ModelSchema } from '@/types/mongoSchema';
-import type { OpenAIApi } from 'openai';
-import { ModelStatusEnum, TrainingStatusEnum } from '@/constants/model';
-import { httpsAgent } from '@/service/utils/tools';
-
-// 关闭next默认的bodyParser处理方式
-export const config = {
-  api: {
-    bodyParser: false
-  }
-};
-
-/* 上传文件，开始微调 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let openai: OpenAIApi, trainId: string, uploadFileId: string;
-
-  try {
-    const { authorization } = req.headers;
-
-    if (!authorization) {
-      throw new Error('无权操作');
-    }
-    const { modelId } = req.query;
-
-    if (!modelId) {
-      throw new Error('参数错误');
-    }
-    const userId = await authToken(authorization);
-
-    await connectToDatabase();
-
-    // 获取模型的状态
-    const model = await Model.findById<ModelSchema>(modelId);
-
-    if (!model || model.status !== 'running') {
-      throw new Error('模型正忙');
-    }
-
-    // const trainingType = model.service.modelType
-    const trainingType = model.service.trainId; // 目前都默认是 openai text-davinci-03
-
-    // 获取用户的 API Key 实例化后的对象
-    const user = await getUserApiOpenai(userId);
-    openai = user.openai;
-
-    // 接收文件并保存
-    const form = formidable({
-      uploadDir: join(process.cwd(), 'public/trainData'),
-      keepExtensions: true
-    });
-
-    const { files } = await new Promise<{
-      fields: formidable.Fields;
-      files: formidable.Files;
-    }>((resolve, reject) => {
-      form.parse(req, (err, fields, files) => {
-        if (err) return reject(err);
-        resolve({ fields, files });
-      });
-    });
-    const file = files.file;
-
-    // 上传文件到 openai
-    // @ts-ignore
-    const uploadRes = await openai.createFile(
-      // @ts-ignore
-      fs.createReadStream(file.filepath),
-      'fine-tune',
-      { httpsAgent: httpsAgent(false) }
-    );
-    uploadFileId = uploadRes.data.id; // 记录上传文件的 ID
-
-    // 开始训练
-    const trainRes = await openai.createFineTune(
-      {
-        training_file: uploadFileId,
-        model: trainingType,
-        suffix: model.name,
-        n_epochs: 4
-      },
-      { httpsAgent: httpsAgent(false) }
-    );
-
-    trainId = trainRes.data.id; // 记录训练 ID
-
-    // 创建训练记录
-    await Training.create({
-      serviceName: 'openai',
-      tuneId: trainId,
-      status: TrainingStatusEnum.pending,
-      modelId
-    });
-
-    // 修改模型状态
-    await Model.findByIdAndUpdate(modelId, {
-      $inc: {
-        trainingTimes: +1
-      },
-      updateTime: new Date(),
-      status: ModelStatusEnum.training
-    });
-
-    jsonRes(res, {
-      data: 'start training'
-    });
-  } catch (err: any) {
-    /* 清除上传的文件，关闭训练记录 */
-    // @ts-ignore
-    if (openai) {
-      // @ts-ignore
-      uploadFileId && openai.deleteFile(uploadFileId, { httpsAgent: httpsAgent(false) });
-      // @ts-ignore
-      trainId && openai.cancelFineTune(trainId, { httpsAgent: httpsAgent(false) });
-    }
-
-    jsonRes(res, {
-      code: 500,
-      error: err
-    });
-  }
-}

src/pages/api/model/update.ts

@@ -1,15 +1,15 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { Model } from '@/service/models/model';
 import type { ModelUpdateParams } from '@/types/model';
+import { authModel } from '@/service/utils/auth';
 
 /* 获取我的模型 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { name, search, service, security, systemPrompt, intro, temperature } =
-      req.body as ModelUpdateParams;
+    const { name, avatar, chat, share, security } = req.body as ModelUpdateParams;
     const { modelId } = req.query as { modelId: string };
     const { authorization } = req.headers;
 
@@ -17,7 +17,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       throw new Error('无权操作');
     }
 
-    if (!name || !service || !security || !modelId) {
+    if (!name || !chat || !security || !modelId) {
       throw new Error('参数错误');
     }
 
