feat: openapi cors

修复 filterSystemPrompt为'\n'时, 判断有问题

.dockerignore

@@ -7,4 +7,5 @@ README.md
 .git
 
 .yalc/
-yalc.lock
+yalc.lock
+testApi/

.env.template

@@ -1,6 +1,31 @@
-AXIOS_PROXY_HOST=127.0.0.1
-AXIOS_PROXY_PORT=33210
-MONGODB_URI=
-MY_MAIL=
-MAILE_CODE=
-TOKEN_KEY=
+# proxy
+# AXIOS_PROXY_HOST=127.0.0.1
+# AXIOS_PROXY_PORT=7890
+# 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
+# OPENAI_BASE_URL=https://api.openai.com/v1
+# OPENAI_BASE_URL_AUTH=可选的安全凭证
+OPENAIKEY=sk-xxx
+GPT4KEY=sk-xxx
+# claude
+CLAUDE_BASE_URL=calude模型请求地址
+CLAUDE_KEY=CLAUDE_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

.eslintrc.json

@@ -1,3 +1,6 @@
 {
-  "extends": "next/core-web-vitals"
+  "extends": "next/core-web-vitals",
+  "rules": {
+    "react-hooks/rules-of-hooks": 0
+  }
 }

.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 }}/fastgpt
+        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=fastgpt image" \
+          --label "org.opencontainers.image.licenses=MIT" \
+          --push \
+          -t ${DOCKER_REPO}:latest \
+          -f Dockerfile \
+          .

.gitignore

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

.husky/pre-commit

@@ -1,6 +1,6 @@
-#!/usr/bin/env sh
-. "$(dirname -- "$0")/_/husky.sh"
-
-if command -v npx >/dev/null 2>&1; then
-  npx lint-staged
+#!/usr/bin/env sh
+. "$(dirname -- "$0")/_/husky.sh"
+
+if command -v npx >/dev/null 2>&1; then
+  npx lint-staged
 fi

.prettierignore

@@ -1,4 +1,4 @@
 dist
 .vscode
 **/.DS_Store
-node_modules
+node_modules

.prettierrc.js

@@ -1,21 +1,20 @@
 module.exports = {
-    printWidth: 100,
-    tabWidth: 2,
-    useTabs: false,
-    semi: true,
-    singleQuote: true,
-    quoteProps: 'as-needed',
-    jsxSingleQuote: false,
-    trailingComma: 'none',
-    bracketSpacing: true,
-    jsxBracketSameLine: false,
-    arrowParens: 'always',
-    rangeStart: 0,
-    rangeEnd: Infinity,
-    requirePragma: false,
-    insertPragma: false,
-    proseWrap: 'preserve',
-    htmlWhitespaceSensitivity: 'css',
-    endOfLine: 'lf'
+  printWidth: 100,
+  tabWidth: 2,
+  useTabs: false,
+  semi: true,
+  singleQuote: true,
+  quoteProps: 'as-needed',
+  jsxSingleQuote: false,
+  trailingComma: 'none',
+  bracketSpacing: true,
+  jsxBracketSameLine: false,
+  arrowParens: 'always',
+  rangeStart: 0,
+  rangeEnd: Infinity,
+  requirePragma: false,
+  insertPragma: false,
+  proseWrap: 'preserve',
+  htmlWhitespaceSensitivity: 'css',
+  endOfLine: 'lf'
 };
-  

.vscode/settings.json

@@ -1,5 +0,0 @@
-{
-    "editor.formatOnType": true, 
-    "editor.formatOnSave": true ,
-    "prettier.tabWidth": 2
-}

Dockerfile

@@ -54,13 +54,4 @@ USER nextjs
 
 EXPOSE 3000
 
-ENV PORT 3000
-ENV MAX_USER ''
-ENV AXIOS_PROXY_HOST ''
-ENV AXIOS_PROXY_PORT ''
-ENV MONGODB_URI ''
-ENV MY_MAIL ''
-ENV MAILE_CODE ''
-ENV TOKEN_KEY ''
-
 CMD ["node", "server.js"]

LICENSE

@@ -0,0 +1,201 @@
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Makefile

@@ -1,4 +1,4 @@
-SERVICE_NAME=doc-gpt
+SERVICE_NAME=fastgpt
 # Image URL to use all building/pushing image targets
 IMG ?= $(SERVICE_NAME):latest
 
@@ -34,13 +34,13 @@ run: ## Run a dev service from host.
 
 .PHONY: docker-build
 docker-build: ## Build docker image with the desktop-frontend.
-	docker build -t c121914yu/doc-gpt:latest .
+	docker build -t registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:latest . --network host  --build-arg HTTP_PROXY=http://127.0.0.1:7890 --build-arg HTTPS_PROXY=http://127.0.0.1:7890
 
 ##@ Deployment
 
 .PHONY: docker-run
 docker-run:  ## Push docker image.
-	docker run -d -p 8008:3000 --name doc-gpt -v /web_project/yjl/doc-gpt/logs:/app/.next/logs c121914yu/doc-gpt:latest
+	docker run -d -p 8008:3000 --name fastgpt -v /web_project/yjl/fastgpt/logs:/app/.next/logs registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:latest
 
 #TODO: add support of docker push
 

README.md

@@ -1,73 +1,45 @@
-# Doc GPT 
+# Fast GPT
 
-## 初始化
-复制 .env.template 成 .env.local ，填写核心参数  
+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。
 
-```
-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=代理端口
-MONGODB_URI=mongo数据库地址
-MY_MAIL=发送验证码邮箱
-MAILE_CODE=邮箱秘钥
-TOKEN_KEY=随便填一个，用于生成和校验token
-```
+## 🛸 在线体验
 
-```bash
-pnpm dev
-```
+🎉 [fastgpt.run](https://fastgpt.run/) （国内版）  
+🎉 [ai.fastgpt.run](https://ai.fastgpt.run/) （海外版）
 
-## 部署
-```bash
-# 本地 docker 打包
-docker build -t imageName .
-docker push imageName
+![Demo](docs/imgs/demo.png?raw=true 'demo')
 
-# 服务器拉取部署
-docker pull imageName
-docker stop doc-gpt || true
-docker rm doc-gpt || true
-# 运行时才把参数写入
-docker run -d --network=host --name doc-gpt -e AXIOS_PROXY_HOST= -e AXIOS_PROXY_PORT= -e MAILE_CODE= -e TOKEN_KEY= -e MONGODB_URI= imageName
-```
+#### 知识库原理图
 
-Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
+![KBProcess](docs/imgs/KBProcess.jpg?raw=true 'KBProcess')
 
-# 介绍页
+## 👨‍💻 开发
 
-## 欢迎使用 Doc GPT
+项目技术栈: NextJs + TS + ChakraUI + Mongo + Postgres（Vector 插件）  
+这是一个平台项目，非单机项目，除了模型调用外还涉及非常多用户的内容。  
+[本地开发 Quick Start](docs/dev/README.md)
 
-时间比较赶，介绍没来得及完善，先直接上怎么使用：  
+## 🚀 私有化部署
 
-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。  
-3. 进入模型页，创建一个模型，建议直接用 ChatGPT。    
-4. 在模型列表点击【对话】，即可使用 API 进行聊天。  
+- [docker-compose 部署教程](docs/deploy/docker.md)
+- [由社区贡献的宝塔部署和本地运行教程](https://space.bilibili.com/431177525/channel/collectiondetail?sid=1370663)
 
-### 模型配置
+## :point_right: RoadMap
 
-1. **提示语**：会在每个对话框的第一句自动加入，用于限定该模型的对话内容。  
+- [FastGpt RoadMap](https://kjqvjse66l.feishu.cn/docx/RVUxdqE2WolDYyxEKATcM0XXnte)
 
+## 🏘️ 交流群
 
-2. **单句最大长度**：每个聊天，单次输入内容的最大长度。  
+添加 wx 进入：  
+![Demo](https://otnvvf-imgs.oss.laf.run/wx300.png?raw=true 'wx')
 
+## 👀 其他
 
-3. **上下文最大长度**：每个聊天，最多的轮数除以2，建议设置为偶数。可以持续聊天，但是旧的聊天内容会被截断，AI 就不会知道被截取的内容。 
-例如：上下文最大长度为6。在第 4 轮对话时，第一轮对话的内容不会被计入。
+- [FastGpt 常见问题](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
+- [FastGpt + Laf 最佳实践，将知识库装入公众号，点击去 Laf 公众号体验效果](https://b4jky7-fastgpt.oss.laf.run/lafercode.png)
+- [FastGpt V3.4 更新集合](https://www.bilibili.com/video/BV1Lo4y147Qh/?vd_source=92041a1a395f852f9d89158eaa3f61b4)
+- [FastGpt 知识库演示](https://www.bilibili.com/video/BV1Wo4y1p7i1/)
 
-4. **过期时间**：生成对话框后，这个对话框多久过期。  
+## 🌟 Star History
 
-5. **聊天最大加载次数**：单个对话框最多被加载几次，设置为-1代表不限制，正数代表只能加载 n 次，防止被盗刷。  
-
-### 对话框介绍
-
-1. 每个对话框以 windowId 作为标识。  
-2. 每次点击【对话】，都会生成新的对话框，无法回到旧的对话框。对话框内刷新，会恢复对话内容。  
-3. 直接分享对话框（网页）的链接给朋友，会共享同一个对话内容。但是！！！千万不要两个人同时用一个链接，会串味，还没解决这个问题。  
-4. 如果想分享一个纯的对话框，可以把链接里 windowId 参数去掉。例如：  
-
-* 当前网页链接：http://docgpt.ahapocket.cn/chat?chatId=6402c9f64cb5d6283f764&windowId=6402c94cb5d6283f76fb49  
-* 分享链接应为：http://docgpt.ahapocket.cn/chat?chatId=6402c9f64cb5d6283f764  
-
-### 其他问题
-还有其他问题，可以加我 wx，拉个交流群大家一起聊聊。
-![](/imgs/erweima.jpg)
+[![Star History Chart](https://api.star-history.com/svg?repos=c121914yu/FastGPT&type=Date)](https://star-history.com/#c121914yu/FastGPT&Date)

docs/FineTunes

@@ -1,4 +0,0 @@
-{"prompt": "sealos的介绍", "completion": "sealos 是以 kubernetes 为内核的云操作系统发行版"}
-{"prompt": "sealos是什么", "completion": "sealos 是以 kubernetes 为内核的云操作系统发行版"}
-{"prompt": "sealos安装的先决条件", "completion": "sealos 是一个简单的 go 二进制文件，可以安装在大多数 Linux 操作系统中。"}
-{"prompt": "sealos的CPU架构", "completion": "目前支持 amd64 和 arm64 架构。"}

docs/deploy/docker.md

@@ -0,0 +1,84 @@
+# Docker 部署 FastGpt
+
+## 代理环境（国外服务器可忽略）
+
+选择一个即可。
+
+1. [sealos nginx 方案](./proxy/sealos.md) - 推荐。约等于不用钱，不需要额外准备任何东西。
+2. [clash 方案](./proxy/clash.md) - 仅需一台服务器（需要有 clash）
+3. [nginx 方案](./proxy/nginx.md) - 需要一台国外服务器
+4. [cloudflare 方案](./proxy/cloudflare.md) - 需要有域名（每日免费 10w 次代理请求）
+5. [腾讯云函数代理方案](https://github.com/easychen/openai-api-proxy/blob/master/FUNC.md) - 仅需一台服务器
+
+### 1. 准备一些内容
+
+> 1. 服务器开通 80 端口。用代理的话，对应的代理端口也需要打开。
+> 2. QQ 邮箱 Code：进入 QQ 邮箱 -> 账号 -> 申请 SMTP 账号
+> 3. 有域名的准备好 SSL 证书
+
+### 2. 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 -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
+# 如果docker-compose运行不了，可以把 deploy/fastgpt/docker-compose 文件复制到服务器，然后在 docker-compose 文件夹里执行 sh init.sh。会把docker-compose文件复制到对应目录。
+```
+
+### 2. 创建 3 个初始化文件
+
+fastgpt 文件夹。分别为：fastgpt/docker-compose.yaml, fastgpt/pg/init.sql, fastgpt/nginx/nginx.conf
+
+手动创建或者直接把 fastgpt 文件夹复制过去。
+
+### 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！"
+
+# 删除本地旧镜像
+images=$(docker images --format "{{.ID}} {{.Repository}}" | grep fastgpt)
+
+# 将镜像 ID 和名称放入数组中
+IFS=$'\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
+```
+
+## 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[在 mac 上面部署 fastgpt 可能存在的问题](./mac.md)

docs/deploy/fastgpt/clash/config.yaml

@@ -0,0 +1,22 @@
+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V02×1.5,ABC, 印度01, 台湾03, 新加坡02, 新加坡03, 日本01, 日本02, 新加坡01,  美国01, 美国02, 台湾01, 台湾02], url: 'https://api.openai.com', interval: 3600}
+rules:
+  - 'DOMAIN-SUFFIX,google.com,♻️ 自动选择'
+  - 'DOMAIN-SUFFIX,ai.fastgpt.run,♻️ 自动选择'
+  - 'DOMAIN-SUFFIX,openai.com,♻️ 自动选择'
+  - 'DOMAIN-SUFFIX,api.openai.com,♻️ 自动选择'
+  - 'MATCH,DIRECT'

docs/deploy/fastgpt/clash/proxy.sh

@@ -0,0 +1,18 @@
+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
+
+OLD_PROCESS=$(pgrep clash)
+if [ ! -z "$OLD_PROCESS" ]; then
+  echo "Killing old process: $OLD_PROCESS"
+  kill $OLD_PROCESS
+fi
+sleep 2
+
+cd  /root/fastgpt/clash/fast
+rm -f ./nohup.out || true
+rm -f ./cache.db || true
+nohup ./clash-linux-amd64-v3  -d ./ &
+echo "Restart clash fast"

docs/deploy/fastgpt/clash/stop.sh

@@ -0,0 +1,10 @@
+export ALL_PROXY=''
+export http_proxy=''
+export https_proxy=''
+export HTTP_PROXY=''
+export HTTPS_PROXY=''
+OLD_PROCESS=$(pgrep clash)
+if [ ! -z "$OLD_PROCESS" ]; then
+  echo "Killing old process: $OLD_PROCESS"
+  kill $OLD_PROCESS
+fi

docs/deploy/fastgpt/docker-compose.yml

@@ -0,0 +1,83 @@
+version: '3.3'
+services:
+  pg:
+    image: ankane/pgvector:v0.4.2
+    container_name: pg
+    restart: always
+    ports:
+      - 8100:5432
+    environment:
+      # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
+      - POSTGRES_USER=fastgpt
+      - POSTGRES_PASSWORD=1234
+      - POSTGRES_DB=fastgpt
+    volumes:
+      # 刚创建的文件
+      - /root/fastgpt/pg/init.sql:/docker-entrypoint-initdb.d/init.sh
+      - /root/fastgpt/pg/data:/var/lib/postgresql/data
+      - /etc/localtime:/etc/localtime:ro
+  mongodb:
+    image: mongo:6.0.4
+    container_name: mongo
+    restart: always
+    ports:
+      - 27017:27017
+    environment:
+      # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
+      - MONGO_INITDB_ROOT_USERNAME=username
+      - MONGO_INITDB_ROOT_PASSWORD=password
+    volumes:
+      - /root/fastgpt/mongo/data:/data/db
+      - /root/fastgpt/mongo/logs:/var/log/mongodb
+      - /etc/localtime:/etc/localtime:ro
+  fastgpt:
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:latest
+    network_mode: host
+    restart: always
+    container_name: fastgpt
+    environment:
+      # proxy（可选）
+      - AXIOS_PROXY_HOST=127.0.0.1
+      - AXIOS_PROXY_PORT=7890
+      # 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。用的是QQ邮箱。参考 nodeMail 获取MAILE_CODE，自行百度。
+      - MY_MAIL=xxxx@qq.com
+      - MAILE_CODE=xxxx
+      # 阿里短信服务（邮箱和短信至少二选一）
+      - aliAccessKeyId=xxxx
+      - aliAccessKeySecret=xxxx
+      - aliSignName=xxxxx
+      - aliTemplateCode=SMS_xxxx
+      # token加密凭证（随便填，作为登录凭证）
+      - TOKEN_KEY=xxxx
+      # 和上方mongo镜像的username,password对应
+      - MONGODB_URI=mongodb://username:password@0.0.0.0:27017/?authSource=admin
+      - MONGODB_NAME=fastgpt
+      - PG_HOST=0.0.0.0
+      - PG_PORT=8100
+      # 和上方PG镜像对应.
+      - PG_USER=fastgpt # POSTGRES_USER
+      - PG_PASSWORD=1234 # POSTGRES_PASSWORD
+      - PG_DB_NAME=fastgpt # POSTGRES_DB
+      # openai
+      - OPENAIKEY=sk-xxxxx
+      - GPT4KEY=sk-xxx
+      - OPENAI_BASE_URL=https://api.openai.com/v1
+      - OPENAI_BASE_URL_AUTH=可选的安全凭证
+      # claude
+      - CLAUDE_BASE_URL=calude模型请求地址
+      - CLAUDE_KEY=CLAUDE_KEY
+  nginx:
+    image: nginx:alpine3.17
+    container_name: nginx
+    restart: always
+    network_mode: host
+    volumes:
+      # 刚创建的文件
+      - /root/fastgpt/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+      - /root/fastgpt/nginx/logs:/var/log/nginx
+      # https证书，没有的话不填，对应的nginx.conf也要修改
+      - /root/fastgpt/nginx/ssl/docgpt.key:/ssl/docgpt.key
+      - /root/fastgpt/nginx/ssl/docgpt.pem:/ssl/docgpt.pem

docs/deploy/fastgpt/docker-compose/init.sh

@@ -0,0 +1,2 @@
+cp ./docker-compose /usr/local/bin/docker-compose
+sudo chmod +x /usr/local/bin/docker-compose

docs/deploy/fastgpt/nginx/nginx.conf

@@ -0,0 +1,69 @@
+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 64k;
+    large_client_header_buffers 4 64k;
+    client_max_body_size 50M;
+
+    proxy_connect_timeout       240s;
+    proxy_read_timeout          240s;
+    proxy_buffer_size 128k;
+    proxy_buffers 4 256k;
+ 
+    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;
+    }
+
+    server {
+        listen 3000;
+        server_name 120.0.0.0;
+
+        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;        
+        }
+    }
+}

docs/deploy/fastgpt/pg/init.sql

@@ -0,0 +1,21 @@
+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),
+    kb_id VARCHAR(50),
+    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_userId_index ON modelData USING HASH (model_id);
+CREATE INDEX modelData_kbId_index ON modelData USING HASH (kb_id);
+EOSQL

docs/deploy/fastgpt/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=$(docker images --format "{{.ID}} {{.Repository}}" | grep fastgpt)
+
+# 将镜像 ID 和名称放入数组中
+IFS=$'\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/deploy/mac.md

@@ -0,0 +1,96 @@
+## Mac 上部署可能遇到的问题
+
+### 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
+
+```
+➜  fastgpt pwd
+/Users/jie/fastgpt
+➜  fastgpt 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 fastgpt 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 ~/fastgpt/mongo/data:/data/db -d mongo:4.0.1
+```
+
+**3、部署 pgsql**
+
+```
+docker run -it --name pg -e "POSTGRES_DB=fastgpt" -e "POSTGRES_PASSWORD=xxx" -e POSTGRES_USER=xxx -p 8100:5432 -v ~/fastgpt/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 (model_id);
+CREATE INDEX modelData_userId_index ON modelData (user_id);
+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/deploy/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/deploy/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/deploy/proxy/nginx.md

@@ -0,0 +1,73 @@
+# 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 ($auth != "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;
+    }
+}
+```

docs/deploy/proxy/sealos.md

@@ -0,0 +1,100 @@
+# sealos 部署 openai 中转
+
+## 登录 sealos cloud
+
+[sealos cloud](https://cloud.sealos.io/)
+
+## 创建应用
+
+打开 App Launchpad -> 新建应用
+
+![step1](./imgs//sealos1.png)  
+![step2](./imgs//sealos2.png)
+
+### 开启外网访问
+
+![step3](./imgs//sealos3.png)
+
+### 添加 configmap 文件
+
+1. 复制下面这段代码，注意 `server_name` 后面的内容替换成上图的地址。
+
+```
+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 64k;
+    large_client_header_buffers 4 64k;
+    client_max_body_size 50M;
+
+    proxy_connect_timeout       240s;
+    proxy_read_timeout          240s;
+    proxy_buffer_size 128k;
+    proxy_buffers 4 256k;
+
+
+    server {
+        listen 80;
+        server_name tgohwtdlrmer.cloud.sealos.io; # 这个地方替换成 sealos 提供的内容
+
+        location ~ /openai/(.*) {
+            # auth check
+            if ($http_auth != "auth") { # 安全凭证
+                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;
+            # 如果响应是流式的
+            proxy_set_header Connection '';
+            proxy_http_version 1.1;
+            chunked_transfer_encoding off;
+            proxy_buffering off;
+            proxy_cache off;
+            # 如果响应是一般的
+            proxy_buffer_size 128k;
+            proxy_buffers 4 256k;
+            proxy_busy_buffers_size 256k;
+        }
+    }
+}
+```
+
+2. 点开高级配置
+3. 点击新增 configmap
+4. 文件名写: `/etc/nginx/nginx.conf`
+5. 文件值为刚刚复制的那段代码
+6. 点击确认
+
+![step4](./imgs//sealos4.png)
+
+### 部署应用
+
+填写完毕后，点击右上角的 `部署应用`，即可完成。
+
+## 修改 FastGpt 环境变量
+
+1. 进入刚刚部署应用的详情，复制外网地址
+   ![step5](./imgs//sealos5.png)
+
+2. 修改环境变量:
+
+```
+OPENAI_BASE_URL=https://tgohwtdlrmer.cloud.sealos.io/openai/v1
+OPENAI_BASE_URL_AUTH=auth
+```
+
+**Done!**

docs/dev/README.md

@@ -0,0 +1,47 @@
+# FastGpt 本地开发
+
+第一次开发，请先[部署教程](../deploy/docker.md)，需要部署数据库.
+
+## 环境变量配置
+
+复制.env.template 文件，生成一个.env.local 环境变量文件夹，修改.env.local 里内容。
+
+```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。用的是 QQ 邮箱。参考 nodeMail 获取MAILE_CODE，自行百度。
+MY_MAIL=xxxx@qq.com
+MAILE_CODE=xxxx
+# 阿里短信服务（邮箱和短信至少二选一）
+aliAccessKeyId=xxxx
+aliAccessKeySecret=xxxx
+aliSignName=xxxxx
+aliTemplateCode=SMS_xxxx
+# token加密凭证（随便填，作为登录凭证）
+TOKEN_KEY=xxxx
+queueTask=1
+parentUrl=https://hostname/api/openapi/startEvents
+# 和mongo镜像的username,password对应
+MONGODB_URI=mongodb://username:passsword@0.0.0.0:27017/?authSource=admin
+MONGODB_NAME=xxx
+PG_HOST=0.0.0.0
+PG_PORT=8100
+# 和PG镜像对应.
+PG_USER=fastgpt # POSTGRES_USER
+PG_PASSWORD=1234 # POSTGRES_PASSWORD
+PG_DB_NAME=fastgpt # POSTGRES_DB
+OPENAIKEY=sk-xxxxx
+```
+
+## 运行
+
+```
+pnpm dev
+```

next.config.js

@@ -1,12 +1,25 @@
 /** @type {import('next').NextConfig} */
 
-const path = require('path');
-const isDev = process.env.NODE_ENV === 'development';
-
 const nextConfig = {
   output: 'standalone',
   reactStrictMode: false,
-  compress: true
+  compress: true,
+
+  webpack(config) {
+    config.experiments = {
+      asyncWebAssembly: true,
+      layers: true
+    };
+    config.module.rules = config.module.rules.concat([
+      {
+        test: /\.svg$/i,
+        issuer: /\.[jt]sx?$/,
+        use: ['@svgr/webpack']
+      }
+    ]);
+
+    return config;
+  }
 };
 
 module.exports = nextConfig;

package.json

@@ -1,5 +1,5 @@
 {
-  "name": "docgpt",
+  "name": "fastgpt",
   "version": "0.1.0",
   "private": true,
   "scripts": {
@@ -11,56 +11,75 @@
     "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": "^2.5.1",
+    "@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",
-    "@reduxjs/toolkit": "^1.9.3",
     "@tanstack/react-query": "^4.24.10",
     "@types/nprogress": "^0.2.0",
     "axios": "^1.3.3",
+    "cookie": "^0.5.0",
     "crypto": "^1.0.1",
     "dayjs": "^1.11.7",
-    "eslint": "8.34.0",
-    "eslint-config-next": "13.1.6",
+    "eventsource-parser": "^0.1.0",
     "formidable": "^2.1.1",
     "framer-motion": "^9.0.6",
+    "graphemer": "^1.4.0",
     "hyperdown": "^2.4.29",
     "immer": "^9.0.19",
     "jsonwebtoken": "^9.0.0",
+    "lodash": "^4.17.21",
+    "mammoth": "^1.5.1",
     "mongoose": "^6.10.0",
+    "nanoid": "^4.0.1",
     "next": "13.1.6",
+    "nextjs-cors": "^2.1.2",
     "nodemailer": "^6.9.1",
     "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",
     "react-markdown": "^8.0.5",
     "react-syntax-highlighter": "^15.5.0",
+    "redis": "^4.6.5",
+    "rehype-katex": "^6.0.2",
     "remark-gfm": "^3.0.1",
+    "remark-math": "^5.1.1",
     "sass": "^1.58.3",
     "sharp": "^0.31.3",
     "tunnel": "^0.0.6",
-    "typescript": "4.9.5",
-    "uuid": "^9.0.0",
+    "wxpay-v3": "^3.0.2",
     "zustand": "^4.3.5"
   },
   "devDependencies": {
+    "@svgr/webpack": "^6.5.1",
+    "@types/cookie": "^0.5.1",
     "@types/formidable": "^2.0.5",
     "@types/jsonwebtoken": "^9.0.1",
+    "@types/lodash": "^4.14.191",
     "@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",
     "lint-staged": "^13.1.2",
-    "prettier": "^2.8.4"
+    "prettier": "^2.8.4",
+    "typescript": "4.9.5"
   },
   "lint-staged": {
     "./src/**/*.{ts,tsx,scss}": "npm run format"

public/TrainingTemplate.jsonl

@@ -1,21 +0,0 @@
-{"prompt":"什么是死锁？如何避免死锁？\n\n###\n\n","completion":" 死锁是指两个或多个进程在执行过程中，由于互相等待对方释放资源而造成的一种僵局。避免死锁的常用方法包括：破坏互斥条件、破坏请求和保持条件、破坏不剥夺条件、破坏循环等待条件。###"}
-{"prompt":"什么是虚拟内存？\n\n###\n\n","completion":" 虚拟内存是指一种计算机内存管理技术，它使得操作系统可以将进程所使用的虚拟地址空间映射到物理内存中，从而可以让多个进程共享物理内存。当物理内存不足时，操作系统会将一部分不常用的内存页面暂时存储到硬盘上，这样就可以释放出更多的物理内存供其他进程使用。###"}
-{"prompt":"什么是分页和分段？有什么区别？\n\n###\n\n","completion":" 分页和分段是虚拟内存管理中常用的两种技术。分页是将虚拟地址空间划分为固定大小的页面，而分段则是将虚拟地址空间划分为不同大小的段。区别在于，分页的页面大小是固定的，而分段的段大小是可变的；另外，分页是为了实现虚拟内存，而分段则是为了实现逻辑地址空间的管理。###"}
-{"prompt":"什么是lru算法？\n\n###\n\n","completion":" lru算法是一种页面置换算法，它的全称是least recently used，即最近最少使用算法。lru算法的基本思想是在物理内存中维护一个页面访问历史记录，当需要替换一页时，选择最近最少被访问的页面进行替换。###"}
-{"prompt":"什么是文件系统？\n\n###\n\n","completion":" 文件系统是一种用于管理计算机存储设备上文件和目录的组织方式。文件系统通常包括存储管理、目录管理、文件访问控制、文件系统维护等功能。常见的文件系统包括fat、ntfs、ext等。###"}
-{"prompt":"什么是并发和并行？\n\n###\n\n","completion":" 并发是指多个任务交替执行的情况，而并行是指多个任务同时执行的情况。并发的实现方式是通过时间分片技术，而并行的实现方式是通过多核处理器等硬件设备。###"}
-{"prompt":"什么是系统调用？\n\n###\n\n","completion":" 系统调用是操作系统中的一种机制，它允许用户空间程序请求操作系统内核提供一些服务，如读写文件、创建进程等。系统调用通常是通过软中断实现的###"}
-{"prompt":"什么是进程间通信？\n\n###\n\n","completion":" 进程间通信是指不同进程之间进行数据交换和通信的机制，常见的方式有管道、共享内存、消息队列、信号量等。###"}
-{"prompt":"什么是文件描述符？\n\n###\n\n","completion":" 文件描述符是一个非负整数，它是操作系统内核为了管理打开的文件而维护的一种抽象概念。应用程序使用文件描述符来访问文件或其他i\/o设备###"}
-{"prompt":"什么是中断？ \n\n###\n\n","completion":" 中断是指计算机硬件或软件在执行程序时，暂停当前程序的执行，转而去执行另一个程序或处理器所需的其他任务的过程。中断可以是外部中断、内部中断或软中断。###"}
-{"prompt":"什么是页表？\n\n###\n\n","completion":" 页表是一种数据结构，它用于将虚拟地址转换为物理地址。在虚拟内存中，每个进程都有自己的页表，它描述了虚拟地址空间中每个页面对应的物理地址。 ###"}
-{"prompt":"什么是僵尸进程？\n\n###\n\n","completion":" 僵尸进程是指一个已经完成执行但其父进程还没有对其进行善后处理的进程，它会一直占用系统资源，直到其父进程将其处理为止。###"}
-{"prompt":"什么是守护进程？ \n\n###\n\n","completion":" 守护进程是一种在后台运行的特殊进程，它通常用于提供某种服务或执行某种系统任务。守护进程通常不与任何用户界面交互，也不会终止，直到操作系统关机或重启。###"}
-{"prompt":"计算机操作系统是什么？\n\n###\n\n","completion":" 计算机操作系统是一种控制计算机硬件和协调应用程序运行的系统软件。###"}
-{"prompt":"什么是进程？\n\n###\n\n","completion":" 进程是一个正在执行中的程序实例，它包括了程序计数器、堆栈、数据区等信息。###"}
-{"prompt":"什么是线程？\n\n###\n\n","completion":" 线程是操作系统能够进行运算调度的最小单位，它是进程的一个执行流程，共享进程的地址空间。###"}
-{"prompt":"什么是虚拟内存？\n\n###\n\n","completion":" 虚拟内存是一种计算机系统内存管理技术，它使得应用程序认为它拥有连续的可用的内存，而实际上它通常是被分成多个物理内存碎片。###"}
-{"prompt":"什么是死锁？\n\n###\n\n","completion":" 死锁是指两个或多个进程在执行过程中，因争夺资源而造成的一种互相等待的现象，导致所有进程都无法继续执行。###"}
-{"prompt":"什么是缓存？\n\n###\n\n","completion":" 缓存是指在计算机中暂存数据的高速存储器，它可以提高计算机对数据的访问速度，避免频繁地访问较慢的主存储器。###"}
-{"prompt":"什么是文件系统？\n\n###\n\n","completion":" 文件系统是计算机中用来管理和组织文件的一种机制，它通过一系列的数据结构来描述文件和目录的组织方式，以及文件如何存储和访问。###"}
-{"prompt":"什么是调度算法？\n\n###\n\n","completion":" 调度算法是指操作系统中用来决定进程或线程在cpu上执行顺序的一种算法，它的目标是最大化系统吞吐量、最小化响应时间或最大化资源利用率等。###"}

public/docs/chatProblem.md

@@ -0,0 +1,27 @@
+### 常见问题
+
+**Git 地址**
+[项目地址，完全开源，随便用。](https://github.com/c121914yu/FastGPT)
+
+**问题文档**
+[先看文档，再提问](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
+
+**删除和复制**
+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。
+
+**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。
+| 计费项 | 价格: 元/ 1K tokens（包含上下文）|
+| --- | --- |
+| claude - 对话 | 免费 |
+| 知识库 - 索引 | 免费 |
+| chatgpt - 对话 | 0.025 |
+| gpt4 - 对话 | 0.5 |
+| 文件拆分 | 0.025 |
+
+**其他问题**
+请 WX 联系: fastgpt123
+| 交流群 | 小助手 |
+| ----------------------- | -------------------- |
+| ![](https://otnvvf-imgs.oss.laf.run/wxqun300.jpg) | ![](https://otnvvf-imgs.oss.laf.run/wx300.png) |

public/docs/csvSelect.md

@@ -0,0 +1,9 @@
+接受一个 csv 文件，表格头包含 question 和 answer。question 代表问题，answer 代表答案。
+导入前会进行去重，如果问题和答案完全相同，则不会被导入，所以最终导入的内容可能会比文件的内容少。但是，对于带有换行的内容，目前无法去重。
+
+### 请保证 csv 文件为 utf-8 编码
+
+| question      | answer                                                 |
+| ------------- | ------------------------------------------------------ |
+| 什么是 laf    | laf 是一个云函数开发平台……                             |
+| 什么是 sealos | Sealos 是以 kubernetes 为内核的云操作系统发行版,可以…… |

public/docs/intro.md

@@ -0,0 +1,34 @@
+## 欢迎使用 Fast GPT
+
+### 项目开源
+
+FastGpt 项目完全开源，可随意私有化部署，去除平台风险忧虑。项目地址：[Git 仓库](https://github.com/c121914yu/FastGPT)
+
+### 开始使用知识库
+
+1. AI 助手详情里，有一个模型效果。打开知识库搜索开关即可使用知识库搜索功能。
+2. 导入知识库数据。可以手动输入或文件导入。
+3. 开始对话。
+4. 对话结束后，会看到聊天下方有一个“查看提示词”,可以看到搜索到了哪些内容。
+
+注意：使用知识库模型对话时，tokens 消耗会加快。
+
+### 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。
+| 计费项 | 价格: 元/ 1K tokens（包含上下文）|
+| --- | --- |
+| claude - 对话 | 免费 |
+| 知识库 - 索引 | 免费 |
+| chatgpt - 对话 | 0.025 |
+| gpt4 - 对话 | 0.5 |
+| 文件拆分 | 0.025 |
+
+### 交流群/问题反馈
+
+如果群满了，可加个小助手，定时拉
+wx 号: fastgpt123
+
+| 交流群                                            | 小助手                                         |
+| ------------------------------------------------- | ---------------------------------------------- |
+| ![](https://otnvvf-imgs.oss.laf.run/wxqun300.jpg) | ![](https://otnvvf-imgs.oss.laf.run/wx300.png) |

public/docs/shareHint.md

@@ -0,0 +1,3 @@
+你正准备分享对话，请确保分享链接不会滥用，因为它是使用的是你的 API key。  
+* 分享空白对话：为该模型创建一个空白的聊天分享出去。  
+* 分享当前对话：会把当前聊天的内容也分享出去，但是要注意不要多个人同时用一个聊天内容。

public/docs/versionIntro.md

@@ -0,0 +1,3 @@
+### Fast GPT V3.7
+
+- 新增 - 知识库与 AI 助手对多对关系，一个知识库可以被多个 AI 助手关联，一个 AI 助手可以关联多个知识库。

public/icon/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">
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public/trainData/4d89aa7a10c65cf0e3cec4300.jsonl

@@ -1,21 +0,0 @@
-{"prompt": "什么是高潜公司\n\n###\n\n", "completion": " 高潜公司是指高潜力的公司，其所处的赛道有发展潜力和前景。###"}
-{"prompt": "高潜公司的优势是什么\n\n###\n\n", "completion": " 高潜公司所处的整个行业和赛道有一定的增量空间，头部vc通过严格的筛选和加持为高潜公司背书，高潜公司的创始者一般都特别优秀。加入高潜公司可以获得很多机会来锻炼自己、强化自己的认知，快速成长、展现自己，并有可能成为公司扩张后的管理层###"}
-{"prompt": "高潜公司的风险是什么\n\n###\n\n", "completion": " 高潜公司的高风险问题也很明显。一旦公司失败，很多边缘人就会被淘汰掉。但宏观来讲，只要赛道是有潜力的，即便这家公司失败了，也可以跳槽到成功的公司去。###"}
-{"prompt": "高潜公司的例子有哪些\n\n###\n\n", "completion": " 很多高潜公司在做最近比较火的AIGC，包括去年的元宇宙，前两年比较火的新消费、企业服务和出海之类的。###"}
-{"prompt": "为什么现在加入大厂的前景不广阔？\n\n###\n\n", "completion": " 今年的大形势之下，互联网大厂纷纷开始裁员、取消普调、晋升比例严重缩水，HC也急剧减少。###"}
-{"prompt": "加入高潜公司可以获得什么样的机会？\n\n###\n\n", "completion": " 加入高潜公司可以获得很多机会来锻炼自己、强化自己的认知，快速成长、展现自己，并有可能成为公司扩张后的管理层。###"}
-{"prompt": "什么是高潜公司？\n\n###\n\n", "completion": " 高潜公司的定义是“高潜力的公司”，所处的行业和赛道有发展潜力和前景，头部vc为其背书，创始者一般都特别优秀。###"}
-{"prompt": "加入高潜公司有哪些优点\n\n###\n\n", "completion": " 加入高潜公司能够获得锻炼自己、强化认知的机会，快速成长、展现自己，在公司扩张后成为团队的管理层。同时，所处的行业还处于上升期，发展前景广阔。###"}
-{"prompt": "高潜公司存在哪些风险？\n\n###\n\n", "completion": " 高潜公司存在高风险问题，一旦公司失败，很多边缘人就会被淘汰掉。但宏观来讲，只要赛道是有潜力的，即便这家公司失败了，也可以跳槽到成功的公司去。###"}
-{"prompt": "高潜公司和互联网有什么相似之处？\n\n###\n\n", "completion": " 目前来说，高潜公司的风格大部分都比较像互联网大厂，有风格，但又没有那么内卷，因为大家每天都在开拓边疆，突破和探索市场的边界。同时，互联网产业的蓬勃发展也给其他行业，包括新能源汽车、新消费等，带来了用户增长和运营的经验###"}
-{"prompt": "互联网大厂的制度和分工如何？\n\n###\n\n", "completion": " 目前的互联网大厂的制度和分工非常明确，基本是按照一些标准SOP做事。同时，由于已经没有用户增量了，内卷和向上管理的问题也比较严重。###"}
-{"prompt": "高潜公司对于哪些毕业生是很好的选择\n\n###\n\n", "completion": " 对于追求长期创造价值而非想找份安稳的工作的毕业生来说，高潜公司是很好的选择。###"}
-{"prompt": "互联网大厂的晋升方式有哪些？\n\n###\n\n", "completion": " 互联网大厂的晋升方式有两种：老板特别喜欢你或者你的战功支撑你的竞争###"}
-{"prompt": "为什么目前更多优秀的人都会加入创业公司？\n\n###\n\n", "completion": " 目前社会的大趋势是更多优秀的人都会加入创业公司，因为真正在创造价值的其实永远是创业公司###"}
-{"prompt": "为什么选择高潜公司主要是因为我们迎来了什么三个繁荣？\n\n###\n\n", "completion": " 选择高潜公司主要是因为我们迎来了创新生态的三个繁荣：人才繁荣、资本繁荣和环境繁荣###"}
-{"prompt": "资本繁荣是如何推动创业生态的崛起的？\n\n###\n\n", "completion": " 资本繁荣，无论中国还是美国，创业生态的崛起都是伴随着移动互联网的发展。中国这一代VC的崛起，主要是通过投资移动互联网项目所积累的战绩扩大了资金池，通过这些成本低、增长快、回报率高的项目，才有了底气去推动更多行业发展，尝试着投资toB和硬科技这类成本高、增长慢、回报率低、风险大的项目。###"}
-{"prompt": "环境繁荣是指什么？\n\n###\n\n", "completion": " 环境繁荣是指互联网带动起经济发展后，各地政府也开始了对于创业进行培育，免费场地、巨额无偿补贴、各地送钱竞赛，大幅度降低了创业成本。###"}
-{"prompt": "高潜公司对于追求长期创造价值的毕业生来说为什么是好的选择？\n\n###\n\n", "completion": " 因为在高潜公司，毕业生可以通过参与创业公司的发展，获得更多的机会和成长空间，而不是被固定在某个职位上。此外，高潜公司通常会注重团队建设和文化建设，能够提供更好的工作环境和发展机会。###"}
-{"prompt": "如果想要寻找高潜公司，有哪些渠道可以利用？\n\n###\n\n", "completion": " 可以利用领英职场app和知潜微信小程序。领英职场app中入驻了很多高潜公司及高管，而知潜小程序现在也已经有100+高潜力创业公司入驻，都是经过筛选的、top VC投资过且赛道有前景的公司。此外，红杉和真格等VC机构自己的公众号也会经常披露投资的企业。###"}
-{"prompt": "为什么现在更多优秀的人才会加入创业公司？\n\n###\n\n", "completion": " 因为在当前社会的大趋势下，创业公司成为了创新生态的重要组成部分。创业公司在创造价值和推动行业发展方面具有更大的空间和潜力，而且随着移动互联网的发展，创业公司的崛起也得到了资本和政策的支持。因此，更多优秀的人才选择加入创业公司，以实现自己的创业梦想和获得更好的发展机会。###"}
-{"prompt": "高潜公司的优势在哪些方面？\n\n###\n\n", "completion": " 高潜公司在团队建设、文化建设和发展机会等方面具有优势。高潜公司通常会注重团队建设和文化建设，能够提供更好的工作环境和发展机会。同时，高潜公司的发展潜力和创新能力也很强，可以为毕业生提供更多的机会和成长空间。###"}

public/trainData/d95c4a3c319667d5f24955602.jsonl

@@ -1,21 +0,0 @@
-{"prompt":"什么是死锁？如何避免死锁？\n\n###\n\n","completion":" 死锁是指两个或多个进程在执行过程中，由于互相等待对方释放资源而造成的一种僵局。避免死锁的常用方法包括：破坏互斥条件、破坏请求和保持条件、破坏不剥夺条件、破坏循环等待条件。###"}
-{"prompt":"什么是虚拟内存？\n\n###\n\n","completion":" 虚拟内存是指一种计算机内存管理技术，它使得操作系统可以将进程所使用的虚拟地址空间映射到物理内存中，从而可以让多个进程共享物理内存。当物理内存不足时，操作系统会将一部分不常用的内存页面暂时存储到硬盘上，这样就可以释放出更多的物理内存供其他进程使用。###"}
-{"prompt":"什么是分页和分段？有什么区别？\n\n###\n\n","completion":" 分页和分段是虚拟内存管理中常用的两种技术。分页是将虚拟地址空间划分为固定大小的页面，而分段则是将虚拟地址空间划分为不同大小的段。区别在于，分页的页面大小是固定的，而分段的段大小是可变的；另外，分页是为了实现虚拟内存，而分段则是为了实现逻辑地址空间的管理。###"}
-{"prompt":"什么是lru算法？\n\n###\n\n","completion":" lru算法是一种页面置换算法，它的全称是least recently used，即最近最少使用算法。lru算法的基本思想是在物理内存中维护一个页面访问历史记录，当需要替换一页时，选择最近最少被访问的页面进行替换。###"}
-{"prompt":"什么是文件系统？\n\n###\n\n","completion":" 文件系统是一种用于管理计算机存储设备上文件和目录的组织方式。文件系统通常包括存储管理、目录管理、文件访问控制、文件系统维护等功能。常见的文件系统包括fat、ntfs、ext等。###"}
-{"prompt":"什么是并发和并行？\n\n###\n\n","completion":" 并发是指多个任务交替执行的情况，而并行是指多个任务同时执行的情况。并发的实现方式是通过时间分片技术，而并行的实现方式是通过多核处理器等硬件设备。###"}
-{"prompt":"什么是系统调用？\n\n###\n\n","completion":" 系统调用是操作系统中的一种机制，它允许用户空间程序请求操作系统内核提供一些服务，如读写文件、创建进程等。系统调用通常是通过软中断实现的###"}
-{"prompt":"什么是进程间通信？\n\n###\n\n","completion":" 进程间通信是指不同进程之间进行数据交换和通信的机制，常见的方式有管道、共享内存、消息队列、信号量等。###"}
-{"prompt":"什么是文件描述符？\n\n###\n\n","completion":" 文件描述符是一个非负整数，它是操作系统内核为了管理打开的文件而维护的一种抽象概念。应用程序使用文件描述符来访问文件或其他i\/o设备###"}
-{"prompt":"什么是中断？ \n\n###\n\n","completion":" 中断是指计算机硬件或软件在执行程序时，暂停当前程序的执行，转而去执行另一个程序或处理器所需的其他任务的过程。中断可以是外部中断、内部中断或软中断。###"}
-{"prompt":"什么是页表？\n\n###\n\n","completion":" 页表是一种数据结构，它用于将虚拟地址转换为物理地址。在虚拟内存中，每个进程都有自己的页表，它描述了虚拟地址空间中每个页面对应的物理地址。 ###"}
-{"prompt":"什么是僵尸进程？\n\n###\n\n","completion":" 僵尸进程是指一个已经完成执行但其父进程还没有对其进行善后处理的进程，它会一直占用系统资源，直到其父进程将其处理为止。###"}
-{"prompt":"什么是守护进程？ \n\n###\n\n","completion":" 守护进程是一种在后台运行的特殊进程，它通常用于提供某种服务或执行某种系统任务。守护进程通常不与任何用户界面交互，也不会终止，直到操作系统关机或重启。###"}
-{"prompt":"计算机操作系统是什么？\n\n###\n\n","completion":" 计算机操作系统是一种控制计算机硬件和协调应用程序运行的系统软件。###"}
-{"prompt":"什么是进程？\n\n###\n\n","completion":" 进程是一个正在执行中的程序实例，它包括了程序计数器、堆栈、数据区等信息。###"}
-{"prompt":"什么是线程？\n\n###\n\n","completion":" 线程是操作系统能够进行运算调度的最小单位，它是进程的一个执行流程，共享进程的地址空间。###"}
-{"prompt":"什么是虚拟内存？\n\n###\n\n","completion":" 虚拟内存是一种计算机系统内存管理技术，它使得应用程序认为它拥有连续的可用的内存，而实际上它通常是被分成多个物理内存碎片。###"}
-{"prompt":"什么是死锁？\n\n###\n\n","completion":" 死锁是指两个或多个进程在执行过程中，因争夺资源而造成的一种互相等待的现象，导致所有进程都无法继续执行。###"}
-{"prompt":"什么是缓存？\n\n###\n\n","completion":" 缓存是指在计算机中暂存数据的高速存储器，它可以提高计算机对数据的访问速度，避免频繁地访问较慢的主存储器。###"}
-{"prompt":"什么是文件系统？\n\n###\n\n","completion":" 文件系统是计算机中用来管理和组织文件的一种机制，它通过一系列的数据结构来描述文件和目录的组织方式，以及文件如何存储和访问。###"}
-{"prompt":"什么是调度算法？\n\n###\n\n","completion":" 调度算法是指操作系统中用来决定进程或线程在cpu上执行顺序的一种算法，它的目标是最大化系统吞吐量、最小化响应时间或最大化资源利用率等。###"}

src/api/chat.ts

@@ -1,65 +1,66 @@
 import { GET, POST, DELETE } from './request';
-import { ChatItemType, ChatSiteType, ChatSiteItemType } from '@/types/chat';
-
-/**
- * 获取一个聊天框的ID
- */
-export const getChatSiteId = (modelId: string) => GET<string>(`/chat/generate?modelId=${modelId}`);
+import type { ChatItemType, HistoryItemType } from '@/types/chat';
+import type { InitChatResponse, InitShareChatResponse } from './response/chat';
+import { RequestPaging } from '../types/index';
+import type { ShareChatSchema } from '@/types/mongoSchema';
+import type { ShareChatEditType } from '@/types/model';
+import { Obj2Query } from '@/utils/tools';
 
 /**
  * 获取初始化聊天内容
  */
-export const getInitChatSiteInfo = (chatId: string, windowId: string = '') =>
-  GET<{
-    windowId: string;
-    chatSite: ChatSiteType;
-    history: ChatItemType[];
-  }>(`/chat/init?chatId=${chatId}&windowId=${windowId}`);
+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 = (data: RequestPaging) =>
+  POST<HistoryItemType[]>('/chat/getHistory', data);
 
 /**
- * 预发 prompt 进行存储
+ * 删除一条历史记录
  */
-export const postChatGptPrompt = ({
-  prompt,
-  windowId,
-  chatId
-}: {
-  prompt: ChatSiteItemType;
-  windowId: string;
-  chatId: string;
-}) =>
-  POST<string>(`/chat/preChat`, {
-    windowId,
-    prompt: {
-      obj: prompt.obj,
-      value: prompt.value
-    },
-    chatId
-  });
-/* 获取 Chat 的 Event 对象，进行持续通信 */
-export const getChatGPTSendEvent = (chatId: string, windowId: string) =>
-  new EventSource(`/api/chat/chatGpt?chatId=${chatId}&windowId=${windowId}`);
+export const delChatHistoryById = (id: string) => GET(`/chat/removeHistory?id=${id}`);
 
 /**
- * 删除最后一句
+ * 存储一轮对话
  */
-export const delLastMessage = (windowId?: string) =>
-  windowId ? DELETE(`/chat/delLastMessage?windowId=${windowId}`) : null;
+export const postSaveChat = (data: {
+  modelId: string;
+  newChatId: '' | string;
+  chatId: '' | string;
+  prompts: [ChatItemType, ChatItemType];
+}) => POST<string>('/chat/saveChat', data);
+
+/**
+ * 删除一句对话
+ */
+export const delChatRecordByIndex = (chatId: string, contentId: string) =>
+  DELETE(`/chat/delChatRecordByContentId?chatId=${chatId}&contentId=${contentId}`);
+
+/**
+ * create a shareChat
+ */
+export const createShareChat = (
+  data: ShareChatEditType & {
+    modelId: string;
+  }
+) => POST<string>(`/chat/shareChat/create`, data);
+
+/**
+ * get  shareChat
+ */
+export const getShareChatList = (modelId: string) =>
+  GET<ShareChatSchema[]>(`/chat/shareChat/list?modelId=${modelId}`);
+
+/**
+ * delete a  shareChat
+ */
+export const delShareChatById = (id: string) => DELETE(`/chat/shareChat/delete?id=${id}`);
+
+/**
+ * 初始化分享聊天
+ */
+export const initShareChatInfo = (data: { shareId: string; password: string }) =>
+  GET<InitShareChatResponse>(`/chat/shareChat/init?${Obj2Query(data)}`);

src/api/common.ts

@@ -0,0 +1 @@
+import { GET, POST, DELETE } from './request';

src/api/fetch.ts

@@ -0,0 +1,61 @@
+import { SYSTEM_PROMPT_HEADER, NEW_CHATID_HEADER } from '@/constants/chat';
+
+interface StreamFetchProps {
+  url: string;
+  data: any;
+  onMessage: (text: string) => void;
+  abortSignal: AbortController;
+}
+export const streamFetch = ({ url, data, onMessage, abortSignal }: StreamFetchProps) =>
+  new Promise<{ responseText: string; systemPrompt: string; newChatId: string }>(
+    async (resolve, reject) => {
+      try {
+        const res = await fetch(url, {
+          method: 'POST',
+          headers: {
+            'Content-Type': 'application/json'
+          },
+          body: JSON.stringify(data),
+          signal: abortSignal.signal
+        });
+        const reader = res.body?.getReader();
+        if (!reader) return;
+
+        const decoder = new TextDecoder();
+
+        const systemPrompt = decodeURIComponent(res.headers.get(SYSTEM_PROMPT_HEADER) || '').trim();
+        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);
+            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');
+          }
+        };
+        read();
+      } catch (err: any) {
+        console.log(err, '====');
+        reject(typeof err === 'string' ? err : err?.message || '请求异常');
+      }
+    }
+  );

src/api/model.ts

@@ -1,28 +1,47 @@
 import { GET, POST, DELETE, PUT } from './request';
-import type { ModelType } from '@/types/model';
-import { ModelUpdateParams } from '@/types/model';
-import { TrainingItemType } from '../types/training';
+import type { ModelSchema } from '@/types/mongoSchema';
+import type { ModelUpdateParams, ShareModelItem } from '@/types/model';
+import { RequestPaging } from '../types/index';
+import type { ModelListResponse } from './response/model';
 
-export const getMyModels = () => GET<ModelType[]>('/model/list');
+/**
+ * 获取模型列表
+ */
+export const getMyModels = () => GET<ModelListResponse>('/model/list');
 
-export const postCreateModel = (data: { name: string; serviceModelName: string }) =>
-  POST<ModelType>('/model/create', data);
+/**
+ * 创建一个模型
+ */
+export const postCreateModel = (data: { name: string }) => POST<string>('/model/create', data);
 
+/**
+ * 根据 ID 删除模型
+ */
 export const delModelById = (id: string) => DELETE(`/model/del?modelId=${id}`);
 
-export const getModelById = (id: string) => GET<ModelType>(`/model/detail?modelId=${id}`);
+/**
+ * 根据 ID 获取模型
+ */
+export const getModelById = (id: string) => GET<ModelSchema>(`/model/detail?modelId=${id}`);
 
+/**
+ * 根据 ID 更新模型
+ */
 export const putModelById = (id: string, data: ModelUpdateParams) =>
   PUT(`/model/update?modelId=${id}`, data);
 
-export const postTrainModel = (id: string, form: FormData) =>
-  POST(`/model/train?modelId=${id}`, form, {
-    headers: {
-      'content-type': 'multipart/form-data'
-    }
-  });
-
-export const putModelTrainingStatus = (id: string) => PUT(`/model/putTrainStatus?modelId=${id}`);
-
-export const getModelTrainings = (id: string) =>
-  GET<TrainingItemType[]>(`/model/getTrainings?modelId=${id}`);
+/* 共享市场 */
+/**
+ * 获取共享市场模型
+ */
+export const getShareModelList = (data: { searchText?: string } & RequestPaging) =>
+  POST(`/model/share/getModels`, data);
+/**
+ * 获取我收藏的模型
+ */
+export const getCollectionModels = () => GET<ShareModelItem[]>(`/model/share/getCollection`);
+/**
+ * 收藏/取消收藏模型
+ */
+export const triggerModelCollection = (modelId: string) =>
+  POST<number>(`/model/share/collection?modelId=${modelId}`);

src/api/openapi.ts

@@ -0,0 +1,16 @@
+import { GET, POST, DELETE } from './request';
+import { UserOpenApiKey } from '@/types/openapi';
+/**
+ * crete a api key
+ */
+export const createAOpenApiKey = () => POST<string>('/openapi/postKey');
+
+/**
+ * get api keys
+ */
+export const getOpenApiKeys = () => GET<UserOpenApiKey[]>('/openapi/getKeys');
+
+/**
+ * delete api by id
+ */
+export const delOpenApiById = (id: string) => DELETE(`/openapi/delKey?id=${id}`);

src/api/plugins/kb.ts

@@ -0,0 +1,75 @@
+import { GET, POST, PUT, DELETE } from '../request';
+import type { KbItemType } from '@/types/plugin';
+import { RequestPaging } from '@/types/index';
+import { SplitTextTypEnum } from '@/constants/plugin';
+import { KbDataItemType } from '@/types/plugin';
+
+export type KbUpdateParams = { id: string; name: string; tags: string; avatar: string };
+
+/* knowledge base */
+export const getKbList = () => GET<KbItemType[]>(`/plugins/kb/list`);
+
+export const getKbById = (id: string) => GET<KbItemType>(`/plugins/kb/detail?id=${id}`);
+
+export const postCreateKb = (data: { name: string }) => POST<string>(`/plugins/kb/create`, data);
+
+export const putKbById = (data: KbUpdateParams) => PUT(`/plugins/kb/update`, data);
+
+export const delKbById = (id: string) => DELETE(`/plugins/kb/delete?id=${id}`);
+
+/* kb data */
+type GetKbDataListProps = RequestPaging & {
+  kbId: string;
+  searchText: string;
+};
+export const getKbDataList = (data: GetKbDataListProps) =>
+  POST(`/plugins/kb/data/getDataList`, data);
+
+/**
+ * 获取导出数据（不分页）
+ */
+export const getExportDataList = (kbId: string) =>
+  GET<[string, string][]>(`/plugins/kb/data/exportModelData?kbId=${kbId}`);
+
+/**
+ * 获取模型正在拆分数据的数量
+ */
+export const getTrainingData = (kbId: string) =>
+  GET<{
+    splitDataQueue: number;
+    embeddingQueue: number;
+  }>(`/plugins/kb/data/getTrainingData?kbId=${kbId}`);
+
+/**
+ * 获取 web 页面内容
+ */
+export const getWebContent = (url: string) => POST<string>(`/model/data/fetchingUrlData`, { url });
+
+/**
+ * 直接push数据
+ */
+export const postKbDataFromList = (data: {
+  kbId: string;
+  data: { a: KbDataItemType['a']; q: KbDataItemType['q'] }[];
+}) => POST(`/openapi/kb/pushData`, data);
+
+/**
+ * 更新一条数据
+ */
+export const putKbDataById = (data: { dataId: string; a: string; q?: string }) =>
+  PUT('/openapi/kb/updateData', data);
+/**
+ * 删除一条知识库数据
+ */
+export const delOneKbDataByDataId = (dataId: string) =>
+  DELETE(`/openapi/kb/delDataById?dataId=${dataId}`);
+
+/**
+ * 拆分数据
+ */
+export const postSplitData = (data: {
+  kbId: string;
+  chunks: string[];
+  prompt: string;
+  mode: `${SplitTextTypEnum}`;
+}) => POST(`/openapi/text/splitText`, data);

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 { clearCookie } from '@/utils/user';
+import { TOKEN_ERROR_CODE } from '@/service/errorCode';
 
 interface ConfigType {
   headers?: { [key: string]: string };
@@ -17,7 +17,7 @@ interface ResponseDataType {
  */
 function requestStart(config: InternalAxiosRequestConfig): InternalAxiosRequestConfig {
   if (config.headers) {
-    config.headers.Authorization = getToken();
+    // config.headers.Authorization = getToken();
   }
 
   return config;
@@ -34,10 +34,10 @@ function responseSuccess(response: AxiosResponse<ResponseDataType>) {
  */
 function checkRes(data: ResponseDataType) {
   if (data === undefined) {
-    console.log(data, 'data is empty');
+    console.log('error->', data, 'data is empty');
     return Promise.reject('服务器异常');
   } else if (data.code < 200 || data.code >= 400) {
-    return Promise.reject(data.message);
+    return Promise.reject(data);
   }
   return data.data;
 }
@@ -46,24 +46,23 @@ function checkRes(data: ResponseDataType) {
  * 响应错误
  */
 function responseError(err: any) {
-  console.error('请求错误', err);
+  console.log('error->', '请求错误', err);
 
   if (!err) {
-    return Promise.reject('未知错误');
+    return Promise.reject({ message: '未知错误' });
   }
   if (typeof err === 'string') {
-    return Promise.reject(err);
+    return Promise.reject({ message: err });
   }
   if (err.response) {
     // 有报错响应
     const res = err.response;
-    /* token过期,判断请求token与本地是否相同，若不同需要重发 */
     if (res.data.code in TOKEN_ERROR_CODE) {
-      clearToken();
-      return Promise.reject('token过期，重新登录');
+      clearCookie();
+      return Promise.reject({ message: 'token过期，重新登录' });
     }
   }
-  return Promise.reject('未知错误');
+  return Promise.reject(err);
 }
 
 /* 创建请求实例 */

src/api/response/chat.d.ts

@@ -0,0 +1,25 @@
+import type { ChatPopulate, ModelSchema } from '@/types/mongoSchema';
+import type { ChatItemType } from '@/types/chat';
+
+export interface InitChatResponse {
+  chatId: string;
+  modelId: string;
+  model: {
+    name: string;
+    avatar: string;
+    intro: string;
+    canUse: boolean;
+  };
+  chatModel: ModelSchema['chat']['chatModel']; // 对话模型名
+  history: ChatItemType[];
+}
+
+export interface InitShareChatResponse {
+  maxContext: number;
+  model: {
+    name: string;
+    avatar: string;
+    intro: string;
+  };
+  chatModel: ModelSchema['chat']['chatModel']; // 对话模型名
+}

src/api/response/model.d.ts

@@ -0,0 +1,6 @@
+import { ModelListItemType } from '@/types/model';
+
+export type ModelListResponse = {
+  myModels: ModelListItemType[];
+  myCollectionModels: ModelListItemType[];
+};

src/api/response/user.d.ts

@@ -1,5 +1,12 @@
 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/system.ts

@@ -0,0 +1,6 @@
+import { GET, POST, PUT } from './request';
+import type { ChatModelItemType } from '@/constants/model';
+
+export const getFilling = () => GET<{ beianText: string }>('/system/getFiling');
+
+export const getSystemModelList = () => GET<ChatModelItemType[]>('/system/getModels');

src/api/user.ts

@@ -1,48 +1,89 @@
 import { GET, POST, PUT } from './request';
-import { createHashPassword } from '@/utils/tools';
-import { ResLogin } from './response/user';
-import { EmailTypeEnum } from '@/constants/common';
+import { createHashPassword, Obj2Query } from '@/utils/tools';
+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)
   });
 
+export const loginOut = () => GET('/user/loginout');
+
 export const putUserInfo = (data: UserUpdateParams) => PUT('/user/update', data);
+
+export const getUserBills = (data: RequestPaging) =>
+  GET<PagingData<BillSchema>>(`/user/getBill?${Obj2Query(data)}`).then((res) => ({
+    ...res,
+    data: res.data.map((bill) => adaptBill(bill))
+  }));
+
+export const getPayOrders = () => GET<PaySchema[]>(`/user/getPayOrders`);
+
+export const getPayCode = (amount: number) =>
+  GET<{
+    codeUrl: string;
+    payId: string;
+  }>(`/user/getPayCode?amount=${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/back.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="1683436459815" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1278" xmlns:xlink="http://www.w3.org/1999/xlink" width="64" height="64"><path d="M377.04830749 512.02677874l395.88826112-382.68981248c23.33363769-22.59430969 23.33363769-59.16132466 0-81.68344804-23.33247261-22.5582171-61.18836224-22.5582171-84.52083485 0L250.30081877 471.19378659c-23.29754397 22.5582171-23.29754397 59.14385977 0 81.63105451l438.11491385 423.52280349c11.70233003 11.27968995 26.99767353 16.91837099 42.29534607 16.91837098 15.29883648 0 30.59418112-5.63984498 42.22548878-16.95446471 23.33363769-22.5582171 23.33363769-59.07283854 0-81.63105451L377.04830749 512.02677874" p-id="1279"></path></svg>

src/components/Icon/icons/chat.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="1683254586102" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="940" xmlns:xlink="http://www.w3.org/1999/xlink" width="64" height="64"><path d="M512 34.13333333c263.91893333 0 477.86666667 213.94773333 477.86666667 477.86666667S775.91893333 989.86666667 512 989.86666667H79.6448A45.51146667 45.51146667 0 0 1 34.13333333 944.3552V512C34.13333333 248.08106667 248.08106667 34.13333333 512 34.13333333zM307.2 580.26666667a22.7552 22.7552 0 0 0-22.7552 22.7552V648.53333333A22.7552 22.7552 0 0 0 307.2 671.28853333h227.5552A22.7552 22.7552 0 0 0 557.51146667 648.53333333v-45.51146666A22.7552 22.7552 0 0 0 534.7552 580.26666667H307.2z m0-182.0448a22.7552 22.7552 0 0 0-22.7552 22.75626666v45.5104A22.7552 22.7552 0 0 0 307.2 489.2448h409.6a22.7552 22.7552 0 0 0 22.7552-22.75626667v-45.5104A22.7552 22.7552 0 0 0 716.8 398.22186667H307.2z" p-id="941"></path></svg>

src/components/Icon/icons/chatSend.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="1679805359001" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1328" xmlns:xlink="http://www.w3.org/1999/xlink" width="48" height="48"><path d="M416.583186 1022.194004c-5.417989 0-10.835979-1.203998-16.253968-3.611993-15.049971-6.621987-24.681952-21.069959-24.681952-37.323927l0-299.795414c0-12.641975 5.417989-24.079953 15.651969-31.905938 9.631981-7.825985 22.273956-10.23398 34.915932-7.825985l417.787184 99.931805 84.279835-599.590829c1.203998-9.631981-8.427984-16.253968-16.855967-11.437978L147.489712 573.102881l139.061728 35.517931c19.865961 4.815991 34.313933 22.875955 32.507937 43.343915-2.407995 25.885949-26.487948 42.139918-50.567901 36.119929L30.70194 627.282775c-16.253968-4.213992-27.691946-17.457966-30.099941-33.711934-2.407995-16.253968 5.417989-32.507937 19.865961-40.93592L962.59612 6.621987c13.243974-7.825985 30.099941-7.223986 43.343915 1.203998 12.641975 8.427984 19.865961 24.079953 17.457966 39.129924l-105.349794 750.090535c-1.805996 11.437978-7.825985 21.671958-17.457966 28.293945-9.631981 6.621987-21.069959 8.427984-32.507937 6.019988l-411.165197-98.125808 0 154.111699 81.87184-76.453851c15.049971-13.845973 37.925926-16.855967 54.179894-4.213992 20.46796 15.651969 21.069959 45.149912 3.009994 62.005879L444.275132 1011.358025C436.449148 1018.582011 426.817166 1022.194004 416.583186 1022.194004L416.583186 1022.194004z" p-id="1329"></path><path d="M416.583186 722.398589c-9.631981 0-19.263962-3.611993-27.089947-10.23398-16.855967-15.049971-18.059965-40.93592-3.009994-57.791887l216.117578-242.003527c15.049971-16.855967 40.93592-18.059965 57.791887-3.009994 16.855967 15.049971 18.059965 40.93592 3.009994 57.791887l-216.117578 242.003527C438.857143 718.184597 427.419165 722.398589 416.583186 722.398589L416.583186 722.398589z" p-id="1330"></path></svg>

src/components/Icon/icons/closeSolid.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="1683455612885" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1736" xmlns:xlink="http://www.w3.org/1999/xlink" width="64" height="64"><path d="M848.41813333 174.4896q69.90506667 69.90506667 104.31146667 157.2864t34.4064 179.13173333-34.4064 179.13173334-104.31146667 157.2864-157.2864 104.8576-179.13173333 34.95253333-179.67786667-34.95253333-157.83253333-104.8576-104.8576-157.2864-34.95253333-179.13173334 34.95253333-179.13173333 104.8576-157.2864 157.83253333-104.31146667 179.67786667-34.4064 179.13173333 34.4064 157.2864 104.31146667zM734.8224 729.36106667q22.9376-22.9376 20.20693333-52.4288t-25.66826666-52.4288l-114.688-114.688 114.688-114.688q22.9376-22.9376 25.66826666-52.4288t-20.20693333-52.4288-55.15946667-22.9376-55.15946666 22.9376l-114.688 113.59573333-111.4112-111.4112q-22.9376-21.84533333-52.4288-24.576t-52.4288 19.11466667q-22.9376 22.9376-22.9376 55.7056t22.9376 55.7056l111.4112 111.4112-111.4112 111.4112q-22.9376 22.9376-22.9376 55.15946666t22.9376 55.15946667 52.4288 20.20693333 52.4288-25.66826666l111.4112-111.4112 114.688 114.688q22.9376 22.9376 55.15946666 22.9376t55.15946667-22.9376z" p-id="1737"></path></svg>

src/components/Icon/icons/collectionLight.svg

@@ -0,0 +1 @@
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src/components/Icon/icons/collectionSolid.svg

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src/components/Icon/icons/copy.svg

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src/components/Icon/icons/delete.svg

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src/components/Icon/icons/develop.svg

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src/components/Icon/icons/empty.svg

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src/components/Icon/icons/git.svg

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src/components/Icon/icons/kb.svg

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src/components/Icon/icons/model.svg

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src/components/Icon/icons/more.svg

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src/components/Icon/icons/out.svg

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src/components/Icon/icons/phoneTabbar/chat.svg

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src/components/Icon/icons/phoneTabbar/me.svg

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src/components/Icon/icons/phoneTabbar/model.svg

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src/components/Icon/icons/phoneTabbar/more.svg

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src/components/Icon/icons/promotion.svg

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src/components/Icon/icons/shareMarket.svg

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src/components/Icon/icons/stop.svg

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+<?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/user.svg

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