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test-tool
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gru/projec
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2
.vscode/settings.json
vendored
2
.vscode/settings.json
vendored
@@ -21,7 +21,7 @@
|
||||
"i18n-ally.namespace": true,
|
||||
"i18n-ally.pathMatcher": "{locale}/{namespaces}.json",
|
||||
"i18n-ally.extract.targetPickingStrategy": "most-similar-by-key",
|
||||
"i18n-ally.translate.engines": ["google"],
|
||||
"i18n-ally.translate.engines": ["deepl","google"],
|
||||
"[typescript]": {
|
||||
"editor.defaultFormatter": "esbenp.prettier-vscode"
|
||||
},
|
||||
|
||||
@@ -132,15 +132,15 @@ services:
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.9 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt-mcp-server:
|
||||
container_name: fastgpt-mcp-server
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3005:3000
|
||||
networks:
|
||||
@@ -150,8 +150,8 @@ services:
|
||||
- FASTGPT_ENDPOINT=http://fastgpt:3000
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@@ -109,15 +109,15 @@ services:
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.9 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt-mcp-server:
|
||||
container_name: fastgpt-mcp-server
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3005:3000
|
||||
networks:
|
||||
@@ -127,8 +127,8 @@ services:
|
||||
- FASTGPT_ENDPOINT=http://fastgpt:3000
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@@ -23,7 +23,7 @@ services:
|
||||
volumes:
|
||||
- ./pg/data:/var/lib/postgresql/data
|
||||
healthcheck:
|
||||
test: ['CMD', 'pg_isready', '-U', 'postgres', '-d', 'aiproxy']
|
||||
test: ['CMD', 'pg_isready', '-U', 'postgres', '-d', 'postgres']
|
||||
interval: 5s
|
||||
timeout: 5s
|
||||
retries: 10
|
||||
@@ -96,15 +96,15 @@ services:
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.9 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt-mcp-server:
|
||||
container_name: fastgpt-mcp-server
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3005:3000
|
||||
networks:
|
||||
@@ -114,8 +114,8 @@ services:
|
||||
- FASTGPT_ENDPOINT=http://fastgpt:3000
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@@ -72,15 +72,15 @@ services:
|
||||
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.9 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt-mcp-server:
|
||||
container_name: fastgpt-mcp-server
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3005:3000
|
||||
networks:
|
||||
@@ -90,8 +90,8 @@ services:
|
||||
- FASTGPT_ENDPOINT=http://fastgpt:3000
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.7-fix2 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.9.9 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.9 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
BIN
docSite/assets/imgs/official_account_faq.png
Normal file
BIN
docSite/assets/imgs/official_account_faq.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 386 KiB |
@@ -959,10 +959,16 @@ curl --location --request POST 'http://localhost:3000/api/core/chat/getHistories
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
目前仅能获取到当前 API key 的创建者的对话。
|
||||
|
||||
- appId - 应用 Id
|
||||
- offset - 偏移量,即从第几条数据开始取
|
||||
- pageSize - 记录数量
|
||||
- source - 对话源。source=api,表示获取通过 API 创建的对话(不会获取到页面上的对话记录)
|
||||
- startCreateTime - 开始创建时间(可选)
|
||||
- endCreateTime - 结束创建时间(可选)
|
||||
- startUpdateTime - 开始更新时间(可选)
|
||||
- endUpdateTime - 结束更新时间(可选)
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
|
||||
34
docSite/content/zh-cn/docs/development/upgrading/4910.md
Normal file
34
docSite/content/zh-cn/docs/development/upgrading/4910.md
Normal file
@@ -0,0 +1,34 @@
|
||||
---
|
||||
title: 'V4.9.10(进行中)'
|
||||
description: 'FastGPT V4.9.10 更新说明'
|
||||
icon: 'upgrade'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 790
|
||||
---
|
||||
|
||||
|
||||
## 🚀 新增内容
|
||||
|
||||
1. 支持 PG 设置`systemEnv.hnswMaxScanTuples`参数,提高迭代搜索的数据总量。
|
||||
2. 工作流调整为单向接入和接出,支持快速的添加下一步节点。
|
||||
3. 开放飞书和语雀知识库到开源版。
|
||||
4. gemini 和 claude 最新模型预设。
|
||||
|
||||
## ⚙️ 优化
|
||||
|
||||
1. LLM stream调用,默认超时调大。
|
||||
2. 部分确认交互优化。
|
||||
3. 纠正原先知识库的“表格数据集”名称,改成“备份导入”。同时支持知识库索引的导出和导入。
|
||||
4. 工作流知识库引用上限,如果工作流中没有相关 AI 节点,则交互模式改成纯手动输入,并且上限为 1000万。
|
||||
5. 语音输入,移动端判断逻辑,准确判断是否为手机,而不是小屏。
|
||||
6. 优化上下文截取算法,至少保证留下一组 Human 信息。
|
||||
|
||||
## 🐛 修复
|
||||
|
||||
1. 全文检索多知识库时排序得分排序不正确。
|
||||
2. 流响应捕获 finish_reason 可能不正确。
|
||||
3. 工具调用模式,未保存思考输出。
|
||||
4. 知识库 indexSize 参数未生效。
|
||||
5. 工作流嵌套 2 层后,获取预览引用、上下文不正确。
|
||||
6. xlsx 转成 Markdown 时候,前面会多出一个空格。
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: 'V4.9.8(进行中)'
|
||||
title: 'V4.9.8'
|
||||
description: 'FastGPT V4.9.8 更新说明'
|
||||
icon: 'upgrade'
|
||||
draft: false
|
||||
@@ -7,6 +7,17 @@ toc: true
|
||||
weight: 792
|
||||
---
|
||||
|
||||
## 升级指南
|
||||
|
||||
### 1. 做好数据备份
|
||||
|
||||
### 2. 更新镜像 tag
|
||||
|
||||
- 更新 FastGPT 镜像 tag: v4.9.8
|
||||
- 更新 FastGPT 商业版镜像 tag: v4.9.8
|
||||
- mcp_server 无需更新
|
||||
- Sandbox 无需更新
|
||||
- AIProxy 无需更新
|
||||
|
||||
## 🚀 新增内容
|
||||
|
||||
@@ -14,14 +25,25 @@ weight: 792
|
||||
2. 将所有内置任务,从非 stream 模式调整成 stream 模式,避免部分模型不支持非 stream 模式。如需覆盖,则可以在模型`额外 Body`参数中,强制指定`stream=false`。
|
||||
3. qwen3 模型预设
|
||||
4. 语雀知识库支持设置根目录。
|
||||
5. 可配置密码过期时间,过期后下次登录会强制要求修改密码。
|
||||
6. 密码登录增加 preLogin 临时密钥校验。
|
||||
7. 支持 Admin 后台配置发布渠道和第三方知识库的显示隐藏。
|
||||
|
||||
## ⚙️ 优化
|
||||
|
||||
1. Chat log list 优化,避免大数据时超出内存限制。
|
||||
2. 预加载 token 计算 worker,避免主任务中并发创建导致线程阻塞。
|
||||
3. 工作流节点版本控制交互优化。
|
||||
4. 网络获取以及 html2md 优化,支持视频和音频标签的转换。
|
||||
|
||||
## 🐛 修复
|
||||
|
||||
1. 应用列表/知识库列表,删除行权限展示问题。
|
||||
2. 打开知识库搜索参数后,重排选项自动被打开。
|
||||
3. LLM json_schema 模式 API 请求格式错误。
|
||||
4. 重新训练时,图片过期索引未成功清除,导致图片会丢失。
|
||||
5. 重新训练权限问题。
|
||||
6. 文档链接地址。
|
||||
7. Claude 工具调用,由于 index 为空,导致工具调用失败。
|
||||
8. 嵌套工作流,工具调用下包含交互节点时,流程异常。
|
||||
|
||||
|
||||
43
docSite/content/zh-cn/docs/development/upgrading/499.md
Normal file
43
docSite/content/zh-cn/docs/development/upgrading/499.md
Normal file
@@ -0,0 +1,43 @@
|
||||
---
|
||||
title: 'V4.9.9'
|
||||
description: 'FastGPT V4.9.9 更新说明'
|
||||
icon: 'upgrade'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 791
|
||||
---
|
||||
|
||||
## 升级指南
|
||||
|
||||
### 1. 做好数据备份
|
||||
|
||||
### 2. 商业版用户替换新 License
|
||||
|
||||
商业版用户可以联系 FastGPT 团队支持同学,获取 License 替换方案。替换后,可以直接升级系统,管理后台会提示输入新 License。
|
||||
|
||||
### 3. 更新镜像 tag
|
||||
|
||||
- 更新 FastGPT 镜像 tag: v4.9.9
|
||||
- 更新 FastGPT 商业版镜像 tag: v4.9.9
|
||||
- mcp_server 无需更新
|
||||
- Sandbox 无需更新
|
||||
- AIProxy 无需更新
|
||||
|
||||
## 🚀 新增内容
|
||||
|
||||
1. 切换 SessionId 来替代 JWT 实现登录鉴权,可控制最大登录客户端数量。
|
||||
2. 新的商业版 License 管理模式。
|
||||
3. 公众号调用,显示记录 chat 对话错误,方便排查。
|
||||
4. API 知识库支持 BasePath 选择,需增加 API 接口,具体可见[API 知识库介绍](/docs/guide/knowledge_base/api_dataset/#4-获取文件详细信息用于获取文件信息)
|
||||
|
||||
## ⚙️ 优化
|
||||
|
||||
1. 优化工具调用,新工具的判断逻辑。
|
||||
2. 调整 Cite 引用提示词。
|
||||
|
||||
## 🐛 修复
|
||||
|
||||
1. 无法正常获取应用历史保存/发布记录。
|
||||
2. 成员创建 MCP 工具权限问题。
|
||||
3. 来源引用展示,存在 ID 传递错误,导致提示无权操作该文件。
|
||||
4. 回答标注前端数据报错。
|
||||
@@ -43,7 +43,7 @@ type ResponseType = {
|
||||
// 文件列表中,单项的文件类型
|
||||
type FileListItem = {
|
||||
id: string;
|
||||
parentId: string | null;
|
||||
parentId: string //也可能为 null 或者 undefined 类型;
|
||||
name: string;
|
||||
type: 'file' | 'folder';
|
||||
updateTime: Date;
|
||||
@@ -59,7 +59,7 @@ type FileListItem = {
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- parentId - 父级 id,可选,或者 null。
|
||||
- parentId - 父级 id,可选,或者 null | undefined。
|
||||
- searchKey - 检索词,可选
|
||||
{{% /alert %}}
|
||||
|
||||
@@ -68,7 +68,7 @@ curl --location --request POST '{{baseURL}}/v1/file/list' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"parentId": null,
|
||||
"parentId": "",
|
||||
"searchKey": ""
|
||||
}'
|
||||
```
|
||||
@@ -185,3 +185,40 @@ curl --location --request GET '{{baseURL}}/v1/file/read?id=xx' \
|
||||
{{< /tabs >}}
|
||||
|
||||
|
||||
### 4. 获取文件详细信息(用于获取文件信息)
|
||||
|
||||
{{< tabs tabTotal="2" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
id 为文件的 id。
|
||||
|
||||
```bash
|
||||
curl --location --request GET '{{baseURL}}/v1/file/detail?id=xx' \
|
||||
--header 'Authorization: Bearer {{authorization}}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"success": true,
|
||||
"message": "",
|
||||
"data": {
|
||||
"id": "docs",
|
||||
"parentId": "",
|
||||
"name": "docs"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
|
||||
|
||||
@@ -28,7 +28,6 @@ FastGPT 商业版是基于 FastGPT 开源版的增强版本,增加了一些独
|
||||
| 应用发布安全配置 | ❌ | ✅ | ✅ |
|
||||
| 内容审核 | ❌ | ✅ | ✅ |
|
||||
| web站点同步 | ❌ | ✅ | ✅ |
|
||||
| 主流文档库接入(目前支持:语雀、飞书) | ❌ | ✅ | ✅ |
|
||||
| 增强训练模式 | ❌ | ✅ | ✅ |
|
||||
| 第三方应用快速接入(飞书、公众号) | ❌ | ✅ | ✅ |
|
||||
| 管理后台 | ❌ | ✅ | 不需要 |
|
||||
|
||||
@@ -95,6 +95,10 @@ weight: 506
|
||||
121.196.228.45
|
||||
121.43.126.202
|
||||
120.26.144.37
|
||||
47.98.196.113
|
||||
47.97.204.90
|
||||
118.31.41.236
|
||||
118.178.185.61
|
||||
```
|
||||
|
||||
## 4. 获取AES Key,选择加密方式
|
||||
@@ -125,6 +129,13 @@ weight: 506
|
||||
|
||||
## FAQ
|
||||
|
||||
### 公众号没响应
|
||||
|
||||
检查应用对话日志,如果有对话日志,但是微信公众号无响应,则是白名单 IP未成功。
|
||||
添加白名单IP 后,通常需要等待几分钟微信更新。可以在对话日志中,找点错误日志。
|
||||
|
||||

|
||||
|
||||
### 如何新开一个聊天记录
|
||||
|
||||
如果你想重置你的聊天记录,可以给机器人发送 `Reset` 消息(注意大小写),机器人会新开一个聊天记录。
|
||||
如果你想重置你的聊天记录,可以给机器人发送 `Reset` 消息(注意大小写),机器人会新开一个聊天记录。
|
||||
|
||||
3
env.d.ts
vendored
3
env.d.ts
vendored
@@ -4,7 +4,6 @@ declare global {
|
||||
LOG_DEPTH: string;
|
||||
DEFAULT_ROOT_PSW: string;
|
||||
DB_MAX_LINK: string;
|
||||
TOKEN_KEY: string;
|
||||
FILE_TOKEN_KEY: string;
|
||||
ROOT_KEY: string;
|
||||
OPENAI_BASE_URL: string;
|
||||
@@ -36,6 +35,8 @@ declare global {
|
||||
SHOW_COUPON?: string;
|
||||
CONFIG_JSON_PATH?: string;
|
||||
PASSWORD_LOGIN_LOCK_SECONDS?: string;
|
||||
PASSWORD_EXPIRED_MONTH?: string;
|
||||
MAX_LOGIN_SESSION?: string;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -27,7 +27,7 @@ const datasetErr = [
|
||||
},
|
||||
{
|
||||
statusText: DatasetErrEnum.unExist,
|
||||
message: 'core.dataset.error.unExistDataset'
|
||||
message: i18nT('common:core.dataset.error.unExistDataset')
|
||||
},
|
||||
{
|
||||
statusText: DatasetErrEnum.unExistCollection,
|
||||
|
||||
@@ -2,13 +2,28 @@ import { type ErrType } from '../errorCode';
|
||||
import { i18nT } from '../../../../web/i18n/utils';
|
||||
/* dataset: 509000 */
|
||||
export enum SystemErrEnum {
|
||||
communityVersionNumLimit = 'communityVersionNumLimit'
|
||||
communityVersionNumLimit = 'communityVersionNumLimit',
|
||||
licenseAppAmountLimit = 'licenseAppAmountLimit',
|
||||
licenseDatasetAmountLimit = 'licenseDatasetAmountLimit',
|
||||
licenseUserAmountLimit = 'licenseUserAmountLimit'
|
||||
}
|
||||
|
||||
const systemErr = [
|
||||
{
|
||||
statusText: SystemErrEnum.communityVersionNumLimit,
|
||||
message: i18nT('common:code_error.system_error.community_version_num_limit')
|
||||
},
|
||||
{
|
||||
statusText: SystemErrEnum.licenseAppAmountLimit,
|
||||
message: i18nT('common:code_error.system_error.license_app_amount_limit')
|
||||
},
|
||||
{
|
||||
statusText: SystemErrEnum.licenseDatasetAmountLimit,
|
||||
message: i18nT('common:code_error.system_error.license_dataset_amount_limit')
|
||||
},
|
||||
{
|
||||
statusText: SystemErrEnum.licenseUserAmountLimit,
|
||||
message: i18nT('common:code_error.system_error.license_user_amount_limit')
|
||||
}
|
||||
];
|
||||
|
||||
|
||||
@@ -5,7 +5,7 @@ export const checkPasswordRule = (password: string) => {
|
||||
/[A-Z]/, // Contains uppercase letters
|
||||
/[!@#$%^&*()_+=-]/ // Contains special characters
|
||||
];
|
||||
const validChars = /^[\dA-Za-z!@#$%^&*()_+=-]{6,100}$/;
|
||||
const validChars = /^[\dA-Za-z!@#$%^&*()_+=-]{8,100}$/;
|
||||
|
||||
// Check length and valid characters
|
||||
if (!validChars.test(password)) return false;
|
||||
|
||||
@@ -1,7 +1,8 @@
|
||||
export enum SystemConfigsTypeEnum {
|
||||
fastgpt = 'fastgpt',
|
||||
fastgptPro = 'fastgptPro',
|
||||
systemMsgModal = 'systemMsgModal'
|
||||
systemMsgModal = 'systemMsgModal',
|
||||
license = 'license'
|
||||
}
|
||||
|
||||
export const SystemConfigsTypeMap = {
|
||||
@@ -13,5 +14,8 @@ export const SystemConfigsTypeMap = {
|
||||
},
|
||||
[SystemConfigsTypeEnum.systemMsgModal]: {
|
||||
label: 'systemMsgModal'
|
||||
},
|
||||
[SystemConfigsTypeEnum.license]: {
|
||||
label: 'license'
|
||||
}
|
||||
};
|
||||
|
||||
31
packages/global/common/system/types/index.d.ts
vendored
31
packages/global/common/system/types/index.d.ts
vendored
@@ -64,6 +64,15 @@ export type FastGPTFeConfigsType = {
|
||||
show_coupon?: boolean;
|
||||
concatMd?: string;
|
||||
|
||||
show_dataset_feishu?: boolean;
|
||||
show_dataset_yuque?: boolean;
|
||||
show_publish_feishu?: boolean;
|
||||
show_publish_dingtalk?: boolean;
|
||||
show_publish_offiaccount?: boolean;
|
||||
|
||||
show_dataset_enhance?: boolean;
|
||||
show_batch_eval?: boolean;
|
||||
|
||||
concatMd?: string;
|
||||
docUrl?: string;
|
||||
openAPIDocUrl?: string;
|
||||
@@ -121,9 +130,11 @@ export type SystemEnvType = {
|
||||
vectorMaxProcess: number;
|
||||
qaMaxProcess: number;
|
||||
vlmMaxProcess: number;
|
||||
hnswEfSearch: number;
|
||||
tokenWorkers: number; // token count max worker
|
||||
|
||||
hnswEfSearch: number;
|
||||
hnswMaxScanTuples: number;
|
||||
|
||||
oneapiUrl?: string;
|
||||
chatApiKey?: string;
|
||||
|
||||
@@ -136,3 +147,21 @@ export type customPdfParseType = {
|
||||
doc2xKey?: string;
|
||||
price?: number;
|
||||
};
|
||||
|
||||
export type LicenseDataType = {
|
||||
startTime: string;
|
||||
expiredTime: string;
|
||||
company: string;
|
||||
description?: string; // 描述
|
||||
hosts?: string[]; // 管理端有效域名
|
||||
maxUsers?: number; // 最大用户数,不填默认不上限
|
||||
maxApps?: number; // 最大应用数,不填默认不上限
|
||||
maxDatasets?: number; // 最大数据集数,不填默认不上限
|
||||
functions: {
|
||||
sso: boolean;
|
||||
pay: boolean;
|
||||
customTemplates: boolean;
|
||||
datasetEnhance: boolean;
|
||||
batchEval: boolean;
|
||||
};
|
||||
};
|
||||
|
||||
@@ -2,6 +2,248 @@ import { type PromptTemplateItem } from '../type.d';
|
||||
import { i18nT } from '../../../../web/i18n/utils';
|
||||
import { getPromptByVersion } from './utils';
|
||||
|
||||
export const Prompt_userQuotePromptList: PromptTemplateItem[] = [
|
||||
{
|
||||
title: i18nT('app:template.standard_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
你是一个知识库回答助手,可以使用 <Cites></Cites> 中的内容作为你本次回答的参考。
|
||||
同时,为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记,标识参考了哪些内容。
|
||||
|
||||
## 追溯展示规则
|
||||
|
||||
- 使用 [id](CITE) 的格式来引用 <Cites></Cites> 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在 **每段话结尾** 自然地整合引用。例如: "Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)。"。
|
||||
- 每段话**至少包含一个引用**,多个引用时按顺序排列,例如:"Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)[67e517e74767063e882d6862](CITE)。\n 它的特点是非常轻量[67e517e74767063e882d6863](CITE)。"
|
||||
- 不要把示例作为知识点。
|
||||
- 不要伪造 id,返回的 id 必须都存在 <Cites></Cites> 中!