@@ -26,6 +26,11 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
 
     await connectToDatabase();
 
+    await authModel({
+      modelId,
+      userId
+    });
+
     // 更新模型
     await Model.updateOne(
       {
@@ -34,11 +39,11 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       },
       {
         name,
-        systemPrompt,
-        intro,
-        temperature,
-        search,
-        // service,
+        avatar,
+        chat,
+        'share.isShare': share.isShare,
+        'share.isShareDetail': share.isShareDetail,
+        'share.intro': share.intro,
         security
       }
     );

src/pages/api/openapi/chat/chat.ts

@@ -0,0 +1,147 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { connectToDatabase } from '@/service/mongo';
+import { authOpenApiKey, authModel } from '@/service/utils/auth';
+import { modelServiceToolMap, resStreamResponse } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
+import { jsonRes } from '@/service/response';
+import { PassThrough } from 'stream';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
+import { pushChatBill } from '@/service/events/pushBill';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
+
+/* 发送提示词 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  let step = 0; // step=1时，表示开始了流响应
+  const stream = new PassThrough();
+  stream.on('error', () => {
+    console.log('error: ', 'stream error');
+    stream.destroy();
+  });
+  res.on('close', () => {
+    stream.destroy();
+  });
+  res.on('error', () => {
+    console.log('error: ', 'request error');
+    stream.destroy();
+  });
+
+  try {
+    const {
+      prompts,
+      modelId,
+      isStream = true
+    } = req.body as {
+      prompts: ChatItemSimpleType[];
+      modelId: string;
+      isStream: boolean;
+    };
+
+    if (!prompts || !modelId) {
+      throw new Error('缺少参数');
+    }
+    if (!Array.isArray(prompts)) {
+      throw new Error('prompts is not array');
+    }
+    if (prompts.length > 30 || prompts.length === 0) {
+      throw new Error('prompts length range 1-30');
+    }
+
+    await connectToDatabase();
+    let startTime = Date.now();
+
+    /* 凭证校验 */
+    const { apiKey, userId } = await authOpenApiKey(req);
+
+    const { model } = await authModel({
+      userId,
+      modelId
+    });
+
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
+    // 使用了知识库搜索
+    if (model.chat.useKb) {
+      const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
+
+      const { code, searchPrompt } = await searchKb({
+        prompts,
+        similarity,
+        model,
+        userId
+      });
+
+      // search result is empty
+      if (code === 201) {
+        return res.send(searchPrompt?.value);
+      }
+
+      searchPrompt && prompts.unshift(searchPrompt);
+    } else {
+      // 没有用知识库搜索，仅用系统提示词
+      if (model.chat.systemPrompt) {
+        prompts.unshift({
+          obj: ChatRoleEnum.System,
+          value: model.chat.systemPrompt
+        });
+      }
+    }
+
+    // 计算温度
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
+    );
+
+    // 发出请求
+    const { streamResponse, responseMessages, responseText, totalTokens } =
+      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+        apiKey,
+        temperature: +temperature,
+        messages: prompts,
+        stream: isStream
+      });
+
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
+
+    let textLen = 0;
+    let tokens = totalTokens;
+
+    if (isStream) {
+      step = 1;
+      const { finishMessages, totalTokens } = await resStreamResponse({
+        model: model.chat.chatModel,
+        res,
+        stream,
+        chatResponse: streamResponse,
+        prompts
+      });
+      textLen = finishMessages.map((item) => item.value).join('').length;
+      tokens = totalTokens;
+    } else {
+      textLen = responseMessages.map((item) => item.value).join('').length;
+      jsonRes(res, {
+        data: responseText
+      });
+    }
+
+    pushChatBill({
+      isPay: true,
+      chatModel: model.chat.chatModel,
+      userId,
+      textLen,
+      tokens
+    });
+  } catch (err: any) {
+    if (step === 1) {
+      // 直接结束流
+      console.log('error，结束');
+      stream.destroy();
+    } else {
+      res.status(500);
+      jsonRes(res, {
+        code: 500,
+        error: err
+      });
+    }
+  }
+}

src/pages/api/openapi/chat/lafGpt.ts

@@ -1,18 +1,14 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase, Model } from '@/service/mongo';
-import { getOpenAIApi } from '@/service/utils/chat';
-import { authOpenApiKey } from '@/service/utils/tools';
-import { httpsAgent, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
-import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
-import { ChatItemType } from '@/types/chat';
+import { authOpenApiKey } from '@/service/utils/auth';
+import { resStreamResponse, modelServiceToolMap } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { ChatModelNameEnum, modelList, ChatModelNameMap } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
 
