perf: global variable any type (#1387)

* fix: tool name cannot startwith number

* fix: chatbox update

* fix: chatbox

* perf: drag ui

* perf: drag component

* drag component

.github/ISSUE_TEMPLATE/bugs.md

@@ -21,7 +21,7 @@ assignees: ''
 - [ ] 公有云版本
 - [ ] 私有部署版本, 具体版本号: 
 
-**问题描述**
+**问题描述, 日志截图**
 
 **复现步骤**
 

.github/workflows/fastgpt-image.yml

@@ -6,7 +6,7 @@ on:
       - 'projects/app/**'
       - 'packages/**'
     tags:
-      - 'v*.*.*'
+      - 'v*'
 jobs:
   build-fastgpt-images:
     runs-on: ubuntu-20.04

.vscode/nextapi.code-snippets

@@ -0,0 +1,29 @@
+{
+	// Place your FastGPT 工作区 snippets here. Each snippet is defined under a snippet name and has a scope, prefix, body and 
+	// description. Add comma separated ids of the languages where the snippet is applicable in the scope field. If scope 
+	// is left empty or omitted, the snippet gets applied to all languages. The prefix is what is 
+	// used to trigger the snippet and the body will be expanded and inserted. Possible variables are: 
+	// $1, $2 for tab stops, $0 for the final cursor position, and ${1:label}, ${2:another} for placeholders. 
+	// Placeholders with the same ids are connected.
+	// Example:
+	"Next api template": {
+		"scope": "javascript,typescript",
+		"prefix": "nextapi",
+		"body": [
+			"import type { NextApiRequest, NextApiResponse } from 'next';",
+			"import { NextAPI } from '@/service/middle/entry';",
+			"",
+			"type Props = {};",
+			"",
+			"type Response = {};",
+			"",
+			"async function handler(req: NextApiRequest, res: NextApiResponse<any>): Promise<Response> {",
+			"    $1",
+			"    return {}",
+			"}",
+			"",
+			"export default NextAPI(handler);"
+		],
+		"description": "FastGPT Next API template"
+	}
+}

.vscode/settings.json

@@ -4,12 +4,12 @@
     "typescript.tsdk": "node_modules/typescript/lib",
     "prettier.prettierPath": "",
     "i18n-ally.localesPaths": [
-        "projects/app/public/locales",
+        "projects/app/i18n",
     ],
-    "i18n-ally.enabledParsers": ["json"],
+    "i18n-ally.enabledParsers": ["json", "yaml", "js", "ts"],
     "i18n-ally.keystyle": "nested",
     "i18n-ally.sortKeys": true,
-    "i18n-ally.keepFulfilled": true,
+    "i18n-ally.keepFulfilled": false,
     "i18n-ally.sourceLanguage": "zh", // 根据此语言文件翻译其他语言文件的变量和内容
-    "i18n-ally.displayLanguage": "zh", // 显示语言
+    "i18n-ally.displayLanguage": "zh" // 显示语言
 }

Dockerfile

@@ -19,20 +19,6 @@ RUN [ -f pnpm-lock.yaml ] || (echo "Lockfile not found." && exit 1)
 
 RUN pnpm i
 
-# --------- install dependence -----------
-FROM node:18.17-alpine AS workerDeps
-WORKDIR /app
-
-ARG proxy
-
-RUN [ -z "$proxy" ] || sed -i 's/dl-cdn.alpinelinux.org/mirrors.ustc.edu.cn/g' /etc/apk/repositories
-RUN apk add --no-cache libc6-compat && npm install -g pnpm@8.6.0
-# if proxy exists, set proxy
-RUN [ -z "$proxy" ] || pnpm config set registry https://registry.npmmirror.com
-
-COPY ./worker /app/worker
-RUN cd /app/worker && pnpm i --production --ignore-workspace
-
 # --------- builder -----------
 FROM node:18.17-alpine AS builder
 WORKDIR /app
@@ -72,12 +58,15 @@ COPY --from=builder /app/projects/$name/public /app/projects/$name/public
 COPY --from=builder /app/projects/$name/next.config.js /app/projects/$name/next.config.js
 COPY --from=builder --chown=nextjs:nodejs /app/projects/$name/.next/standalone /app/
 COPY --from=builder --chown=nextjs:nodejs /app/projects/$name/.next/static /app/projects/$name/.next/static
+# copy server chunks
+COPY --from=builder --chown=nextjs:nodejs /app/projects/$name/.next/server/chunks /app/projects/$name/.next/server/chunks
+# copy worker
+COPY --from=builder --chown=nextjs:nodejs /app/projects/$name/.next/server/worker /app/projects/$name/.next/server/worker
 # copy package.json to version file
 COPY --from=builder /app/projects/$name/package.json ./package.json 
-# copy woker
-COPY --from=workerDeps /app/worker /app/worker
 # copy config
 COPY ./projects/$name/data /app/data
+
 RUN chown -R nextjs:nodejs /app/data
 
 ENV NODE_ENV production

README.md

@@ -86,6 +86,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
    - [x] Iframe 一键嵌入
    - [x] 聊天窗口嵌入支持自定义 Icon，默认打开，拖拽等功能
    - [x] 统一查阅对话记录，并对数据进行标注
+   
 `6` 其他
    - [x] 支持语音输入和输出 (可配置语音输入语音回答)
 
@@ -121,7 +122,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
 
 wx 扫一下加入：
 
-![](https://oss.laf.run/cofxat-test/fastgpt-qr-code2.jpg)
+![](https://oss.laf.run/htr4n1-images/fastgpt-qr-code.jpg)
 
 <a href="#readme">
     <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">

docSite/assets/docs/scss/custom/pages/_custom.scss

@@ -1,3 +1,16 @@
+:root {
+    --code-bg: rgba(0, 0, 0, 0.03);
+	--code-color: rgba(14, 116, 144, 0.95);
+	--inline-code-border: 0.5px solid var(--gray-400);
+
+}
+
+[data-dark-mode] {
+    --code-bg: hsla(0, 2%, 14%, 1);
+	--code-color: #f3f4f6ed;
+	--inline-code-border: 0.5px solid var(--gray-600);
+}
+
 #content {
 	font-family: JetBrains Mono, LXGW WenKai Screen, -apple-system, BlinkMacSystemFont, "Segoe UI", "Roboto", "Helvetica Neue", "Ubuntu";
 }
@@ -62,11 +75,33 @@ div.code-toolbar {
     z-index: 1;
 }
 
+.docs-content .main-content pre code {
+	padding: 0 2.5rem 1.25rem .9rem;
+  }
+
+.docs-content .main-content code {
+	font-size: .875em;
+	padding: 1px 2px;
+	background: var(--code-bg);
+	border: var(--inline-code-border);
+	padding-top: 3px;
+	padding-bottom: 3px;
+	padding-left: 5px;
+	padding-right: 5px;
+	border-radius: .25rem;
+	color: var(--code-color);
+}
+
 li p {
     margin-top: 1rem !important;
     margin-bottom: 1rem;
 }
 
+.docs-content .main-content ul > li {
+    margin-top: .3rem !important;
+    margin-bottom: .3rem;
+}
+
 footer {
 	height: 118px !important;
 }

docSite/assets/docs/scss/custom/plugins/prism/themes/_lotusdocs.scss

@@ -0,0 +1,178 @@
+ /**
+ * Lotus Docs theme
+ *
+ * Adapted from a theme based on:
+ * https://github.com/chriskempson/tomorrow-theme
+ *
+ * @author Colin Wilson <github.com/colinwilson>
+ * @version 1.0
+ */
+
+ :root {
+    --prism-code-bg: #faf9f8;
+    --prism-code-scrollbar-thumb-color: var(--gray-400);
+    --prism-color: #333;
+    --prism-bg: #f0f0f0;
+    --prism-highlight-bg: var(--blue-200);
+    --prism-copy-bg: var(--gray-500);
+    --prism-copy-hover-bg: var(--gray-700);
+    --prism-copy-success-bg: var(--emerald-500);
+    --prism-token-punctuation: #666;
+    --prism-token-deleted: #2b6cb0;
+    --prism-token-function-name: #3182bd;
+    --prism-token-function: #c53030;
+    --prism-token-number: var(--cardinal-600);
+    --prism-token-symbol: #333;
+    --prism-token-builtin: #1a202c;
+    --prism-token-regex: #2f855a;
+    --prism-token-variable: var(--yellow-700);
+    --prism-token-url: #4fd1c5;
+    --prism-token-inserted: #38a169;
+}
+
+[data-dark-mode] {
+    --prism-code-bg: var(--gray-900);
+    --prism-code-scrollbar-thumb-color: var(--gray-600);
+    --prism-color: #f5fbff;
+    --prism-bg: #32325d;
+    --prism-highlight-bg: var(--blue-400);
+    --prism-copy-bg: var(--gray-400);
+    --prism-copy-hover-bg: var(--white);
+    --prism-copy-success-bg: var(--emerald-200);
+    --prism-token-punctuation: #ccc;
+    --prism-token-deleted: #7fd3ed;
+    --prism-token-function-name: #6196cc;
+    --prism-token-function: #fda3f3;
+    --prism-token-number: var(--cardinal-200);
+    --prism-token-symbol: #ffffff;
+    --prism-token-builtin: #a4cdfe;
+    --prism-token-regex: #7ec699;
+    --prism-token-variable: var(--yellow-100);
+    --prism-token-url: #67cdcc;
+    --prism-token-inserted: green;
+}
+
+ code[class*="language-"],
+ pre[class*="language-"] {
+     color: var(--prism-color) !important;
+     background: var(--prism-code-bg) !important;
+ }
+
+/* Code blocks */
+pre[class*="language-"] {
+    // padding: 1em;
+    // margin: .5em 0;
+    overflow: auto;
+    border-radius: 0 0 4px 4px;
+}
+
+:not(pre) > code[class*="language-"],
+pre[class*="language-"] {
+    background: var(--prism-bg);
+}
+
+/* Inline code */
+:not(pre) > code[class*="language-"] {
+    padding: .1em;
+    border-radius: .3em;
+    white-space: normal;
+}
+
+.line-highlight:before,
+.line-highlight[data-end]:after {
+    background-color: var(--prism-highlight-bg);
+}
+
+[data-copy-state="copy"] span:empty::before {
+    background-color: var(--prism-copy-bg);
+}
+
+[data-copy-state="copy"] span:empty:hover::before {
+    background-color: var(--prism-copy-hover-bg);
+}
+
+[data-copy-state="copy-success"] span:empty::before {
+    background-color: var(--prism-copy-success-bg);
+}
+
+.token.comment,
+.token.block-comment,
+.token.prolog,
+.token.doctype,
+.token.cdata {
+    color: #999;
+}
+
+.token.punctuation {
+    color: var(--prism-token-punctuation);
+}
+
+.token.tag,
+.token.attr-name,
+.token.namespace,
+.token.deleted {
+    color: var(--prism-token-deleted);
+}
+
+.token.function-name {
+    color: var(--prism-token-function-name);
+}
+
+.token.boolean,
+.token.function {
+    color: var(--prism-token-function);
+}
+
+.token.number {
+    color: var(--prism-token-number);
+}
+
+.token.property,
+.token.class-name,
+.token.constant,
+.token.symbol {
+    color: var(--prism-token-symbol);
+    font-weight: 700;
+}
+
+.token.selector,
+.token.important,
+.token.atrule,
+.token.keyword,
+.token.builtin {
+    color: var(--prism-token-builtin);
+    font-weight: 700;
+}
+
+.token.string,
+.token.char,
+.token.attr-value,
+.token.regex {
+    color: var(--prism-token-regex);
+}
+
+.token.variable {
+    color: var(--prism-token-variable);
+}
+
+.token.operator,
+.token.entity,
+.token.url {
+    color: var(--prism-token-url);
+}
+
+.token.important,
+.token.bold {
+    font-weight: bold;
+}
+.token.italic {
+    font-style: italic;
+}
+
+.token.entity {
+    cursor: help;
+}
+
+.token.inserted {
+    color: var(--prism-token-inserted);
+}

docSite/content/docs/commercial/intro.md

@@ -48,15 +48,14 @@ FastGPT 商业版软件根据不同的部署方式，分为 3 类收费模式。
 {{< table "table-hover table-striped-columns" >}}
 | 部署方式 | 特有服务 | 上线时长 | 标品价格 |
 | ---- | ---- | ---- | ---- |
-| Sealos全托管 |  1. 有效期内免费升级。<br>2. 免运维服务&数据库。 |  半天  | 3000元起/月（3个月起）<br>或<br>30000元起/年  |
-| 自有服务器-单机版 |  1. 6个版本的升级服务。 | 14天内 |  60000元/套（不限时长） | 
-| 自有服务器-高可用版 | 1. 6个版本的升级服务。 | 14天内 | 150000元/套（不限时长）|
+| Sealos全托管 |  1. 有效期内免费升级。<br>2. 免运维服务&数据库。 |  半天  | 5000元起/月（3个月起）<br>或<br>50000元起/年  |
+| 自有服务器部署 |  1. 6个版本的升级服务。 | 14天内 |  具体价格可[联系咨询](https://fael3z0zfze.feishu.cn/share/base/form/shrcnRxj3utrzjywsom96Px4sud) |
 {{< /table >}}
 
 {{% alert icon="🤖 " context="success" %}}
 - 6个版本的升级服务不是指只能用 6 个版本，而是指依赖 FastGPT 团队提供的升级服务。大部分时候，建议自行升级，也不麻烦。
 - 全托管版本适合技术人员紧缺的团队，仅需关注业务推动，无需关心服务是否正常运行。
-- 单机版和高可用版可以完全部署在自己服务器中。
+- 自有服务器部署版可以完全部署在自己服务器中。
 - 单机版适合中小团队对内提供服务，需要自己维护数据库备份等。
 - 高可用版适合对外提供在线服务，包含可视化监控、多副本、负载均衡、数据库自动备份等生产环境的基础设施。
 {{% /alert %}}

docSite/content/docs/course/websync.md

@@ -0,0 +1,80 @@
+---
+title: 'Web 站点同步'
+description: 'FastGPT Web 站点同步功能介绍和使用方式'
+icon: 'language'
+draft: false
+toc: true
+weight: 105
+---
+
+![](/imgs/webSync1.jpg)
+
+该功能目前仅向商业版用户开放。
+
+## 什么是 Web 站点同步
+
+Web 站点同步利用爬虫的技术，可以通过一个入口网站，自动捕获`同域名`下的所有网站，目前最多支持`200`个子页面。出于合规与安全角度，FastGPT 仅支持`静态站点`的爬取，主要用于各个文档站点快速构建知识库。
+
+Tips: 国内的媒体站点基本不可用，公众号、csdn、知乎等。可以通过终端发送`curl`请求检测是否为静态站点，例如：
+
+```bash
+curl https://doc.fastgpt.in/docs/intro/
+```
+
+## 如何使用
+
+### 1. 新建知识库，选择 Web 站点同步
+
+![](/imgs/webSync2.png)
+
+![](/imgs/webSync3.png)
+
+### 2. 点击配置站点信息
+
+![](/imgs/webSync4.png)
+
+### 3. 填写网址和选择器
+
+![](/imgs/webSync5.jpg)
+
+好了， 现在点击开始同步，静等系统自动抓取网站信息即可。
+
+
+## 创建应用，绑定知识库
+
+![](/imgs/webSync6.webp)
+
+## 选择器如何使用
+
+选择器是 HTML CSS JS 的产物，你可以通过选择器来定位到你需要抓取的具体内容，而不是整个站点。使用方式为：
+
+### 首先打开浏览器调试面板（通常是 F12，或者【右键 - 检查】）
+
+![](/imgs/webSync7.webp)
+
+![](/imgs/webSync8.webp)
+
+### 输入对应元素的选择器
+
+[菜鸟教程 css 选择器](https://www.runoob.com/cssref/css-selectors.html)，具体选择器的使用方式可以参考菜鸟教程。
+
+上图中，我们选中了一个区域，对应的是`div`标签，它有 `data-prismjs-copy`, `data-prismjs-copy-success`, `data-prismjs-copy-error` 三个属性，这里我们用到一个就够。所以选择器是：
+**`div[data-prismjs-copy]`**
+
+除了属性选择器，常见的还有类和ID选择器。例如：
+
+![](/imgs/webSync9.webp)
+
+上图 class 里的是类名（可能包含多个类名，都是空格隔开的，选择一个即可），选择器可以为：**`.docs-content`**
+
+### 多选择器使用
+
+在开头的演示中，我们对 FastGPT 文档是使用了多选择器的方式来选择，通过逗号隔开了两个选择器。
+
+![](/imgs/webSync10.webp)
+
+我们希望选中上图两个标签中的内容，此时就需要两组选择器。一组是：`.docs-content .mb-0.d-flex`，含义是 `docs-content` 类下同时包含 `mb-0`和`d-flex` 两个类的子元素；
+
+另一组是`.docs-content div[data-prismjs-copy]`，含义是`docs-content` 类下包含`data-prismjs-copy`属性的`div`元素。
+
+把两组选择器用逗号隔开即可：`.docs-content .mb-0.d-flex, .docs-content div[data-prismjs-copy]`