|
||||
|
||||
## 通用规则
|
||||
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Cites></Cites> 获取的知识。
|
||||
- 保持答案与 <Cites></Cites> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。尤其是图片、表格、序列号等内容,需严格完整输出。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
<Cites>
|
||||
{{quote}}
|
||||
</Cites>
|
||||
|
||||
## 用户问题
|
||||
|
||||
{{question}}
|
||||
|
||||
## 回答
|
||||
`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.qa_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
作为一个问答助手,你会使用 <QA></QA> 标记中的提供的数据对进行内容回答。
|
||||
|
||||
## 回答要求
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <Answer></Answer> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 <QA></QA> 获取的知识,只需要回复答案。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
## 用户问题
|
||||
|
||||
{{question}}
|
||||
|
||||
## 回答
|
||||
`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.standard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
你是一个知识库回答助手,可以使用 <Cites></Cites> 中的内容作为你本次回答的参考。
|
||||
同时,为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记,标识参考了哪些内容。
|
||||
|
||||
## 追溯展示规则
|
||||
|
||||
- 使用 [id](CITE) 的格式来引用 <Cites></Cites> 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在 **每段话结尾** 自然地整合引用。例如: "Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)。"。
|
||||
- 每段话**至少包含一个引用**,多个引用时按顺序排列,例如:"Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)[67e517e74767063e882d6862](CITE)。\n 它的特点是非常轻量[67e517e74767063e882d6863](CITE)。"
|
||||
- 不要把示例作为知识点。
|
||||
- 不要伪造 id,返回的 id 必须都存在 <Cites></Cites> 中!
|
||||
|
||||
## 通用规则
|
||||
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Cites></Cites> 获取的知识。
|
||||
- 保持答案与 <Cites></Cites> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。尤其是图片、表格、序列号等内容,需严格完整输出。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
## 严格要求
|
||||
|
||||
你只能使用 <Cites></Cites> 标记中的内容作为参考,不能使用自身的知识,并且回答的内容需严格与 <Cites></Cites> 中的内容一致。
|
||||
|
||||
<Cites>
|
||||
{{quote}}
|
||||
</Cites>
|
||||
|
||||
## 用户问题
|
||||
|
||||
{{question}}
|
||||
|
||||
## 回答
|
||||
`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.hard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
作为一个问答助手,你会使用 <QA></QA> 标记中的提供的数据对进行内容回答。
|
||||
|
||||
## 回答要求
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <Answer></Answer> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 <QA></QA> 获取的知识,只需要回复答案。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
## 严格要求
|
||||
|
||||
你只能使用 <QA></QA> 标记中的内容作为参考,不能使用自身的知识,并且回答的内容需严格与 <QA></QA> 中的内容一致。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
## 用户问题
|
||||
|
||||
{{question}}
|
||||
|
||||
## 回答
|
||||
`
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
export const Prompt_systemQuotePromptList: PromptTemplateItem[] = [
|
||||
{
|
||||
title: i18nT('app:template.standard_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
你是一个知识库回答助手,可以使用 <Cites></Cites> 中的内容作为你本次回答的参考。
|
||||
同时,为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记,标识参考了哪些内容。
|
||||
|
||||
## 追溯展示规则
|
||||
|
||||
- 使用 [id](CITE) 的格式来引用 <Cites></Cites> 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在 **每段话结尾** 自然地整合引用。例如: "Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)。"。
|
||||
- 每段话**至少包含一个引用**,多个引用时按顺序排列,例如:"Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)[67e517e74767063e882d6862](CITE)。\n 它的特点是非常轻量[67e517e74767063e882d6863](CITE)。"
|
||||
- 不要把示例作为知识点。
|
||||
- 不要伪造 id,返回的 id 必须都存在 <Cites></Cites> 中!
|
||||
|
||||
## 通用规则
|
||||
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Cites></Cites> 获取的知识。
|
||||
- 保持答案与 <Cites></Cites> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。尤其是图片、表格、序列号等内容,需严格完整输出。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
<Cites>
|
||||
{{quote}}
|
||||
</Cites>`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.qa_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.8']: `## 任务描述
|
||||
作为一个问答助手,你会使用 <QA></QA> 标记中的提供的数据对进行内容回答。
|
||||
|
||||
## 回答要求
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <Answer></Answer> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 <QA></QA> 获取的知识,只需要回复答案。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.standard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
你是一个知识库回答助手,可以使用 <Cites></Cites> 中的内容作为你本次回答的参考。
|
||||
同时,为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记,标识参考了哪些内容。
|
||||
|
||||
## 追溯展示规则
|
||||
|
||||
- 使用 [id](CITE) 的格式来引用 <Cites></Cites> 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在 **每段话结尾** 自然地整合引用。例如: "Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)。"。
|
||||
- 每段话**至少包含一个引用**,多个引用时按顺序排列,例如:"Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)[67e517e74767063e882d6862](CITE)。\n 它的特点是非常轻量[67e517e74767063e882d6863](CITE)。"
|
||||
- 不要把示例作为知识点。
|
||||
- 不要伪造 id,返回的 id 必须都存在 <Cites></Cites> 中!
|
||||
|
||||
## 通用规则
|
||||
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Cites></Cites> 获取的知识。
|
||||
- 保持答案与 <Cites></Cites> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。尤其是图片、表格、序列号等内容,需严格完整输出。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
## 严格要求
|
||||
|
||||
你只能使用 <Cites></Cites> 标记中的内容作为参考,不能使用自身的知识,并且回答的内容需严格与 <Cites></Cites> 中的内容一致。
|
||||
|
||||
<Cites>
|
||||
{{quote}}
|
||||
</Cites>`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.hard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `## 任务描述
|
||||
作为一个问答助手,你会使用 <QA></QA> 标记中的提供的数据对进行内容回答。
|
||||
|
||||
## 回答要求
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <Answer></Answer> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 <QA></QA> 获取的知识,只需要回复答案。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
## 严格要求
|
||||
|
||||
你只能使用 <QA></QA> 标记中的内容作为参考,不能使用自身的知识,并且回答的内容需严格与 <QA></QA> 中的内容一致。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>`
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
{
|
||||
title: i18nT('app:template.standard_template'),
|
||||
@@ -10,11 +252,6 @@ export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
['4.9.7']: `{
|
||||
"id": "{{id}}",
|
||||
"sourceName": "{{source}}",
|
||||
"content": "{{q}}\n{{a}}"
|
||||
}
|
||||
`,
|
||||
['4.9.2']: `{
|
||||
"sourceName": "{{source}}",
|
||||
"updateTime": "{{updateTime}}",
|
||||
"content": "{{q}}\n{{a}}"
|
||||
}
|
||||
@@ -25,7 +262,7 @@ export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
title: i18nT('app:template.qa_template'),
|
||||
desc: i18nT('app:template.qa_template_des'),
|
||||
value: {
|
||||
['4.9.2']: `<Question>
|
||||
['4.9.7']: `<Question>
|
||||
{{q}}
|
||||
</Question>
|
||||
<Answer>
|
||||
@@ -40,11 +277,6 @@ export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
['4.9.7']: `{
|
||||
"id": "{{id}}",
|
||||
"sourceName": "{{source}}",
|
||||
"content": "{{q}}\n{{a}}"
|
||||
}
|
||||
`,
|
||||
['4.9.2']: `{
|
||||
"sourceName": "{{source}}",
|
||||
"updateTime": "{{updateTime}}",
|
||||
"content": "{{q}}\n{{a}}"
|
||||
}
|
||||
@@ -55,7 +287,7 @@ export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
title: i18nT('app:template.hard_strict'),
|
||||
desc: i18nT('app:template.hard_strict_des'),
|
||||
value: {
|
||||
['4.9.2']: `<Question>
|
||||
['4.9.7']: `<Question>
|
||||
{{q}}
|
||||
</Question>
|
||||
<Answer>
|
||||
@@ -64,263 +296,12 @@ export const Prompt_QuoteTemplateList: PromptTemplateItem[] = [
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
export const getQuoteTemplate = (version?: string) => {
|
||||
const defaultTemplate = Prompt_QuoteTemplateList[0].value;
|
||||
|
||||
return getPromptByVersion(version, defaultTemplate);
|
||||
};
|
||||
|
||||
export const Prompt_userQuotePromptList: PromptTemplateItem[] = [
|
||||
{
|
||||
title: i18nT('app:template.standard_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
回答要求:
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
- 使用 [id](CITE) 格式来引用<Reference></Reference>中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在每段结尾自然地整合引用。例如: "FastGPT 是一个基于大语言模型(LLM)的知识库问答系统[67e517e74767063e882d6861](CITE)。"
|
||||
- 每段至少包含一个引用,也可根据内容需要加入多个引用,按顺序排列。`,
|
||||
['4.9.2']: `使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
回答要求:
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
问题:"""{{question}}"""`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.qa_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.2']: `使用 <QA></QA> 标记中的问答对进行回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
回答要求:
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <答案></答案> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 QA 获取的知识,只需要回复答案。
|
||||
|
||||
问题:"""{{question}}"""`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.standard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `忘记你已有的知识,仅使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <Reference></Reference> 标记中的内容有关。
|
||||
2. 如果有关,你按下面的要求回答。
|
||||
3. 如果无关,你直接拒绝回答本次问题。
|
||||
|
||||
回答要求:
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
- 使用 [id](CITE) 格式来引用<Reference></Reference>中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在每段结尾自然地整合引用。例如: "FastGPT 是一个基于大语言模型(LLM)的知识库问答系统[67e517e74767063e882d6861](CITE)。"
|
||||
- 每段至少包含一个引用,也可根据内容需要加入多个引用,按顺序排列。
|
||||
|
||||
问题:"""{{question}}"""`,
|
||||
['4.9.2']: `忘记你已有的知识,仅使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <Reference></Reference> 标记中的内容有关。
|
||||
2. 如果有关,你按下面的要求回答。
|
||||
3. 如果无关,你直接拒绝回答本次问题。
|
||||
|
||||
回答要求:
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
问题:"""{{question}}"""`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.hard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.2']: `忘记你已有的知识,仅使用 <QA></QA> 标记中的问答对进行回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <QA></QA> 标记中的内容有关。
|
||||
2. 如果无关,你直接拒绝回答本次问题。
|
||||
3. 判断是否有相近或相同的问题。
|
||||
4. 如果有相同的问题,直接输出对应答案。
|
||||
5. 如果只有相近的问题,请把相近的问题和答案一起输出。
|
||||
|
||||
回答要求:
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 回答的内容应尽可能与 <QA></QA> 标记中的内容一致。
|
||||
- 避免提及你是从 QA 获取的知识,只需要回复答案。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
|
||||
问题:"""{{question}}"""`
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
export const Prompt_systemQuotePromptList: PromptTemplateItem[] = [
|
||||
{
|
||||
title: i18nT('app:template.standard_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
回答要求:
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
- 使用 [id](CITE) 格式来引用<Reference></Reference>中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在每段结尾自然地整合引用。例如: "FastGPT 是一个基于大语言模型(LLM)的知识库问答系统[67e517e74767063e882d6861](CITE)。"
|
||||
- 每段至少包含一个引用,也可根据内容需要加入多个引用,按顺序排列。`,
|
||||
['4.9.2']: `使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
回答要求:
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.qa_template'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.2']: `使用 <QA></QA> 标记中的问答对进行回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
回答要求:
|
||||
- 选择其中一个或多个问答对进行回答。
|
||||
- 回答的内容应尽可能与 <答案></答案> 中的内容一致。
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 避免提及你是从 QA 获取的知识,只需要回复答案。`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.standard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.7']: `忘记你已有的知识,仅使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <Reference></Reference> 标记中的内容有关。
|
||||
2. 如果有关,你按下面的要求回答。
|
||||
3. 如果无关,你直接拒绝回答本次问题。
|
||||
|
||||
回答要求:
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。
|
||||
- 使用 [id](CITE) 格式来引用<Reference></Reference>中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在每段结尾自然地整合引用。例如: "FastGPT 是一个基于大语言模型(LLM)的知识库问答系统[67e517e74767063e882d6861](CITE)。"
|
||||
- 每段至少包含一个引用,也可根据内容需要加入多个引用,按顺序排列。
|
||||
|
||||
问题:"""{{question}}"""`,
|
||||
['4.9.2']: `忘记你已有的知识,仅使用 <Reference></Reference> 标记中的内容作为本次对话的参考:
|
||||
|
||||
<Reference>
|
||||
{{quote}}
|
||||
</Reference>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <Reference></Reference> 标记中的内容有关。
|
||||
2. 如果有关,你按下面的要求回答。
|
||||
3. 如果无关,你直接拒绝回答本次问题。
|
||||
|
||||
回答要求:
|
||||
- 避免提及你是从 <Reference></Reference> 获取的知识。
|
||||
- 保持答案与 <Reference></Reference> 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。`
|
||||
}
|
||||
},
|
||||
{
|
||||
title: i18nT('app:template.hard_strict'),
|
||||
desc: '',
|
||||
value: {
|
||||
['4.9.2']: `忘记你已有的知识,仅使用 <QA></QA> 标记中的问答对进行回答。
|
||||
|
||||
<QA>
|
||||
{{quote}}
|
||||
</QA>
|
||||
|
||||
思考流程:
|
||||
1. 判断问题是否与 <QA></QA> 标记中的内容有关。
|
||||
2. 如果无关,你直接拒绝回答本次问题。
|
||||
3. 判断是否有相近或相同的问题。
|
||||
4. 如果有相同的问题,直接输出对应答案。
|
||||
5. 如果只有相近的问题,请把相近的问题和答案一起输出。
|
||||
|
||||
回答要求:
|
||||
- 如果没有相关的问答对,你需要澄清。
|
||||
- 回答的内容应尽可能与 <QA></QA> 标记中的内容一致。
|
||||
- 避免提及你是从 QA 获取的知识,只需要回复答案。
|
||||
- 使用 Markdown 语法优化回答格式。
|
||||
- 使用与问题相同的语言回答。`
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
export const getQuotePrompt = (version?: string, role: 'user' | 'system' = 'user') => {
|
||||
const quotePromptTemplates =
|
||||
role === 'user' ? Prompt_userQuotePromptList : Prompt_systemQuotePromptList;
|
||||
@@ -331,9 +312,9 @@ export const getQuotePrompt = (version?: string, role: 'user' | 'system' = 'user
|
||||
};
|
||||
|
||||
// Document quote prompt
|
||||
export const getDocumentQuotePrompt = (version: string) => {
|
||||
export const getDocumentQuotePrompt = (version?: string) => {
|
||||
const promptMap = {
|
||||
['4.9.2']: `将 <FilesContent></FilesContent> 中的内容作为本次对话的参考:
|
||||
['4.9.7']: `将 <FilesContent></FilesContent> 中的内容作为本次对话的参考:
|
||||
<FilesContent>
|
||||
{{quote}}
|
||||
</FilesContent>
|
||||
|
||||
@@ -1,14 +1,19 @@
|
||||
export const getDatasetSearchToolResponsePrompt = () => {
|
||||
return `## Role
|
||||
你是一个知识库回答助手,可以 "quotes" 中的内容作为本次对话的参考。为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记。
|
||||
你是一个知识库回答助手,可以 "cites" 中的内容作为本次对话的参考。为了使回答结果更加可信并且可追溯,你需要在每段话结尾添加引用标记,标识参考了哪些内容。
|
||||
|
||||
## Rules
|
||||
## 追溯展示规则
|
||||
|
||||
- 使用 **[id](CITE)** 格式来引用 "cites" 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在 **每段话结尾** 自然地整合引用。例如: "Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)。"。
|
||||
- 每段话**至少包含一个引用**,多个引用时按顺序排列,例如:"Nginx是一款轻量级的Web服务器、反向代理服务器[67e517e74767063e882d6861](CITE)[67e517e74767063e882d6862](CITE)。\n 它的特点是非常轻量[67e517e74767063e882d6863](CITE)。"
|
||||
- 不要把示例作为知识点。
|
||||
- 不要伪造 id,返回的 id 必须都存在 cites 中!
|
||||
|
||||
## 通用规则
|
||||
- 如果你不清楚答案,你需要澄清。
|
||||
- 避免提及你是从 "quotes" 获取的知识。
|
||||
- 保持答案与 "quotes" 中描述的一致。
|
||||
- 避免提及你是从 "cites" 获取的知识。
|
||||
- 保持答案与 "cites" 中描述的一致。
|
||||
- 使用 Markdown 语法优化回答格式。尤其是图片、表格、序列号等内容,需严格完整输出。
|
||||
- 使用与问题相同的语言回答。
|
||||
- 使用 [id](CITE) 格式来引用 "quotes" 中的知识,其中 CITE 是固定常量, id 为引文中的 id。
|
||||
- 在每段话结尾自然地整合引用。例如: "FastGPT 是一个基于大语言模型(LLM)的知识库问答系统[67e517e74767063e882d6861](CITE)。"
|
||||
- 每段话至少包含一个引用,也可根据内容需要加入多个引用,按顺序排列。`;
|
||||
- 使用与问题相同的语言回答。`;
|
||||
};
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
export const getPromptByVersion = (version?: string, promptMap: Record<string, string> = {}) => {
|
||||
// 版本号大的在前面
|
||||
const versions = Object.keys(promptMap).sort((a, b) => {
|
||||
const [majorA, minorA, patchA] = a.split('.').map(Number);
|
||||
const [majorB, minorB, patchB] = b.split('.').map(Number);
|
||||
@@ -15,5 +16,5 @@ export const getPromptByVersion = (version?: string, promptMap: Record<string, s
|
||||
if (version in promptMap) {
|
||||
return promptMap[version];
|
||||
}
|
||||
return promptMap[versions[versions.length - 1]];
|
||||
return promptMap[versions[0]];
|
||||
};
|
||||
|
||||
@@ -60,5 +60,3 @@ export enum AppTemplateTypeEnum {
|
||||
// special type
|
||||
contribute = 'contribute'
|
||||
}
|
||||
|
||||
export const defaultDatasetMaxTokens = 16000;
|
||||
|
||||
@@ -5,7 +5,7 @@ import {
|
||||
FlowNodeTypeEnum
|
||||
} from '../../workflow/node/constant';
|
||||
import { nanoid } from 'nanoid';
|
||||
import { type ToolType } from '../type';
|
||||
import { type McpToolConfigType } from '../type';
|
||||
import { i18nT } from '../../../../web/i18n/utils';
|
||||
import { type RuntimeNodeItemType } from '../../workflow/runtime/type';
|
||||
|
||||
@@ -16,7 +16,7 @@ export const getMCPToolSetRuntimeNode = ({
|
||||
avatar
|
||||
}: {
|
||||
url: string;
|
||||
toolList: ToolType[];
|
||||
toolList: McpToolConfigType[];
|
||||
name?: string;
|
||||
avatar?: string;
|
||||
}): RuntimeNodeItemType => {
|
||||
@@ -45,7 +45,7 @@ export const getMCPToolRuntimeNode = ({
|
||||
url,
|
||||
avatar = 'core/app/type/mcpToolsFill'
|
||||
}: {
|
||||
tool: ToolType;
|
||||
tool: McpToolConfigType;
|
||||
url: string;
|
||||
avatar?: string;
|
||||
}): RuntimeNodeItemType => {
|
||||
@@ -65,7 +65,7 @@ export const getMCPToolRuntimeNode = ({
|
||||
...Object.entries(tool.inputSchema?.properties || {}).map(([key, value]) => ({
|
||||
key,
|
||||
label: key,
|
||||
valueType: value.type as WorkflowIOValueTypeEnum,
|
||||
valueType: value.type as WorkflowIOValueTypeEnum, // TODO: 这里需要做一个映射
|
||||
description: value.description,
|
||||
toolDescription: value.description || key,
|
||||
required: tool.inputSchema?.required?.includes(key) || false,
|
||||
|
||||
20
packages/global/core/app/type.d.ts
vendored
20
packages/global/core/app/type.d.ts
vendored
@@ -16,16 +16,6 @@ import { FlowNodeInputTypeEnum } from '../../core/workflow/node/constant';
|
||||
import type { WorkflowTemplateBasicType } from '@fastgpt/global/core/workflow/type';
|
||||
import type { SourceMemberType } from '../../support/user/type';
|
||||
|
||||
export type ToolType = {
|
||||
name: string;
|
||||
description: string;
|
||||
inputSchema: {
|
||||
type: string;
|
||||
properties?: Record<string, { type: string; description?: string }>;
|
||||
required?: string[];
|
||||
};
|
||||
};
|
||||
|
||||
export type AppSchema = {
|
||||
_id: string;
|
||||
parentId?: ParentIdType;
|
||||
@@ -117,6 +107,16 @@ export type AppSimpleEditFormType = {
|
||||
chatConfig: AppChatConfigType;
|
||||
};
|
||||
|
||||
export type McpToolConfigType = {
|
||||
name: string;
|
||||
description: string;
|
||||
inputSchema: {
|
||||
type: string;
|
||||
properties?: Record<string, { type: string; description?: string }>;
|
||||
required?: string[];
|
||||
};
|
||||
};
|
||||
|
||||
/* app chat config type */
|
||||
export type AppChatConfigType = {
|
||||
welcomeText?: string;
|
||||
|
||||
@@ -9,6 +9,7 @@ import { type WorkflowTemplateBasicType } from '../workflow/type';
|
||||
import { AppTypeEnum } from './constants';
|
||||
import { AppErrEnum } from '../../common/error/code/app';
|
||||
import { PluginErrEnum } from '../../common/error/code/plugin';
|
||||
import { i18nT } from '../../../web/i18n/utils';
|
||||
|
||||
export const getDefaultAppForm = (): AppSimpleEditFormType => {
|
||||
return {
|
||||
@@ -189,7 +190,7 @@ export const getAppType = (config?: WorkflowTemplateBasicType | AppSimpleEditFor
|
||||
return '';
|
||||
};
|
||||
|
||||
export const checkAppUnExistError = (error?: string) => {
|
||||
export const formatToolError = (error?: string) => {
|
||||
const unExistError: Array<string> = [
|
||||
AppErrEnum.unAuthApp,
|
||||
AppErrEnum.unExist,
|
||||
@@ -197,9 +198,9 @@ export const checkAppUnExistError = (error?: string) => {
|
||||
PluginErrEnum.unExist
|
||||
];
|
||||
|
||||
if (!!error && unExistError.includes(error)) {
|
||||
return error;
|
||||
if (error && unExistError.includes(error)) {
|
||||
return i18nT('app:un_auth');
|
||||
} else {
|
||||
return undefined;
|
||||
return error;
|
||||
}
|
||||
};
|
||||
|
||||
3
packages/global/core/chat/type.d.ts
vendored
3
packages/global/core/chat/type.d.ts
vendored
@@ -26,6 +26,7 @@ export type ChatSchema = {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
appId: string;
|
||||
createTime: Date;
|
||||
updateTime: Date;
|
||||
title: string;
|
||||
customTitle: string;
|
||||
@@ -112,6 +113,7 @@ export type ChatItemSchema = (UserChatItemType | SystemChatItemType | AIChatItem
|
||||
appId: string;
|
||||
time: Date;
|
||||
durationSeconds?: number;
|
||||
errorMsg?: string;
|
||||
};
|
||||
|
||||
export type AdminFbkType = {
|
||||
@@ -143,6 +145,7 @@ export type ChatSiteItemType = (UserChatItemType | SystemChatItemType | AIChatIt
|
||||
responseData?: ChatHistoryItemResType[];
|
||||
time?: Date;
|
||||
durationSeconds?: number;
|
||||
errorMsg?: string;
|
||||
} & ChatBoxInputType &
|
||||
ResponseTagItemType;
|
||||
|
||||
|
||||
31
packages/global/core/dataset/api.d.ts
vendored
31
packages/global/core/dataset/api.d.ts
vendored
@@ -1,9 +1,11 @@
|
||||
import type { DatasetDataIndexItemType, DatasetSchemaType } from './type';
|
||||
import type { ChunkSettingsType, DatasetDataIndexItemType, DatasetSchemaType } from './type';
|
||||
import type {
|
||||
DatasetCollectionTypeEnum,
|
||||
DatasetCollectionDataProcessModeEnum,
|
||||
ChunkSettingModeEnum,
|
||||
DataChunkSplitModeEnum
|
||||
DataChunkSplitModeEnum,
|
||||
ChunkTriggerConfigTypeEnum,
|
||||
ParagraphChunkAIModeEnum
|
||||
} from './constants';
|
||||
import type { LLMModelItemType } from '../ai/model.d';
|
||||
import type { ParentIdType } from 'common/parentFolder/type';
|
||||
@@ -32,26 +34,16 @@ export type DatasetUpdateBody = {
|
||||
};
|
||||
|
||||
/* ================= collection ===================== */
|
||||
export type DatasetCollectionChunkMetadataType = {
|
||||
// Input + store params
|
||||
type DatasetCollectionStoreDataType = ChunkSettingsType & {
|
||||
parentId?: string;
|
||||
customPdfParse?: boolean;
|
||||
trainingType?: DatasetCollectionDataProcessModeEnum;
|
||||
imageIndex?: boolean;
|
||||
autoIndexes?: boolean;
|
||||
|
||||
chunkSettingMode?: ChunkSettingModeEnum;
|
||||
chunkSplitMode?: DataChunkSplitModeEnum;
|
||||
|
||||
chunkSize?: number;
|
||||
indexSize?: number;
|
||||
|
||||
chunkSplitter?: string;
|
||||
qaPrompt?: string;
|
||||
metadata?: Record<string, any>;
|
||||
|
||||
customPdfParse?: boolean;
|
||||
};
|
||||
|
||||
// create collection params
|
||||
export type CreateDatasetCollectionParams = DatasetCollectionChunkMetadataType & {
|
||||
export type CreateDatasetCollectionParams = DatasetCollectionStoreDataType & {
|
||||
datasetId: string;
|
||||
name: string;
|
||||
type: DatasetCollectionTypeEnum;
|
||||
@@ -72,7 +64,7 @@ export type CreateDatasetCollectionParams = DatasetCollectionChunkMetadataType &
|
||||
nextSyncTime?: Date;
|
||||
};
|
||||
|
||||
export type ApiCreateDatasetCollectionParams = DatasetCollectionChunkMetadataType & {
|
||||
export type ApiCreateDatasetCollectionParams = DatasetCollectionStoreDataType & {
|
||||
datasetId: string;
|
||||
tags?: string[];
|
||||
};
|
||||
@@ -90,7 +82,7 @@ export type ApiDatasetCreateDatasetCollectionParams = ApiCreateDatasetCollection
|
||||
export type FileIdCreateDatasetCollectionParams = ApiCreateDatasetCollectionParams & {
|
||||
fileId: string;
|
||||
};
|
||||
export type reTrainingDatasetFileCollectionParams = DatasetCollectionChunkMetadataType & {
|
||||
export type reTrainingDatasetFileCollectionParams = DatasetCollectionStoreDataType & {
|
||||
datasetId: string;
|
||||
collectionId: string;
|
||||
};
|
||||
@@ -147,6 +139,7 @@ export type PushDatasetDataProps = {
|
||||
collectionId: string;
|
||||
data: PushDatasetDataChunkProps[];
|
||||
trainingType?: DatasetCollectionDataProcessModeEnum;
|
||||
indexSize?: number;
|
||||
autoIndexes?: boolean;
|
||||
imageIndex?: boolean;
|
||||
prompt?: string;
|
||||
|
||||
@@ -120,6 +120,8 @@ export const DatasetCollectionSyncResultMap = {
|
||||
export enum DatasetCollectionDataProcessModeEnum {
|
||||
chunk = 'chunk',
|
||||
qa = 'qa',
|
||||
backup = 'backup',
|
||||
|
||||
auto = 'auto' // abandon
|
||||
}
|
||||
export const DatasetCollectionDataProcessModeMap = {
|
||||
@@ -131,21 +133,35 @@ export const DatasetCollectionDataProcessModeMap = {
|
||||
label: i18nT('common:core.dataset.training.QA mode'),
|
||||
tooltip: i18nT('common:core.dataset.import.QA Import Tip')
|
||||
},
|
||||
[DatasetCollectionDataProcessModeEnum.backup]: {
|
||||
label: i18nT('dataset:backup_mode'),
|
||||
tooltip: i18nT('dataset:backup_mode')
|
||||
},
|
||||
[DatasetCollectionDataProcessModeEnum.auto]: {
|
||||
label: i18nT('common:core.dataset.training.Auto mode'),
|
||||
tooltip: i18nT('common:core.dataset.training.Auto mode Tip')
|
||||
}
|
||||
};
|
||||
|
||||
export enum ChunkTriggerConfigTypeEnum {
|
||||
minSize = 'minSize',
|
||||
forceChunk = 'forceChunk',
|
||||
maxSize = 'maxSize'
|
||||
}
|
||||
export enum ChunkSettingModeEnum {
|
||||
auto = 'auto',
|
||||
custom = 'custom'
|
||||
}
|
||||
|
||||
export enum DataChunkSplitModeEnum {
|
||||
paragraph = 'paragraph',
|
||||
size = 'size',
|
||||
char = 'char'
|
||||
}
|
||||
export enum ParagraphChunkAIModeEnum {
|
||||
auto = 'auto',
|
||||
force = 'force'
|
||||
}
|
||||
|
||||
/* ------------ data -------------- */
|
||||
|
||||
@@ -154,7 +170,6 @@ export enum ImportDataSourceEnum {
|
||||
fileLocal = 'fileLocal',
|
||||
fileLink = 'fileLink',
|
||||
fileCustom = 'fileCustom',
|
||||
csvTable = 'csvTable',
|
||||
externalFile = 'externalFile',
|
||||
apiDataset = 'apiDataset',
|
||||
reTraining = 'reTraining'
|
||||
|
||||
@@ -32,7 +32,7 @@ export const DatasetDataIndexMap: Record<
|
||||
color: 'red'
|
||||
},
|
||||
[DatasetDataIndexTypeEnum.image]: {
|
||||
label: i18nT('common:data_index_image'),
|
||||
label: i18nT('dataset:data_index_image'),
|
||||
color: 'purple'
|
||||
}
|
||||
};
|
||||
|
||||
@@ -118,7 +118,7 @@ export const computeChunkSize = (params: {
|
||||
return getLLMMaxChunkSize(params.llmModel);
|
||||
}
|
||||
|
||||
return Math.min(params.chunkSize || chunkAutoChunkSize, getLLMMaxChunkSize(params.llmModel));
|
||||
return Math.min(params.chunkSize ?? chunkAutoChunkSize, getLLMMaxChunkSize(params.llmModel));
|
||||
};
|
||||
|
||||
export const computeChunkSplitter = (params: {
|
||||
|
||||
46
packages/global/core/dataset/type.d.ts
vendored
46
packages/global/core/dataset/type.d.ts
vendored
@@ -8,26 +8,42 @@ import type {
|
||||
DatasetStatusEnum,
|
||||
DatasetTypeEnum,
|
||||
SearchScoreTypeEnum,
|
||||
TrainingModeEnum
|
||||
TrainingModeEnum,
|
||||
ChunkSettingModeEnum
|
||||
} from './constants';
|
||||
import type { DatasetPermission } from '../../support/permission/dataset/controller';
|
||||
import { Permission } from '../../support/permission/controller';
|
||||
import type { APIFileServer, FeishuServer, YuqueServer } from './apiDataset';
|
||||
import type { SourceMemberType } from 'support/user/type';
|
||||
import type { DatasetDataIndexTypeEnum } from './data/constants';
|
||||
import type { ChunkSettingModeEnum } from './constants';
|
||||
|
||||
export type ChunkSettingsType = {
|
||||
trainingType: DatasetCollectionDataProcessModeEnum;
|
||||
autoIndexes?: boolean;
|
||||
trainingType?: DatasetCollectionDataProcessModeEnum;
|
||||
|
||||
// Chunk trigger
|
||||
chunkTriggerType?: ChunkTriggerConfigTypeEnum;
|
||||
chunkTriggerMinSize?: number; // maxSize from agent model, not store
|
||||
|
||||
// Data enhance
|
||||
dataEnhanceCollectionName?: boolean; // Auto add collection name to data
|
||||
|
||||
// Index enhance
|
||||
imageIndex?: boolean;
|
||||
autoIndexes?: boolean;
|
||||
|
||||
chunkSettingMode?: ChunkSettingModeEnum;
|
||||
// Chunk setting
|
||||
chunkSettingMode?: ChunkSettingModeEnum; // 系统参数/自定义参数
|
||||
chunkSplitMode?: DataChunkSplitModeEnum;
|
||||
|
||||
// Paragraph split
|
||||
paragraphChunkAIMode?: ParagraphChunkAIModeEnum;
|
||||
paragraphChunkDeep?: number; // Paragraph deep
|
||||
paragraphChunkMinSize?: number; // Paragraph min size, if too small, it will merge
|
||||
paragraphChunkMaxSize?: number; // Paragraph max size, if too large, it will split
|
||||
// Size split
|
||||
chunkSize?: number;
|
||||
indexSize?: number;
|
||||
// Char split
|
||||
chunkSplitter?: string;
|
||||
indexSize?: number;
|
||||
|
||||
qaPrompt?: string;
|
||||
};
|
||||
|
||||
@@ -66,7 +82,7 @@ export type DatasetSchemaType = {
|
||||
defaultPermission?: number;
|
||||
};
|
||||
|
||||
export type DatasetCollectionSchemaType = {
|
||||
export type DatasetCollectionSchemaType = ChunkSettingsType & {
|
||||
_id: string;
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
@@ -101,18 +117,7 @@ export type DatasetCollectionSchemaType = {
|
||||
|
||||
// Parse settings
|
||||
customPdfParse?: boolean;
|
||||
// Chunk settings
|
||||
autoIndexes?: boolean;
|
||||
imageIndex?: boolean;
|
||||
trainingType: DatasetCollectionDataProcessModeEnum;
|
||||
|
||||
chunkSettingMode?: ChunkSettingModeEnum;
|
||||
chunkSplitMode?: DataChunkSplitModeEnum;
|
||||
|
||||
chunkSize?: number;
|
||||
indexSize?: number;
|
||||
chunkSplitter?: string;
|
||||
qaPrompt?: string;
|
||||
};
|
||||
|
||||
export type DatasetCollectionTagsSchemaType = {
|
||||
@@ -175,6 +180,7 @@ export type DatasetTrainingSchemaType = {
|
||||
q: string;
|
||||
a: string;
|
||||
chunkIndex: number;
|
||||
indexSize?: number;
|
||||
weight: number;
|
||||
indexes: Omit<DatasetDataIndexItemType, 'dataId'>[];
|
||||
retryCount: number;
|
||||
|
||||
@@ -218,7 +218,6 @@ export const FlowValueTypeMap: Record<
|
||||
};
|
||||
|
||||
export const EDGE_TYPE = 'default';
|
||||
export const defaultNodeVersion = '481';
|
||||
|
||||
export const chatHistoryValueDesc = `{
|
||||
obj: System | Human | AI;
|
||||
@@ -236,3 +235,10 @@ export const datasetQuoteValueDesc = `{
|
||||
export const datasetSelectValueDesc = `{
|
||||
datasetId: string;
|
||||
}[]`;
|
||||
|
||||
export const AppNodeFlowNodeTypeMap: Record<any, boolean> = {
|
||||
[FlowNodeTypeEnum.pluginModule]: true,
|
||||
[FlowNodeTypeEnum.appModule]: true,
|
||||
[FlowNodeTypeEnum.tool]: true,
|
||||
[FlowNodeTypeEnum.toolSet]: true
|
||||
};
|
||||
|
||||
@@ -7,7 +7,7 @@ import type {
|
||||
} from '../../chat/type';
|
||||
import { NodeOutputItemType } from '../../chat/type';
|
||||
import type { FlowNodeInputItemType, FlowNodeOutputItemType } from '../type/io.d';
|
||||
import type { StoreNodeItemType } from '../type/node';
|
||||
import type { NodeToolConfigType, StoreNodeItemType } from '../type/node';
|
||||
import type { DispatchNodeResponseKeyEnum } from './constants';
|
||||
import type { StoreEdgeItemType } from '../type/edge';
|
||||
import type { NodeInputKeyEnum } from '../constants';
|
||||
@@ -101,7 +101,10 @@ export type RuntimeNodeItemType = {
|
||||
outputs: FlowNodeOutputItemType[];
|
||||
|
||||
pluginId?: string; // workflow id / plugin id
|
||||
version: string;
|
||||
version?: string;
|
||||
|
||||
// tool
|
||||
toolConfig?: NodeToolConfigType;
|
||||
};
|
||||
|
||||
export type RuntimeEdgeItemType = StoreEdgeItemType & {
|
||||
@@ -114,7 +117,7 @@ export type DispatchNodeResponseType = {
|
||||
runningTime?: number;
|
||||
query?: string;
|
||||
textOutput?: string;
|
||||
error?: Record<string, any>;
|
||||
error?: Record<string, any> | string;
|
||||
customInputs?: Record<string, any>;
|
||||
customOutputs?: Record<string, any>;
|
||||
nodeInputs?: Record<string, any>;
|
||||
|
||||
@@ -25,7 +25,6 @@ export const RunAppModule: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:application_call'),
|
||||
intro: i18nT('workflow:select_another_application_to_call'),
|
||||
showStatus: true,
|
||||
version: '481',
|
||||
isTool: true,
|
||||
inputs: [
|
||||
{
|
||||
|
||||
@@ -19,7 +19,6 @@ import {
|
||||
Input_Template_UserChatInput,
|
||||
Input_Template_File_Link
|
||||
} from '../../input';
|
||||
import { chatNodeSystemPromptTip, systemPromptTip } from '../../tip';
|
||||
import { getHandleConfig } from '../../utils';
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
|
||||
@@ -54,7 +53,7 @@ export const AiChatModule: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:template.ai_chat_intro'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/ai_chat/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/ai_chat/',
|
||||
version: '4.9.7',
|
||||
inputs: [
|
||||
Input_Template_SettingAiModel,
|
||||
@@ -121,12 +120,7 @@ export const AiChatModule: FlowNodeTemplateType = {
|
||||
valueType: WorkflowIOValueTypeEnum.string
|
||||
},
|
||||
// settings modal ---
|
||||
{
|
||||
...Input_Template_System_Prompt,
|
||||
label: i18nT('common:core.ai.Prompt'),
|
||||
description: systemPromptTip,
|
||||
placeholder: chatNodeSystemPromptTip
|
||||
},
|
||||
Input_Template_System_Prompt,
|
||||
Input_Template_History,
|
||||
Input_Template_Dataset_Quote,
|
||||
Input_Template_File_Link,
|
||||
|
||||
@@ -17,8 +17,7 @@ export const AssignedAnswerModule: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/reply',
|
||||
name: i18nT('workflow:assigned_reply'),
|
||||
intro: i18nT('workflow:intro_assigned_reply'),
|
||||
courseUrl: '/docs/guide/workbench/workflow/reply/',
|
||||
version: '481',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/reply/',
|
||||
isTool: true,
|
||||
inputs: [
|
||||
{
|
||||
|
||||
@@ -31,7 +31,7 @@ export const ClassifyQuestionModule: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:intro_question_classification'),
|
||||
showStatus: true,
|
||||
version: '4.9.2',
|
||||
courseUrl: '/docs/guide/workbench/workflow/question_classify/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/question_classify/',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_SelectAIModel,
|
||||
|
||||
@@ -26,7 +26,7 @@ export const ContextExtractModule: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:intro_text_content_extraction'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/content_extract/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/content_extract/',
|
||||
version: '4.9.2',
|
||||
inputs: [
|
||||
{
|
||||
|
||||
@@ -17,8 +17,7 @@ export const CustomFeedbackNode: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/customFeedback',
|
||||
name: i18nT('workflow:custom_feedback'),
|
||||
intro: i18nT('workflow:intro_custom_feedback'),
|
||||
courseUrl: '/docs/guide/workbench/workflow/custom_feedback/',
|
||||
version: '486',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/custom_feedback/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.textareaInput,
|
||||
|
||||
@@ -42,8 +42,7 @@ export const DatasetConcatModule: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:intro_knowledge_base_search_merge'),
|
||||
|
||||
showStatus: false,
|
||||
version: '486',
|
||||
courseUrl: '/docs/guide/workbench/workflow/knowledge_base_search_merge/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/knowledge_base_search_merge/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.datasetMaxTokens,
|
||||
|
||||
@@ -30,7 +30,7 @@ export const DatasetSearchModule: FlowNodeTemplateType = {
|
||||
intro: Dataset_SEARCH_DESC,
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/dataset_search/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/dataset_search/',
|
||||
version: '4.9.2',
|
||||
inputs: [
|
||||
{
|
||||
|
||||
@@ -27,8 +27,7 @@ export const HttpNode468: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:intro_http_request'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/http/',
|
||||
version: '481',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/http/',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
|
||||
@@ -23,8 +23,7 @@ export const IfElseNode: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:condition_checker'),
|
||||
intro: i18nT('workflow:execute_different_branches_based_on_conditions'),
|
||||
showStatus: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/tfswitch/',
|
||||
version: '481',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/tfswitch/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.ifElseList,
|
||||
|
||||
@@ -23,7 +23,6 @@ export const FormInputNode: FlowNodeTemplateType = {
|
||||
name: i18nT('app:workflow.form_input'),
|
||||
intro: i18nT(`app:workflow.form_input_tip`),
|
||||
isTool: true,
|
||||
version: '4811',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.description,
|
||||
|
||||
@@ -24,8 +24,7 @@ export const UserSelectNode: FlowNodeTemplateType = {
|
||||
name: i18nT('app:workflow.user_select'),
|
||||
intro: i18nT(`app:workflow.user_select_tip`),
|
||||
isTool: true,
|
||||
version: '489',
|
||||
courseUrl: '/docs/guide/workbench/workflow/user-selection/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/user-selection/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.description,
|
||||
|
||||
@@ -32,8 +32,7 @@ export const LafModule: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:intro_laf_function_call'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/laf/',
|
||||
version: '481',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/laf/',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
|
||||
@@ -29,8 +29,7 @@ export const LoopNode: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:loop'),
|
||||
intro: i18nT('workflow:intro_loop'),
|
||||
showStatus: true,
|
||||
version: '4811',
|
||||
courseUrl: '/docs/guide/workbench/workflow/loop/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/loop/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.loopInputArray,
|
||||
|
||||
@@ -19,7 +19,6 @@ export const LoopEndNode: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/loopEnd',
|
||||
name: i18nT('workflow:loop_end'),
|
||||
showStatus: false,
|
||||
version: '4811',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.loopEndInput,
|
||||
|
||||
@@ -24,7 +24,6 @@ export const LoopStartNode: FlowNodeTemplateType = {
|
||||
unique: true,
|
||||
forbidDelete: true,
|
||||
showStatus: false,
|
||||
version: '4811',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.loopStartInput,
|
||||
|
||||
@@ -15,7 +15,6 @@ export const PluginConfigNode: FlowNodeTemplateType = {
|
||||
intro: '',
|
||||
unique: true,
|
||||
forbidDelete: true,
|
||||
version: '4811',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -16,7 +16,6 @@ export const PluginInputModule: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:plugin_input'),
|
||||
intro: i18nT('workflow:intro_plugin_input'),
|
||||
showStatus: false,
|
||||
version: '481',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -16,7 +16,6 @@ export const PluginOutputModule: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:template.plugin_output'),
|
||||
intro: i18nT('workflow:intro_custom_plugin_output'),
|
||||
showStatus: false,
|
||||
version: '481',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -13,7 +13,6 @@ export const RunAppNode: FlowNodeTemplateType = {
|
||||
name: '',
|
||||
showStatus: false,
|
||||
isTool: false,
|
||||
version: '481',
|
||||
inputs: [], // [{key:'pluginId'},...]
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -13,7 +13,6 @@ export const RunPluginModule: FlowNodeTemplateType = {
|
||||
name: '',
|
||||
showStatus: false,
|
||||
isTool: true,
|
||||
version: '481',
|
||||
inputs: [], // [{key:'pluginId'},...]
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -13,7 +13,6 @@ export const RunToolNode: FlowNodeTemplateType = {
|
||||
name: '',
|
||||
showStatus: false,
|
||||
isTool: true,
|
||||
version: '4.9.6',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -13,7 +13,6 @@ export const RunToolSetNode: FlowNodeTemplateType = {
|
||||
name: '',
|
||||
showStatus: false,
|
||||
isTool: true,
|
||||
version: '4.9.6',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -26,8 +26,7 @@ export const CodeNode: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:code_execution'),
|
||||
intro: i18nT('workflow:execute_a_simple_script_code_usually_for_complex_data_processing'),
|
||||
showStatus: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/sandbox/',
|
||||
version: '482',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/sandbox/',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
|
||||
@@ -13,7 +13,6 @@ export const StopToolNode: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/stopTool',
|
||||
name: i18nT('workflow:tool_call_termination'),
|
||||
intro: i18nT('workflow:intro_tool_call_termination'),
|
||||
version: '481',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -15,7 +15,6 @@ export const SystemConfigNode: FlowNodeTemplateType = {
|
||||
intro: '',
|
||||
unique: true,
|
||||
forbidDelete: true,
|
||||
version: '481',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
};
|
||||
|
||||
@@ -23,8 +23,7 @@ export const TextEditorNode: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/textConcat',
|
||||
name: i18nT('workflow:text_concatenation'),
|
||||
intro: i18nT('workflow:intro_text_concatenation'),
|
||||
courseUrl: '/docs/guide/workbench/workflow/text_editor/',
|
||||
version: '4813',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/text_editor/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.textareaInput,
|
||||
|
||||
@@ -13,7 +13,6 @@ export const ToolParamsNode: FlowNodeTemplateType = {
|
||||
avatar: 'core/workflow/template/toolParams',
|
||||
name: i18nT('workflow:tool_custom_field'),
|
||||
intro: i18nT('workflow:intro_tool_params_config'),
|
||||
version: '4811',
|
||||
isTool: true,
|
||||
inputs: [],
|
||||
outputs: []
|
||||
|
||||
@@ -32,7 +32,7 @@ export const ToolModule: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:template.tool_call'),
|
||||
intro: i18nT('workflow:template.tool_call_intro'),
|
||||
showStatus: true,
|
||||
courseUrl: '/docs/guide/workbench/workflow/tool/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/tool/',
|
||||
version: '4.9.2',
|
||||
inputs: [
|
||||
{
|
||||
|
||||
@@ -19,8 +19,7 @@ export const VariableUpdateNode: FlowNodeTemplateType = {
|
||||
intro: i18nT('workflow:update_specified_node_output_or_global_variable'),
|
||||
showStatus: false,
|
||||
isTool: true,
|
||||
version: '481',
|
||||
courseUrl: '/docs/guide/workbench/workflow/variable_update/',
|
||||
courseUrl: '/docs/guide/dashboard/workflow/variable_update/',
|
||||
inputs: [
|
||||
{
|
||||
key: NodeInputKeyEnum.updateList,
|
||||
|
||||
@@ -30,7 +30,6 @@ export const WorkflowStart: FlowNodeTemplateType = {
|
||||
intro: '',
|
||||
forbidDelete: true,
|
||||
unique: true,
|
||||
version: '481',
|
||||
inputs: [{ ...Input_Template_UserChatInput, toolDescription: i18nT('workflow:user_question') }],
|
||||
outputs: [
|
||||
{
|
||||
|
||||
@@ -37,7 +37,10 @@ export type WorkflowTemplateType = {
|
||||
intro?: string;
|
||||
author?: string;
|
||||
courseUrl?: string;
|
||||
version: string;
|
||||
|
||||
version?: string;
|
||||
versionLabel?: string;
|
||||
isLatestVersion?: boolean;
|
||||
|
||||
showStatus?: boolean;
|
||||
weight?: number;
|
||||
|
||||
4
packages/global/core/workflow/type/io.d.ts
vendored
4
packages/global/core/workflow/type/io.d.ts
vendored
@@ -63,6 +63,8 @@ export type FlowNodeInputItemType = InputComponentPropsType & {
|
||||
canSelectFile?: boolean;
|
||||
canSelectImg?: boolean;
|
||||
maxFiles?: number;
|
||||
|
||||
deprecated?: boolean;
|
||||
};
|
||||
|
||||
export type FlowNodeOutputItemType = {
|
||||
@@ -86,6 +88,8 @@ export type FlowNodeOutputItemType = {
|
||||
|
||||
// component params
|
||||
customFieldConfig?: CustomFieldConfigType;
|
||||
|
||||
deprecated?: boolean;
|
||||
};
|
||||
|
||||
export type ReferenceItemValueType = [string, string | undefined];
|
||||
|
||||
21
packages/global/core/workflow/type/node.d.ts
vendored
21
packages/global/core/workflow/type/node.d.ts
vendored
@@ -20,11 +20,17 @@ import { RuntimeNodeItemType } from '../runtime/type';
|
||||
import { PluginTypeEnum } from '../../plugin/constants';
|
||||
import { RuntimeEdgeItemType, StoreEdgeItemType } from './edge';
|
||||
import { NextApiResponse } from 'next';
|
||||
import { AppDetailType, AppSchema } from '../../app/type';
|
||||
import type { AppDetailType, AppSchema, McpToolConfigType } from '../../app/type';
|
||||
import type { ParentIdType } from 'common/parentFolder/type';
|
||||
import { AppTypeEnum } from 'core/app/constants';
|
||||
import { AppTypeEnum } from '../../app/constants';
|
||||
import type { WorkflowInteractiveResponseType } from '../template/system/interactive/type';
|
||||
|
||||
export type NodeToolConfigType = {
|
||||
mcpTool?: McpToolConfigType & {
|
||||
url: string;
|
||||
};
|
||||
};
|
||||
|
||||
export type FlowNodeCommonType = {
|
||||
parentNodeId?: string;
|
||||
flowNodeType: FlowNodeTypeEnum; // render node card
|
||||
@@ -34,7 +40,10 @@ export type FlowNodeCommonType = {
|
||||
name: string;
|
||||
intro?: string; // template list intro
|
||||
showStatus?: boolean; // chatting response step status
|
||||
version: string;
|
||||
|
||||
version?: string;
|
||||
versionLabel?: string; // Just ui show
|
||||
isLatestVersion?: boolean; // Just ui show
|
||||
|
||||
// data
|
||||
inputs: FlowNodeInputItemType[];
|
||||
@@ -43,12 +52,14 @@ export type FlowNodeCommonType = {
|
||||
// plugin data
|
||||
pluginId?: string;
|
||||
isFolder?: boolean;
|
||||
// pluginType?: AppTypeEnum;
|
||||
pluginData?: PluginDataType;
|
||||
|
||||
// tool data
|
||||
toolData?: NodeToolConfigType;
|
||||
};
|
||||
|
||||
export type PluginDataType = {
|
||||
version: string;
|
||||
version?: string;
|
||||
diagram?: string;
|
||||
userGuide?: string;
|
||||
courseUrl?: string;
|
||||
|
||||
1
packages/global/support/user/api.d.ts
vendored
1
packages/global/support/user/api.d.ts
vendored
@@ -9,6 +9,7 @@ import type { TeamMemberItemType } from './team/type';
|
||||
export type PostLoginProps = {
|
||||
username: string;
|
||||
password: string;
|
||||
code: string;
|
||||
};
|
||||
|
||||
export type OauthLoginProps = {
|
||||
|
||||
@@ -3,7 +3,8 @@ export enum UserAuthTypeEnum {
|
||||
findPassword = 'findPassword',
|
||||
wxLogin = 'wxLogin',
|
||||
bindNotification = 'bindNotification',
|
||||
captcha = 'captcha'
|
||||
captcha = 'captcha',
|
||||
login = 'login'
|
||||
}
|
||||
|
||||
export const userAuthTypeMap = {
|
||||
@@ -11,5 +12,6 @@ export const userAuthTypeMap = {
|
||||
[UserAuthTypeEnum.findPassword]: 'findPassword',
|
||||
[UserAuthTypeEnum.wxLogin]: 'wxLogin',
|
||||
[UserAuthTypeEnum.bindNotification]: 'bindNotification',
|
||||
[UserAuthTypeEnum.captcha]: 'captcha'
|
||||
[UserAuthTypeEnum.captcha]: 'captcha',
|
||||
[UserAuthTypeEnum.login]: 'login'
|
||||
};
|
||||
|
||||
10
packages/global/support/user/auth/type.d.ts
vendored
Normal file
10
packages/global/support/user/auth/type.d.ts
vendored
Normal file
@@ -0,0 +1,10 @@
|
||||
import type { UserAuthTypeEnum } from '@fastgpt/global/support/user/auth/constants';
|
||||
|
||||
export type UserAuthSchemaType = {
|
||||
key: string;
|
||||
type: `${UserAuthTypeEnum}`;
|
||||
code?: string;
|
||||
openid?: string;
|
||||
createTime: Date;
|
||||
expiredTime: Date;
|
||||
};
|
||||
1
packages/global/support/user/type.d.ts
vendored
1
packages/global/support/user/type.d.ts
vendored
@@ -14,6 +14,7 @@ export type UserModelSchema = {
|
||||
timezone: string;
|
||||
status: `${UserStatusEnum}`;
|
||||
lastLoginTmbId?: string;
|
||||
passwordUpdateTime?: Date;
|
||||
fastgpt_sem?: {
|
||||
keyword: string;
|
||||
};
|
||||
|
||||
18
packages/service/common/api/type.d.ts
vendored
18
packages/service/common/api/type.d.ts
vendored
@@ -6,12 +6,6 @@ import type {
|
||||
} from '../../core/dataset/search/controller';
|
||||
import type { AuthOpenApiLimitProps } from '../../support/openapi/auth';
|
||||
import type { CreateUsageProps, ConcatUsageProps } from '@fastgpt/global/support/wallet/usage/api';
|
||||
import type {
|
||||
GetProApiDatasetFileContentParams,
|
||||
GetProApiDatasetFileDetailParams,
|
||||
GetProApiDatasetFileListParams,
|
||||
GetProApiDatasetFilePreviewUrlParams
|
||||
} from '../../core/dataset/apiDataset/proApi';
|
||||
|
||||
declare global {
|
||||
var textCensorHandler: (params: { text: string }) => Promise<{ code: number; message?: string }>;
|
||||
@@ -19,16 +13,4 @@ declare global {
|
||||
var authOpenApiHandler: (data: AuthOpenApiLimitProps) => Promise<any>;
|
||||
var createUsageHandler: (data: CreateUsageProps) => any;
|
||||
var concatUsageHandler: (data: ConcatUsageProps) => any;
|
||||
|
||||
// API dataset
|
||||
var getProApiDatasetFileList: (data: GetProApiDatasetFileListParams) => Promise<APIFileItem[]>;
|
||||
var getProApiDatasetFileContent: (
|
||||
data: GetProApiDatasetFileContentParams
|
||||
) => Promise<ApiFileReadContentResponse>;
|
||||
var getProApiDatasetFilePreviewUrl: (
|
||||
data: GetProApiDatasetFilePreviewUrlParams
|
||||
) => Promise<string>;
|
||||
var getProApiDatasetFileDetail: (
|
||||
data: GetProApiDatasetFileDetailParams
|
||||
) => Promise<ApiDatasetDetailResponse>;
|
||||
}
|
||||
|
||||
@@ -210,15 +210,15 @@ export const readFileContentFromMongo = async ({
|
||||
tmbId,
|
||||
bucketName,
|
||||
fileId,
|
||||
isQAImport = false,
|
||||
customPdfParse = false
|
||||
customPdfParse = false,
|
||||
getFormatText
|
||||
}: {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
bucketName: `${BucketNameEnum}`;
|
||||
fileId: string;
|
||||
isQAImport?: boolean;
|
||||
customPdfParse?: boolean;
|
||||
getFormatText?: boolean; // 数据类型都尽可能转化成 markdown 格式
|
||||
}): Promise<{
|
||||
rawText: string;
|
||||
filename: string;
|
||||
@@ -254,8 +254,8 @@ export const readFileContentFromMongo = async ({
|
||||
// Get raw text
|
||||
const { rawText } = await readRawContentByFileBuffer({
|
||||
customPdfParse,
|
||||
getFormatText,
|
||||
extension,
|
||||
isQAImport,
|
||||
teamId,
|
||||
tmbId,
|
||||
buffer: fileBuffers,
|
||||
|
||||
@@ -16,6 +16,7 @@ export type readRawTextByLocalFileParams = {
|
||||
path: string;
|
||||
encoding: string;
|
||||
customPdfParse?: boolean;
|
||||
getFormatText?: boolean;
|
||||
metadata?: Record<string, any>;
|
||||
};
|
||||
export const readRawTextByLocalFile = async (params: readRawTextByLocalFileParams) => {
|
||||
@@ -27,8 +28,8 @@ export const readRawTextByLocalFile = async (params: readRawTextByLocalFileParam
|
||||
|
||||
return readRawContentByFileBuffer({
|
||||
extension,
|
||||
isQAImport: false,
|
||||
customPdfParse: params.customPdfParse,
|
||||
getFormatText: params.getFormatText,
|
||||
teamId: params.teamId,
|
||||
tmbId: params.tmbId,
|
||||
encoding: params.encoding,
|
||||
@@ -46,7 +47,7 @@ export const readRawContentByFileBuffer = async ({
|
||||
encoding,
|
||||
metadata,
|
||||
customPdfParse = false,
|
||||
isQAImport = false
|
||||
getFormatText = true
|
||||
}: {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
@@ -57,8 +58,10 @@ export const readRawContentByFileBuffer = async ({
|
||||
metadata?: Record<string, any>;
|
||||
|
||||
customPdfParse?: boolean;
|
||||
isQAImport: boolean;
|
||||
}): Promise<ReadFileResponse> => {
|
||||
getFormatText?: boolean;
|
||||
}): Promise<{
|
||||
rawText: string;
|
||||
}> => {
|
||||
const systemParse = () =>
|
||||
runWorker<ReadFileResponse>(WorkerNameEnum.readFile, {
|
||||
extension,
|
||||
@@ -149,7 +152,7 @@ export const readRawContentByFileBuffer = async ({
|
||||
return await systemParse();
|
||||
})();
|
||||
|
||||
addLog.debug(`Parse file success, time: ${Date.now() - start}ms. Uploading file image.`);
|
||||
addLog.debug(`Parse file success, time: ${Date.now() - start}ms. `);
|
||||
|
||||
// markdown data format
|
||||
if (imageList) {
|
||||
@@ -176,16 +179,7 @@ export const readRawContentByFileBuffer = async ({
|
||||
});
|
||||
}
|
||||
|
||||
if (['csv', 'xlsx'].includes(extension)) {
|
||||
// qa data
|
||||
if (isQAImport) {
|
||||
rawText = rawText || '';
|
||||
} else {
|
||||
rawText = formatText || rawText;
|
||||
}
|
||||
}
|
||||
addLog.debug(`Upload file success, time: ${Date.now() - start}ms`);
|
||||
|
||||
addLog.debug(`Upload file image success, time: ${Date.now() - start}ms`);
|
||||
|
||||
return { rawText, formatText, imageList };
|
||||
return { rawText: getFormatText ? formatText || rawText : rawText };
|
||||
};
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import { jsonRes } from '../response';
|
||||
import type { NextApiResponse } from 'next';
|
||||
import type { NextApiRequest, NextApiResponse } from 'next';
|
||||
import { withNextCors } from './cors';
|
||||
import { type ApiRequestProps } from '../../type/next';
|
||||
import { addLog } from '../system/log';
|
||||
@@ -9,14 +9,21 @@ export type NextApiHandler<T = any> = (
|
||||
res: NextApiResponse<T>
|
||||
) => unknown | Promise<unknown>;
|
||||
|
||||
export const NextEntry = ({ beforeCallback = [] }: { beforeCallback?: Promise<any>[] }) => {
|
||||
export const NextEntry = ({
|
||||
beforeCallback = []
|
||||
}: {
|
||||
beforeCallback?: ((req: NextApiRequest, res: NextApiResponse) => Promise<any>)[];
|
||||
}) => {
|
||||
return (...args: NextApiHandler[]): NextApiHandler => {
|
||||
return async function api(req: ApiRequestProps, res: NextApiResponse) {
|
||||
const start = Date.now();
|
||||
addLog.debug(`Request start ${req.url}`);
|
||||
|
||||
try {
|
||||
await Promise.all([withNextCors(req, res), ...beforeCallback]);
|
||||
await Promise.all([
|
||||
withNextCors(req, res),
|
||||
...beforeCallback.map((item) => item(req, res))
|
||||
]);
|
||||
|
||||
let response = null;
|
||||
for await (const handler of args) {
|
||||
|
||||
@@ -1,7 +1,10 @@
|
||||
import { getGlobalRedisCacheConnection } from './index';
|
||||
import { getGlobalRedisConnection } from './index';
|
||||
import { addLog } from '../system/log';
|
||||
import { retryFn } from '@fastgpt/global/common/system/utils';
|
||||
|
||||
const redisPrefix = 'cache:';
|
||||
const getCacheKey = (key: string) => `${redisPrefix}${key}`;
|
||||
|
||||
export enum CacheKeyEnum {
|
||||
team_vector_count = 'team_vector_count'
|
||||
}
|
||||
@@ -13,12 +16,12 @@ export const setRedisCache = async (
|
||||
) => {
|
||||
return await retryFn(async () => {
|
||||
try {
|
||||
const redis = getGlobalRedisCacheConnection();
|
||||
const redis = getGlobalRedisConnection();
|
||||
|
||||
if (expireSeconds) {
|
||||
await redis.set(key, data, 'EX', expireSeconds);
|
||||
await redis.set(getCacheKey(key), data, 'EX', expireSeconds);
|
||||
} else {
|
||||
await redis.set(key, data);
|
||||
await redis.set(getCacheKey(key), data);
|
||||
}
|
||||
} catch (error) {
|
||||
addLog.error('Set cache error:', error);
|
||||
@@ -28,11 +31,11 @@ export const setRedisCache = async (
|
||||
};
|
||||
|
||||
export const getRedisCache = async (key: string) => {
|
||||
const redis = getGlobalRedisCacheConnection();
|
||||
return await retryFn(() => redis.get(key));
|
||||
const redis = getGlobalRedisConnection();
|
||||
return await retryFn(() => redis.get(getCacheKey(key)));
|
||||
};
|
||||
|
||||
export const delRedisCache = async (key: string) => {
|
||||
const redis = getGlobalRedisCacheConnection();
|
||||
await retryFn(() => redis.del(key));
|
||||
const redis = getGlobalRedisConnection();
|
||||
await retryFn(() => redis.del(getCacheKey(key)));
|
||||
};
|
||||
|
||||
@@ -27,17 +27,26 @@ export const newWorkerRedisConnection = () => {
|
||||
return redis;
|
||||
};
|
||||
|
||||
export const getGlobalRedisCacheConnection = () => {
|
||||
if (global.redisCache) return global.redisCache;
|
||||
export const FASTGPT_REDIS_PREFIX = 'fastgpt:';
|
||||
export const getGlobalRedisConnection = () => {
|
||||
if (global.redisClient) return global.redisClient;
|
||||
|
||||
global.redisCache = new Redis(REDIS_URL, { keyPrefix: 'fastgpt:cache:' });
|
||||
global.redisClient = new Redis(REDIS_URL, { keyPrefix: FASTGPT_REDIS_PREFIX });
|
||||
|
||||
global.redisCache.on('connect', () => {
|
||||
global.redisClient.on('connect', () => {
|
||||
addLog.info('Redis connected');
|
||||
});
|
||||
global.redisCache.on('error', (error) => {
|
||||
global.redisClient.on('error', (error) => {
|
||||
addLog.error('Redis connection error', error);
|
||||
});
|
||||
|
||||
return global.redisCache;
|
||||
return global.redisClient;
|
||||
};
|
||||
|
||||
export const getAllKeysByPrefix = async (key: string) => {
|
||||
const redis = getGlobalRedisConnection();
|
||||
const keys = (await redis.keys(`${FASTGPT_REDIS_PREFIX}${key}:*`)).map((key) =>
|
||||
key.replace(FASTGPT_REDIS_PREFIX, '')
|
||||
);
|
||||
return keys;
|
||||
};
|
||||
|
||||
2
packages/service/common/redis/type.d.ts
vendored
2
packages/service/common/redis/type.d.ts
vendored
@@ -1,5 +1,5 @@
|
||||
import type Redis from 'ioredis';
|
||||
|
||||
declare global {
|
||||
var redisCache: Redis | null;
|
||||
var redisClient: Redis | null;
|
||||
}
|
||||
|
||||
@@ -42,7 +42,7 @@ export const cheerioToHtml = ({
|
||||
}
|
||||
}
|
||||
});
|
||||
selectDom.find('img').each((i, el) => {
|
||||
selectDom.find('img, video, source, audio, iframe').each((i, el) => {
|
||||
const src = $(el).attr('src');
|
||||
if (src) {
|
||||
if (src.startsWith('//')) {
|
||||
|
||||
@@ -10,6 +10,7 @@ let jieba: Jieba | undefined;
|
||||
})();
|
||||
|
||||
const stopWords = new Set([
|
||||
'\n',
|
||||
'--',
|
||||
'?',
|
||||
'“',
|
||||
@@ -1519,8 +1520,7 @@ const stopWords = new Set([
|
||||
]);
|
||||
|
||||
export async function jiebaSplit({ text }: { text: string }) {
|
||||
text = text.replace(/[#*`_~>[\](){}|]/g, '').replace(/\S*https?\S*/gi, '');
|
||||
|
||||
text = text.replace(/[#*`_~>[\](){}|]|\S*https?\S*/g, '').trim();
|
||||
const tokens = (await jieba!.cutAsync(text, true)) as string[];
|
||||
|
||||
return (
|
||||
|
||||
@@ -2,26 +2,44 @@ import { SystemConfigsTypeEnum } from '@fastgpt/global/common/system/config/cons
|
||||
import { MongoSystemConfigs } from './schema';
|
||||
import { type FastGPTConfigFileType } from '@fastgpt/global/common/system/types';
|
||||
import { FastGPTProUrl } from '../constants';
|
||||
import { type LicenseDataType } from '@fastgpt/global/common/system/types';
|
||||
|
||||
export const getFastGPTConfigFromDB = async () => {
|
||||
export const getFastGPTConfigFromDB = async (): Promise<{
|
||||
fastgptConfig: FastGPTConfigFileType;
|
||||
licenseData?: LicenseDataType;
|
||||
}> => {
|
||||
if (!FastGPTProUrl) {
|
||||
return {
|
||||
config: {} as FastGPTConfigFileType
|
||||
fastgptConfig: {} as FastGPTConfigFileType
|
||||
};
|
||||
}
|
||||
|
||||
const res = await MongoSystemConfigs.findOne({
|
||||
type: SystemConfigsTypeEnum.fastgpt
|
||||
}).sort({
|
||||
createTime: -1
|
||||
});
|
||||
const [fastgptConfig, licenseConfig] = await Promise.all([
|
||||
MongoSystemConfigs.findOne({
|
||||
type: SystemConfigsTypeEnum.fastgpt
|
||||
}).sort({
|
||||
createTime: -1
|
||||
}),
|
||||
MongoSystemConfigs.findOne({
|
||||
type: SystemConfigsTypeEnum.license
|
||||
}).sort({
|
||||
createTime: -1
|
||||
})
|
||||
]);
|
||||
|
||||
const config = res?.value || {};
|
||||
const config = fastgptConfig?.value || {};
|
||||
const licenseData = licenseConfig?.value?.data as LicenseDataType | undefined;
|
||||
|
||||
const fastgptConfigTime = fastgptConfig?.createTime.getTime().toString();
|
||||
const licenseConfigTime = licenseConfig?.createTime.getTime().toString();
|
||||
// 利用配置文件的创建时间(更新时间)来做缓存,如果前端命中缓存,则不需要再返回配置文件
|
||||
global.systemInitBufferId = res ? res.createTime.getTime().toString() : undefined;
|
||||
global.systemInitBufferId = fastgptConfigTime
|
||||
? `${fastgptConfigTime}-${licenseConfigTime}`
|
||||
: undefined;
|
||||
|
||||
return {
|
||||
config: config as FastGPTConfigFileType
|
||||
fastgptConfig: config as FastGPTConfigFileType,
|
||||
licenseData
|
||||
};
|
||||
};
|
||||
|
||||
|
||||
@@ -57,14 +57,19 @@ export const addLog = {
|
||||
|
||||
level === LogLevelEnum.error && console.error(obj);
|
||||
|
||||
// store
|
||||
// store log
|
||||
if (level >= STORE_LOG_LEVEL && connectionMongo.connection.readyState === 1) {
|
||||
// store log
|
||||
getMongoLog().create({
|
||||
text: msg,
|
||||
level,
|
||||
metadata: obj
|
||||
});
|
||||
(async () => {
|
||||
try {
|
||||
await getMongoLog().create({
|
||||
text: msg,
|
||||
level,
|
||||
metadata: obj
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('store log error', error);
|
||||
}
|
||||
})();
|
||||
}
|
||||
},
|
||||
debug(msg: string, obj?: Record<string, any>) {
|
||||
|
||||
@@ -188,6 +188,7 @@ export class PgVectorCtrl {
|
||||
const results: any = await PgClient.query(
|
||||
`BEGIN;
|
||||
SET LOCAL hnsw.ef_search = ${global.systemEnv?.hnswEfSearch || 100};
|
||||
SET LOCAL hnsw.max_scan_tuples = ${global.systemEnv?.hnswMaxScanTuples || 100000};
|
||||
SET LOCAL hnsw.iterative_scan = relaxed_order;
|
||||
WITH relaxed_results AS MATERIALIZED (
|
||||
select id, collection_id, vector <#> '[${vector}]' AS score
|
||||
@@ -199,7 +200,7 @@ export class PgVectorCtrl {
|
||||
) SELECT id, collection_id, score FROM relaxed_results ORDER BY score;
|
||||
COMMIT;`
|
||||
);
|
||||
const rows = results?.[3]?.rows as PgSearchRawType[];
|
||||
const rows = results?.[results.length - 2]?.rows as PgSearchRawType[];
|
||||
|
||||
if (!Array.isArray(rows)) {
|
||||
return {
|
||||
|
||||
@@ -78,7 +78,7 @@ export const createChatCompletion = async ({
|
||||
}
|
||||
body.model = modelConstantsData.model;
|
||||
|
||||
const formatTimeout = timeout ? timeout : body.stream ? 60000 : 600000;
|
||||
const formatTimeout = timeout ? timeout : 600000;
|
||||
const ai = getAIApi({
|
||||
userKey,
|
||||
timeout: formatTimeout
|
||||
|
||||
@@ -1,6 +1,54 @@
|
||||
{
|
||||
"provider": "Claude",
|
||||
"list": [
|
||||
{
|
||||
"model": "claude-sonnet-4-20250514",
|
||||
"name": "claude-sonnet-4-20250514",
|
||||
"maxContext": 200000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 100000,
|
||||
"maxTemperature": 1,
|
||||
"showTopP": true,
|
||||
"showStopSign": true,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "claude-opus-4-20250514",
|
||||
"name": "claude-opus-4-20250514",
|
||||
"maxContext": 200000,
|
||||
"maxResponse": 4096,
|
||||
"quoteMaxToken": 100000,
|
||||
"maxTemperature": 1,
|
||||
"showTopP": true,
|
||||
"showStopSign": true,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "claude-3-7-sonnet-20250219",
|
||||
"name": "claude-3-7-sonnet-20250219",
|
||||
|
||||
@@ -25,6 +25,30 @@
|
||||
"showTopP": true,
|
||||
"showStopSign": true
|
||||
},
|
||||
{
|
||||
"model": "gemini-2.5-flash-preview-04-17",
|
||||
"name": "gemini-2.5-flash-preview-04-17",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm",
|
||||
"showTopP": true,
|
||||
"showStopSign": true
|
||||
},
|
||||
{
|
||||
"model": "gemini-2.0-flash",
|
||||
"name": "gemini-2.0-flash",
|
||||
|
||||
@@ -11,21 +11,24 @@ import type {
|
||||
import { getLLMModel } from './model';
|
||||
import { getLLMDefaultUsage } from '@fastgpt/global/core/ai/constants';
|
||||
import { getNanoid } from '@fastgpt/global/common/string/tools';
|
||||
import json5 from 'json5';
|
||||
|
||||
/*
|
||||
Count response max token
|
||||
*/
|
||||
export const computedMaxToken = ({
|
||||
maxToken,
|
||||
model
|
||||
model,
|
||||
min
|
||||
}: {
|
||||
maxToken?: number;
|
||||
model: LLMModelItemType;
|
||||
min?: number;
|
||||
}) => {
|
||||
if (maxToken === undefined) return;
|
||||
|
||||
maxToken = Math.min(maxToken, model.maxResponse);
|
||||
return maxToken;
|
||||
return Math.max(maxToken, min || 0);
|
||||
};
|
||||
|
||||
// FastGPT temperature range: [0,10], ai temperature:[0,2],{0,1]……
|
||||
@@ -54,8 +57,6 @@ type InferCompletionsBody<T> = T extends { stream: true }
|
||||
|
||||
export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
|
||||
body: T & {
|
||||
response_format?: any;
|
||||
json_schema?: string;
|
||||
stop?: string;
|
||||
},
|
||||
model: string | LLMModelItemType
|
||||
@@ -65,8 +66,26 @@ export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
|
||||
return body as unknown as InferCompletionsBody<T>;
|
||||
}
|
||||
|
||||
const response_format = body.response_format;
|
||||
const json_schema = body.json_schema ?? undefined;
|
||||
const response_format = (() => {
|
||||
if (!body.response_format?.type) return undefined;
|
||||
if (body.response_format.type === 'json_schema') {
|
||||
try {
|
||||
return {
|
||||
type: 'json_schema',
|
||||
json_schema: json5.parse(body.response_format?.json_schema as unknown as string)
|
||||
};
|
||||
} catch (error) {
|
||||
throw new Error('Json schema error');
|
||||
}
|
||||
}
|
||||
if (body.response_format.type) {
|
||||
return {
|
||||
type: body.response_format.type
|
||||
};
|
||||
}
|
||||
return undefined;
|
||||
})();
|
||||
|
||||
const stop = body.stop ?? undefined;
|
||||
|
||||
const requestBody: T = {
|
||||
@@ -80,12 +99,7 @@ export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
|
||||
})
|
||||
: undefined,
|
||||
...modelData?.defaultConfig,
|
||||
response_format: response_format
|
||||
? {
|
||||
type: response_format,
|
||||
json_schema
|
||||
}
|
||||
: undefined,
|
||||
response_format,
|
||||
stop: stop?.split('|')
|
||||
};
|
||||
|
||||
@@ -123,12 +137,14 @@ export const llmStreamResponseToAnswerText = async (
|
||||
|
||||
// Tool calls
|
||||
if (responseChoice?.tool_calls?.length) {
|
||||
responseChoice.tool_calls.forEach((toolCall) => {
|
||||
const index = toolCall.index;
|
||||
responseChoice.tool_calls.forEach((toolCall, i) => {
|
||||
const index = toolCall.index ?? i;
|
||||
|
||||
if (toolCall.id || callingTool) {
|
||||
// 有 id,代表新 call 工具
|
||||
if (toolCall.id) {
|
||||
// Call new tool
|
||||
const hasNewTool = toolCall?.function?.name || callingTool;
|
||||
if (hasNewTool) {
|
||||
// 有 function name,代表新 call 工具
|
||||
if (toolCall?.function?.name) {
|
||||
callingTool = {
|
||||
name: toolCall.function?.name || '',
|
||||
arguments: toolCall.function?.arguments || ''
|
||||
@@ -164,7 +180,7 @@ export const llmStreamResponseToAnswerText = async (
|
||||
}
|
||||
}
|
||||
return {
|
||||
text: parseReasoningContent(answer)[1],
|
||||
text: removeDatasetCiteText(parseReasoningContent(answer)[1], false),
|
||||
usage,
|
||||
toolCalls
|
||||
};
|
||||
@@ -178,8 +194,9 @@ export const llmUnStreamResponseToAnswerText = async (
|
||||
}> => {
|
||||
const answer = response.choices?.[0]?.message?.content || '';
|
||||
const toolCalls = response.choices?.[0]?.message?.tool_calls;
|
||||
|
||||
return {
|
||||
text: answer,
|
||||
text: removeDatasetCiteText(parseReasoningContent(answer)[1], false),
|
||||
usage: response.usage,
|
||||
toolCalls
|
||||
};
|
||||
@@ -209,7 +226,9 @@ export const parseReasoningContent = (text: string): [string, string] => {
|
||||
};
|
||||
|
||||
export const removeDatasetCiteText = (text: string, retainDatasetCite: boolean) => {
|
||||
return retainDatasetCite ? text : text.replace(/\[([a-f0-9]{24})\]\(CITE\)/g, '');
|
||||
return retainDatasetCite
|
||||
? text.replace(/\[id\]\(CITE\)/g, '')
|
||||
: text.replace(/\[([a-f0-9]{24})\](?:\([^\)]*\)?)?/g, '').replace(/\[id\]\(CITE\)/g, '');
|
||||
};
|
||||
|
||||
// Parse llm stream part
|
||||
@@ -224,6 +243,12 @@ export const parseLLMStreamResponse = () => {
|
||||
let citeBuffer = '';
|
||||
const maxCiteBufferLength = 32; // [Object](CITE)总长度为32
|
||||
|
||||
// Buffer
|
||||
let buffer_finishReason: CompletionFinishReason = null;
|
||||
let buffer_usage: CompletionUsage = getLLMDefaultUsage();
|
||||
let buffer_reasoningContent = '';
|
||||
let buffer_content = '';
|
||||
|
||||
/*
|
||||
parseThinkTag - 只控制是否主动解析 <think></think>,如果接口已经解析了,则不再解析。
|
||||
retainDatasetCite -
|
||||
@@ -241,6 +266,7 @@ export const parseLLMStreamResponse = () => {
|
||||
};
|
||||
finish_reason?: CompletionFinishReason;
|
||||
}[];
|
||||
usage?: CompletionUsage;
|
||||
};
|
||||
parseThinkTag?: boolean;
|
||||
retainDatasetCite?: boolean;
|
||||
@@ -250,72 +276,71 @@ export const parseLLMStreamResponse = () => {
|
||||
responseContent: string;
|
||||
finishReason: CompletionFinishReason;
|
||||
} => {
|
||||
const finishReason = part.choices?.[0]?.finish_reason || null;
|
||||
const content = part.choices?.[0]?.delta?.content || '';
|
||||
// @ts-ignore
|
||||
const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
|
||||
const isStreamEnd = !!finishReason;
|
||||
const data = (() => {
|
||||
buffer_usage = part.usage || buffer_usage;
|
||||
|
||||
// Parse think
|
||||
const { reasoningContent: parsedThinkReasoningContent, content: parsedThinkContent } = (() => {
|
||||
if (reasoningContent || !parseThinkTag) {
|
||||
isInThinkTag = false;
|
||||
return { reasoningContent, content };
|
||||
}
|
||||
const finishReason = part.choices?.[0]?.finish_reason || null;
|
||||
buffer_finishReason = finishReason || buffer_finishReason;
|
||||
|
||||
if (!content) {
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
const content = part.choices?.[0]?.delta?.content || '';
|
||||
// @ts-ignore
|
||||
const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
|
||||
const isStreamEnd = !!buffer_finishReason;
|
||||
|
||||
// 如果不在 think 标签中,或者有 reasoningContent(接口已解析),则返回 reasoningContent 和 content
|
||||
if (isInThinkTag === false) {
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content
|
||||
};
|
||||
}
|
||||
// Parse think
|
||||
const { reasoningContent: parsedThinkReasoningContent, content: parsedThinkContent } =
|
||||
(() => {
|
||||
if (reasoningContent || !parseThinkTag) {
|
||||
isInThinkTag = false;
|
||||
return { reasoningContent, content };
|
||||
}
|
||||
|
||||
// 检测是否为 think 标签开头的数据
|
||||
if (isInThinkTag === undefined) {
|
||||
// Parse content think and answer
|
||||
startTagBuffer += content;
|
||||
// 太少内容时候,暂时不解析
|
||||
if (startTagBuffer.length < thinkStartChars.length) {
|
||||
if (isStreamEnd) {
|
||||
const tmpContent = startTagBuffer;
|
||||
startTagBuffer = '';
|
||||
// 如果不在 think 标签中,或者有 reasoningContent(接口已解析),则返回 reasoningContent 和 content
|
||||
if (isInThinkTag === false) {
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: tmpContent
|
||||
content
|
||||
};
|
||||
}
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
|
||||
if (startTagBuffer.startsWith(thinkStartChars)) {
|
||||
isInThinkTag = true;
|
||||
return {
|
||||
reasoningContent: startTagBuffer.slice(thinkStartChars.length),
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
// 检测是否为 think 标签开头的数据
|
||||
if (isInThinkTag === undefined) {
|
||||
// Parse content think and answer
|
||||
startTagBuffer += content;
|
||||
// 太少内容时候,暂时不解析
|
||||
if (startTagBuffer.length < thinkStartChars.length) {
|
||||
if (isStreamEnd) {
|
||||
const tmpContent = startTagBuffer;
|
||||
startTagBuffer = '';
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: tmpContent
|
||||
};
|
||||
}
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
|
||||
// 如果未命中 think 标签,则认为不在 think 标签中,返回 buffer 内容作为 content
|
||||
isInThinkTag = false;
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: startTagBuffer
|
||||
};
|
||||
}
|
||||
if (startTagBuffer.startsWith(thinkStartChars)) {
|
||||
isInThinkTag = true;
|
||||
return {
|
||||
reasoningContent: startTagBuffer.slice(thinkStartChars.length),
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
|
||||
// 确认是 think 标签内容,开始返回 think 内容,并实时检测 </think>
|
||||
/*
|
||||
// 如果未命中 think 标签,则认为不在 think 标签中,返回 buffer 内容作为 content
|
||||
isInThinkTag = false;
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: startTagBuffer
|
||||
};
|
||||
}
|
||||
|
||||
// 确认是 think 标签内容,开始返回 think 内容,并实时检测 </think>
|
||||
/*
|
||||
检测 </think> 方案。
|
||||
存储所有疑似 </think> 的内容,直到检测到完整的 </think> 标签或超出 </think> 长度。
|
||||
content 返回值包含以下几种情况:
|
||||
@@ -326,124 +351,145 @@ export const parseLLMStreamResponse = () => {
|
||||
</think>abc - 完全命中尾标签
|
||||
k>abc - 命中一部分尾标签
|
||||
*/
|
||||
// endTagBuffer 专门用来记录疑似尾标签的内容
|
||||
if (endTagBuffer) {
|
||||
endTagBuffer += content;
|
||||
if (endTagBuffer.includes(thinkEndChars)) {
|
||||
isInThinkTag = false;
|
||||
const answer = endTagBuffer.slice(thinkEndChars.length);
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: answer
|
||||
};
|
||||
} else if (endTagBuffer.length >= thinkEndChars.length) {
|
||||
// 缓存内容超出尾标签长度,且仍未命中 </think>,则认为本次猜测 </think> 失败,仍处于 think 阶段。
|
||||
const tmp = endTagBuffer;
|
||||
endTagBuffer = '';
|
||||
return {
|
||||
reasoningContent: tmp,
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: ''
|
||||
};
|
||||
} else if (content.includes(thinkEndChars)) {
|
||||
// 返回内容,完整命中</think>,直接结束
|
||||
isInThinkTag = false;
|
||||
const [think, answer] = content.split(thinkEndChars);
|
||||
return {
|
||||
reasoningContent: think,
|
||||
content: answer
|
||||
};
|
||||
} else {
|
||||
// 无 buffer,且未命中 </think>,开始疑似 </think> 检测。
|
||||
for (let i = 1; i < thinkEndChars.length; i++) {
|
||||
const partialEndTag = thinkEndChars.slice(0, i);
|
||||
// 命中一部分尾标签
|
||||
if (content.endsWith(partialEndTag)) {
|
||||
const think = content.slice(0, -partialEndTag.length);
|
||||
endTagBuffer += partialEndTag;
|
||||
// endTagBuffer 专门用来记录疑似尾标签的内容
|
||||
if (endTagBuffer) {
|
||||
endTagBuffer += content;
|
||||
if (endTagBuffer.includes(thinkEndChars)) {
|
||||
isInThinkTag = false;
|
||||
const answer = endTagBuffer.slice(thinkEndChars.length);
|
||||
return {
|
||||
reasoningContent: '',
|
||||
content: answer
|
||||
};
|
||||
} else if (endTagBuffer.length >= thinkEndChars.length) {
|
||||
// 缓存内容超出尾标签长度,且仍未命中 </think>,则认为本次猜测 </think> 失败,仍处于 think 阶段。
|
||||
const tmp = endTagBuffer;
|
||||
endTagBuffer = '';
|
||||
return {
|
||||
reasoningContent: tmp,
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
return {
|
||||
reasoningContent: think,
|
||||
reasoningContent: '',
|
||||
content: ''
|
||||
};
|
||||
} else if (content.includes(thinkEndChars)) {
|
||||
// 返回内容,完整命中</think>,直接结束
|
||||
isInThinkTag = false;
|
||||
const [think, answer] = content.split(thinkEndChars);
|
||||
return {
|
||||
reasoningContent: think,
|
||||
content: answer
|
||||
};
|
||||
} else {
|
||||
// 无 buffer,且未命中 </think>,开始疑似 </think> 检测。
|
||||
for (let i = 1; i < thinkEndChars.length; i++) {
|
||||
const partialEndTag = thinkEndChars.slice(0, i);
|
||||
// 命中一部分尾标签
|
||||
if (content.endsWith(partialEndTag)) {
|
||||
const think = content.slice(0, -partialEndTag.length);
|
||||
endTagBuffer += partialEndTag;
|
||||
return {
|
||||
reasoningContent: think,
|
||||
content: ''
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 完全未命中尾标签,还是 think 阶段。
|
||||
return {
|
||||
reasoningContent: content,
|
||||
content: ''
|
||||
};
|
||||
})();
|
||||
|
||||
// Parse datset cite
|
||||
if (retainDatasetCite) {
|
||||
return {
|
||||
reasoningContent: parsedThinkReasoningContent,
|
||||
content: parsedThinkContent,
|
||||
responseContent: parsedThinkContent,
|
||||
finishReason: buffer_finishReason
|
||||
};
|
||||
}
|
||||
|
||||
// 完全未命中尾标签,还是 think 阶段。
|
||||
return {
|
||||
reasoningContent: content,
|
||||
content: ''
|
||||
};
|
||||
})();
|
||||
// 缓存包含 [ 的字符串,直到超出 maxCiteBufferLength 再一次性返回
|
||||
const parseCite = (text: string) => {
|
||||
// 结束时,返回所有剩余内容
|
||||
if (isStreamEnd) {
|
||||
const content = citeBuffer + text;
|
||||
return {
|
||||
content: removeDatasetCiteText(content, false)
|
||||
};
|
||||
}
|
||||
|
||||
// 新内容包含 [,初始化缓冲数据
|
||||
if (text.includes('[')) {
|
||||
const index = text.indexOf('[');
|
||||
const beforeContent = citeBuffer + text.slice(0, index);
|
||||
citeBuffer = text.slice(index);
|
||||
|
||||
// beforeContent 可能是:普通字符串,带 [ 的字符串
|
||||
return {
|
||||
content: removeDatasetCiteText(beforeContent, false)
|
||||
};
|
||||
}
|
||||
// 处于 Cite 缓冲区,判断是否满足条件
|
||||
else if (citeBuffer) {
|
||||
citeBuffer += text;
|
||||
|
||||
// 检查缓冲区长度是否达到完整Quote长度或已经流结束
|
||||
if (citeBuffer.length >= maxCiteBufferLength) {
|
||||
const content = removeDatasetCiteText(citeBuffer, false);
|
||||
citeBuffer = '';
|
||||
|
||||
return {
|
||||
content
|
||||
};
|
||||
} else {
|
||||
// 暂时不返回内容
|
||||
return { content: '' };
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
content: text
|
||||
};
|
||||
};
|
||||
const { content: pasedCiteContent } = parseCite(parsedThinkContent);
|
||||
|
||||
// Parse datset cite
|
||||
if (retainDatasetCite) {
|
||||
return {
|
||||
reasoningContent: parsedThinkReasoningContent,
|
||||
content: parsedThinkContent,
|
||||
responseContent: parsedThinkContent,
|
||||
finishReason
|
||||
responseContent: pasedCiteContent,
|
||||
finishReason: buffer_finishReason
|
||||
};
|
||||
}
|
||||
})();
|
||||
|
||||
// 缓存包含 [ 的字符串,直到超出 maxCiteBufferLength 再一次性返回
|
||||
const parseCite = (text: string) => {
|
||||
// 结束时,返回所有剩余内容
|
||||
if (isStreamEnd) {
|
||||
const content = citeBuffer + text;
|
||||
return {
|
||||
content: removeDatasetCiteText(content, false)
|
||||
};
|
||||
}
|
||||
buffer_reasoningContent += data.reasoningContent;
|
||||
buffer_content += data.content;
|
||||
|
||||
// 新内容包含 [,初始化缓冲数据
|
||||
if (text.includes('[')) {
|
||||
const index = text.indexOf('[');
|
||||
const beforeContent = citeBuffer + text.slice(0, index);
|
||||
citeBuffer = text.slice(index);
|
||||
|
||||
// beforeContent 可能是:普通字符串,带 [ 的字符串
|
||||
return {
|
||||
content: removeDatasetCiteText(beforeContent, false)
|
||||
};
|
||||
}
|
||||
// 处于 Cite 缓冲区,判断是否满足条件
|
||||
else if (citeBuffer) {
|
||||
citeBuffer += text;
|
||||
|
||||
// 检查缓冲区长度是否达到完整Quote长度或已经流结束
|
||||
if (citeBuffer.length >= maxCiteBufferLength) {
|
||||
const content = removeDatasetCiteText(citeBuffer, false);
|
||||
citeBuffer = '';
|
||||
|
||||
return {
|
||||
content
|
||||
};
|
||||
} else {
|
||||
// 暂时不返回内容
|
||||
return { content: '' };
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
content: text
|
||||
};
|
||||
};
|
||||
const { content: pasedCiteContent } = parseCite(parsedThinkContent);
|
||||
return data;
|
||||
};
|
||||
|
||||
const getResponseData = () => {
|
||||
return {
|
||||
reasoningContent: parsedThinkReasoningContent,
|
||||
content: parsedThinkContent,
|
||||
responseContent: pasedCiteContent,
|
||||
finishReason
|
||||
finish_reason: buffer_finishReason,
|
||||
usage: buffer_usage,
|
||||
reasoningContent: buffer_reasoningContent,
|
||||
content: buffer_content
|
||||
};
|
||||
};
|
||||
|
||||
const updateFinishReason = (finishReason: CompletionFinishReason) => {
|
||||
buffer_finishReason = finishReason;
|
||||
};
|
||||
|
||||
return {
|
||||
parsePart
|
||||
parsePart,
|
||||
getResponseData,
|
||||
updateFinishReason
|
||||
};
|
||||
};
|
||||
|
||||
@@ -11,40 +11,6 @@ export const beforeUpdateAppFormat = <T extends AppSchema['modules'] | undefined
|
||||
nodes: T;
|
||||
isPlugin: boolean;
|
||||
}) => {
|
||||
if (nodes) {
|
||||
// Check dataset maxTokens
|
||||
if (isPlugin) {
|
||||
let maxTokens = 16000;
|
||||
|
||||
nodes.forEach((item) => {
|
||||
if (
|
||||
item.flowNodeType === FlowNodeTypeEnum.chatNode ||
|
||||
item.flowNodeType === FlowNodeTypeEnum.tools
|
||||
) {
|
||||
const model =
|
||||
item.inputs.find((item) => item.key === NodeInputKeyEnum.aiModel)?.value || '';
|
||||
const chatModel = getLLMModel(model);
|
||||
const quoteMaxToken = chatModel.quoteMaxToken || 16000;
|
||||
|
||||
maxTokens = Math.max(maxTokens, quoteMaxToken);
|
||||
}
|
||||
});
|
||||
|
||||
nodes.forEach((item) => {
|
||||
if (item.flowNodeType === FlowNodeTypeEnum.datasetSearchNode) {
|
||||
item.inputs.forEach((input) => {
|
||||
if (input.key === NodeInputKeyEnum.datasetMaxTokens) {
|
||||
const val = input.value as number;
|
||||
if (val > maxTokens) {
|
||||
input.value = maxTokens;
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
nodes
|
||||
};
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import { Client } from '@modelcontextprotocol/sdk/client/index.js';
|
||||
import { SSEClientTransport } from '@modelcontextprotocol/sdk/client/sse.js';
|
||||
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';
|
||||
import { type ToolType } from '@fastgpt/global/core/app/type';
|
||||
import { type McpToolConfigType } from '@fastgpt/global/core/app/type';
|
||||
import { addLog } from '../../common/system/log';
|
||||
import { retryFn } from '@fastgpt/global/common/system/utils';
|
||||
|
||||
@@ -41,7 +41,7 @@ export class MCPClient {
|
||||
* Get available tools list
|
||||
* @returns List of tools
|
||||
*/
|
||||
public async getTools(): Promise<ToolType[]> {
|
||||
public async getTools(): Promise<McpToolConfigType[]> {
|
||||
try {
|
||||
const client = await this.getConnection();
|
||||
const response = await client.listTools();
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import { type FlowNodeTemplateType } from '@fastgpt/global/core/workflow/type/node.d';
|
||||
import { FlowNodeTypeEnum, defaultNodeVersion } from '@fastgpt/global/core/workflow/node/constant';
|
||||
import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
|
||||
import {
|
||||
appData2FlowNodeIO,
|
||||
pluginData2FlowNodeIO,
|
||||
@@ -14,10 +14,15 @@ import { cloneDeep } from 'lodash';
|
||||
import { MongoApp } from '../schema';
|
||||
import { type SystemPluginTemplateItemType } from '@fastgpt/global/core/workflow/type';
|
||||
import { getSystemPluginTemplates } from '../../../../plugins/register';
|
||||
import { getAppLatestVersion, getAppVersionById } from '../version/controller';
|
||||
import {
|
||||
checkIsLatestVersion,
|
||||
getAppLatestVersion,
|
||||
getAppVersionById
|
||||
} from '../version/controller';
|
||||
import { type PluginRuntimeType } from '@fastgpt/global/core/plugin/type';
|
||||
import { MongoSystemPlugin } from './systemPluginSchema';
|
||||
import { PluginErrEnum } from '@fastgpt/global/common/error/code/plugin';
|
||||
import { Types } from 'mongoose';
|
||||
|
||||
/*
|
||||
plugin id rule:
|
||||
@@ -90,20 +95,28 @@ const getSystemPluginTemplateById = async (
|
||||
|
||||
/* Format plugin to workflow preview node data */
|
||||
export async function getChildAppPreviewNode({
|
||||
id
|
||||
appId,
|
||||
versionId
|
||||
}: {
|
||||
id: string;
|
||||
appId: string;
|
||||
versionId?: string;
|
||||
}): Promise<FlowNodeTemplateType> {
|
||||
const app: ChildAppType = await (async () => {
|
||||
const { source, pluginId } = await splitCombinePluginId(id);
|
||||
const { source, pluginId } = await splitCombinePluginId(appId);
|
||||
|
||||
if (source === PluginSourceEnum.personal) {
|
||||
const item = await MongoApp.findById(id).lean();
|
||||
const item = await MongoApp.findById(appId).lean();
|
||||
if (!item) return Promise.reject('plugin not found');
|
||||
|
||||
const version = await getAppLatestVersion(id, item);
|
||||
const version = await getAppVersionById({ appId, versionId, app: item });
|
||||
|
||||
if (!version.versionId) return Promise.reject('App version not found');
|
||||
const isLatest =
|
||||
version.versionId && Types.ObjectId.isValid(version.versionId)
|
||||
? await checkIsLatestVersion({
|
||||
appId,
|
||||
versionId: version.versionId
|
||||
})
|
||||
: true;
|
||||
|
||||
return {
|
||||
id: String(item._id),
|
||||
@@ -118,7 +131,11 @@ export async function getChildAppPreviewNode({
|
||||
chatConfig: version.chatConfig
|
||||
},
|
||||
templateType: FlowNodeTemplateTypeEnum.teamApp,
|
||||
|
||||
version: version.versionId,
|
||||
versionLabel: version?.versionName || '',
|
||||
isLatestVersion: isLatest,
|
||||
|
||||
originCost: 0,
|
||||
currentCost: 0,
|
||||
hasTokenFee: false,
|
||||
@@ -175,7 +192,11 @@ export async function getChildAppPreviewNode({
|
||||
userGuide: app.userGuide,
|
||||
showStatus: app.showStatus,
|
||||
isTool: true,
|
||||
|
||||
version: app.version,
|
||||
versionLabel: app.versionLabel,
|
||||
isLatestVersion: app.isLatestVersion,
|
||||
|
||||
sourceHandle: isToolSet
|
||||
? getHandleConfig(false, false, false, false)
|
||||
: getHandleConfig(true, true, true, true),
|
||||
@@ -224,7 +245,7 @@ export async function getChildAppRuntimeById(
|
||||
templateType: FlowNodeTemplateTypeEnum.teamApp,
|
||||
|
||||
// 用不到
|
||||
version: item?.pluginData?.nodeVersion || defaultNodeVersion,
|
||||
version: item?.pluginData?.nodeVersion,
|
||||
originCost: 0,
|
||||
currentCost: 0,
|
||||
hasTokenFee: false,
|
||||
|
||||
@@ -119,6 +119,7 @@ const AppSchema = new Schema({
|
||||
defaultPermission: Number
|
||||
});
|
||||
|
||||
AppSchema.index({ type: 1 });
|
||||
AppSchema.index({ teamId: 1, updateTime: -1 });
|
||||
AppSchema.index({ teamId: 1, type: 1 });
|
||||
AppSchema.index(
|
||||
|
||||
@@ -1,8 +1,14 @@
|
||||
import { MongoDataset } from '../dataset/schema';
|
||||
import { getEmbeddingModel } from '../ai/model';
|
||||
import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
|
||||
import {
|
||||
AppNodeFlowNodeTypeMap,
|
||||
FlowNodeTypeEnum
|
||||
} from '@fastgpt/global/core/workflow/node/constant';
|
||||
import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
|
||||
import type { StoreNodeItemType } from '@fastgpt/global/core/workflow/type/node';
|
||||
import { MongoAppVersion } from './version/schema';
|
||||
import { checkIsLatestVersion } from './version/controller';
|
||||
import { Types } from '../../common/mongo';
|
||||
|
||||
export async function listAppDatasetDataByTeamIdAndDatasetIds({
|
||||
teamId,
|
||||
@@ -35,6 +41,46 @@ export async function rewriteAppWorkflowToDetail({
|
||||
}) {
|
||||
const datasetIdSet = new Set<string>();
|
||||
|
||||
// Add node(App Type) versionlabel and latest sign
|
||||
const appNodes = nodes.filter((node) => AppNodeFlowNodeTypeMap[node.flowNodeType]);
|
||||
const versionIds = appNodes
|
||||
.filter((node) => node.version && Types.ObjectId.isValid(node.version))
|
||||
.map((node) => node.version);
|
||||
|
||||
if (versionIds.length > 0) {
|
||||
const versionDataList = await MongoAppVersion.find(
|
||||
{
|
||||
_id: { $in: versionIds }
|
||||
},
|
||||
'_id versionName appId time'
|
||||
).lean();
|
||||
|
||||
const versionMap: Record<string, any> = {};
|
||||
|
||||
const isLatestChecks = await Promise.all(
|
||||
versionDataList.map(async (version) => {
|
||||
const isLatest = await checkIsLatestVersion({
|
||||
appId: version.appId,
|
||||
versionId: version._id
|
||||
});
|
||||
|
||||
return { versionId: String(version._id), isLatest };
|
||||
})
|
||||
);
|
||||
const isLatestMap = new Map(isLatestChecks.map((item) => [item.versionId, item.isLatest]));
|
||||
versionDataList.forEach((version) => {
|
||||
versionMap[String(version._id)] = version;
|
||||
});
|
||||
appNodes.forEach((node) => {
|
||||
if (!node.version) return;
|
||||
const versionData = versionMap[String(node.version)];
|
||||
if (versionData) {
|
||||
node.versionLabel = versionData.versionName;
|
||||
node.isLatestVersion = isLatestMap.get(String(node.version)) || false;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Get all dataset ids from nodes
|
||||
nodes.forEach((node) => {
|
||||
if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
|
||||
|
||||
@@ -15,6 +15,7 @@ export const getAppLatestVersion = async (appId: string, app?: AppSchema) => {
|
||||
if (version) {
|
||||
return {
|
||||
versionId: version._id,
|
||||
versionName: version.versionName,
|
||||
nodes: version.nodes,
|
||||
edges: version.edges,
|
||||
chatConfig: version.chatConfig || app?.chatConfig || {}
|
||||
@@ -22,6 +23,7 @@ export const getAppLatestVersion = async (appId: string, app?: AppSchema) => {
|
||||
}
|
||||
return {
|
||||
versionId: app?.pluginData?.nodeVersion,
|
||||
versionName: app?.name,
|
||||
nodes: app?.modules || [],
|
||||
edges: app?.edges || [],
|
||||
chatConfig: app?.chatConfig || {}
|
||||
@@ -47,6 +49,7 @@ export const getAppVersionById = async ({
|
||||
if (version) {
|
||||
return {
|
||||
versionId: version._id,
|
||||
versionName: version.versionName,
|
||||
nodes: version.nodes,
|
||||
edges: version.edges,
|
||||
chatConfig: version.chatConfig || app?.chatConfig || {}
|
||||
@@ -57,3 +60,22 @@ export const getAppVersionById = async ({
|
||||
// If the version does not exist, the latest version is returned
|
||||
return getAppLatestVersion(appId, app);
|
||||
};
|
||||
|
||||
export const checkIsLatestVersion = async ({
|
||||
appId,
|
||||
versionId
|
||||
}: {
|
||||
appId: string;
|
||||
versionId: string;
|
||||
}) => {
|
||||
const version = await MongoAppVersion.findOne(
|
||||
{
|
||||
appId,
|
||||
isPublish: true,
|
||||
_id: { $gt: versionId }
|
||||
},
|
||||
'_id'
|
||||
).lean();
|
||||
|
||||
return !version;
|
||||
};
|
||||
|
||||
@@ -61,6 +61,7 @@ const ChatItemSchema = new Schema({
|
||||
type: Array,
|
||||
default: []
|
||||
},
|
||||
errorMsg: String,
|
||||
userGoodFeedback: {
|
||||
type: String
|
||||
},
|
||||
|
||||
@@ -34,6 +34,10 @@ const ChatSchema = new Schema({
|
||||
ref: AppCollectionName,
|
||||
required: true
|
||||
},
|
||||
createTime: {
|
||||
type: Date,
|
||||
default: () => new Date()
|
||||
},
|
||||
updateTime: {
|
||||
type: Date,
|
||||
default: () => new Date()
|
||||
|
||||
@@ -32,6 +32,7 @@ type Props = {
|
||||
content: [UserChatItemType & { dataId?: string }, AIChatItemType & { dataId?: string }];
|
||||
metadata?: Record<string, any>;
|
||||
durationSeconds: number; //s
|
||||
errorMsg?: string;
|
||||
};
|
||||
|
||||
export async function saveChat({
|
||||
@@ -50,6 +51,7 @@ export async function saveChat({
|
||||
outLinkUid,
|
||||
content,
|
||||
durationSeconds,
|
||||
errorMsg,
|
||||
metadata = {}
|
||||
}: Props) {
|
||||
if (!chatId || chatId === 'NO_RECORD_HISTORIES') return;
|
||||
@@ -104,7 +106,8 @@ export async function saveChat({
|
||||
return {
|
||||
...item,
|
||||
[DispatchNodeResponseKeyEnum.nodeResponse]: nodeResponse,
|
||||
durationSeconds
|
||||
durationSeconds,
|
||||
errorMsg
|
||||
};
|
||||
}
|
||||
return item;
|
||||
|
||||
@@ -65,8 +65,8 @@ export const filterGPTMessageByMaxContext = async ({
|
||||
if (lastMessage.role === ChatCompletionRequestMessageRoleEnum.User) {
|
||||
const tokens = await countGptMessagesTokens([lastMessage, ...tmpChats]);
|
||||
maxContext -= tokens;
|
||||
// 该轮信息整体 tokens 超出范围,这段数据不要了
|
||||
if (maxContext < 0) {
|
||||
// 该轮信息整体 tokens 超出范围,这段数据不要了。但是至少保证一组。
|
||||
if (maxContext < 0 && chats.length > 0) {
|
||||
break;
|
||||
}
|
||||
|
||||
|
||||
@@ -2,7 +2,9 @@ import type {
|
||||
APIFileListResponse,
|
||||
ApiFileReadContentResponse,
|
||||
APIFileReadResponse,
|
||||
APIFileServer
|
||||
ApiDatasetDetailResponse,
|
||||
APIFileServer,
|
||||
APIFileItem
|
||||
} from '@fastgpt/global/core/dataset/apiDataset';
|
||||
import axios, { type Method } from 'axios';
|
||||
import { addLog } from '../../../common/system/log';
|
||||
@@ -89,7 +91,7 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
|
||||
`/v1/file/list`,
|
||||
{
|
||||
searchKey,
|
||||
parentId
|
||||
parentId: parentId || apiServer.basePath
|
||||
},
|
||||
'POST'
|
||||
);
|
||||
@@ -144,7 +146,8 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
|
||||
tmbId,
|
||||
url: previewUrl,
|
||||
relatedId: apiFileId,
|
||||
customPdfParse
|
||||
customPdfParse,
|
||||
getFormatText: true
|
||||
});
|
||||
return {
|
||||
title,
|
||||
@@ -164,9 +167,34 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
|
||||
return url;
|
||||
};
|
||||
|
||||
const getFileDetail = async ({
|
||||
apiFileId
|
||||
}: {
|
||||
apiFileId: string;
|
||||
}): Promise<ApiDatasetDetailResponse> => {
|
||||
const fileData = await request<ApiDatasetDetailResponse>(
|
||||
`/v1/file/detail`,
|
||||
{
|
||||
id: apiFileId
|
||||
},
|
||||
'GET'
|
||||
);
|
||||
|
||||
if (fileData) {
|
||||
return {
|
||||
id: fileData.id,
|
||||
name: fileData.name,
|
||||
parentId: fileData.parentId === null ? '' : fileData.parentId
|
||||
};
|
||||
}
|
||||
|
||||
return Promise.reject('File not found');
|
||||
};
|
||||
|
||||
return {
|
||||
getFileContent,
|
||||
listFiles,
|
||||
getFilePreviewUrl
|
||||
getFilePreviewUrl,
|
||||
getFileDetail
|
||||
};
|
||||
};
|
||||
|
||||
27
packages/service/core/dataset/apiDataset/index.ts
Normal file
27
packages/service/core/dataset/apiDataset/index.ts
Normal file
@@ -0,0 +1,27 @@
|
||||
import type {
|
||||
APIFileServer,
|
||||
YuqueServer,
|
||||
FeishuServer
|
||||
} from '@fastgpt/global/core/dataset/apiDataset';
|
||||
import { useApiDatasetRequest } from './api';
|
||||
import { useYuqueDatasetRequest } from '../yuqueDataset/api';
|
||||
import { useFeishuDatasetRequest } from '../feishuDataset/api';
|
||||
|
||||
export const getApiDatasetRequest = async (data: {
|
||||
apiServer?: APIFileServer;
|
||||
yuqueServer?: YuqueServer;
|
||||
feishuServer?: FeishuServer;
|
||||
}) => {
|
||||
const { apiServer, yuqueServer, feishuServer } = data;
|
||||
|
||||
if (apiServer) {
|
||||
return useApiDatasetRequest({ apiServer });
|
||||
}
|
||||
if (yuqueServer) {
|
||||
return useYuqueDatasetRequest({ yuqueServer });
|
||||
}
|
||||
if (feishuServer) {
|
||||
return useFeishuDatasetRequest({ feishuServer });
|
||||
}
|
||||
return Promise.reject('Can not find api dataset server');
|
||||
};
|
||||
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Reference in New Issue
Block a user