 /* 发送提示词 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -36,7 +32,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       modelId,
       isStream = true
     } = req.body as {
-      prompt: ChatItemType;
+      prompt: ChatItemSimpleType;
       modelId: string;
       isStream: boolean;
     };
@@ -46,7 +42,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     }
 
     await connectToDatabase();
-    const redis = await connectRedis();
     let startTime = Date.now();
 
     /* 凭证校验 */
@@ -58,181 +53,123 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('找不到模型');
     }
 
-    const modelConstantsData = modelList.find(
-      (item) => item.model === ChatModelNameEnum.VECTOR_GPT
-    );
-    if (!modelConstantsData) {
-      throw new Error('模型已下架');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
     console.log('laf gpt start');
 
-    // 获取 chatAPI
-    const chatAPI = getOpenAIApi(apiKey);
-
     // 请求一次 chatgpt 拆解需求
-    const promptResponse = await chatAPI.createChatCompletion(
-      {
-        model: ChatModelNameMap[ChatModelNameEnum.GPT35],
-        temperature: 0,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        messages: [
-          {
-            role: 'system',
-            content: `服务端逻辑生成器.根据用户输入的需求,拆解成代码实现的步骤,并按格式返回: 1.\n2.\n3.\n ......
+    const { responseText: resolveText, totalTokens: resolveTokens } = await modelServiceToolMap[
+      model.chat.chatModel
+    ].chatCompletion({
+      apiKey,
+      temperature: 0,
+      messages: [
+        {
+          obj: ChatRoleEnum.System,
+          value: `服务端逻辑生成器.根据用户输入的需求,拆解成 laf 云函数实现的步骤,只返回步骤,按格式返回步骤: 1.\n2.\n3.\n ......
 下面是一些例子:
+一个 hello world 例子
+1. 返回字符串: "hello world"
+
+计算圆的面积
+1. 从 body 中获取半径 radius.
+2. 校验 radius 是否为有效的数字.
+3. 计算圆的面积.
+4. 返回圆的面积: {area} 
+
 实现一个手机号发生注册验证码方法.
 1. 从 query 中获取 phone.
-2. 校验手机号格式是否正确,不正确则返回错误响应,消息为:手机号格式错误.
+2. 校验手机号格式是否正确,不正确则返回错误原因:手机号格式错误.
 3. 给 phone 发送一个短信验证码,验证码长度为6位字符串,内容为:你正在注册laf,验证码为:code.
 4. 数据库添加数据,表为"codes",内容为 {phone, code}.
 
-实现根据手机号注册账号,需要验证手机验证码.
+实现一个云函数，使用手机号注册账号,需要验证手机验证码.
 1. 从 body 中获取 phone 和 code.
-2. 校验手机号格式是否正确,不正确返回错误响应,消息为:手机号格式错误.
-2. 获取数据库数据,表为"codes",查找是否有符合 phone, code 等于body参数的记录,没有的话错误响应,消息为:验证码不正确.
+2. 校验手机号格式是否正确,不正确则返回错误原因:手机号格式错误.
+2. 获取数据库数据,表为"codes",查找是否有符合 phone, code 等于body参数的记录,没有的话返回错误原因:验证码不正确.
 4. 添加数据库数据,表为"users" ,内容为{phone, code, createTime}.
 5. 删除数据库数据,删除 code 记录.
+6. 返回新建用户的Id: return {userId}
 