docSite/content/docs/development/configuration.md

@@ -20,7 +20,7 @@ llm模型全部合并
 ```json
 {
   "feConfigs": {
-    "lafEnv": "https://laf.dev" // laf环境
+    "lafEnv": "https://laf.dev" // laf环境。 https://laf.run （杭州阿里云） ,或者私有化的laf环境。如果使用 Laf openapi 功能，需要最新版的 laf 。
   },
   "systemEnv": {
     "vectorMaxProcess": 15,

docSite/content/docs/development/custom-models/bge-rerank.md

@@ -4,7 +4,7 @@ description: '接入 bge-rerank 重排模型'
 icon: 'sort'
 draft: false
 toc: true
-weight: 910
+weight: 920
 ---
 
 ## 不同模型推荐配置
@@ -100,7 +100,7 @@ docker run -d --name reranker -p 6006:6006 -e ACCESS_TOKEN=mytoken --gpus all re
 version: "3"
 services:
   reranker:
-    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/rerank:v0.2
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-base:v0.1
     container_name: reranker
     # GPU运行环境，如果宿主机未安装，将deploy配置隐藏即可
     deploy:

docSite/content/docs/development/custom-models/chatglm2-m3e.md

@@ -4,7 +4,7 @@ description: ' 将 FastGPT 接入私有化模型 ChatGLM2和m3e-large'
 icon: 'model_training'
 draft: false
 toc: true
-weight: 930
+weight: 950
 ---
 
 ## 前言

docSite/content/docs/development/custom-models/chatglm2.md

@@ -4,7 +4,7 @@ description: ' 将 FastGPT 接入私有化模型 ChatGLM2-6B'
 icon: 'model_training'
 draft: false
 toc: true
-weight: 910
+weight: 930
 ---
 
 ## 前言

docSite/content/docs/development/custom-models/m3e.md

@@ -4,7 +4,7 @@ description: ' 将 FastGPT 接入私有化模型 M3E'
 icon: 'model_training'
 draft: false
 toc: true
-weight: 920
+weight: 940
 ---
 
 ## 前言

docSite/content/docs/development/custom-models/xinference.md

@@ -0,0 +1,184 @@
+---
+title: '使用 Xinference 接入本地模型'
+description: '一站式本地 LLM 私有化部署'
+icon: 'api'
+draft: false
+toc: true
+weight: 910
+---
+
+[Xinference](https://github.com/xorbitsai/inference) 是一款开源模型推理平台，除了支持 LLM，它还可以部署 Embedding 和 ReRank 模型，这在企业级 RAG 构建中非常关键。同时，Xinference 还提供 Function Calling 等高级功能。还支持分布式部署，也就是说，随着未来应用调用量的增长，它可以进行水平扩展。
+
+## 安装 Xinference
+
+Xinference 支持多种推理引擎作为后端，以满足不同场景下部署大模型的需要，下面会分使用场景来介绍一下这三种推理后端，以及他们的使用方法。
+
+### 1. 服务器
+
+如果你的目标是在一台 Linux 或者 Window 服务器上部署大模型，可以选择 Transformers 或 vLLM 作为 Xinference 的推理后端：
+
++ [Transformers](https://huggingface.co/docs/transformers/index)：通过集成 Huggingface 的 Transformers 库作为后端，Xinference 可以最快地 集成当今自然语言处理（NLP）领域的最前沿模型（自然也包括 LLM）。
++ [vLLM](https://vllm.ai/): vLLM 是由加州大学伯克利分校开发的一个开源库，专为高效服务大型语言模型（LLM）而设计。它引入了 PagedAttention 算法， 通过有效管理注意力键和值来改善内存管理，吞吐量能够达到 Transformers 的 24 倍，因此 vLLM 适合在生产环境中使用，应对高并发的用户访问。
+
+假设你服务器配备 NVIDIA 显卡，可以参考[这篇文章中的指令来安装 CUDA](https://xorbits.cn/blogs/langchain-streamlit-doc-chat)，从而让 Xinference 最大限度地利用显卡的加速功能。
+
+#### Docker 部署
+
+你可以使用 Xinference 官方的 Docker 镜像来一键安装和启动 Xinference 服务（确保你的机器上已经安装了 Docker），命令如下：
+
+```bash
+docker run  -p 9997:9997 --gpus all xprobe/xinference:latest xinference-local -H 0.0.0.0
+```
+
+#### 直接部署
+
+首先我们需要准备一个 3.9 以上的 Python 环境运行来 Xinference，建议先根据 conda 官网文档安装 conda。 然后使用以下命令来创建 3.11 的 Python 环境：
+
+```bash
+conda create --name py311 python=3.11
+conda activate py311
+```
+
+以下两条命令在安装 Xinference 时，将安装 Transformers 和 vLLM 作为 Xinference 的推理引擎后端：
+
+```bash
+pip install "xinference[transformers]"
+pip install "xinference[vllm]"
+pip install "xinference[transformers,vllm]" # 同时安装
+```
+
+PyPi 在 安装 Transformers 和 vLLM 时会自动安装 PyTorch，但自动安装的 CUDA 版本可能与你的环境不匹配，此时你可以根据 PyTorch 官网中的[安装指南](https://pytorch.org/get-started/locally/)来手动安装。
+
+只需要输入如下命令，就可以在服务上启动 Xinference 服务：
+
+```bash
+xinference-local -H 0.0.0.0
+```
+
+Xinference 默认会在本地启动服务，端口默认为 9997。因为这里配置了-H 0.0.0.0参数，非本地客户端也可以通过机器的 IP 地址来访问 Xinference 服务。
+
+### 2. 个人设备
+
+如果你想在自己的 Macbook 或者个人电脑上部署大模型，推荐安装 CTransformers 作为 Xinference 的推理后端。CTransformers 是用 GGML 实现的 C++ 版本 Transformers。
+
+[GGML](https://ggml.ai/) 是一个能让大语言模型在[消费级硬件上运行](https://github.com/ggerganov/llama.cpp/discussions/205)的 C++ 库。 GGML 最大的特色在于模型量化。量化一个大语言模型其实就是降低权重表示精度的过程，从而减少使用模型所需的资源。 例如，表示一个高精度浮点数（例如 0.0001）比表示一个低精度浮点数（例如 0.1）需要更多空间。由于 LLM 在推理时需要加载到内存中的，因此你需要花费硬盘空间来存储它们，并且在执行期间有足够大的 RAM 来加载它们，GGML 支持许多不同的量化策略，每种策略在效率和性能之间提供不同的权衡。
+
+通过以下命令来安装 CTransformers 作为 Xinference 的推理后端：
+
+```bash
+pip install xinference
+pip install ctransformers
+```
+
+因为 GGML 是一个 C++ 库，Xinference 通过 `llama-cpp-python` 这个库来实现语言绑定。对于不同的硬件平台，我们需要使用不同的编译参数来安装：
+
+- Apple Metal（MPS）：`CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python`
+- Nvidia GPU：`CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python`
+- AMD GPU：`CMAKE_ARGS="-DLLAMA_HIPBLAS=on" pip install llama-cpp-python`
+
+安装后只需要输入 `xinference-local`，就可以在你的 Mac 上启动 Xinference 服务。
+
+## 创建并部署模型（以 Qwen-14B 模型为例）
+
+### 1. WebUI 方式启动模型
+
+Xinference 启动之后，在浏览器中输入: `http://127.0.0.1:9997`，我们可以访问到本地 Xinference 的 Web UI。
+
+打开“Launch Model”标签，搜索到 qwen-chat，选择模型启动的相关参数，然后点击模型卡片左下方的小火箭🚀按钮，就可以部署该模型到 Xinference。 默认 Model UID 是 qwen-chat（后续通过将通过这个 ID 来访问模型）。
+
+![](/imgs/xinference-launch-model.png)
+
+当你第一次启动 Qwen 模型时，Xinference 会从 HuggingFace 下载模型参数，大概需要几分钟的时间。Xinference 将模型文件缓存在本地，这样之后启动时就不需要重新下载了。 Xinference 还支持从其他模型站点下载模型文件，例如 [modelscope](https://inference.readthedocs.io/en/latest/models/sources/sources.html)。
+
+### 2. 命令行方式启动模型
+
+我们也可以使用 Xinference 的命令行工具来启动模型，默认 Model UID 是 qwen-chat（后续通过将通过这个 ID 来访问模型）。
+
+```bash
+xinference launch -n qwen-chat -s 14 -f pytorch
+```
+
+除了 WebUI 和命令行工具， Xinference 还提供了 Python SDK 和 RESTful API 等多种交互方式， 更多用法可以参考 [Xinference 官方文档](https://inference.readthedocs.io/en/latest/getting_started/index.html)。
+
+## 将本地模型接入 One API
+
+One API 的部署和接入请参考[这里](/docs/development/one-api/)。
+
+为 qwen1.5-chat 添加一个渠道，这里的 Base URL 需要填 Xinference 服务的端点，并且注册 qwen-chat (模型的 UID) 。
+
+![](/imgs/one-api-add-xinference-models.jpg)
+
+可以使用以下命令进行测试：
+
+```bash
+curl --location --request POST 'https://<oneapi_url>/v1/chat/completions' \
+--header 'Authorization: Bearer <oneapi_token>' \
+--header 'Content-Type: application/json' \
+--data-raw '{
+  "model": "qwen-chat",
+  "messages": [{"role": "user", "content": "Hello!"}]
+}'
+```
+
+将 <oneapi_url> 替换为你的 One API 地址，<oneapi_token> 替换为你的 One API 令牌。model 为刚刚在 One API 填写的自定义模型。
+
+## 将本地模型接入 FastGPT
+
+修改 FastGPT 的 `config.json` 配置文件，其中 chatModels（对话模型）用于聊天对话，cqModels（问题分类模型）用来对问题进行分类，extractModels（内容提取模型）则用来进行工具选择。我们分别在 chatModels、cqModels 和 extractModels 中加入 qwen-chat 模型：
+
+```json
+{
+  "chatModels": [
+      ...
+      {
+        "model": "qwen-chat",
+        "name": "Qwen",
+        "maxContext": 2048,
+        "maxResponse": 2048, 
+        "quoteMaxToken": 2000,
+        "maxTemperature": 1, 
+        "vision": false, 
+        "defaultSystemChatPrompt": "" 
+      }
+      ...
+  ],
+  "cqModels": [
+      ...
+      {
+        "model": "qwen-chat",
+        "name": "Qwen",
+        "maxContext": 2048,
+        "maxResponse": 2048,
+        "inputPrice": 0,
+        "outputPrice": 0,
+        "toolChoice": true,
+        "functionPrompt": ""
+      }
+      ...
+  ],    
+  "extractModels": [
+      ...
+      {
+        "model": "qwen-chat",
+        "name": "Qwen",
+        "maxContext": 2048,
+        "maxResponse": 2048,
+        "inputPrice": 0,
+        "outputPrice": 0,
+        "toolChoice": true,
+        "functionPrompt": ""
+      }
+      ...
+  ]
+}
+```
+
+然后重启 FastGPT 就可以在应用配置中选择 Qwen 模型进行对话：
+
+![](/imgs/fastgpt-list-models.png)
+
+---
+
++ 参考：[FastGPT + Xinference：一站式本地 LLM 私有化部署和应用开发](https://xorbits.cn/blogs/fastgpt-weather-chat)
+
+

docSite/content/docs/development/faq.md

@@ -13,7 +13,8 @@ images: []
 
 1. `docker ps -a` 查看所有容器运行状态，检查是否全部 running，如有异常，尝试`docker logs 容器名`查看对应日志。
 2. 容器都运行正常的，`docker logs 容器名` 查看报错日志
-3. 无法解决时，可以找找[Issue](https://github.com/labring/FastGPT/issues)，或新提 Issue，私有部署错误，务必提供详细的日志，否则很难排查。
+3. 带有`requestId`的，都是 OneAPI 提示错误，大部分都是因为模型接口报错。
+4. 无法解决时，可以找找[Issue](https://github.com/labring/FastGPT/issues)，或新提 Issue，私有部署错误，务必提供详细的日志，否则很难排查。
 
 
 ## 二、通用问题
@@ -28,8 +29,8 @@ images: []
 
 ### 其他模型没法进行问题分类/内容提取
 
-需要给其他模型配置`toolChoice=false`，就会默认走提示词模式。目前内置提示词仅针对了商业模型API进行测试。
-问题分类基本可用，内容提取不太行。
+1. 看日志。如果提示 JSON invalid，not support tool 之类的，说明该模型不支持工具调用或函数调用，需要设置`toolChoice=false`和`functionCall=false`，就会默认走提示词模式。目前内置提示词仅针对了商业模型API进行测试。问题分类基本可用，内容提取不太行。
+2. 如果已经配置正常，并且没有错误日志，则说明可能提示词不太适合该模型，可以通过修改`customCQPrompt`来自定义提示词。
    
 ### 页面崩溃
 
@@ -44,7 +45,7 @@ images: []
 
 ### 模型响应为空(core.chat.Chat API is error or undefined)
 
-1. 检查 key 问题。
+1. 检查 key 问题。curl 请求看是否正常。务必用 stream=true 模式。并且 maxToken 等相关参数尽量一致。
 2. 如果是国内模型，可能是命中风控了。
 3. 查看模型请求日志，检查出入参数是否异常。
 
@@ -90,4 +91,9 @@ FastGPT 模型配置文件中的 model 必须与 OneAPI 渠道中的模型对应
 
 OneAPI 的 API Key 配置错误，需要修改`OPENAI_API_KEY`环境变量，并重启容器（先 docker-compose down 然后再 docker-compose up -d 运行一次）。
 
-可以`exec`进入容器，`env`查看环境变量是否生效。
+可以`exec`进入容器，`env`查看环境变量是否生效。
+
+### bad_response_status_code bad response status code 503
+
+1. 模型服务不可用
+2. ....

docSite/content/docs/development/one-api.md

@@ -1,7 +1,7 @@
 ---
-title: '部署和使用OneAPI，实现Azure、ChatGLM、本地模型接入'
-description: '部署和使用OneAPI，实现Azure、ChatGLM、本地模型接入。OneAPI使用教程'
-icon: 'Api'
+title: '使用 One API 接入 Azure、ChatGLM 和本地模型'
+description: '部署和使用 One API，实现 Azure、ChatGLM 和本地模型的接入。'
+icon: 'api'
 draft: false
 toc: true
 weight: 708
@@ -9,19 +9,19 @@ weight: 708
 
 * 默认情况下，FastGPT 只配置了 GPT 的模型，如果你需要接入其他模型，需要进行一些额外配置。
 * [One API](https://github.com/songquanpeng/one-api) 是一个 OpenAI 接口管理 & 分发系统，可以通过标准的 OpenAI API 格式访问所有的大模型，开箱即用。
-* FastGPT 可以通过接入 OneAPI 来实现对不同大模型的支持。OneAPI 的部署方法也很简单。
+* FastGPT 可以通过接入 One API 来实现对不同大模型的支持。One API 的部署方法也很简单。
 
-## FastGPT 与 OneAPI 关系
+## FastGPT 与 One API 关系
 
-可以把 OneAPI 当做一个网关。
+可以把 One API 当做一个网关。
 
 ![](/imgs/sealos-fastgpt.webp)
 
 ## 部署
 
-### docker 版本
+### Docker 版本
 
-已加入最新的`docker-compose.yml`文件中。
+已加入最新的 `docker-compose.yml` 文件中。
 
 ### Sealos - MySQL 版本
 
@@ -62,21 +62,21 @@ BATCH_UPDATE_ENABLED=true
 BATCH_UPDATE_INTERVAL=60
 ```
 
-## One API使用教程
+## One API 使用教程
 
 ### 概念
 
 1. 渠道：
    1. OneApi 中一个渠道对应一个 `Api Key`，这个 `Api Key` 可以是GPT、微软、ChatGLM、文心一言的。一个`Api Key`通常可以调用同一个厂商的多个模型。
-   2. OneAPI 会根据请求传入的`模型`来决定使用哪一个`Key`，如果一个模型对应了多个`Key`，则会随机调用。
-2. 令牌：访问 OneAPI 所需的凭证，只需要这`1`个凭证即可访问`OneAPI`上配置的模型。因此`FastGPT`中，只需要配置`OneAPI`的`baseurl`和`令牌`即可。
+   2. One API 会根据请求传入的`模型`来决定使用哪一个`Key`，如果一个模型对应了多个`Key`，则会随机调用。
+2. 令牌：访问 One API 所需的凭证，只需要这`1`个凭证即可访问`One API`上配置的模型。因此`FastGPT`中，只需要配置`One API`的`baseurl`和`令牌`即可。
 
 ### 大致工作流程
 
-1. 客户端请求 OneAPI
+1. 客户端请求 One API
 2. 根据请求中的 `model` 参数，匹配对应的渠道（根据渠道里的模型进行匹配，必须完全一致）。如果匹配到多个渠道，则随机选择一个（同优先级）。
-3. OneAPI 向真正的地址发出请求。
-4. OneAPI 将结果返回给客户端。
+3. One API 向真正的地址发出请求。
+4. One API 将结果返回给客户端。
 
 ### 1. 登录 One API
 
@@ -96,7 +96,7 @@ BATCH_UPDATE_INTERVAL=60
 
 ### 3. 修改账号余额
 
-OneAPI 默认 root 用户只有 200刀，可以自行修改编辑。
+One API 默认 root 用户只有 200刀，可以自行修改编辑。
 
 ### 4. 修改 FastGPT 的环境变量
 

docSite/content/docs/development/openapi/share.md

@@ -286,7 +286,7 @@ type ResponseType = {
     pluginOutput?: Record<string, any>; // 插件输出
     pluginDetail?: ChatHistoryItemResType[]; // 插件详情
 
-    tfSwitchResult?: boolean; // 判断器结果
+    isElseResult?: boolean; // 判断器结果
 }
 ```
 

docSite/content/docs/development/sealos.md

@@ -106,6 +106,7 @@ FastGPT 商业版共包含了2个应用（fastgpt, fastgpt-plus）和2个数据
 
 ```
 SYSTEM_NAME=FastGPT
+SYSTEM_DESCRIPTION=
 SYSTEM_FAVICON=/favicon.ico
 HOME_URL=/app/list
 ```

docSite/content/docs/development/upgrading/471.md

@@ -1,5 +1,5 @@
 ---
-title: 'V4.7.1(进行中)'
+title: 'V4.7.1(需要初始化)'
 description: 'FastGPT V4.7.1 更新说明'
 icon: 'upgrade'
 draft: false
@@ -19,15 +19,23 @@ curl --location --request POST 'https://{{host}}/api/admin/clearInvalidData' \
 
 该请求会执行脏数据清理（清理无效的文件、清理无效的图片、清理无效的知识库集合、清理无效的向量）
 
+
+## 修改配置文件
+
+增加了Laf环境配置：[点击查看最新的配置文件](/docs/development/configuration/)
+
+
 ## V4.7.1 更新说明
 
 1. 新增 - 语音输入完整配置。支持选择是否打开语音输入（包括分享页面），支持语音输入后自动发送，支持语音输入后自动语音播放（流式）。
-2. 新增 - Pptx 和 xlsx 文件读取。但所有文件读取都放服务端，会消耗更多的服务器资源，以及无法在上传时预览更多内容。
+2. 新增 - pptx 和 xlsx 文件读取。但所有文件读取都放服务端，会消耗更多的服务器资源，以及无法在上传时预览更多内容。
 3. 新增 - 集成 Laf 云函数，可以读取 Laf 账号中的云函数作为 HTTP 模块。
 4. 新增 - 定时器，清理垃圾数据。（采用小范围清理，会清理最近n个小时的，所以请保证服务持续运行，长时间不允许，可以继续执行 clearInvalidData 的接口进行全量清理。）
 5. 商业版新增 - 后台配置系统通知。
-6. 修改 - csv导入模板，取消 header 校验，自动获取前两列。
-7. 修复 - 工具调用模块连线数据类型校验错误。
-8. 修复 - 自定义索引输入时，解构数据失败。
-9. 修复 - rerank 模型数据格式。
-10. 修复 - 问题补全历史记录BUG
+6. 优化 - 支持ip模式导出知识库。
+7. 修改 - csv导入模板，取消 header 校验，自动获取前两列。
+8. 修复 - 工具调用模块连线数据类型校验错误。
+9. 修复 - 自定义索引输入时，解构数据失败。
+10. 修复 - rerank 模型数据格式。
+11. 修复 - 问题补全历史记录BUG
+12. 修复 - 分享页面特殊情况下加载缓慢问题（由于ssr时候数据库不会触发连接）

docSite/content/docs/development/upgrading/48.md

@@ -0,0 +1,31 @@
+---
+title: 'V4.8(开发中)'
+description: 'FastGPT V4.8 更新说明'
+icon: 'upgrade'
+draft: false
+toc: true
+weight: 824
+---
+
+## 新工作流
+
+FastGPT workflow V2上线，支持更加简洁的工作流模式。
+
+**由于工作流差异较大，需要手动重新构建。**
+
+给应用和插件增加了 version 的字段，用于标识是旧工作流还是新工作流。当你更新 4.8 后，保存和新建的工作流均为新版，旧版工作流会有一个重置的弹窗提示。并且，如果是通过 API 和 分享链接 调用的工作流，仍可以正常使用，直到你下次保存它们。
+
+## V4.8 更新说明
+
+1. 重构 - 工作流
+2. 新增 - 判断器。支持 if elseIf else 判断。
+3. 新增 - 变量更新节点。支持更新运行中工作流输出变量，或更新全局变量。
+4. 新增 - 工作流 Debug 模式，可以调试单个节点或者逐步调试工作流。
+5. 新增 - 定时执行应用。可轻松实现定时任务。
+6. 新增 - 插件自定义输入优化，可以渲染输入组件。
+7. 优化 - 工作流连线，可以四向连接，方便构建循环工作流。
+8. 优化 - 工作流上下文传递，性能🚀。
+9. 优化 - 简易模式，更新配置后自动更新调试框内容，无需保存。
+10. 优化 - worker进程管理，并将计算 Token 任务分配给 worker 进程。
+11. 修复 - 工具调用时候，name不能是数字开头（随机数有概率数字开头）
+12. 修复 - 分享链接， query 全局变量会被缓存。

docSite/content/docs/pricing.md

@@ -5,6 +5,8 @@ icon: 'currency_yen'
 draft: false
 toc: true
 weight: 1200
+type: redirect
+target: https://cloud.fastgpt.in/price
 ---
 
-线上版价格请查看：https://cloud.fastgpt.in/price
+线上版价格请查看：[https://cloud.fastgpt.in/price](https://cloud.fastgpt.in/price)

docSite/content/docs/workflow/examples/dalle3.md

@@ -9,7 +9,7 @@ weight: 404
 
 |                       |                       |
 | --------------------- | --------------------- |
-| ![](/imgs/demo-dalle1.png) | ![](/imgs/demo-dalle2.webp) |
+| ![](/imgs/demo-dalle1.webp) | ![](/imgs/demo-dalle2.webp) |
 
 ## OpenAI Dalle3 接口
 
@@ -44,14 +44,14 @@ Response
 
 ## 编排思路
 
-1. 通过 AI 来优化图片绘制的提示词（这部省略了，自己找提示词即可）
-2. 通过`HTTP 模块`调用 Dalle3 接口，获取图片的 URL。
-3. 通过`文本加工`来构建`Markdown`的图片格式。
-4. 通过`指定回复`来直接输出图片链接。
+1. 通过 AI 来优化图片绘制的提示词（这步省略了，自己找提示词即可）
+2. 通过 `【HTTP 请求】模块` 调用 Dalle3 接口，获取图片的 URL。
+3. 通过 `【文本加工】模块` 来构建 `Markdown` 的图片格式。
+4. 通过 `【指定回复】模块` 来直接输出图片链接。
 
 ### 1. 构建 HTTP 模块
 
-请求参数直接复制 Dalle3 接口的即可，并求改 prompt 为变量。需要增加一个`Headers.Authorization`。
+请求参数直接复制 Dalle3 接口的即可，并求改 prompt 为变量。需要增加一个 `Headers.Authorization` 。
 
 Body:
 
@@ -70,448 +70,402 @@ Headers:
 
 Response:
 
-响应值需要根据Dalle3接口的返回值进行获取，我们只绘制了1张图片，所以只需要取第一张图片的URL即可。给 HTTP 模块增加一个`key`为`data[0].url`的输出值。
+响应值需要根据 Dalle3 接口的返回值进行获取，我们只绘制了1张图片，所以只需要取第一张图片的 URL 即可。给 HTTP 模块增加一个自定义输出 `data[0].url` 。
 
 ### 2. 文本加工 - 构建图片链接
 
-在`Markdown`语法中`![图片描述](图片链接)`表示插入图片，图片链接由`HTTP模块`输出。
+在 `Markdown` 语法中 `![图片描述](图片链接)` 表示插入图片，图片链接由【HTTP 请求】模块输出。
 
-因此可以增加一个输入来接收`HTTP模块`的图片链接输出，并在`文本内容`中通过变量来引用图片链接，从而得到一个完整的`Markdown`图片格式。
+因此可以增加一个输入来接收 `【HTTP 请求】模块` 的图片链接输出，并在 `【文本加工】模块 - 文本` 中通过变量来引用图片链接，从而得到一个完整的 `Markdown` 图片格式。
 
 ### 3. 指定回复
 
-指定回复可以直接输出传入的内容到客户端，因此可以直接输出加工好的`Markdown`图片格式即可。
+指定回复可以直接输出传入的内容到客户端，因此可以直接输出加工好的 `Markdown` 图片格式即可。
 
 ## 编排代码
 
+{{% details title="编排配置" closed="true" %}}
+
 ```json
-[
-  {
-    "moduleId": "userGuide",
-    "name": "core.module.template.User guide",
-    "flowType": "userGuide",
-    "position": {
-      "x": 454.98510354678695,
-      "y": 721.4016845336229
-    },
-    "inputs": [
-      {
-        "key": "welcomeText",
-        "type": "hidden",
-        "valueType": "string",
-        "label": "core.app.Welcome Text",
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
+{
+  "nodes": [
+    {
+      "nodeId": "userGuide",
+      "name": "系统配置",
+      "intro": "可以配置应用的系统参数",
+      "avatar": "/imgs/workflow/userGuide.png",
+      "flowNodeType": "userGuide",
+      "position": {
+        "x": 531.2422736065552,
+        "y": -486.7611729549753
       },
-      {
-        "key": "variables",
-        "type": "hidden",
-        "valueType": "any",
-        "label": "core.module.Variable",
-        "value": [],
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "questionGuide",
-        "valueType": "boolean",
-        "type": "switch",
-        "label": "",
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "tts",
-        "type": "hidden",
-        "valueType": "any",
-        "label": "",
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      }
-    ],
-    "outputs": []
-  },
-  {
-    "moduleId": "userChatInput",
-    "name": "core.module.template.Chat entrance",
-    "flowType": "questionInput",
-    "position": {
-      "x": 597.8136543694757,
-      "y": 1709.9244174501202
-    },
-    "inputs": [
-      {
-        "key": "userChatInput",
-        "type": "systemInput",
-        "valueType": "string",
-        "label": "core.module.input.label.user question",
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      }
-    ],
-    "outputs": [
-      {
-        "key": "userChatInput",
-        "label": "core.module.input.label.user question",
-        "type": "source",
-        "valueType": "string",
-        "targets": [
-          {
-            "moduleId": "mqgfub",
-            "key": "prompt"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "mqgfub",
-    "name": "Dalle3绘图",
-    "flowType": "httpRequest468",
-    "showStatus": true,
-    "position": {
-      "x": 1071.8956245626034,
-      "y": 1236.690825267034
-    },
-    "inputs": [
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "core.module.input.label.switch",
-        "description": "core.module.input.description.Trigger",
-        "valueType": "any",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": false
-      },
-      {
-        "key": "system_httpMethod",
-        "type": "custom",
-        "valueType": "string",
-        "label": "",
-        "value": "POST",
-        "required": true,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "system_httpReqUrl",
-        "type": "hidden",
-        "valueType": "string",
-        "label": "",
-        "description": "core.module.input.description.Http Request Url",
-        "placeholder": "https://api.ai.com/getInventory",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "value": "https://api.openai.com/v1/images/generations",
-        "connected": false
-      },
-      {
-        "key": "system_httpHeader",
-        "type": "custom",
-        "valueType": "any",
-        "value": [
-          {
-            "key": "Authorization",
-            "type": "string",
-            "value": "sk-xxx"
-          }
-        ],
-        "label": "",
-        "description": "core.module.input.description.Http Request Header",
-        "placeholder": "core.module.input.description.Http Request Header",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "system_httpParams",
-        "type": "hidden",
-        "valueType": "any",
-        "value": [],
-        "label": "",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "system_httpJsonBody",
-        "type": "hidden",
-        "valueType": "any",
-        "value": "{\r\n    \"model\": \"dall-e-3\",\r\n    \"prompt\": \"{{prompt}}\",\r\n    \"n\": 1,\r\n    \"size\": \"1024x1024\"\r\n  }",
-        "label": "",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "connected": false
-      },
-      {
-        "key": "DYNAMIC_INPUT_KEY",
-        "type": "target",
-        "valueType": "any",
-        "label": "core.module.inputType.dynamicTargetInput",
-        "description": "core.module.input.description.dynamic input",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": true,
-        "hideInApp": true,
-        "connected": false
-      },
-      {
-        "key": "prompt",
-        "valueType": "string",
-        "label": "prompt",
-        "type": "target",
-        "required": true,
-        "description": "",
-        "edit": true,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "required": true,
-          "dataType": true
-        },
-        "connected": true
-      },
-      {
-        "key": "system_addInputParam",
-        "type": "addInputParam",
-        "valueType": "any",
-        "label": "",
-        "required": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "required": true,
-          "dataType": true
-        },
-        "defaultEditField": {
-          "label": "",
-          "key": "",
-          "description": "",
-          "inputType": "target",
+      "inputs": [
+        {
+          "key": "welcomeText",
+          "renderTypeList": [
+            "hidden"
+          ],
           "valueType": "string",
-          "required": true
+          "label": "core.app.Welcome Text",
+          "value": ""
         },
-        "connected": false
-      }
-    ],
-    "outputs": [
-      {
-        "key": "finish",
-        "label": "core.module.output.label.running done",
-        "description": "core.module.output.description.running done",
-        "valueType": "boolean",
-        "type": "source",
-        "targets": []
-      },
-      {
-        "key": "system_addOutputParam",
-        "type": "addOutputParam",
-        "valueType": "any",
-        "label": "",
-        "targets": [],
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "dataType": true
+        {
+          "key": "variables",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "core.app.Chat Variable",
+          "value": []
         },
-        "defaultEditField": {
+        {
+          "key": "questionGuide",
+          "valueType": "boolean",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "core.app.Question Guide",
+          "value": false
+        },
+        {
+          "key": "tts",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
           "label": "",
-          "key": "",
-          "description": "",
-          "outputType": "source",
-          "valueType": "string"
+          "value": {
+            "type": "web"
+          }
+        },
+        {
+          "key": "whisper",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "",
+          "value": {
+            "open": false,
+            "autoSend": false,
+            "autoTTSResponse": false
+          }
+        },
+        {
+          "key": "scheduleTrigger",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "",
+          "value": null
         }
-      },
-      {
-        "type": "source",
-        "valueType": "string",
-        "key": "data[0].url",
-        "label": "url",
-        "description": "",
-        "edit": true,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "dataType": true
-        },
-        "targets": [
-          {
-            "moduleId": "nl6mr9",
-            "key": "url"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "xy76o2",
-    "name": "core.module.template.Assigned reply",
-    "flowType": "answerNode",
-    "position": {
-      "x": 2204.027057268489,
-      "y": 1256.786345213533
+      ],
+      "outputs": []
     },
-    "inputs": [
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "core.module.input.label.switch",
-        "description": "core.module.input.description.Trigger",
-        "valueType": "any",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": false
+    {
+      "nodeId": "448745",
+      "name": "流程开始",
+      "intro": "",
+      "avatar": "/imgs/workflow/userChatInput.svg",
+      "flowNodeType": "workflowStart",
+      "position": {
+        "x": 532.1275542407774,
+        "y": 46.03775600322817
       },
-      {
-        "key": "text",
-        "type": "textarea",
-        "valueType": "any",
-        "label": "core.module.input.label.Response content",
-        "description": "core.module.input.description.Response content",
-        "placeholder": "core.module.input.description.Response content",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "finish",
-        "label": "core.module.output.label.running done",
-        "description": "core.module.output.description.running done",
-        "valueType": "boolean",
-        "type": "source",
-        "targets": []
-      }
-    ]
-  },
-  {
-    "moduleId": "nl6mr9",
-    "name": "core.module.template.textEditor",
-    "flowType": "pluginModule",
-    "showStatus": false,
-    "position": {
-      "x": 1690.1826860670342,
-      "y": 1262.3858719789062
-    },
-    "inputs": [
-      {
-        "key": "pluginId",
-        "type": "hidden",
-        "label": "",
-        "value": "community-textEditor",
-        "valueType": "string",
-        "connected": false,
-        "showTargetInApp": false,
-        "showTargetInPlugin": false
-      },
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "core.module.input.label.switch",
-        "description": "core.module.input.description.Trigger",
-        "valueType": "any",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": false
-      },
-      {
-        "key": "textarea",
-        "valueType": "string",
-        "label": "文本内容",
-        "type": "textarea",
-        "required": true,
-        "description": "可以通过 {{key}} 的方式引用传入的变量。变量仅支持字符串或数字。",
-        "edit": false,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "required": true,
-          "dataType": true,
-          "inputType": true
-        },
-        "connected": false,
-        "placeholder": "可以通过 {{key}} 的方式引用传入的变量。变量仅支持字符串或数字。",
-        "value": "![]({{url}})"
-      },
-      {
-        "key": "url",
-        "valueType": "string",
-        "label": "url",
-        "type": "target",
-        "required": true,
-        "description": "",
-        "edit": true,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "required": true,
-          "dataType": true,
-          "inputType": false
-        },
-        "connected": true
-      },
-      {
-        "key": "DYNAMIC_INPUT_KEY",
-        "valueType": "any",
-        "label": "需要加工的输入",
-        "type": "addInputParam",
-        "required": false,
-        "description": "可动态的添加字符串类型变量，在文本编辑中通过 {{key}} 使用变量。非字符串类型，会自动转成字符串类型。",
-        "edit": false,
-        "editField": {
-          "key": true,
-          "name": true,
-          "description": true,
-          "required": true,
-          "dataType": true,
-          "inputType": false
-        },
-        "defaultEditField": {
-          "label": "",
-          "key": "",
-          "description": "",
-          "inputType": "target",
+      "inputs": [
+        {
+          "key": "userChatInput",
+          "renderTypeList": [
+            "reference",
+            "textarea"
+          ],
           "valueType": "string",
+          "label": "用户问题",
+          "required": true,
+          "toolDescription": "用户问题"
+        }
+      ],
+      "outputs": [
+        {
+          "id": "userChatInput",
+          "key": "userChatInput",
+          "label": "core.module.input.label.user question",
+          "valueType": "string",
+          "type": "static"
+        }
+      ]
+    },
+    {
+      "nodeId": "tMyUnRL5jIrC",
+      "name": "HTTP 请求",
+      "intro": "可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）",
+      "avatar": "/imgs/workflow/http.png",
+      "flowNodeType": "httpRequest468",
+      "showStatus": true,
+      "position": {
+        "x": 921.2377506442713,
+        "y": -483.94114977914256
+      },
+      "inputs": [
+        {
+          "key": "system_addInputParam",
+          "renderTypeList": [
+            "addInputParam"
+          ],
+          "valueType": "dynamic",
+          "label": "",
+          "required": false,
+          "description": "core.module.input.description.HTTP Dynamic Input",
+          "editField": {
+            "key": true,
+            "valueType": true
+          }
+        },
+        {
+          "key": "prompt",
+          "valueType": "string",
+          "label": "prompt",
+          "renderTypeList": [
+            "reference"
+          ],
+          "description": "",
+          "canEdit": true,
+          "editField": {
+            "key": true,
+            "valueType": true
+          },
+          "value": [
+            "448745",
+            "userChatInput"
+          ]
+        },
+        {
+          "key": "system_httpMethod",
+          "renderTypeList": [
+            "custom"
+          ],
+          "valueType": "string",
+          "label": "",
+          "value": "POST",
           "required": true
         },
-        "connected": false
-      }
-    ],
-    "outputs": [
-      {
-        "key": "text",
-        "valueType": "string",
-        "label": "core.module.output.label.text",
-        "type": "source",
-        "edit": false,
-        "targets": [
-          {
-            "moduleId": "xy76o2",
-            "key": "text"
+        {
+          "key": "system_httpReqUrl",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "string",
+          "label": "",
+          "description": "core.module.input.description.Http Request Url",
+          "placeholder": "https://api.ai.com/getInventory",
+          "required": false,
+          "value": "https://api.openai.com/v1/images/generations"
+        },
+        {
+          "key": "system_httpHeader",
+          "renderTypeList": [
+            "custom"
+          ],
+          "valueType": "any",
+          "value": [
+            {
+              "key": "Authorization",
+              "type": "string",
+              "value": "Bearer sk-zsfBsxEU3ApSFGYxF4CdB97e9556412588421823371b9f7b"
+            }
+          ],
+          "label": "",
+          "description": "core.module.input.description.Http Request Header",
+          "placeholder": "core.module.input.description.Http Request Header",
+          "required": false
+        },
+        {
+          "key": "system_httpParams",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "value": [],
+          "label": "",
+          "required": false
+        },
+        {
+          "key": "system_httpJsonBody",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "value": "{\n  \"model\": \"dall-e-3\",\n  \"prompt\": \"{{prompt}}\",\n  \"n\": 1,\n  \"size\": \"1024x1024\"\n}",
+          "label": "",
+          "required": false
+        }
+      ],
+      "outputs": [
+        {
+          "id": "system_addOutputParam",
+          "key": "system_addOutputParam",
+          "type": "dynamic",
+          "valueType": "dynamic",
+          "label": "",
+          "editField": {
+            "key": true,
+            "valueType": true
           }
-        ]
-      }
-    ]
-  }
-]
-```
+        },
+        {
+          "id": "httpRawResponse",
+          "key": "httpRawResponse",
+          "label": "原始响应",
+          "description": "HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。",
+          "valueType": "any",
+          "type": "static"
+        },
+        {
+          "id": "DeKGGioBwaMf",
+          "type": "dynamic",
+          "key": "data[0].url",
+          "valueType": "string",
+          "label": "data[0].url"
+        }
+      ]
+    },
+    {
+      "nodeId": "CO3POL8svbbi",
+      "name": "文本加工",
+      "intro": "可对固定或传入的文本进行加工后输出，非字符串类型数据最终会转成字符串类型。",
+      "avatar": "/imgs/workflow/textEditor.svg",
+      "flowNodeType": "pluginModule",
+      "showStatus": false,
+      "position": {
+        "x": 1417.5940290051137,
+        "y": -478.81889618104356
+      },
+      "inputs": [
+        {
+          "key": "system_addInputParam",
+          "valueType": "dynamic",
+          "label": "动态外部数据",
+          "renderTypeList": [
+            "addInputParam"
+          ],
+          "required": false,
+          "description": "",
+          "canEdit": false,
+          "value": "",
+          "editField": {
+            "key": true
+          },
+          "dynamicParamDefaultValue": {
+            "inputType": "reference",
+            "valueType": "string",
+            "required": true
+          }
+        },
+        {
+          "key": "url",
+          "valueType": "string",
+          "label": "url",
+          "renderTypeList": [
+            "reference"
+          ],
+          "required": true,
+          "description": "",
+          "canEdit": true,
+          "editField": {
+            "key": true
+          },
+          "value": [
+            "tMyUnRL5jIrC",
+            "DeKGGioBwaMf"
+          ]
+        },
+        {
+          "key": "文本",
+          "valueType": "string",
+          "label": "文本",
+          "renderTypeList": [
+            "textarea"
+          ],
+          "required": true,
+          "description": "",
+          "canEdit": false,
+          "value": "![]({{url}})",
+          "editField": {
+            "key": true
+          },
+          "maxLength": "",
+          "dynamicParamDefaultValue": {
+            "inputType": "reference",
+            "valueType": "string",
+            "required": true
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "id": "text",
+          "type": "static",
+          "key": "text",
+          "valueType": "string",
+          "label": "text",
+          "description": ""
+        }
+      ],
+      "pluginId": "community-textEditor"
+    },
+    {
+      "nodeId": "7mapnCgHfKW6",
+      "name": "指定回复",
+      "intro": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
+      "avatar": "/imgs/workflow/reply.png",
+      "flowNodeType": "answerNode",
+      "position": {
+        "x": 1922.5628399315042,
+        "y": -471.67391598231796
+      },
+      "inputs": [
+        {
+          "key": "text",
+          "renderTypeList": [
+            "textarea",
+            "reference"
+          ],
+          "valueType": "string",
+          "label": "core.module.input.label.Response content",
+          "description": "core.module.input.description.Response content",
+          "placeholder": "core.module.input.description.Response content",
+          "selectedTypeIndex": 1,
+          "value": [
+            "CO3POL8svbbi",
+            "text"
+          ]
+        }
+      ],
+      "outputs": []
+    }
+  ],
+  "edges": [
+    {
+      "source": "448745",
+      "target": "tMyUnRL5jIrC",
+      "sourceHandle": "448745-source-right",
+      "targetHandle": "tMyUnRL5jIrC-target-left"
+    },
+    {
+      "source": "tMyUnRL5jIrC",
+      "target": "CO3POL8svbbi",
+      "sourceHandle": "tMyUnRL5jIrC-source-right",
+      "targetHandle": "CO3POL8svbbi-target-left"
+    },
+    {
+      "source": "CO3POL8svbbi",
+      "target": "7mapnCgHfKW6",
+      "sourceHandle": "CO3POL8svbbi-source-right",
+      "targetHandle": "7mapnCgHfKW6-target-left"
+    }
+  ]
+}
+```
+
+{{% /details %}}

docSite/content/docs/workflow/examples/feishu_webhook.md

@@ -11,7 +11,7 @@ weight: 404
 
 |                       |                       |
 | --------------------- | --------------------- |
-| ![](/imgs/feishuwebhook1.png) | ![](/imgs/feishuwebhook2.webp) |
+| ![](/imgs/feishuwebhook1.webp) | ![](/imgs/feishuwebhook2.webp) |
 
 ## 1. 准备飞书机器人
 
@@ -23,14 +23,16 @@ weight: 404
 
 复制下面配置，点击「高级编排」右上角的导入按键，导入该配置，导入后将飞书提供的接口地址复制到「HTTP 模块」。
 
+{{% details title="编排配置" closed="true" %}}
+
 ```json
 [
   {
-    "moduleId": "userGuide",
-    "name": "core.module.template.User guide",
+    "nodeId": "userGuide",
+    "name": "core.module.template.App system setting",
     "intro": "core.app.tip.userGuideTip",
-    "avatar": "/imgs/module/userGuide.png",
-    "flowType": "userGuide",
+    "avatar": "/imgs/workflow/userGuide.png",
+    "flowNodeType": "userGuide",
     "position": {
       "x": -92.26884681344463,
       "y": 710.9354029649536
@@ -82,11 +84,11 @@ weight: 404
     "outputs": []
   },
   {
-    "moduleId": "userChatInput",
+    "nodeId": "userChatInput",
     "name": "core.module.template.Chat entrance",
     "intro": "当用户发送一个内容后，流程将会从这个模块开始执行。",
-    "avatar": "/imgs/module/userChatInput.svg",
-    "flowType": "questionInput",
+    "avatar": "/imgs/workflow/userChatInput.svg",
+    "flowNodeType": "questionInput",
     "position": {
       "x": 241.60980819261408,
       "y": 1330.9528898009685
@@ -110,7 +112,7 @@ weight: 404
         "valueType": "string",
         "targets": [
           {
-            "moduleId": "n84rvg",
+            "nodeId": "n84rvg",
             "key": "userChatInput"
           }
         ]
@@ -118,27 +120,17 @@ weight: 404
     ]
   },
   {
-    "moduleId": "n84rvg",
+    "nodeId": "n84rvg",
     "name": "工具调用（实验）",
     "intro": "通过AI模型自动选择一个或多个功能块进行调用，也可以对插件进行调用。",
-    "avatar": "/imgs/module/tool.svg",
-    "flowType": "tools",
+    "avatar": "/imgs/workflow/tool.svg",
+    "flowNodeType": "tools",
     "showStatus": true,
     "position": {
       "x": 809.4264785615641,
       "y": 873.3971746859133
     },
     "inputs": [
-      {
-        "key": "switch",
-        "type": "triggerAndFinish",
-        "label": "",
-        "description": "core.module.input.description.Trigger",
-        "valueType": "any",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": false
-      },
       {
         "key": "model",
         "type": "settingLLMModel",
@@ -227,7 +219,7 @@ weight: 404
         "type": "hidden",
         "targets": [
           {
-            "moduleId": "3mbu91",
+            "nodeId": "3mbu91",
             "key": "selectedTools"
           }
         ]
@@ -243,27 +235,18 @@ weight: 404
     ]
   },
   {
-    "moduleId": "3mbu91",
+    "nodeId": "3mbu91",
     "name": "HTTP 请求",
     "intro": "调用飞书webhook，发送一个通知",
-    "avatar": "/imgs/module/http.png",
-    "flowType": "httpRequest468",
+    "avatar": "/imgs/workflow/http.png",
+    "flowNodeType": "httpRequest468",
     "showStatus": true,
     "position": {
       "x": 1483.6437630977423,
       "y": 798.9716928475544
     },
     "inputs": [
-      {
-        "key": "switch",
-        "type": "triggerAndFinish",
-        "label": "",
-        "description": "core.module.input.description.Trigger",
-        "valueType": "any",
-        "showTargetInApp": true,
-        "showTargetInPlugin": true,
-        "connected": false
-      },
+     
       {
         "key": "system_httpMethod",
         "type": "custom",
@@ -327,7 +310,7 @@ weight: 404
         "key": "DYNAMIC_INPUT_KEY",
         "type": "target",
         "valueType": "any",
-        "label": "core.module.inputType.dynamicTargetInput",
+        "label": "core.workflow.inputType.dynamicTargetInput",
         "description": "core.module.input.description.dynamic input",
         "required": false,
         "showTargetInApp": false,
@@ -376,11 +359,11 @@ weight: 404
         "type": "source",
         "targets": [
           {
-            "moduleId": "rzx4mj",
+            "nodeId": "rzx4mj",
             "key": "switch"
           },
           {
-            "moduleId": "psdhs1",
+            "nodeId": "psdhs1",
             "key": "switch"
           }
         ]
@@ -424,11 +407,11 @@ weight: 404
     ]
   },
   {
-    "moduleId": "rzx4mj",
+    "nodeId": "rzx4mj",
     "name": "工具调用终止",
     "intro": "该模块需配置工具调用使用。当该模块被执行时，本次工具调用将会强制结束，并且不再调用AI针对工具调用结果回答问题。",
-    "avatar": "/imgs/module/toolStop.svg",
-    "flowType": "stopTool",
+    "avatar": "/imgs/workflow/toolStop.svg",
+    "flowNodeType": "stopTool",
     "position": {
       "x": 2145.5070710160267,
       "y": 1306.3581817783079
@@ -448,11 +431,11 @@ weight: 404
     "outputs": []
   },
   {
-    "moduleId": "psdhs1",
+    "nodeId": "psdhs1",
     "name": "指定回复",
     "intro": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
-    "avatar": "/imgs/module/reply.png",
-    "flowType": "answerNode",
+    "avatar": "/imgs/workflow/reply.png",
+    "flowNodeType": "answerNode",
     "position": {
       "x": 2117.0429459850598,
       "y": 1658.4125434513746
@@ -495,6 +478,9 @@ weight: 404
 ]
 ```
 
+{{% /details %}}
+
+
 ## 3. 流程说明
 
 1. 为工具调用挂载一个HTTP模块，功能描述写上：调用飞书webhook，发送一个通知。

docSite/content/docs/workflow/examples/fixingEvidence.md

@@ -7,9 +7,9 @@ toc: true
 weight: 401
 ---
 
-![](/imgs/demo-fix-evidence1.png)
+![](/imgs/demo-fix-evidence1.jpg)
 
-![](/imgs/demo-fix-evidence2.png)
+![](/imgs/demo-fix-evidence2.jpg)
 
 
 如上图，可以通过指定回复编排一个固定的开头和结尾内容。
@@ -21,318 +21,411 @@ weight: 401
 {{% details title="编排配置" closed="true" %}}
 
 ```json
-[
-  {
-    "moduleId": "userChatInput",
-    "name": "用户问题(对话入口)",
-    "flowType": "questionInput",
-    "position": {
-      "x": 59.03170043915989,
-      "y": 1604.8595605938747
+{
+  "nodes": [
+    {
+      "nodeId": "7z5g5h",
+      "name": "流程开始",
+      "intro": "",
+      "avatar": "/imgs/workflow/userChatInput.svg",
+      "flowNodeType": "workflowStart",
+      "position": {
+        "x": -269.50851681351924,
+        "y": 1657.6123698022448
+      },
+      "inputs": [
+        {
+          "key": "userChatInput",
+          "renderTypeList": [
+            "reference",
+            "textarea"
+          ],
+          "valueType": "string",
+          "label": "问题输入",
+          "required": true,
+          "toolDescription": "用户问题",
+          "type": "systemInput",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0,
+          "value": [
+            "7z5g5h",
+            "userChatInput"
+          ]
+        }
+      ],
+      "outputs": [
+        {
+          "id": "userChatInput",
+          "type": "static",
+          "key": "userChatInput",
+          "valueType": "string",
+          "label": "core.module.input.label.user question"
+        }
+      ]
     },
-    "inputs": [
-      {
-        "key": "userChatInput",
-        "type": "systemInput",
-        "label": "用户问题",
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "userChatInput",
-        "label": "用户问题",
-        "type": "source",
-        "valueType": "string",
-        "targets": [
-          {
-            "moduleId": "chatModule",
-            "key": "userChatInput"
-          },
-          {
-            "moduleId": "ymqh0t",
-            "key": "switch"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "history",
-    "name": "聊天记录",
-    "flowType": "historyNode",
-    "position": {
-      "x": 38.19233923987295,
-      "y": 1184.4581738905642
+    {
+      "nodeId": "nlfwkc",
+      "name": "AI 对话",
+      "intro": "AI 大模型对话",
+      "avatar": "/imgs/workflow/AI.png",
+      "flowNodeType": "chatNode",
+      "showStatus": true,
+      "position": {
+        "x": 907.2058332478431,
+        "y": 1348.9992737142143
+      },
+      "inputs": [
+        {
+          "key": "model",
+          "renderTypeList": [
+            "settingLLMModel",
+            "reference"
+          ],
+          "label": "core.module.input.label.aiModel",
+          "valueType": "string",
+          "type": "selectLLMModel",
+          "required": true,
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "value": "gpt-3.5-turbo",
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "temperature",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "value": 0,
+          "valueType": "number",
+          "min": 0,
+          "max": 10,
+          "step": 1,
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "maxToken",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "value": 2000,
+          "valueType": "number",
+          "min": 100,
+          "max": 4000,
+          "step": 50,
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "isResponseAnswerText",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "value": true,
+          "valueType": "boolean",
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "quoteTemplate",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "valueType": "string",
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "quotePrompt",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "valueType": "string",
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "systemPrompt",
+          "renderTypeList": [
+            "textarea",
+            "reference"
+          ],
+          "max": 300,
+          "valueType": "string",
+          "label": "core.ai.Prompt",
+          "description": "core.app.tip.chatNodeSystemPromptTip",
+          "placeholder": "core.app.tip.chatNodeSystemPromptTip",
+          "type": "textarea",
+          "showTargetInApp": true,
+          "showTargetInPlugin": true,
+          "value": "",
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "history",
+          "renderTypeList": [
+            "numberInput",
+            "reference"
+          ],
+          "valueType": "chatHistory",
+          "label": "core.module.input.label.chat history",
+          "required": true,
+          "min": 0,
+          "max": 30,
+          "value": 6,
+          "type": "numberInput",
+          "showTargetInApp": true,
+          "showTargetInPlugin": true,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "userChatInput",
+          "renderTypeList": [
+            "reference",
+            "textarea"
+          ],
+          "valueType": "string",
+          "label": "问题输入",
+          "required": true,
+          "toolDescription": "用户问题",
+          "type": "custom",
+          "showTargetInApp": true,
+          "showTargetInPlugin": true,
+          "connected": true,
+          "selectedTypeIndex": 0,
+          "value": [
+            "7z5g5h",
+            "userChatInput"
+          ]
+        },
+        {
+          "key": "quoteQA",
+          "renderTypeList": [
+            "settingDatasetQuotePrompt"
+          ],
+          "label": "",
+          "debugLabel": "知识库引用",
+          "description": "core.module.Dataset quote.Input description",
+          "valueType": "datasetQuote",
+          "type": "target",
+          "showTargetInApp": true,
+          "showTargetInPlugin": true,
+          "connected": true,
+          "selectedTypeIndex": 0,
+          "value": [
+            "fljhzy",
+            "quoteQA"
+          ]
+        }
+      ],
+      "outputs": [
+        {
+          "id": "answerText",
+          "type": "static",
+          "key": "answerText",
+          "valueType": "string",
+          "label": "core.module.output.label.Ai response content",
+          "description": "core.module.output.description.Ai response content"
+        },
+        {
+          "id": "history",
+          "type": "static",
+          "key": "history",
+          "valueType": "chatHistory",
+          "label": "core.module.output.label.New context",
+          "description": "core.module.output.description.New context"
+        }
+      ]
     },
-    "inputs": [
-      {
-        "key": "maxContext",
-        "type": "numberInput",
-        "label": "最长记录数",
-        "value": 6,
-        "min": 0,
-        "max": 50,
-        "connected": true
+    {
+      "nodeId": "q9equb",
+      "name": "core.module.template.App system setting",
+      "intro": "可以配置应用的系统参数。",
+      "avatar": "/imgs/workflow/userGuide.png",
+      "flowNodeType": "userGuide",
+      "position": {
+        "x": -275.92529567956024,
+        "y": 1094.1001488133452
       },
-      {
-        "key": "history",
-        "type": "hidden",
-        "label": "聊天记录",
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "history",
-        "label": "聊天记录",
-        "valueType": "chatHistory",
-        "type": "source",
-        "targets": [
-          {
-            "moduleId": "chatModule",
-            "key": "history"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "chatModule",
-    "name": "AI 对话",
-    "flowType": "chatNode",
-    "showStatus": true,
-    "position": {
-      "x": 943.1225685246793,
-      "y": 891.3094521573212
+      "inputs": [
+        {
+          "key": "welcomeText",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "string",
+          "label": "core.app.Welcome Text",
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "value": "你好，我是电影《星际穿越》 AI 助手，有什么可以帮助你的？\n[导演是谁]\n[剧情介绍]\n[票房分析]",
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "variables",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "core.module.Variable",
+          "value": [],
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "questionGuide",
+          "valueType": "boolean",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "label": "",
+          "type": "switch",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "tts",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "",
+          "type": "hidden",
+          "showTargetInApp": false,
+          "showTargetInPlugin": false,
+          "connected": false,
+          "selectedTypeIndex": 0
+        },
+        {
+          "key": "whisper",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": ""
+        },
+        {
+          "key": "scheduleTrigger",
+          "renderTypeList": [
+            "hidden"
+          ],
+          "valueType": "any",
+          "label": "",
+          "value": null
+        }
+      ],
+      "outputs": []
     },
-    "inputs": [
-      {
-        "key": "model",
-        "type": "custom",
-        "label": "对话模型",
-        "value": "gpt-3.5-turbo",
-        "list": [
-          {
-            "label": "FastGPT-4k",
-            "value": "gpt-3.5-turbo"
-          },
-          {
-            "label": "FastGPT-16k",
-            "value": "gpt-3.5-turbo-16k"
-          },
-          {
-            "label": "文心一言",
-            "value": "ERNIE-Bot"
-          },
-          {
-            "label": "FastGPT-Plus",
-            "value": "gpt-4"
-          },
-          {
-            "label": "glm2(演示娱乐)",
-            "value": "glm2-6b"
-          }
-        ],
-        "connected": true
+    {
+      "nodeId": "tc90wz",
+      "name": "指定回复",
+      "intro": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
+      "avatar": "/imgs/workflow/reply.png",
+      "flowNodeType": "answerNode",
+      "position": {
+        "x": 159.49274056478237,
+        "y": 1621.4635230667668
       },
-      {
-        "key": "temperature",
-        "type": "slider",
-        "label": "温度",
-        "value": 0,
-        "min": 0,
-        "max": 10,
-        "step": 1,
-        "markList": [
-          {
-            "label": "严谨",
-            "value": 0
-          },
-          {
-            "label": "发散",
-            "value": 10
-          }
-        ],
-        "connected": true
-      },
-      {
-        "key": "maxToken",
-        "type": "custom",
-        "label": "回复上限",
-        "value": 2000,
-        "min": 100,
-        "max": 4000,
-        "step": 50,
-        "markList": [
-          {
-            "label": "100",
-            "value": 100
-          },
-          {
-            "label": "4000",
-            "value": 4000
-          }
-        ],
-        "connected": true
-      },
-      {
-        "key": "systemPrompt",
-        "type": "textarea",
-        "label": "系统提示词",
-        "max": 300,
-        "valueType": "string",
-        "description": "模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。可使用变量，例如 {{language}}",
-        "placeholder": "模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。可使用变量，例如 {{language}}",
-        "value": "",
-        "connected": true
-      },
-      {
-        "key": "limitPrompt",
-        "type": "textarea",
-        "valueType": "string",
-        "label": "限定词",
-        "max": 500,
-        "description": "限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。不建议内容太长，会影响上下文，可使用变量，例如 {{language}}。可在文档中找到对应的限定例子",
-        "placeholder": "限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。不建议内容太长，会影响上下文，可使用变量，例如 {{language}}。可在文档中找到对应的限定例子",
-        "value": "",
-        "connected": true
-      },
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "触发器",
-        "valueType": "any",
-        "connected": true
-      },
-      {
-        "key": "quoteQA",
-        "type": "target",
-        "label": "引用内容",
-        "description": "对象数组格式，结构：\n [{q:'问题',a:'回答'}]",
-        "valueType": "datasetQuote",
-        "connected": false
-      },
-      {
-        "key": "history",
-        "type": "target",
-        "label": "聊天记录",
-        "valueType": "chatHistory",
-        "connected": true
-      },
-      {
-        "key": "userChatInput",
-        "type": "target",
-        "label": "用户问题",
-        "required": true,
-        "valueType": "string",
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "answerText",
-        "label": "AI回复",
-        "description": "将在 stream 回复完毕后触发",
-        "valueType": "string",
-        "type": "source",
-        "targets": []
-      },
-      {
-        "key": "finish",
-        "label": "回复结束",
-        "description": "AI 回复完成后触发",
-        "valueType": "boolean",
-        "type": "source",
-        "targets": [
-          {
-            "moduleId": "ojeopv",
-            "key": "switch"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "ymqh0t",
-    "name": "指定回复",
-    "flowType": "answerNode",
-    "position": {
-      "x": 435.27459673941917,
-      "y": 1081.9477378716076
+      "inputs": [
+        {
+          "key": "text",
+          "renderTypeList": [
+            "textarea",
+            "reference"
+          ],
+          "valueType": "any",
+          "label": "core.module.input.label.Response content",
+          "description": "core.module.input.description.Response content",
+          "placeholder": "core.module.input.description.Response content",
+          "type": "textarea",
+          "showTargetInApp": true,
+          "showTargetInPlugin": true,
+          "value": "这是开头\\n",
+          "connected": false,
+          "selectedTypeIndex": 0
+        }
+      ],
+      "outputs": []
     },
-    "inputs": [
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "触发器",
-        "valueType": "any",
-        "connected": true
+    {
+      "nodeId": "U5T3dMVY4wj7",
+      "name": "指定回复",
+      "intro": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
+      "avatar": "/imgs/workflow/reply.png",
+      "flowNodeType": "answerNode",
+      "position": {
+        "x": 1467.0625486167608,
+        "y": 1597.346243737531
       },
-      {
-        "key": "text",
-        "type": "textarea",
-        "valueType": "string",
-        "value": "这是AI作答：\n\n---\n\n",
-        "label": "回复的内容",
-        "description": "可以使用 \\n 来实现换行。也可以通过外部模块输入实现回复，外部模块输入时会覆盖当前填写的内容",
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "finish",
-        "label": "回复结束",
-        "description": "回复完成后触发",
-        "valueType": "boolean",
-        "type": "source",
-        "targets": [
-          {
-            "moduleId": "chatModule",
-            "key": "switch"
-          }
-        ]
-      }
-    ]
-  },
-  {
-    "moduleId": "ojeopv",
-    "name": "指定回复",
-    "flowType": "answerNode",
-    "position": {
-      "x": 1573.4540253108476,
-      "y": 1551.9808807287498
+      "inputs": [
+        {
+          "key": "text",
+          "renderTypeList": [
+            "textarea",
+            "reference"
+          ],
+          "valueType": "string",
+          "label": "core.module.input.label.Response content",
+          "description": "core.module.input.description.Response content",
+          "placeholder": "core.module.input.description.Response content",
+          "value": "这是结尾"
+        }
+      ],
+      "outputs": []
+    }
+  ],
+  "edges": [
+    {
+      "source": "7z5g5h",
+      "target": "tc90wz",
+      "sourceHandle": "7z5g5h-source-right",
+      "targetHandle": "tc90wz-target-left"
     },
-    "inputs": [
-      {
-        "key": "switch",
-        "type": "target",
-        "label": "触发器",
-        "valueType": "any",
-        "connected": true
-      },
-      {
-        "key": "text",
-        "type": "textarea",
-        "valueType": "string",
-        "value": "\\n\n---\n\n这是固定的结尾",
-        "label": "回复的内容",
-        "description": "可以使用 \\n 来实现换行。也可以通过外部模块输入实现回复，外部模块输入时会覆盖当前填写的内容",
-        "connected": true
-      }
-    ],
-    "outputs": [
-      {
-        "key": "finish",
-        "label": "回复结束",
-        "description": "回复完成后触发",
-        "valueType": "boolean",
-        "type": "source",
-        "targets": []
-      }
-    ]
-  }
-]
+    {
+      "source": "tc90wz",
+      "target": "nlfwkc",
+      "sourceHandle": "tc90wz-source-right",
+      "targetHandle": "nlfwkc-target-left"
+    },
+    {
+      "source": "nlfwkc",
+      "target": "U5T3dMVY4wj7",
+      "sourceHandle": "nlfwkc-source-right",
+      "targetHandle": "U5T3dMVY4wj7-target-left"
+    }
+  ]
+}
 ```
 
 {{% /details %}}

docSite/content/docs/workflow/modules/laf.md

@@ -27,8 +27,6 @@ Laf 提供了 PAT(访问凭证) 来实现 Laf 平台外的快捷登录，可以
 
 填入 PAT 验证后，选择需要绑定的应用（应用需要是 Running 状态），即可调用该应用下的云函数。
 
-> 如果需要解绑则取消绑定后，点击“更新”即可
-
 ![](/imgs/laf2.webp)
 
 ## 编写云函数

docSite/layouts/redirect/single.html

@@ -0,0 +1 @@
+{{- template "_internal/alias.html" (dict "Permalink" .Params.target) -}}

packages/global/common/file/image/constants.ts

@@ -53,4 +53,4 @@ export const uniqueImageTypeList = Object.entries(mongoImageTypeMap)
 
 export const FolderIcon = 'file/fill/folder';
 export const FolderImgUrl = '/imgs/files/folder.svg';
-export const HttpImgUrl = '/imgs/module/http.png';
+export const HttpImgUrl = '/imgs/workflow/http.png';

packages/global/common/file/tools.ts

@@ -10,6 +10,6 @@ export const formatFileSize = (bytes: number): string => {
   return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i];
 };
 
-export const detectFileEncoding = (buffers: string | Buffer) => {
-  return (detect(buffers)?.encoding || 'utf-8') as BufferEncoding;
+export const detectFileEncoding = (buffer: Buffer) => {
+  return detect(buffer.slice(0, 200))?.encoding?.toLocaleLowerCase();
 };

packages/global/common/string/textSplitter.ts

@@ -1,5 +1,5 @@
 import { getErrText } from '../error/utils';
-import { countPromptTokens } from './tiktoken';
+import { replaceRegChars } from './tools';
 
 /**
  * text split into chunks
@@ -31,7 +31,7 @@ export const splitText2Chunks = (props: {
   // The larger maxLen is, the next sentence is less likely to trigger splitting
   const stepReges: { reg: RegExp; maxLen: number }[] = [
     ...customReg.map((text) => ({
-      reg: new RegExp(`(${text.replace(/[.*+?^${}()|[\]\\]/g, '\\$&')})`, 'g'),
+      reg: new RegExp(`(${replaceRegChars(text)})`, 'g'),
       maxLen: chunkLen * 1.4
     })),
     { reg: /^(#\s[^\n]+)\n/gm, maxLen: chunkLen * 1.2 },

packages/global/common/string/tiktoken/index.ts

@@ -1,152 +0,0 @@
-/* Only the token of gpt-3.5-turbo is used */
-import type { ChatItemType } from '../../../core/chat/type';
-import { Tiktoken } from 'js-tiktoken/lite';
-import { chats2GPTMessages } from '../../../core/chat/adapt';
-import encodingJson from './cl100k_base.json';
-import {
-  ChatCompletionMessageParam,
-  ChatCompletionContentPart,
-  ChatCompletionCreateParams,
-  ChatCompletionTool
-} from '../../../core/ai/type';
-import { ChatCompletionRequestMessageRoleEnum } from '../../../core/ai/constants';
-
-/* init tikToken obj */
-export function getTikTokenEnc() {
-  if (typeof window !== 'undefined' && window.TikToken) {
-    return window.TikToken;
-  }
-  if (typeof global !== 'undefined' && global.TikToken) {
-    return global.TikToken;
-  }
-
-  const enc = new Tiktoken(encodingJson);
-
-  if (typeof window !== 'undefined') {
-    window.TikToken = enc;
-  }
-  if (typeof global !== 'undefined') {
-    global.TikToken = enc;
-  }
-
-  return enc;
-}
-
-/* count one prompt tokens */
-export function countPromptTokens(
-  prompt: string | ChatCompletionContentPart[] | null | undefined = '',
-  role: '' | `${ChatCompletionRequestMessageRoleEnum}` = ''
-) {
-  const enc = getTikTokenEnc();
-  const promptText = (() => {
-    if (!prompt) return '';
-    if (typeof prompt === 'string') return prompt;
-    let promptText = '';
-    prompt.forEach((item) => {
-      if (item.type === 'text') {
-        promptText += item.text;
-      } else if (item.type === 'image_url') {
-        promptText += item.image_url.url;
-      }
-    });
-    return promptText;
-  })();
-
-  const text = `${role}\n${promptText}`.trim();
-
-  try {
-    const encodeText = enc.encode(text);
-    const supplementaryToken = role ? 4 : 0;
-    return encodeText.length + supplementaryToken;
-  } catch (error) {
-    return text.length;
-  }
-}
-export const countToolsTokens = (
-  tools?: ChatCompletionTool[] | ChatCompletionCreateParams.Function[]
-) => {
-  if (!tools || tools.length === 0) return 0;
-
-  const enc = getTikTokenEnc();
-
-  const toolText = tools
-    ? JSON.stringify(tools)
-        .replace('"', '')
-        .replace('\n', '')
-        .replace(/( ){2,}/g, ' ')
-    : '';
-
-  return enc.encode(toolText).length;
-};
-
-/* count messages tokens */
-export const countMessagesTokens = (messages: ChatItemType[]) => {
-  const adaptMessages = chats2GPTMessages({ messages, reserveId: true });
-
-  return countGptMessagesTokens(adaptMessages);
-};
-export const countGptMessagesTokens = (
-  messages: ChatCompletionMessageParam[],
-  tools?: ChatCompletionTool[],
-  functionCall?: ChatCompletionCreateParams.Function[]
-) =>
-  messages.reduce((sum, item) => {
-    // Evaluates the text of toolcall and functioncall
-    const functionCallPrompt = (() => {
-      let prompt = '';
-      if (item.role === ChatCompletionRequestMessageRoleEnum.Assistant) {
-        const toolCalls = item.tool_calls;
-        prompt +=
-          toolCalls
-            ?.map((item) => `${item?.function?.name} ${item?.function?.arguments}`.trim())
-            ?.join('') || '';
-
-        const functionCall = item.function_call;
-        prompt += `${functionCall?.name} ${functionCall?.arguments}`.trim();
-      }
-      return prompt;
-    })();
-
-    const contentPrompt = (() => {
-      if (!item.content) return '';
-      if (typeof item.content === 'string') return item.content;
-      return item.content
-        .map((item) => {
-          if (item.type === 'text') return item.text;
-          return '';
-        })
-        .join('');
-    })();
-
-    return sum + countPromptTokens(`${contentPrompt}${functionCallPrompt}`, item.role);
-  }, 0) +
-  countToolsTokens(tools) +
-  countToolsTokens(functionCall);
-
-/* slice messages from top to bottom by maxTokens */
-export function sliceMessagesTB({
-  messages,
-  maxTokens
-}: {
-  messages: ChatItemType[];
-  maxTokens: number;
-}) {
-  const adaptMessages = chats2GPTMessages({ messages, reserveId: true });
-  let reduceTokens = maxTokens;
-  let result: ChatItemType[] = [];
-
-  for (let i = 0; i < adaptMessages.length; i++) {
-    const item = adaptMessages[i];
-
-    const tokens = countPromptTokens(item.content, item.role);
-    reduceTokens -= tokens;
-
-    if (reduceTokens > 0) {
-      result.push(messages[i]);
-    } else {
-      break;
-    }
-  }
-
-  return result.length === 0 && messages[0] ? [messages[0]] : result;
-}

packages/global/common/string/tiktoken/type.d.ts

@@ -1,5 +0,0 @@
-import type { Tiktoken } from 'js-tiktoken';
-
-declare global {
-  var TikToken: Tiktoken;
-}

packages/global/common/string/time.ts

@@ -1,5 +1,37 @@
 import dayjs from 'dayjs';
+import cronParser from 'cron-parser';
 
 export const formatTime2YMDHM = (time?: Date) =>
   time ? dayjs(time).format('YYYY-MM-DD HH:mm') : '';
 export const formatTime2YMD = (time?: Date) => (time ? dayjs(time).format('YYYY-MM-DD') : '');
+export const formatTime2HM = (time: Date = new Date()) => dayjs(time).format('HH:mm');
+
+/* cron time parse */
+export const cronParser2Fields = (cronString: string) => {
+  try {
+    const cronField = cronParser.parseExpression(cronString).fields;
+    return cronField;
+  } catch (error) {
+    return null;
+  }
+};
+// 根据cron表达式和时区获取下一个时间
+export const getNextTimeByCronStringAndTimezone = ({
+  cronString,
+  timezone
+}: {
+  cronString: string;
+  timezone: string;
+}) => {
+  try {
+    const options = {
+      currentDate: dayjs().tz(timezone).format(),
+      tz: timezone
+    };
+    const interval = cronParser.parseExpression(cronString, options);
+    const date = interval.next().toString();
+    return new Date(date);
+  } catch (error) {
+    return new Date('2099');
+  }
+};

packages/global/common/string/tools.ts

@@ -28,7 +28,9 @@ export const simpleText = (text = '') => {
 /* 
   replace {{variable}} to value
 */
-export function replaceVariable(text: string, obj: Record<string, string | number>) {
+export function replaceVariable(text: any, obj: Record<string, string | number>) {
+  if (!(typeof text === 'string')) return text;
+
   for (const key in obj) {
     const val = obj[key];
     if (!['string', 'number'].includes(typeof val)) continue;
@@ -48,6 +50,18 @@ export const replaceSensitiveText = (text: string) => {
   return text;
 };
 
+/* Make sure the first letter is definitely lowercase */
 export const getNanoid = (size = 12) => {
-  return customAlphabet('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890', size)();
+  const firstChar = customAlphabet('abcdefghijklmnopqrstuvwxyz', 1)();
+
+  if (size === 1) return firstChar;
+
+  const randomsStr = customAlphabet(
+    'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890',
+    size - 1
+  )();
+
+  return `${firstChar}${randomsStr}`;
 };
+
+export const replaceRegChars = (text: string) => text.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');

packages/global/common/system/types/index.d.ts

@@ -37,6 +37,7 @@ export type FastGPTFeConfigsType = {
   chatbotUrl?: string;
   openAPIDocUrl?: string;
   systemTitle?: string;
+  systemDescription?: string;
   googleClientVerKey?: string;
   isPlus?: boolean;
   show_phoneLogin?: boolean;

packages/global/common/time/timezone.ts

@@ -76,5 +76,5 @@ export const getSystemTime = (timeZone: string) => {
   const timezoneDiff = getTimezoneOffset(timeZone);
   const now = Date.now();
   const targetTime = now + timezoneDiff * 60 * 60 * 1000;
-  return dayjs(targetTime).format('YYYY-MM-DD HH:mm:ss');
+  return dayjs(targetTime).format('YYYY-MM-DD HH:mm:ss dddd');
 };

packages/global/core/ai/prompt/agent.ts

@@ -41,20 +41,22 @@ export const Prompt_ExtractJson = `你可以从 <对话记录></对话记录>
 </对话记录>
 `;
 
-export const Prompt_CQJson = `我会给你几个问题类型，请参考背景知识（可能为空）和对话记录，判断我“本次问题”的类型，并返回一个问题“类型ID”:
-<问题类型>
+export const Prompt_CQJson = `请帮我执行一个“问题分类”任务，将问题分类为以下几种类型之一：
+
+"""
 {{typeList}}
-</问题类型>
+"""
 
-<背景知识>
+## 背景知识
 {{systemPrompt}}
-</背景知识>
 
-<对话记录>
+## 对话记录
 {{history}}
-</对话记录>
 
-Human："{{question}}"
+## 开始任务
 
+现在，我们开始分类，我会给你一个"问题"，请结合背景知识和对话记录，将问题分类到对应的类型中，并返回类型ID。
+
+问题："{{question}}"
 类型ID=
 `;

packages/global/core/app/api.d.ts

@@ -1,20 +0,0 @@
-import type { LLMModelItemType } from '../ai/model.d';
-import { AppTypeEnum } from './constants';
-import { AppSchema } from './type';
-
-export type CreateAppParams = {
-  name?: string;
-  avatar?: string;
-  type?: `${AppTypeEnum}`;
-  modules: AppSchema['modules'];
-};
-
-export interface AppUpdateParams {
-  name?: string;
-  type?: `${AppTypeEnum}`;
-  avatar?: string;
-  intro?: string;
-  modules?: AppSchema['modules'];
-  permission?: AppSchema['permission'];
-  teamTags?: AppSchema['teamTags'];
-}

packages/global/core/app/type.d.ts

@@ -1,23 +1,31 @@
-import type { FlowNodeTemplateType, ModuleItemType } from '../module/type.d';
+import type { FlowNodeTemplateType, StoreNodeItemType } from '../workflow/type';
 
 import { AppTypeEnum } from './constants';
 import { PermissionTypeEnum } from '../../support/permission/constant';
-import type { DatasetModuleProps } from '../module/node/type.d';
-import { VariableInputEnum } from '../module/constants';
-import { SelectedDatasetType } from '../module/api';
+import { VariableInputEnum } from '../workflow/constants';
+import { SelectedDatasetType } from '../workflow/api';
 import { DatasetSearchModeEnum } from '../dataset/constants';
 import { TeamTagSchema as TeamTagsSchemaType } from '@fastgpt/global/support/user/team/type.d';
+import { StoreEdgeItemType } from '../workflow/type/edge';
+
 export interface AppSchema {
   _id: string;
-  userId: string;
   teamId: string;
   tmbId: string;
   name: string;
   type: `${AppTypeEnum}`;
+  version?: 'v1' | 'v2';
   avatar: string;
   intro: string;
   updateTime: number;
-  modules: ModuleItemType[];
+
+  modules: StoreNodeItemType[];
+  edges: StoreEdgeItemType[];
+
+  // App system config
+  scheduledTriggerConfig?: AppScheduledTriggerConfigType | null;
+  scheduledTriggerNextTime?: Date;
+
   permission: `${PermissionTypeEnum}`;
   inited?: boolean;
   teamTags: string[];
@@ -79,10 +87,19 @@ export type AppSimpleEditFormType = {
       speed?: number | undefined;
     };
     whisper: AppWhisperConfigType;
+    scheduleTrigger: AppScheduledTriggerConfigType | null;
   };
 };
 
 /* app function config */
+export type SettingAIDataType = {
+  model: string;
+  temperature: number;
+  maxToken: number;
+  isResponseAnswerText?: boolean;
+  maxHistories?: number;
+};
+
 // variable
 export type VariableItemType = {
   id: string;
@@ -106,3 +123,9 @@ export type AppWhisperConfigType = {
   autoSend: boolean;
   autoTTSResponse: boolean;
 };
+// interval timer
+export type AppScheduledTriggerConfigType = {
+  cronString: string;
+  timezone: string;
+  defaultPrompt: string;
+};

packages/global/core/app/utils.ts

@@ -1,13 +1,9 @@
 import type { AppSimpleEditFormType } from '../app/type';
-import { FlowNodeTypeEnum } from '../module/node/constant';
-import {
-  ModuleOutputKeyEnum,
-  ModuleInputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../module/constants';
-import type { FlowNodeInputItemType } from '../module/node/type.d';
-import { getGuideModule, splitGuideModule } from '../module/utils';
-import { ModuleItemType } from '../module/type.d';
+import { FlowNodeTypeEnum } from '../workflow/node/constant';
+import { NodeInputKeyEnum, FlowNodeTemplateTypeEnum } from '../workflow/constants';
+import type { FlowNodeInputItemType } from '../workflow/type/io.d';
+import { getGuideModule, splitGuideModule } from '../workflow/utils';
+import { StoreNodeItemType } from '../workflow/type';
 import { DatasetSearchModeEnum } from '../dataset/constants';
 import { defaultWhisperConfig } from './constants';
 
@@ -38,97 +34,105 @@ export const getDefaultAppForm = (): AppSimpleEditFormType => {
       tts: {
         type: 'web'
       },
-      whisper: defaultWhisperConfig
+      whisper: defaultWhisperConfig,
+      scheduleTrigger: null
     }
   };
 };
 
-/* format app modules to edit form */
-export const appModules2Form = ({ modules }: { modules: ModuleItemType[] }) => {
+/* format app nodes to edit form */
+export const appWorkflow2Form = ({ nodes }: { nodes: StoreNodeItemType[] }) => {
   const defaultAppForm = getDefaultAppForm();
 
   const findInputValueByKey = (inputs: FlowNodeInputItemType[], key: string) => {
     return inputs.find((item) => item.key === key)?.value;
   };
 
-  modules.forEach((module) => {
+  nodes.forEach((node) => {
     if (
-      module.flowType === FlowNodeTypeEnum.chatNode ||
-      module.flowType === FlowNodeTypeEnum.tools
+      node.flowNodeType === FlowNodeTypeEnum.chatNode ||
+      node.flowNodeType === FlowNodeTypeEnum.tools
     ) {
-      defaultAppForm.aiSettings.model = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.aiModel
-      );
+      defaultAppForm.aiSettings.model = findInputValueByKey(node.inputs, NodeInputKeyEnum.aiModel);
       defaultAppForm.aiSettings.systemPrompt = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.aiSystemPrompt
+        node.inputs,
+        NodeInputKeyEnum.aiSystemPrompt
       );
       defaultAppForm.aiSettings.temperature = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.aiChatTemperature
+        node.inputs,
+        NodeInputKeyEnum.aiChatTemperature
       );
       defaultAppForm.aiSettings.maxToken = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.aiChatMaxToken
+        node.inputs,
+        NodeInputKeyEnum.aiChatMaxToken
       );
       defaultAppForm.aiSettings.maxHistories = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.history
+        node.inputs,
+        NodeInputKeyEnum.history
       );
-    } else if (module.flowType === FlowNodeTypeEnum.datasetSearchNode) {
+    } else if (node.flowNodeType === FlowNodeTypeEnum.datasetSearchNode) {
       defaultAppForm.dataset.datasets = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSelectList
+        node.inputs,
+        NodeInputKeyEnum.datasetSelectList
       );
       defaultAppForm.dataset.similarity = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSimilarity
+        node.inputs,
+        NodeInputKeyEnum.datasetSimilarity
       );
       defaultAppForm.dataset.limit = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetMaxTokens
+        node.inputs,
+        NodeInputKeyEnum.datasetMaxTokens
       );
       defaultAppForm.dataset.searchMode =
-        findInputValueByKey(module.inputs, ModuleInputKeyEnum.datasetSearchMode) ||
+        findInputValueByKey(node.inputs, NodeInputKeyEnum.datasetSearchMode) ||
         DatasetSearchModeEnum.embedding;
       defaultAppForm.dataset.usingReRank = !!findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSearchUsingReRank
+        node.inputs,
+        NodeInputKeyEnum.datasetSearchUsingReRank
       );
       defaultAppForm.dataset.datasetSearchUsingExtensionQuery = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSearchUsingExtensionQuery
+        node.inputs,
+        NodeInputKeyEnum.datasetSearchUsingExtensionQuery
       );
       defaultAppForm.dataset.datasetSearchExtensionModel = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSearchExtensionModel
+        node.inputs,
+        NodeInputKeyEnum.datasetSearchExtensionModel
       );
       defaultAppForm.dataset.datasetSearchExtensionBg = findInputValueByKey(
-        module.inputs,
-        ModuleInputKeyEnum.datasetSearchExtensionBg
+        node.inputs,
+        NodeInputKeyEnum.datasetSearchExtensionBg
       );
-    } else if (module.flowType === FlowNodeTypeEnum.userGuide) {
-      const { welcomeText, variableModules, questionGuide, ttsConfig, whisperConfig } =
-        splitGuideModule(getGuideModule(modules));
+    } else if (node.flowNodeType === FlowNodeTypeEnum.systemConfig) {
+      const {
+        welcomeText,
+        variableModules,
+        questionGuide,
+        ttsConfig,
+        whisperConfig,
+        scheduledTriggerConfig
+      } = splitGuideModule(getGuideModule(nodes));
 
       defaultAppForm.userGuide = {
         welcomeText: welcomeText,
         variables: variableModules,
         questionGuide: questionGuide,
         tts: ttsConfig,
-        whisper: whisperConfig
+        whisper: whisperConfig,
+        scheduleTrigger: scheduledTriggerConfig
       };
-    } else if (module.flowType === FlowNodeTypeEnum.pluginModule) {
+    } else if (node.flowNodeType === FlowNodeTypeEnum.pluginModule) {
+      if (!node.pluginId) return;
+
       defaultAppForm.selectedTools.push({
-        id: module.inputs.find((input) => input.key === ModuleInputKeyEnum.pluginId)?.value || '',
-        name: module.name,
-        avatar: module.avatar,
-        intro: module.intro || '',
-        flowType: module.flowType,
-        showStatus: module.showStatus,
-        inputs: module.inputs,
-        outputs: module.outputs,
+        id: node.pluginId,
+        pluginId: node.pluginId,
+        name: node.name,
+        avatar: node.avatar,
+        intro: node.intro || '',
+        flowNodeType: node.flowNodeType,
+        showStatus: node.showStatus,
+        inputs: node.inputs,
+        outputs: node.outputs,
         templateType: FlowNodeTemplateTypeEnum.other
       });
     }

packages/global/core/app/version.d.ts

@@ -0,0 +1,10 @@
+import { StoreNodeItemType } from '../workflow/type';
+import { StoreEdgeItemType } from '../workflow/type/edge';
+
+export type AppVersionSchemaType = {
+  _id: string;
+  appId: string;
+  time: Date;
+  nodes: StoreNodeItemType[];
+  edges: StoreEdgeItemType[];
+};

packages/global/core/chat/type.d.ts

@@ -1,4 +1,4 @@
-import { ClassifyQuestionAgentItemType } from '../module/type';
+import { ClassifyQuestionAgentItemType } from '../workflow/type';
 import { SearchDataResponseItemType } from '../dataset/type';
 import {
   ChatFileTypeEnum,
@@ -7,14 +7,14 @@ import {
   ChatSourceEnum,
   ChatStatusEnum
 } from './constants';
-import { FlowNodeTypeEnum } from '../module/node/constant';
-import { ModuleOutputKeyEnum } from '../module/constants';
-import { DispatchNodeResponseKeyEnum } from '../module/runtime/constants';
+import { FlowNodeTypeEnum } from '../workflow/node/constant';
+import { NodeOutputKeyEnum } from '../workflow/constants';
+import { DispatchNodeResponseKeyEnum } from '../workflow/runtime/constants';
 import { AppSchema } from '../app/type';
 import type { AppSchema as AppType } from '@fastgpt/global/core/app/type.d';
 import { DatasetSearchModeEnum } from '../dataset/constants';
 import { ChatBoxInputType } from '../../../../projects/app/src/components/ChatBox/type';
-import { DispatchNodeResponseType } from '../module/runtime/type.d';
+import { DispatchNodeResponseType } from '../workflow/runtime/type.d';
 
 export type ChatSchema = {
   _id: string;
@@ -136,6 +136,7 @@ export type ChatHistoryItemType = HistoryItemType & {
 
 /* ------- response data ------------ */
 export type ChatHistoryItemResType = DispatchNodeResponseType & {
+  nodeId: string;
   moduleType: `${FlowNodeTypeEnum}`;
   moduleName: string;
 };
@@ -154,6 +155,6 @@ export type ToolModuleResponseItemType = {
 
 /* dispatch run time */
 export type RuntimeUserPromptType = {
-  files?: UserChatItemValueItemType['file'][];
+  files: UserChatItemValueItemType['file'][];
   text: string;
 };

packages/global/core/chat/utils.ts

@@ -1,7 +1,7 @@
-import { DispatchNodeResponseType } from '../module/runtime/type';
-import { FlowNodeInputTypeEnum, FlowNodeTypeEnum } from '../module/node/constant';
+import { DispatchNodeResponseType } from '../workflow/runtime/type';
+import { FlowNodeTypeEnum } from '../workflow/node/constant';
 import { ChatItemValueTypeEnum, ChatRoleEnum } from './constants';
-import { ChatHistoryItemResType, ChatItemType } from './type.d';
+import { ChatHistoryItemResType, ChatItemType, UserChatItemValueItemType } from './type.d';
 
 export const getChatTitleFromChatMessage = (message?: ChatItemType, defaultValue = '新对话') => {
   // @ts-ignore
@@ -77,3 +77,15 @@ export const filterPublicNodeResponseData = ({
       return obj as ChatHistoryItemResType;
     });
 };
+
+export const removeEmptyUserInput = (input: UserChatItemValueItemType[]) => {
+  return input.filter((item) => {
+    if (item.type === ChatItemValueTypeEnum.text && !item.text?.content?.trim()) {
+      return false;
+    }
+    if (item.type === ChatItemValueTypeEnum.file && !item.file?.url) {
+      return false;
+    }
+    return true;
+  });
+};

packages/global/core/dataset/search/utils.ts

@@ -1,4 +1,3 @@
-import { countPromptTokens } from '../../../common/string/tiktoken';
 import { SearchScoreTypeEnum } from '../constants';
 import { SearchDataResponseItemType } from '../type';
 
@@ -71,25 +70,3 @@ export const datasetSearchResultConcat = (
     return item;
   });
 };
-
-export const filterSearchResultsByMaxChars = (
-  list: SearchDataResponseItemType[],
-  maxTokens: number
-) => {
-  const results: SearchDataResponseItemType[] = [];
-  let totalTokens = 0;
-
-  for (let i = 0; i < list.length; i++) {
-    const item = list[i];
-    totalTokens += countPromptTokens(item.q + item.a);
-    if (totalTokens > maxTokens + 500) {
-      break;
-    }
-    results.push(item);
-    if (totalTokens > maxTokens) {
-      break;
-    }
-  }
-
-  return results.length === 0 ? list.slice(0, 1) : results;
-};

packages/global/core/module/node/constant.ts

@@ -1,70 +0,0 @@
-export enum FlowNodeInputTypeEnum {
-  triggerAndFinish = 'triggerAndFinish',
-  systemInput = 'systemInput', // history, userChatInput, variableInput
-
-  input = 'input', // one line input
-  numberInput = 'numberInput',
-  select = 'select',
-  slider = 'slider',
-  target = 'target', // data input
-  switch = 'switch',
-
-  // editor
-  textarea = 'textarea',
-  JSONEditor = 'JSONEditor',
-
-  addInputParam = 'addInputParam', // params input
-
-  selectApp = 'selectApp',
-
-  // chat special input
-  aiSettings = 'aiSettings',
-
-  // ai model select
-  selectLLMModel = 'selectLLMModel',
-  settingLLMModel = 'settingLLMModel',
-
-  // dataset special input
-  selectDataset = 'selectDataset',
-  selectDatasetParamsModal = 'selectDatasetParamsModal',
-  settingDatasetQuotePrompt = 'settingDatasetQuotePrompt',
-
-  hidden = 'hidden',
-  custom = 'custom'
-}
-
-export enum FlowNodeOutputTypeEnum {
-  answer = 'answer',
-  source = 'source',
-  hidden = 'hidden',
-
-  addOutputParam = 'addOutputParam'
-}
-
-export enum FlowNodeTypeEnum {
-  userGuide = 'userGuide',
-  questionInput = 'questionInput',
-  historyNode = 'historyNode',
-  chatNode = 'chatNode',
-
-  datasetSearchNode = 'datasetSearchNode',
-  datasetConcatNode = 'datasetConcatNode',
-
-  answerNode = 'answerNode',
-  classifyQuestion = 'classifyQuestion',
-  contentExtract = 'contentExtract',
-  httpRequest = 'httpRequest',
-  httpRequest468 = 'httpRequest468',
-  runApp = 'app',
-  pluginModule = 'pluginModule',
-  pluginInput = 'pluginInput',
-  pluginOutput = 'pluginOutput',
-  queryExtension = 'cfr',
-  tools = 'tools',
-  stopTool = 'stopTool',
-  lafModule = 'lafModule'
-
-  // abandon
-}
-
-export const EDGE_TYPE = 'default';

packages/global/core/module/node/type.d.ts

@@ -1,128 +0,0 @@
-import { FlowNodeInputTypeEnum, FlowNodeOutputTypeEnum, FlowNodeTypeEnum } from './constant';
-import { ModuleIOValueTypeEnum, ModuleInputKeyEnum, ModuleOutputKeyEnum } from '../constants';
-import { SelectedDatasetType } from '../api';
-import { EditInputFieldMap, EditOutputFieldMap } from './type';
-import { LLMModelTypeEnum } from '../../ai/constants';
-
-export type FlowNodeChangeProps = {
-  moduleId: string;
-  type:
-    | 'attr' // key: attr, value: new value
-    | 'updateInput' // key: update input key, value: new input value
-    | 'replaceInput' // key: old input key, value: new input value
-    | 'addInput' // key: null, value: new input value
-    | 'delInput' // key: delete input key, value: null
-    | 'updateOutput' // key: update output key, value: new output value
-    | 'replaceOutput' // key: old output key, value: new output value
-    | 'addOutput' // key: null, value: new output value
-    | 'delOutput'; // key: delete output key, value: null
-  key?: string;
-  value?: any;
-  index?: number;
-};
-
-export type FlowNodeInputItemType = {
-  valueType?: `${ModuleIOValueTypeEnum}`; // data type
-  type: `${FlowNodeInputTypeEnum}`; // Node Type. Decide on a render style
-  key: `${ModuleInputKeyEnum}` | string;
-  value?: any;
-  label: string;
-  description?: string;
-  required?: boolean;
-  toolDescription?: string; // If this field is not empty, it is entered as a tool
-
-  edit?: boolean; // Whether to allow editing
-  editField?: EditInputFieldMap;
-  defaultEditField?: EditNodeFieldType;
-
-  connected?: boolean; // There are incoming data
-
-  showTargetInApp?: boolean;
-  showTargetInPlugin?: boolean;
-
-  hideInApp?: boolean;
-  hideInPlugin?: boolean;
-
-  placeholder?: string; // input,textarea
-
-  list?: { label: string; value: any }[]; // select
-
-  markList?: { label: string; value: any }[]; // slider
-  step?: number; // slider
-  max?: number; // slider, number input
-  min?: number; // slider, number input
-
-  llmModelType?: `${LLMModelTypeEnum}`;
-};
-
-export type FlowNodeOutputTargetItemType = {
-  moduleId: string;
-  key: string;
-};
-export type FlowNodeOutputItemType = {
-  type?: `${FlowNodeOutputTypeEnum}`;
-  key: `${ModuleOutputKeyEnum}` | string;
-  valueType?: `${ModuleIOValueTypeEnum}`;
-
-  label?: string;
-  description?: string;
-  required?: boolean;
-  defaultValue?: any;
-
-  edit?: boolean;
-  editField?: EditOutputFieldMap;
-  defaultEditField?: EditNodeFieldType;
-
-  targets: FlowNodeOutputTargetItemType[];
-};
-
-/* --------------- edit field ------------------- */
-export type EditInputFieldMap = EditOutputFieldMap & {
-  inputType?: boolean;
-  required?: boolean;
-  isToolInput?: boolean;
-};
-export type EditOutputFieldMap = {
-  name?: boolean;
-  key?: boolean;
-  description?: boolean;
-  dataType?: boolean;
-  defaultValue?: boolean;
-};
-export type EditNodeFieldType = {
-  inputType?: `${FlowNodeInputTypeEnum}`; // input type
-  outputType?: `${FlowNodeOutputTypeEnum}`;
-  required?: boolean;
-  key?: string;
-  label?: string;
-  description?: string;
-  valueType?: `${ModuleIOValueTypeEnum}`;
-  isToolInput?: boolean;
-  defaultValue?: string;
-};
-
-/* ------------- item type --------------- */
-export type SettingAIDataType = {
-  model: string;
-  temperature: number;
-  maxToken: number;
-  isResponseAnswerText?: boolean;
-  maxHistories?: number;
-};
-/* ai chat modules props */
-export type AIChatModuleProps = {
-  [ModuleInputKeyEnum.aiModel]: string;
-  [ModuleInputKeyEnum.aiSystemPrompt]?: string;
-  [ModuleInputKeyEnum.aiChatTemperature]: number;
-  [ModuleInputKeyEnum.aiChatMaxToken]: number;
-  [ModuleInputKeyEnum.aiChatIsResponseText]: boolean;
-  [ModuleInputKeyEnum.aiChatQuoteTemplate]?: string;
-  [ModuleInputKeyEnum.aiChatQuotePrompt]?: string;
-};
-
-export type DatasetModuleProps = {
-  [ModuleInputKeyEnum.datasetSelectList]: SelectedDatasetType;
-  [ModuleInputKeyEnum.datasetSimilarity]: number;
-  [ModuleInputKeyEnum.datasetMaxTokens]: number;
-  [ModuleInputKeyEnum.datasetStartReRank]: boolean;
-};

packages/global/core/module/runtime/utils.ts

@@ -1,31 +0,0 @@
-import { ChatCompletionRequestMessageRoleEnum } from '../../ai/constants';
-
-export const textAdaptGptResponse = ({
-  text,
-  model = '',
-  finish_reason = null,
-  extraData = {}
-}: {
-  model?: string;
-  text: string | null;
-  finish_reason?: null | 'stop';
-  extraData?: Object;
-}) => {
-  return JSON.stringify({
-    ...extraData,
-    id: '',
-    object: '',
-    created: 0,
-    model,
-    choices: [
-      {
-        delta:
-          text === null
-            ? {}
-            : { role: ChatCompletionRequestMessageRoleEnum.Assistant, content: text },
-        index: 0,
-        finish_reason
-      }
-    ]
-  });
-};

packages/global/core/module/template/input.ts

@@ -1,101 +0,0 @@
-import type { FlowNodeInputItemType } from '../node/type.d';
-import { DYNAMIC_INPUT_KEY, ModuleInputKeyEnum } from '../constants';
-import { FlowNodeInputTypeEnum } from '../node/constant';
-import { ModuleIOValueTypeEnum } from '../constants';
-import { chatNodeSystemPromptTip } from './tip';
-
-export const Input_Template_Switch: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.switch,
-  type: FlowNodeInputTypeEnum.hidden,
-  label: '',
-  description: 'core.module.input.description.Trigger',
-  valueType: ModuleIOValueTypeEnum.any,
-  showTargetInApp: true,
-  showTargetInPlugin: true
-};
-
-export const Input_Template_History: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.history,
-  type: FlowNodeInputTypeEnum.numberInput,
-  label: 'core.module.input.label.chat history',
-  required: true,
-  min: 0,
-  max: 30,
-  valueType: ModuleIOValueTypeEnum.chatHistory,
-  value: 6,
-  showTargetInApp: true,
-  showTargetInPlugin: true
-};
-
-export const Input_Template_UserChatInput: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.userChatInput,
-  type: FlowNodeInputTypeEnum.custom,
-  label: '',
-  required: true,
-  valueType: ModuleIOValueTypeEnum.string,
-  showTargetInApp: true,
-  showTargetInPlugin: true
-};
-
-export const Input_Template_AddInputParam: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.addInputParam,
-  type: FlowNodeInputTypeEnum.addInputParam,
-  valueType: ModuleIOValueTypeEnum.any,
-  label: '',
-  required: false,
-  showTargetInApp: false,
-  showTargetInPlugin: false
-};
-
-export const Input_Template_DynamicInput: FlowNodeInputItemType = {
-  key: DYNAMIC_INPUT_KEY,
-  type: FlowNodeInputTypeEnum.target,
-  valueType: ModuleIOValueTypeEnum.any,
-  label: 'core.module.inputType.dynamicTargetInput',
-  description: 'core.module.input.description.dynamic input',
-  required: false,
-  showTargetInApp: false,
-  showTargetInPlugin: true,
-  hideInApp: true
-};
-
-export const Input_Template_SelectAIModel: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.aiModel,
-  type: FlowNodeInputTypeEnum.selectLLMModel,
-  label: 'core.module.input.label.aiModel',
-  required: true,
-  valueType: ModuleIOValueTypeEnum.string,
-  showTargetInApp: false,
-  showTargetInPlugin: false
-};
-export const Input_Template_SettingAiModel: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.aiModel,
-  type: FlowNodeInputTypeEnum.settingLLMModel,
-  label: 'core.module.input.label.aiModel',
-  required: true,
-  valueType: ModuleIOValueTypeEnum.string,
-  showTargetInApp: false,
-  showTargetInPlugin: false
-};
-
-export const Input_Template_System_Prompt: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.aiSystemPrompt,
-  type: FlowNodeInputTypeEnum.textarea,
-  max: 3000,
-  valueType: ModuleIOValueTypeEnum.string,
-  label: 'core.ai.Prompt',
-  description: chatNodeSystemPromptTip,
-  placeholder: chatNodeSystemPromptTip,
-  showTargetInApp: true,
-  showTargetInPlugin: true
-};
-
-export const Input_Template_Dataset_Quote: FlowNodeInputItemType = {
-  key: ModuleInputKeyEnum.aiChatDatasetQuote,
-  type: FlowNodeInputTypeEnum.settingDatasetQuotePrompt,
-  label: '知识库引用',
-  description: 'core.module.Dataset quote.Input description',
-  valueType: ModuleIOValueTypeEnum.datasetQuote,
-  showTargetInApp: true,
-  showTargetInPlugin: true
-};

packages/global/core/module/template/output.ts

@@ -1,29 +0,0 @@
-import type { FlowNodeOutputItemType } from '../node/type';
-import { ModuleOutputKeyEnum } from '../constants';
-import { FlowNodeOutputTypeEnum } from '../node/constant';
-import { ModuleIOValueTypeEnum } from '../constants';
-
-export const Output_Template_UserChatInput: FlowNodeOutputItemType = {
-  key: ModuleOutputKeyEnum.userChatInput,
-  label: 'core.module.input.label.user question',
-  type: FlowNodeOutputTypeEnum.hidden,
-  valueType: ModuleIOValueTypeEnum.string,
-  targets: []
-};
-
-export const Output_Template_Finish: FlowNodeOutputItemType = {
-  key: ModuleOutputKeyEnum.finish,
-  label: '',
-  description: '',
-  valueType: ModuleIOValueTypeEnum.boolean,
-  type: FlowNodeOutputTypeEnum.hidden,
-  targets: []
-};
-
-export const Output_Template_AddOutput: FlowNodeOutputItemType = {
-  key: ModuleOutputKeyEnum.addOutputParam,
-  type: FlowNodeOutputTypeEnum.addOutputParam,
-  valueType: ModuleIOValueTypeEnum.any,
-  label: '',
-  targets: []
-};

packages/global/core/module/template/system/abandon/http.ts

@@ -1,112 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../../node/constant';
-import { FlowNodeTemplateType } from '../../../type';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../../constants';
-import {
-  Input_Template_AddInputParam,
-  Input_Template_DynamicInput,
-  Input_Template_Switch
-} from '../../input';
-import { Output_Template_AddOutput, Output_Template_Finish } from '../../output';
-
-export const HttpModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.httpRequest,
-  templateType: FlowNodeTemplateTypeEnum.externalCall,
-  flowType: FlowNodeTypeEnum.httpRequest,
-  avatar: '/imgs/module/http.png',
-  name: 'core.module.template.Http request',
-  intro:
-    '该Http模块已被弃用，将于2024/3/31 不再提供服务。请尽快删除该模块并重新添加新的 Http 模块。',
-  showStatus: true,
-  inputs: [
-    Input_Template_Switch,
-    {
-      key: ModuleInputKeyEnum.httpMethod,
-      type: FlowNodeInputTypeEnum.select,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: 'core.module.input.label.Http Request Method',
-      value: 'POST',
-      list: [
-        {
-          label: 'GET',
-          value: 'GET'
-        },
-        {
-          label: 'POST',
-          value: 'POST'
-        }
-      ],
-      required: true,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpReqUrl,
-      type: FlowNodeInputTypeEnum.input,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: 'core.module.input.label.Http Request Url',
-      description: 'core.module.input.description.Http Request Url',
-      placeholder: 'https://api.ai.com/getInventory',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpHeaders,
-      type: FlowNodeInputTypeEnum.JSONEditor,
-      valueType: ModuleIOValueTypeEnum.string,
-      value: '',
-      label: 'core.module.input.label.Http Request Header',
-      description: 'core.module.input.description.Http Request Header',
-      placeholder: 'core.module.input.description.Http Request Header',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    Input_Template_DynamicInput,
-    {
-      ...Input_Template_AddInputParam,
-      editField: {
-        key: true,
-        name: true,
-        description: true,
-        required: true,
-        dataType: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        inputType: FlowNodeInputTypeEnum.target,
-        valueType: ModuleIOValueTypeEnum.string,
-        required: true
-      }
-    }
-  ],
-  outputs: [
-    Output_Template_Finish,
-    {
-      ...Output_Template_AddOutput,
-      editField: {
-        key: true,
-        name: true,
-        description: true,
-        dataType: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        outputType: FlowNodeOutputTypeEnum.source,
-        valueType: ModuleIOValueTypeEnum.string
-      }
-    }
-  ]
-};

packages/global/core/module/template/system/aiChat.ts

@@ -1,117 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type.d';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import {
-  Input_Template_SettingAiModel,
-  Input_Template_Dataset_Quote,
-  Input_Template_History,
-  Input_Template_Switch,
-  Input_Template_System_Prompt,
-  Input_Template_UserChatInput
-} from '../input';
-import { chatNodeSystemPromptTip } from '../tip';
-import { Output_Template_Finish, Output_Template_UserChatInput } from '../output';
-
-export const AiChatModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.chatNode,
-  templateType: FlowNodeTemplateTypeEnum.textAnswer,
-  flowType: FlowNodeTypeEnum.chatNode,
-  avatar: '/imgs/module/AI.png',
-  name: 'AI 对话',
-  intro: 'AI 大模型对话',
-  showStatus: true,
-  isTool: true,
-  inputs: [
-    Input_Template_Switch,
-    Input_Template_SettingAiModel,
-    // --- settings modal
-    {
-      key: ModuleInputKeyEnum.aiChatTemperature,
-      type: FlowNodeInputTypeEnum.hidden, // Set in the pop-up window
-      label: '',
-      value: 0,
-      valueType: ModuleIOValueTypeEnum.number,
-      min: 0,
-      max: 10,
-      step: 1,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.aiChatMaxToken,
-      type: FlowNodeInputTypeEnum.hidden, // Set in the pop-up window
-      label: '',
-      value: 2000,
-      valueType: ModuleIOValueTypeEnum.number,
-      min: 100,
-      max: 4000,
-      step: 50,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.aiChatIsResponseText,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      value: true,
-      valueType: ModuleIOValueTypeEnum.boolean,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.aiChatQuoteTemplate,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.aiChatQuotePrompt,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    // settings modal ---
-    {
-      ...Input_Template_System_Prompt,
-      label: 'core.ai.Prompt',
-      description: chatNodeSystemPromptTip,
-      placeholder: chatNodeSystemPromptTip
-    },
-    Input_Template_History,
-    { ...Input_Template_UserChatInput, toolDescription: '用户问题' },
-    Input_Template_Dataset_Quote
-  ],
-  outputs: [
-    Output_Template_UserChatInput,
-    {
-      key: ModuleOutputKeyEnum.history,
-      label: 'core.module.output.label.New context',
-      description: 'core.module.output.description.New context',
-      valueType: ModuleIOValueTypeEnum.chatHistory,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    {
-      key: ModuleOutputKeyEnum.answerText,
-      label: 'core.module.output.label.Ai response content',
-      description: 'core.module.output.description.Ai response content',
-      valueType: ModuleIOValueTypeEnum.string,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    Output_Template_Finish
-  ]
-};

packages/global/core/module/template/system/contextExtract.ts

@@ -1,94 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type.d';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import {
-  Input_Template_SelectAIModel,
-  Input_Template_History,
-  Input_Template_Switch
-} from '../input';
-import { LLMModelTypeEnum } from '../../../ai/constants';
-
-export const ContextExtractModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.contentExtract,
-  templateType: FlowNodeTemplateTypeEnum.functionCall,
-  flowType: FlowNodeTypeEnum.contentExtract,
-  avatar: '/imgs/module/extract.png',
-  name: '文本内容提取',
-  intro: '可从文本中提取指定的数据，例如：sql语句、搜索关键词、代码等',
-  showStatus: true,
-  isTool: true,
-  inputs: [
-    Input_Template_Switch,
-    {
-      ...Input_Template_SelectAIModel,
-      llmModelType: LLMModelTypeEnum.extractFields
-    },
-    {
-      key: ModuleInputKeyEnum.description,
-      type: FlowNodeInputTypeEnum.textarea,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: '提取要求描述',
-      description:
-        '给AI一些对应的背景知识或要求描述，引导AI更好的完成任务。\n该输入框可使用全局变量。',
-      placeholder:
-        '例如: \n1. 当前时间为: {{cTime}}。你是一个实验室预约助手，你的任务是帮助用户预约实验室，从文本中获取对应的预约信息。\n2. 你是谷歌搜索助手，需要从文本中提取出合适的搜索词。',
-      showTargetInApp: true,
-      showTargetInPlugin: true
-    },
-    Input_Template_History,
-    {
-      key: ModuleInputKeyEnum.contextExtractInput,
-      type: FlowNodeInputTypeEnum.target,
-      label: '需要提取的文本',
-      required: true,
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: true,
-      showTargetInPlugin: true,
-      toolDescription: '需要检索的内容'
-    },
-    {
-      key: ModuleInputKeyEnum.extractKeys,
-      type: FlowNodeInputTypeEnum.custom,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.any,
-      description: "由 '描述' 和 'key' 组成一个目标字段，可提取多个目标字段",
-      value: [], // {desc: string; key: string; required: boolean; enum: string[]}[]
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    }
-  ],
-  outputs: [
-    {
-      key: ModuleOutputKeyEnum.success,
-      label: '字段完全提取',
-      valueType: ModuleIOValueTypeEnum.boolean,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    {
-      key: ModuleOutputKeyEnum.failed,
-      label: '提取字段缺失',
-      description: '存在一个或多个字段未提取成功。尽管使用了默认值也算缺失。',
-      valueType: ModuleIOValueTypeEnum.boolean,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    {
-      key: ModuleOutputKeyEnum.contextExtractFields,
-      label: '完整提取结果',
-      description: '一个 JSON 字符串，例如：{"name:":"YY","Time":"2023/7/2 18:00"}',
-      valueType: ModuleIOValueTypeEnum.string,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    }
-  ]
-};

packages/global/core/module/template/system/datasetConcat.ts

@@ -1,53 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type.d';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import { Input_Template_Dataset_Quote, Input_Template_Switch } from '../input';
-import { Output_Template_Finish } from '../output';
-import { getNanoid } from '../../../../common/string/tools';
-
-export const getOneQuoteInputTemplate = (key = getNanoid()) => ({
-  ...Input_Template_Dataset_Quote,
-  key,
-  type: FlowNodeInputTypeEnum.hidden
-});
-
-export const DatasetConcatModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.datasetConcatNode,
-  flowType: FlowNodeTypeEnum.datasetConcatNode,
-  templateType: FlowNodeTemplateTypeEnum.other,
-  avatar: '/imgs/module/concat.svg',
-  name: '知识库搜索引用合并',
-  intro: '可以将多个知识库搜索结果进行合并输出。使用 RRF 的合并方式进行最终排序输出。',
-  showStatus: false,
-  inputs: [
-    Input_Template_Switch,
-    {
-      key: ModuleInputKeyEnum.datasetMaxTokens,
-      type: FlowNodeInputTypeEnum.custom,
-      label: '最大 Tokens',
-      value: 1500,
-      valueType: ModuleIOValueTypeEnum.number,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    getOneQuoteInputTemplate('defaultQuote')
-  ],
-  outputs: [
-    {
-      key: ModuleOutputKeyEnum.datasetQuoteQA,
-      label: 'core.module.Dataset quote.label',
-      type: FlowNodeOutputTypeEnum.source,
-      valueType: ModuleIOValueTypeEnum.datasetQuote,
-      targets: []
-    }
-  ]
-};

packages/global/core/module/template/system/datasetSearch.ts

@@ -1,133 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type.d';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import { Input_Template_Switch, Input_Template_UserChatInput } from '../input';
-import { Output_Template_Finish, Output_Template_UserChatInput } from '../output';
-import { DatasetSearchModeEnum } from '../../../dataset/constants';
-
-export const Dataset_SEARCH_DESC =
-  '调用“语义检索”和“全文检索”能力，从“知识库”中查找可能与问题相关的参考内容';
-
-export const DatasetSearchModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.datasetSearchNode,
-  templateType: FlowNodeTemplateTypeEnum.functionCall,
-  flowType: FlowNodeTypeEnum.datasetSearchNode,
-  avatar: '/imgs/module/db.png',
-  name: '知识库搜索',
-  intro: Dataset_SEARCH_DESC,
-  showStatus: true,
-  isTool: true,
-  inputs: [
-    Input_Template_Switch,
-    {
-      key: ModuleInputKeyEnum.datasetSelectList,
-      type: FlowNodeInputTypeEnum.selectDataset,
-      label: 'core.module.input.label.Select dataset',
-      value: [],
-      valueType: ModuleIOValueTypeEnum.selectDataset,
-      list: [],
-      required: true,
-      showTargetInApp: false,
-      showTargetInPlugin: true
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSimilarity,
-      type: FlowNodeInputTypeEnum.selectDatasetParamsModal,
-      label: '',
-      value: 0.4,
-      valueType: ModuleIOValueTypeEnum.number,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.datasetMaxTokens,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      value: 1500,
-      valueType: ModuleIOValueTypeEnum.number,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSearchMode,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: false,
-      showTargetInPlugin: false,
-      value: DatasetSearchModeEnum.embedding
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSearchUsingReRank,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.boolean,
-      showTargetInApp: false,
-      showTargetInPlugin: false,
-      value: false
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSearchUsingExtensionQuery,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.boolean,
-      showTargetInApp: false,
-      showTargetInPlugin: false,
-      value: true
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSearchExtensionModel,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.datasetSearchExtensionBg,
-      type: FlowNodeInputTypeEnum.hidden,
-      label: '',
-      valueType: ModuleIOValueTypeEnum.string,
-      showTargetInApp: false,
-      showTargetInPlugin: false,
-      value: ''
-    },
-    {
-      ...Input_Template_UserChatInput,
-      toolDescription: '需要检索的内容'
-    }
-  ],
-  outputs: [
-    Output_Template_UserChatInput,
-    {
-      key: ModuleOutputKeyEnum.datasetIsEmpty,
-      label: 'core.module.output.label.Search result empty',
-      type: FlowNodeOutputTypeEnum.source,
-      valueType: ModuleIOValueTypeEnum.boolean,
-      targets: []
-    },
-    {
-      key: ModuleOutputKeyEnum.datasetUnEmpty,
-      label: 'core.module.output.label.Search result not empty',
-      type: FlowNodeOutputTypeEnum.source,
-      valueType: ModuleIOValueTypeEnum.boolean,
-      targets: []
-    },
-    {
-      key: ModuleOutputKeyEnum.datasetQuoteQA,
-      label: 'core.module.Dataset quote.label',
-      type: FlowNodeOutputTypeEnum.source,
-      valueType: ModuleIOValueTypeEnum.datasetQuote,
-      targets: []
-    }
-  ]
-};

packages/global/core/module/template/system/http468.ts

@@ -1,128 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import {
-  Input_Template_AddInputParam,
-  Input_Template_DynamicInput,
-  Input_Template_Switch
-} from '../input';
-import { Output_Template_AddOutput, Output_Template_Finish } from '../output';
-
-export const HttpModule468: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.httpRequest468,
-  templateType: FlowNodeTemplateTypeEnum.externalCall,
-  flowType: FlowNodeTypeEnum.httpRequest468,
-  avatar: '/imgs/module/http.png',
-  name: 'HTTP 请求',
-  intro: '可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）',
-  showStatus: true,
-  isTool: true,
-  inputs: [
-    Input_Template_Switch,
-    {
-      key: ModuleInputKeyEnum.httpMethod,
-      type: FlowNodeInputTypeEnum.custom,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: '',
-      value: 'POST',
-      required: true,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpReqUrl,
-      type: FlowNodeInputTypeEnum.hidden,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: '',
-      description: 'core.module.input.description.Http Request Url',
-      placeholder: 'https://api.ai.com/getInventory',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpHeaders,
-      type: FlowNodeInputTypeEnum.custom,
-      valueType: ModuleIOValueTypeEnum.any,
-      value: [],
-      label: '',
-      description: 'core.module.input.description.Http Request Header',
-      placeholder: 'core.module.input.description.Http Request Header',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpParams,
-      type: FlowNodeInputTypeEnum.hidden,
-      valueType: ModuleIOValueTypeEnum.any,
-      value: [],
-      label: '',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    {
-      key: ModuleInputKeyEnum.httpJsonBody,
-      type: FlowNodeInputTypeEnum.hidden,
-      valueType: ModuleIOValueTypeEnum.any,
-      value: '',
-      label: '',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    Input_Template_DynamicInput,
-    {
-      ...Input_Template_AddInputParam,
-      editField: {
-        key: true,
-        description: true,
-        dataType: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        inputType: FlowNodeInputTypeEnum.target,
-        valueType: ModuleIOValueTypeEnum.string
-      }
-    }
-  ],
-  outputs: [
-    {
-      key: ModuleOutputKeyEnum.httpRawResponse,
-      label: '原始响应',
-      description: 'HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。',
-      valueType: ModuleIOValueTypeEnum.any,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    {
-      ...Output_Template_AddOutput,
-      editField: {
-        key: true,
-        description: true,
-        dataType: true,
-        defaultValue: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        outputType: FlowNodeOutputTypeEnum.source,
-        valueType: ModuleIOValueTypeEnum.string
-      }
-    },
-    Output_Template_Finish
-  ]
-};

packages/global/core/module/template/system/laf.ts

@@ -1,86 +0,0 @@
-import {
-  FlowNodeInputTypeEnum,
-  FlowNodeOutputTypeEnum,
-  FlowNodeTypeEnum
-} from '../../node/constant';
-import { FlowNodeTemplateType } from '../../type';
-import {
-  ModuleIOValueTypeEnum,
-  ModuleInputKeyEnum,
-  ModuleOutputKeyEnum,
-  FlowNodeTemplateTypeEnum
-} from '../../constants';
-import {
-  Input_Template_DynamicInput,
-  Input_Template_Switch,
-  Input_Template_AddInputParam
-} from '../input';
-import { Output_Template_Finish, Output_Template_AddOutput } from '../output';
-
-export const lafModule: FlowNodeTemplateType = {
-  id: FlowNodeTypeEnum.lafModule,
-  templateType: FlowNodeTemplateTypeEnum.externalCall,
-  flowType: FlowNodeTypeEnum.lafModule,
-  avatar: '/imgs/module/laf.png',
-  name: 'Laf 函数调用（测试）',
-  intro: '可以调用Laf账号下的云函数。',
-  showStatus: true,
-  isTool: true,
-  inputs: [
-    Input_Template_Switch,
-    {
-      key: ModuleInputKeyEnum.httpReqUrl,
-      type: FlowNodeInputTypeEnum.hidden,
-      valueType: ModuleIOValueTypeEnum.string,
-      label: '',
-      description: 'core.module.input.description.Http Request Url',
-      placeholder: 'https://api.ai.com/getInventory',
-      required: false,
-      showTargetInApp: false,
-      showTargetInPlugin: false
-    },
-    Input_Template_DynamicInput,
-    {
-      ...Input_Template_AddInputParam,
-      editField: {
-        key: true,
-        description: true,
-        dataType: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        inputType: FlowNodeInputTypeEnum.target,
-        valueType: ModuleIOValueTypeEnum.string
-      }
-    }
-  ],
-  outputs: [
-    {
-      key: ModuleOutputKeyEnum.httpRawResponse,
-      label: '原始响应',
-      description: 'HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。',
-      valueType: ModuleIOValueTypeEnum.any,
-      type: FlowNodeOutputTypeEnum.source,
-      targets: []
-    },
-    {
-      ...Output_Template_AddOutput,
-      editField: {
-        key: true,
-        description: true,
-        dataType: true,
-        defaultValue: true
-      },
-      defaultEditField: {
-        label: '',
-        key: '',
-        description: '',
-        outputType: FlowNodeOutputTypeEnum.source,
-        valueType: ModuleIOValueTypeEnum.string
-      }
-    },
-    Output_Template_Finish
-  ]
-};