 更新博客记录。传入blogId,blogText,tags,还需要记录更新的时间.
 1. 从 body 中获取 blogId,blogText 和 tags.
-2. 校验 blogId 是否为空,为空则错误响应,消息为:博客ID不能为空.
-3. 校验 blogText 是否为空,为空则错误响应,消息为:博客内容不能为空.
-4. 校验 tags 是否为数组,不是则错误响应,消息为:标签必须为数组.
+2. 校验 blogId 是否为空,为空则返回错误原因:博客ID不能为空.
+3. 校验 blogText 是否为空,为空则返回错误原因:博客内容不能为空.
+4. 校验 tags 是否为数组,不是则返回错误原因:标签必须为数组.
 5. 获取当前时间,记录为 updateTime.
 6. 更新数据库数据,表为"blogs",更新符合 blogId 的记录的内容为{blogText, tags, updateTime}.
-7. 返回结果 {message: "更新博客记录成功"}.`
-          },
-          {
-            role: 'user',
-            content: prompt.value
-          }
-        ]
-      },
-      {
-        timeout: 120000,
-        httpsAgent: httpsAgent(true)
-      }
-    );
-
-    const promptResolve = promptResponse.data.choices?.[0]?.message?.content || '';
-    if (!promptResolve) {
-      throw new Error('gpt 异常');
-    }
-
-    prompt.value += ` ${promptResolve}`;
-    console.log('prompt resolve success, time:', `${(Date.now() - startTime) / 1000}s`);
-
-    // 获取提示词的向量
-    const { vector: promptVector } = await openaiCreateEmbedding({
-      isPay: true,
-      apiKey,
-      userId,
-      text: prompt.value
+7. 返回结果 "更新博客记录成功"`
+        },
+        {
+          obj: ChatRoleEnum.Human,
+          value: prompt.value
+        }
+      ],
+      stream: false
     });
 
+    prompt.value += ` ${resolveText}`;
+    console.log('prompt resolve success, time:', `${(Date.now() - startTime) / 1000}s`);
+
     // 读取对话内容
     const prompts = [prompt];
 
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${String(model._id)}}=>[KNN 20 @vector $blob AS score]`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'DIALECT',
-      '2'
-    ]);
-
-    // 格式化响应值，获取 qa
-    const formatRedisPrompt: string[] = [];
-    for (let i = 2; i < 42; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
-
-    // textArr 筛选，最多 3200 tokens
-    const systemPrompt = systemPromptFilter(formatRedisPrompt, 3200);
-
-    prompts.unshift({
-      obj: 'SYSTEM',
-      value: `${model.systemPrompt} 知识库内容是最新的，知识库内容为: "${systemPrompt}"`
+    // 获取向量匹配到的提示词
+    const { searchPrompt } = await searchKb({
+      similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
+      prompts,
+      model,
+      userId
     });
 
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
+    searchPrompt && prompts.unshift(searchPrompt);
 
-    // 格式化文本内容成 chatgpt 格式
-    const map = {
-      Human: ChatCompletionRequestMessageRoleEnum.User,
-      AI: ChatCompletionRequestMessageRoleEnum.Assistant,
-      SYSTEM: ChatCompletionRequestMessageRoleEnum.System
-    };
-    const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
-      (item: ChatItemType) => ({
-        role: map[item.obj],
-        content: item.value
-      })
-    );
-    // console.log(formatPrompts);
     // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
+    );
 
     // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: formatPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
+    const { streamResponse, responseMessages, responseText, totalTokens } =
+      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+        apiKey,
+        temperature: +temperature,
+        messages: prompts,
         stream: isStream
-      },
-      {
-        timeout: 120000,
-        responseType: isStream ? 'stream' : 'json',
-        httpsAgent: httpsAgent(true)
-      }
-    );
+      });
 
-    console.log('code response. time:', `${(Date.now() - startTime) / 1000}s`);
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
 
-    step = 1;
-    let responseContent = '';
+    let textLen = resolveText.length;
+    let tokens = resolveTokens;
 
     if (isStream) {
-      const streamResponse = await gpt35StreamResponse({
+      step = 1;
+      const { finishMessages, totalTokens } = await resStreamResponse({
+        model: model.chat.chatModel,
         res,
         stream,
-        chatResponse
+        chatResponse: streamResponse,
+        prompts
       });
-      responseContent = streamResponse.responseContent;
+      textLen += finishMessages.map((item) => item.value).join('').length;
+      tokens += totalTokens;
     } else {
-      responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
+      textLen += responseMessages.map((item) => item.value).join('').length;
+      tokens += totalTokens;
       jsonRes(res, {
-        data: responseContent
+        data: responseText
       });
     }
 
     console.log('laf gpt done. time:', `${(Date.now() - startTime) / 1000}s`);
 
-    const promptsContent = formatPrompts.map((item) => item.content).join('');
-
     pushChatBill({
       isPay: true,
-      modelName: model.service.modelName,
+      chatModel: model.chat.chatModel,
       userId,
-      text: promptsContent + responseContent
+      textLen,
+      tokens
     });
   } catch (err: any) {
     if (step === 1) {

src/pages/api/openapi/chat/vectorGpt.ts

@@ -1,213 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase, Model } from '@/service/mongo';
-import {
-  httpsAgent,
-  openaiChatFilter,
-  systemPromptFilter,
-  authOpenApiKey
-} from '@/service/utils/tools';
-import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import { PassThrough } from 'stream';
-import { modelList } from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
-import dayjs from 'dayjs';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const {
-      prompts,
-      modelId,
-      isStream = true
-    } = req.body as {
-      prompts: ChatItemType[];
-      modelId: string;
-      isStream: boolean;
-    };
-
-    if (!prompts || !modelId) {
-      throw new Error('缺少参数');
-    }
-    if (!Array.isArray(prompts)) {
-      throw new Error('prompts is not array');
-    }
-    if (prompts.length > 30 || prompts.length === 0) {
-      throw new Error('prompts length range 1-30');
-    }
-
-    await connectToDatabase();
-    const redis = await connectRedis();
-    let startTime = Date.now();
-
-    /* 凭证校验 */
-    const { apiKey, userId } = await authOpenApiKey(req);
-
-    const model = await Model.findOne({
-      _id: modelId,
-      userId
-    });
-
-    if (!model) {
-      throw new Error('无权使用该模型');
-    }
-
-    const modelConstantsData = modelList.find((item) => item.model === model?.service?.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型初始化异常');
-    }
-
-    // 获取提示词的向量
-    const { vector: promptVector, chatAPI } = await openaiCreateEmbedding({
-      isPay: true,
-      apiKey,
-      userId,
-      text: prompts[prompts.length - 1].value // 取最后一个
-    });
-
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${modelId}} @vector:[VECTOR_RANGE 0.22 $blob]=>{$YIELD_DISTANCE_AS: score}`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'LIMIT',
-      '0',
-      '30',
-      'DIALECT',
-      '2'
-    ]);
-
-    const formatRedisPrompt: string[] = [];
-
-    // 格式化响应值，获取 qa
-    for (let i = 2; i < 61; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
-
-    // system 合并
-    if (prompts[0].obj === 'SYSTEM') {
-      formatRedisPrompt.unshift(prompts.shift()?.value || '');
-    }
-
-    if (formatRedisPrompt.length > 0) {
-      // 系统提示词过滤，最多 2800 tokens
-      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
-
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
-          'YYYY/MM/DD HH:mm:ss'
-        )} ${systemPrompt}"`
-      });
-    } else {
-      return res.send('对不起，你的问题不在知识库中。');
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
-
-    // 格式化文本内容成 chatgpt 格式
-    const map = {
-      Human: ChatCompletionRequestMessageRoleEnum.User,
-      AI: ChatCompletionRequestMessageRoleEnum.Assistant,
-      SYSTEM: ChatCompletionRequestMessageRoleEnum.System
-    };
-    const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
-      (item: ChatItemType) => ({
-        role: map[item.obj],
-        content: item.value
-      })
-    );
-    // console.log(formatPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature: temperature,
-        messages: formatPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: isStream
-      },
-      {
-        timeout: 120000,
-        responseType: isStream ? 'stream' : 'json',
-        httpsAgent: httpsAgent(true)
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    step = 1;
-    let responseContent = '';
-
-    if (isStream) {
-      const streamResponse = await gpt35StreamResponse({
-        res,
-        stream,
-        chatResponse
-      });
-      responseContent = streamResponse.responseContent;
-    } else {
-      responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
-      jsonRes(res, {
-        data: responseContent
-      });
-    }
-
-    const promptsContent = formatPrompts.map((item) => item.content).join('');
-    pushChatBill({
-      isPay: true,
-      modelName: model.service.modelName,
-      userId,
-      text: promptsContent + responseContent
-    });
-    // jsonRes(res);
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/openapi/delKey.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, OpenApi } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {