Compare commits

...

51 Commits

Author SHA1 Message Date
Archer
e860c56b77 perf: delete dataset (#3949)
* fix: collection list count

* fix: collection list count

* ai proxy ui

* perf: delete dataset

* perf: add dataset text index

* update doc
2025-03-03 12:49:13 +08:00
Archer
efac5312b4 fix: rerank model cannot use ai proxy (#3945)
* fix: collection list count

* fix: collection list count

* fix: rerank model cannot use ai proxy

* mongo init
2025-03-03 11:49:35 +08:00
Finley Ge
4bc7f21182 fix: add order:true to all create transactions (#3948) 2025-03-03 11:37:51 +08:00
gggaaallleee
113e8f711f add env proxypool (#3939) 2025-03-02 17:50:03 +08:00
Archer
abc6dffb41 4.8.23 dev (#3932)
* fix: collection list count

* fix: collection list count

* update doc

* perf: init log

* yml
2025-02-28 19:18:12 +08:00
gggaaallleee
f7b2a57ca3 1 (#3924) 2025-02-28 19:00:58 +08:00
Archer
cf0aaa1091 fix: invalid dataset data clear (#3927)
* fix: collection list count

* fix: collection list count

* fix: invalid dataset data clear

* update ts

* perf: cron clear invalid data

* perf: init

* perf: clear invalid code

* update init

* perf: clear invalid code

* perf: clear invalid code

* perf: init count

* batch init

* batch init

* batch init

* batch init

* add comment

* perf: init

* fix: api proxy type
2025-02-28 17:49:20 +08:00
Archer
ac4255ea0c 4.8.23 dev (#3926)
* fix: collection list count

* fix: collection list count

* fix: ts
2025-02-28 12:33:09 +08:00
Archer
df4d6f86ce fix: delete dataset field error (#3925)
* fix: collection list count

* fix: collection list count

* update doc

* perf: tts selector ui

* fix: delete dataset field error

* doc
2025-02-28 12:29:18 +08:00
heheer
e697fda82f fix: export chat log - chat detail order (#3923) 2025-02-28 11:33:46 +08:00
Archer
1aa319e7aa Update package.json (#3919) 2025-02-27 22:25:26 +08:00
Archer
fc9e614f88 4.8.23 dev (#3917)
* fix: icon refresh

* fix: aiproxy http request

* fix: collection list count

* fix: collection list count

* fix: tts selector name

* update action
2025-02-27 22:15:48 +08:00
Archer
1121ea33bd 更新 docker.md (#3913) 2025-02-27 17:02:06 +08:00
Finley Ge
9bbee60cde fix: ts error (#3911) 2025-02-27 16:31:14 +08:00
Finley Ge
9f57ad0017 fix: mongoose strictquery to false (#3906) 2025-02-27 11:25:29 +08:00
Archer
c3d3b30d7e update code positon (#3907) 2025-02-27 10:30:43 +08:00
Archer
fb0eb49196 fix: pptx encoding (#3905) 2025-02-27 10:04:59 +08:00
ZongLiang
27ebd2e8cf Update parseOffice.ts (#3901)
更新本地导入pptx文件提示文件编码错误
The argument 'windows-1252' is invalid encoding. Received 'encoding'
2025-02-27 09:57:34 +08:00
Archer
81a06718d8 feat: ai proxy v1 (#3898)
* feat: ai proxy v1

* perf: ai proxy channel crud

* feat: ai proxy logs

* feat: channel test

* doc

* update lock
2025-02-27 09:56:52 +08:00
Archer
3c382d1240 Update intro.md (#3900) 2025-02-26 22:37:56 +08:00
Finley Ge
747bb303ec chore: upgrade mongoose to v8.10.x for security (#3868)
* chore: upgrade mongoose to v8.10.x for security

* chore: remove duplicate code

* fix: ts error
2025-02-26 18:32:19 +08:00
Finley Ge
cf9c8e9f6a fix: leave team and refresh memberlist (#3893) 2025-02-26 18:29:05 +08:00
Archer
5d5bee9e41 remove markdown format;refresh username;perf: latext render (#3877)
* refresh username

* remove md format

* perf: latext render

* ignore big image

* model config
2025-02-25 16:16:30 +08:00
Archer
4f0dd96699 perf: work order tip (#3874) 2025-02-24 20:26:15 +08:00
Finley Ge
fb6dbaf2d6 feat/workorder (#3860)
* feat: workorder

* pref: workorder button

* chore: move workorder to common

* chore: format code

* pref: style
2025-02-24 19:59:06 +08:00
风沐白
ffc1520f4c Update quick-start.md (#3873) 2025-02-24 19:56:56 +08:00
Archer
255764400f feat: model config required check;feat: dataset text model default setting (#3866)
* feat: model config required check

* feat: dataset text model default setting

* perf: collection list count

* fix: ts

* remove index count
2025-02-24 19:55:49 +08:00
heheer
3bfe802c48 fix collection folder tags filter (#3853)
* fix collection folder tags filter

* add comment

* fix
2025-02-24 17:43:31 +08:00
YeYuheng
2bf17dbb87 Marker doc update (#3869)
* update-marker-doc

* marker.md

* marker.md
2025-02-24 13:13:05 +08:00
Archer
8d766372fe update doc (#3840)
* update doc

* update doc
2025-02-20 10:40:00 +08:00
Archer
ca5717936b update doc (#3836) 2025-02-19 22:32:08 +08:00
Archer
6762723b10 perf: ery extension and fix filter same embedding result (#3833)
* perf: ery extension and fix filter same embedding result

* fix: extract node too long

* perf: ui

* perf: not chatId will auto save

* fix: laf

* fix: member load

* feat: add completions unstream error response

* feat: add completions unstream error response

* updat emodel provider
2025-02-19 22:16:43 +08:00
heheer
8604cbd021 fix source name (#3834) 2025-02-19 20:42:30 +08:00
Finley Ge
206325bc5f chore: team, orgs, search and so on (#3807)
* feat: clb search support username, memberName, contacts

* feat: popup org names

* feat: update team member table

* feat: restore the member

* feat: search user in team member table

* feat: bind contact

* feat: export members

* feat: org tab could delete member

* feat: org table search

* feat: team notification account bind

* feat: permission tab search

* fix: wecom sso

* chore(init): copy notificationAccount to user.contact

* chore: adjust

* fix: ts error

* fix: useConfirm iconColor customization

* pref: fe

* fix: style

* fix: fix team member manage

* pref: enlarge team member pagesize

* pref: initv4822

* fix: pageSize

* pref: initscritpt
2025-02-19 17:27:19 +08:00
Archer
5fd520c794 perf: gemini config (#3828)
* doc

* doc

* perf: gemini config
2025-02-19 12:00:31 +08:00
Archer
09205e4666 fix: price page init data;perf: usage code;fix: reasoning tokens;fix: workflow basic node cannot upgrade (#3816)
* fix: img read

* fix: price page init data

* perf: ai model avatar

* perf: refresh in change team

* perf: null checker

* perf: usage code

* fix: reasoning tokens

* fix: workflow basic node cannot upgrade

* perf: model refresh

* perf: icon refresh
2025-02-18 20:50:25 +08:00
Finley Ge
ccf28d83b8 fix: app version addSourcemember tmbid could be empty (#3822) 2025-02-18 20:26:49 +08:00
LGiki
420aaad48e chore: fix typo in docs (#3819) 2025-02-18 20:25:51 +08:00
heheer
8ba2339890 download fetch baseurl & node select dnd (#3820) 2025-02-18 20:25:15 +08:00
Archer
e7b8934367 Update 4818.md (#3818) 2025-02-18 14:26:21 +08:00
Finley Ge
3e13397614 fix: refresh memberlist when switching account (#3814) 2025-02-18 13:54:56 +08:00
Archer
b14674cc6f fix: whisper checker;fix: img read (#3813)
* fix: img read

* fix: whisper checker

* perf: dev doc

* perf: dev doc

* remove invalid code
2025-02-18 10:08:25 +08:00
Archer
4d20274a97 feat: think tag parse (#3805) (#3808)
* feat: think tag parse

* remove some model config

* feat: parse think tag test
2025-02-17 20:57:36 +08:00
heheer
4447e40364 fix template market simple app (#3804) 2025-02-17 20:56:46 +08:00
John Chen
23949230ee fix document (#3806)
V2版本“获取集合列表”接口的path区分了大小写,使用/api/core/dataset/collection/listv2会返回404,必须使用大写V
2025-02-17 20:55:34 +08:00
saikidev
cd7a897304 chore: add ppio provider (#3789) 2025-02-14 17:04:43 +08:00
Archer
18aff8b8db update yml version (#3787) 2025-02-14 12:50:54 +08:00
Archer
d2b60ec785 fix: model check circle tip (#3786)
* model config

* feat: normalization embedding

* remove log

* version doc

* version doc

* fix: model check circle tip

* uml
2025-02-14 11:42:14 +08:00
a.e.
1226fe42a1 fix: skip thirdparty sso state verification (#3721) (#3782) 2025-02-14 11:39:34 +08:00
Finley Ge
abd375cdec fix: app/dataset list api return private flag (#3784) 2025-02-14 11:38:48 +08:00
Archer
7aacce8b0b 4.9.0 test (#3779)
* model config

* feat: normalization embedding

* remove log

* version doc

* version doc
2025-02-13 16:27:41 +08:00
374 changed files with 13602 additions and 2529 deletions

View File

@@ -68,14 +68,3 @@ jobs:
SEALOS_TYPE: 'pr_comment'
SEALOS_FILENAME: 'report.md'
SEALOS_REPLACE_TAG: 'DEFAULT_REPLACE_DEPLOY'
helm-check:
runs-on: ubuntu-20.04
steps:
- name: Checkout
uses: actions/checkout@v3
- name: Helm Check
run: |
helm dependency update files/helm/fastgpt
helm lint files/helm/fastgpt
helm package files/helm/fastgpt

View File

@@ -24,6 +24,6 @@ jobs:
export APP_VERSION=${{ steps.vars.outputs.tag }}
export HELM_VERSION=${{ steps.vars.outputs.tag }}
export HELM_REPO=ghcr.io/${{ github.repository_owner }}
helm dependency update files/helm/fastgpt
helm package files/helm/fastgpt --version ${HELM_VERSION}-helm --app-version ${APP_VERSION} -d bin
helm dependency update deploy/helm/fastgpt
helm package deploy/helm/fastgpt --version ${HELM_VERSION}-helm --app-version ${APP_VERSION} -d bin
helm push bin/fastgpt-${HELM_VERSION}-helm.tgz oci://${HELM_REPO}

View File

@@ -58,7 +58,7 @@
"body": [
"import '@/pages/api/__mocks__/base';",
"import { root } from '@/pages/api/__mocks__/db/init';",
"import { getTestRequest } from '@/test/utils';",
"import { getTestRequest } from '@fastgpt/service/test/utils'; ;",
"import { AppErrEnum } from '@fastgpt/global/common/error/code/app';",
"import handler from './demo';",
"",

View File

@@ -114,15 +114,15 @@ services:
# fastgpt
sandbox:
container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt-sandbox:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.23-fix # 阿里云
networks:
- fastgpt
restart: always
fastgpt:
container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.23-fix # 阿里云
ports:
- 3000:3000
networks:
@@ -133,7 +133,7 @@ services:
- sandbox
restart: always
environment:
# 前端访问地址: http://localhost:3000
# 前端外部可访问地址,用于自动补全文件资源路径。例如 https:fastgpt.cn不能填 localhost。这个值可以不填不填则发给模型的图片会是一个相对路径而不是全路径模型可能伪造Host。
- FE_DOMAIN=
# root 密码,用户名为: root。如果需要修改 root 密码,直接修改这个环境变量,并重启即可。
- DEFAULT_ROOT_PSW=1234

View File

@@ -72,15 +72,15 @@ services:
# fastgpt
sandbox:
container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt-sandbox:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.23-fix # 阿里云
networks:
- fastgpt
restart: always
fastgpt:
container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.23-fix # 阿里云
ports:
- 3000:3000
networks:
@@ -91,7 +91,7 @@ services:
- sandbox
restart: always
environment:
# 前端访问地址: http://localhost:3000
# 前端外部可访问地址,用于自动补全文件资源路径。例如 https:fastgpt.cn不能填 localhost。这个值可以不填不填则发给模型的图片会是一个相对路径而不是全路径模型可能伪造Host。
- FE_DOMAIN=
# root 密码,用户名为: root。如果需要修改 root 密码,直接修改这个环境变量,并重启即可。
- DEFAULT_ROOT_PSW=1234

View File

@@ -53,15 +53,15 @@ services:
wait $$!
sandbox:
container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt-sandbox:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.23-fix # 阿里云
networks:
- fastgpt
restart: always
fastgpt:
container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.20-fix2 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20-fix2 # 阿里云
image: ghcr.io/labring/fastgpt:v4.8.23-fix # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.23-fix # 阿里云
ports:
- 3000:3000
networks:
@@ -71,7 +71,7 @@ services:
- sandbox
restart: always
environment:
# 前端访问地址: http://localhost:3000
# 前端外部可访问地址,用于自动补全文件资源路径。例如 https:fastgpt.cn不能填 localhost。这个值可以不填不填则发给模型的图片会是一个相对路径而不是全路径模型可能伪造Host。
- FE_DOMAIN=
# root 密码,用户名为: root。如果需要修改 root 密码,直接修改这个环境变量,并重启即可。
- DEFAULT_ROOT_PSW=1234

Binary file not shown.

After

Width:  |  Height:  |  Size: 332 KiB

View File

@@ -31,9 +31,9 @@ weight: 920
3 个模型代码分别为:
1. [https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-base](https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-base)
2. [https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-large](https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-large)
3. [https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-v2-m3](https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-reranker-v2-m3)
1. [https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-base](https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-base)
2. [https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-large](https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-large)
3. [https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-v2-m3](https://github.com/labring/FastGPT/tree/main/plugins/rerank-bge/bge-reranker-v2-m3)
### 3. 安装依赖

View File

@@ -19,7 +19,7 @@ PDF 是一个相对复杂的文件格式,在 FastGPT 内置的 pdf 解析器
### 1. 按照 Marker
参考文档 [Marker 安装教程](https://github.com/labring/FastGPT/tree/main/python/pdf-marker),安装 Marker 模型。封装的 API 已经适配了 FastGPT 自定义解析服务。
参考文档 [Marker 安装教程](https://github.com/labring/FastGPT/tree/main/plugins/model/pdf-marker),安装 Marker 模型。封装的 API 已经适配了 FastGPT 自定义解析服务。
这里介绍快速 Docker 安装的方法:

View File

@@ -118,7 +118,7 @@ brew install orbstack
非 Linux 环境或无法访问外网环境,可手动创建一个目录,并下载配置文件和对应版本的`docker-compose.yml`在这个文件夹中依据下载的配置文件运行docker若作为本地开发使用推荐`docker-compose-pgvector`版本,并且自行拉取并运行`sandbox``fastgpt`并在docker配置文件中注释掉`sandbox``fastgpt`的部分
- [config.json](https://raw.githubusercontent.com/labring/FastGPT/refs/heads/main/projects/app/data/config.json)
- [docker-compose.yml](https://github.com/labring/FastGPT/blob/main/files/docker) (注意,不同向量库版本的文件不一样)
- [docker-compose.yml](https://github.com/labring/FastGPT/blob/main/deploy/docker) (注意,不同向量库版本的文件不一样)
{{% alert icon="🤖" context="success" %}}
@@ -134,11 +134,11 @@ cd fastgpt
curl -O https://raw.githubusercontent.com/labring/FastGPT/main/projects/app/data/config.json
# pgvector 版本(测试推荐,简单快捷)
curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/files/docker/docker-compose-pgvector.yml
curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/deploy/docker/docker-compose-pgvector.yml
# milvus 版本
# curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/files/docker/docker-compose-milvus.yml
# curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/deploy/docker/docker-compose-milvus.yml
# zilliz 版本
# curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/files/docker/docker-compose-zilliz.yml
# curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/main/deploy/docker/docker-compose-zilliz.yml
```
### 2. 修改环境变量
@@ -201,6 +201,8 @@ docker restart oneapi
在OneApi中添加合适的AI模型渠道。[点击查看相关教程](/docs/development/modelconfig/one-api/)
只需要添加模型即可模板已经配置好了oneapi的连接地址和令牌无需变更。
### 5. 访问 FastGPT
目前可以通过 `ip:3000` 直接访问(注意防火墙)。登录用户名为 `root`,密码为`docker-compose.yml`环境变量里设置的 `DEFAULT_ROOT_PSW`
@@ -211,7 +213,7 @@ docker restart oneapi
### 6. 配置模型
务必先配置至少一组模型,否则系统无法正常使用。
登录FastGPT后进入模型配置页面务必先配置至少一个语言模型和一个向量模型,否则系统无法正常使用。
[点击查看模型配置教程](/docs/development/modelConfig/intro/)

View File

@@ -142,6 +142,10 @@ OneAPI 的 API Key 配置错误,需要修改`OPENAI_API_KEY`环境变量,并
3. ....
### Tiktoken 下载失败
由于 OneAPI 会在启动时从网络下载一个 tiktoken 的依赖,如果网络异常,就会导致启动失败。可以参考[OneAPI 离线部署](https://blog.csdn.net/wanh/article/details/139039216)解决。
## 四、常见模型问题
### 如何检查模型可用性问题

View File

@@ -15,8 +15,8 @@ weight: 705
- [Git](http://git-scm.com/)
- [Docker](https://www.docker.com/)(构建镜像)
- [Node.js v18.17 / v20.x](http://nodejs.org)版本尽量一样可以使用nvm管理node版本
- [pnpm](https://pnpm.io/) 版本 8.6.0 (目前官方的开发环境)
- [Node.js v20.14.0](http://nodejs.org)版本尽量一样可以使用nvm管理node版本
- [pnpm](https://pnpm.io/) 推荐版本 9.4.0 (目前官方的开发环境)
- make命令: 根据不同平台,百度安装 (官方是GNU Make 4.3)
## 开始本地开发
@@ -77,8 +77,6 @@ Mongo 数据库需要注意,需要注意在连接地址中增加 `directConnec
可参考项目根目录下的 `dev.md`,第一次编译运行可能会有点慢,需要点耐心哦
```bash
# 给自动化脚本代码执行权限(非 linux 系统, 可以手动执行里面的 postinstall.sh 文件内容)
chmod -R +x ./scripts/
# 代码根目录下执行,会安装根 package、projects 和 packages 内所有依赖
# 如果提示 isolate-vm 安装失败可以参考https://github.com/laverdet/isolated-vm?tab=readme-ov-file#requirements
pnpm i

View File

@@ -23,7 +23,7 @@ weight: 744
{{% alert icon=" " context="info" %}}
- [SiliconCloud(硅基流动)](https://cloud.siliconflow.cn/i/TR9Ym0c4): 提供开源模型调用的平台。
- [Sealos AIProxy](https://hzh.sealos.run/?openapp=system-aiproxy): 提供国内各家模型代理,无需逐一申请 api。
- [Sealos AIProxy](https://cloud.sealos.run/?uid=fnWRt09fZP&openapp=system-aiproxy): 提供国内各家模型代理,无需逐一申请 api。
{{% /alert %}}
在 OneAPI 配置好模型后,你就可以打开 FastGPT 页面,启用对应模型了。
@@ -43,8 +43,7 @@ weight: 744
{{% alert icon="🤖 " context="success" %}}
注意:
1. 目前语音识别模型和重排模型仅会生效一个,所以配置时候,只需要配置一个即可。
2. 系统必须至少有一个语言模型和一个索引模型才能正常使用。
3. 使用知识库功能,至少要有一个语言模型,用于知识库文件处理(可以在模型配置时候打开该开关),否则知识库会报错。
2. 系统至少需要一个语言模型和一个索引模型才能正常使用。
{{% /alert %}}
#### 核心配置
@@ -468,4 +467,4 @@ OneAPI 的语言识别接口,无法正确的识别其他模型(会始终识
"charsPointsPrice": 0
}
}
```
```

View File

@@ -7,6 +7,12 @@ toc: true
weight: 852
---
# 如何获取 AppId
可在应用详情的路径里获取 AppId。
![](/imgs/appid.png)
# 发起对话
{{% alert icon="🤖 " context="success" %}}
@@ -102,8 +108,8 @@ curl --location --request POST 'http://localhost:3000/api/v1/chat/completions' \
{{% alert context="info" %}}
- headers.Authorization: Bearer {{apikey}}
- chatId: string | undefined 。
-`undefined` 时(不传入),不使用 FastGpt 提供的上下文功能,完全通过传入的 messages 构建上下文。 不会将你的记录存储到数据库中,你也无法在记录汇总中查阅到。
-`非空字符串`时,意味着使用 chatId 进行对话,自动从 FastGpt 数据库取历史记录,并使用 messages 数组最后一个内容作为用户问题。请自行确保 chatId 唯一长度小于250通常可以是自己系统的对话框ID。
-`undefined` 时(不传入),不使用 FastGpt 提供的上下文功能,完全通过传入的 messages 构建上下文。
-`非空字符串`时,意味着使用 chatId 进行对话,自动从 FastGpt 数据库取历史记录,并使用 messages 数组最后一个内容作为用户问题,其余 message 会被忽略。请自行确保 chatId 唯一长度小于250通常可以是自己系统的对话框ID。
- messages: 结构与 [GPT接口](https://platform.openai.com/docs/api-reference/chat/object) chat模式一致。
- responseChatItemId: string | undefined 。如果传入,则会将该值作为本次对话的响应消息的 IDFastGPT 会自动将该 ID 存入数据库。请确保,在当前`chatId`下,`responseChatItemId`是唯一的。
- detail: 是否返回中间值(模块状态,响应的完整结果等),`stream模式`下会通过`event`进行区分,`非stream模式`结果保存在`responseData`中。

View File

@@ -735,7 +735,7 @@ data 为集合的 ID。
**4.8.19+**
```bash
curl --location --request POST 'http://localhost:3000/api/core/dataset/collection/listv2' \
curl --location --request POST 'http://localhost:3000/api/core/dataset/collection/listV2' \
--header 'Authorization: Bearer {{authorization}}' \
--header 'Content-Type: application/json' \
--data-raw '{

View File

@@ -1,6 +1,6 @@
---
title: 'Api Key 使用与鉴权'
description: 'FastGPT Api Key 使用与鉴权'
title: 'OpenAPI 介绍'
description: 'FastGPT OpenAPI 介绍'
icon: 'key'
draft: false
toc: true
@@ -27,6 +27,7 @@ FastGPT 的 API Key **有 2 类**,一类是全局通用的 key (无法直接
| --------------------- | --------------------- |
| ![](/imgs/fastgpt-api2.jpg) | ![](/imgs/fastgpt-api1.jpg) |
## 基本配置
OpenAPI 中,所有的接口都通过 Header.Authorization 进行鉴权。

View File

@@ -1,5 +1,5 @@
---
title: 'V4.8.18'
title: 'V4.8.18(包含升级脚本)'
description: 'FastGPT V4.8.18 更新说明'
icon: 'upgrade'
draft: false

View File

@@ -20,7 +20,7 @@ SANDBOX_URL=内网地址
## Docker 部署
可以拉取最新 [docker-compose.yml](https://github.com/labring/FastGPT/blob/main/files/docker/docker-compose.yml) 文件参考
可以拉取最新 [docker-compose.yml](https://github.com/labring/FastGPT/blob/main/deploy/docker/docker-compose.yml) 文件参考
1. 新增一个容器 `sandbox`
2. fastgpt 和 fastgpt-pro(商业版) 容器新增环境变量: `SANDBOX_URL`

View File

@@ -1,13 +1,21 @@
---
title: 'V4.8.21(进行中)'
title: 'V4.8.21'
description: 'FastGPT V4.8.21 更新说明'
icon: 'upgrade'
draft: false
toc: true
weight: 804
weight: 803
---
## 更新指南
### 1. 做好数据库备份
### 2. 更新镜像:
- 更新 fastgpt 镜像 tag: v4.8.21-fix
- 更新 fastgpt-pro 商业版镜像 tag: v4.8.21-fix
- Sandbox 镜像无需更新
## 完整更新内容

View File

@@ -0,0 +1,61 @@
---
title: 'V4.8.22(包含升级脚本)'
description: 'FastGPT V4.8.22 更新说明'
icon: 'upgrade'
draft: false
toc: true
weight: 802
---
## 🌟更新指南
### 1. 做好数据库备份
### 2. 更新镜像:
- 更新 fastgpt 镜像 tag: v4.8.22
- 更新 fastgpt-pro 商业版镜像 tag: v4.8.22
- Sandbox 镜像无需更新
### 3. 运行升级脚本
仅商业版,并提供 Saas 服务的用户需要运行该升级脚本。
从任意终端,发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`{{host}} 替换成**FastGPT 域名**。
```bash
curl --location --request POST 'https://{{host}}/api/admin/initv4822' \
--header 'rootkey: {{rootkey}}' \
--header 'Content-Type: application/json'
```
会迁移联系方式到对应用户表中。
## 🚀 新增内容
1. AI 对话节点解析 `<think></think>` 标签内容作为思考链,便于各类模型进行思考链输出。需主动开启模型输出思考。
2. 对话 API 优化,无论是否传递 chatId都会保存对话日志。未传递 chatId则随机生成一个 chatId 来进行存储。
3. ppio 模型提供商
## ⚙️ 优化
1. 模型未配置时提示,减少冲突提示。
2. 使用记录代码。
3. 内容提取节点,字段描述过长时换行。同时修改其输出名用 key而不是 description。
4. 团队管理交互。
5. 对话接口,非流响应,增加报错字段。
## 🐛 修复
1. 思考内容未进入到输出 Tokens.
2. 思考链流输出时,有时与正文顺序偏差。
3. API 调用工作流,如果传递的图片不支持 Head 检测时,图片会被过滤。已增加该类错误检测,避免被错误过滤。
4. 模板市场部分模板错误。
5. 免登录窗口无法正常判断语言识别是否开启。
6. 对话日志导出,未兼容 sub path。
7. 切换团队时未刷新成员列表
8. list 接口在联查 member 时,存在空指针可能性。
9. 工作流基础节点无法升级。
10. 向量检索结果未去重。
11. 用户选择节点无法正常连线。
12. 对话记录保存时source 未正常记录。

View File

@@ -0,0 +1,54 @@
---
title: 'V4.8.23'
description: 'FastGPT V4.8.23 更新说明'
icon: 'upgrade'
draft: false
toc: true
weight: 802
---
## 更新指南
### 1. 做好数据库备份
### 2. 更新镜像:
- 更新 fastgpt 镜像 tag: v4.8.23-fix
- 更新 fastgpt-pro 商业版镜像 tag: v4.8.23-fix
- Sandbox 镜像无需更新
### 3. 运行升级脚本
从任意终端,发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`{{host}} 替换成**FastGPT 域名**。
```bash
curl --location --request POST 'https://{{host}}/api/admin/initv4823' \
--header 'rootkey: {{rootkey}}' \
--header 'Content-Type: application/json'
```
脚本会清理一些知识库脏数据,主要是多余的全文索引。
## 🚀 新增内容
1. 增加默认“知识库文本理解模型”配置
2. AI proxy V1版可替换 OneAPI使用同时提供完整模型调用日志便于排查问题。
3. 增加工单入口支持。
## ⚙️ 优化
1. 模型配置表单,增加必填项校验。
2. 集合列表数据统计方式,提高大数据量统计性能。
3. 优化数学公式,转义 Latex 格式成 Markdown 格式。
4. 解析文档图片,图片太大时,自动忽略。
5. 时间选择器当天开始时间自动设0结束设置设 23:59:59避免 UI 与实际逻辑偏差。
6. 升级 mongoose 库版本依赖。
## 🐛 修复
1. 标签过滤时,子文件夹未成功过滤。
2. 暂时移除 md 阅读优化,避免链接分割错误。
3. 离开团队时,未刷新成员列表。
4. PPTX 编码错误,导致解析失败。
5. 删除知识库单条数据时,全文索引未跟随删除。
6. 修复 Mongo Dataset text 索引在查询数据时未生效。

View File

@@ -15,7 +15,7 @@ weight: 821
## V4.8.3 更新说明
1. 新增 - 支持 Milvus 数据库, 可参考最新的 [docker-compose-milvus.yml](https://github.com/labring/FastGPT/blob/main/files/docker/docker-compose-milvus.yml).
1. 新增 - 支持 Milvus 数据库, 可参考最新的 [docker-compose-milvus.yml](https://github.com/labring/FastGPT/blob/main/deploy/docker/docker-compose-milvus.yml).
2. 新增 - 给 chat 接口 empty answer 增加 log便于排查模型问题。
3. 新增 - ifelse判断器字符串支持正则。
4. 新增 - 代码运行支持 console.log 输出调试。

View File

@@ -7,11 +7,11 @@ toc: true
weight: 102
---
更多使用技巧,[查看视教程](https://www.bilibili.com/video/BV1sH4y1T7s9)
更多使用技巧,[查看视教程](https://www.bilibili.com/video/BV1sH4y1T7s9)
## 知识库
开始前请准备一份测试电子文档WORDPDFTXTexcelmarkdown 都可以,比如公司休假制度不涉密的销售说辞产品知识等等。
开始前请准备一份测试电子文档WORDPDFTXTexcelmarkdown 都可以,比如公司休假制度不涉密的销售说辞产品知识等等。
这里使用 FastGPT 中文 README 文件为例。
@@ -31,7 +31,7 @@ weight: 102
![](/imgs/upload-data.png)
点击上传后我们需要等待数据处理完成,到我们上传的文件状态为可用。
点击上传后我们需要等待数据处理完成,到我们上传的文件状态为可用。
![](/imgs/upload-data2.png)

View File

@@ -20,7 +20,7 @@ weight: 502
![](/imgs/fastgpt-api1.jpg)
{{% alert icon="🍅" context="success" %}}
Tips: 安全起见,你可以设置一个额度或者过期时间,放置 key 被滥用。
Tips: 安全起见,你可以设置一个额度或者过期时间,防止 key 被滥用。
{{% /alert %}}

View File

@@ -7,7 +7,7 @@
"format-code": "prettier --config \"./.prettierrc.js\" --write \"./**/src/**/*.{ts,tsx,scss}\"",
"format-doc": "zhlint --dir ./docSite *.md --fix",
"gen:theme-typings": "chakra-cli tokens packages/web/styles/theme.ts --out node_modules/.pnpm/node_modules/@chakra-ui/styled-system/dist/theming.types.d.ts",
"postinstall": "sh ./scripts/postinstall.sh",
"postinstall": "pnpm gen:theme-typings",
"initIcon": "node ./scripts/icon/init.js",
"previewIcon": "node ./scripts/icon/index.js",
"api:gen": "tsc ./scripts/openapi/index.ts && node ./scripts/openapi/index.js && npx @redocly/cli build-docs ./scripts/openapi/openapi.json -o ./projects/app/public/openapi/index.html",

3
packages/README.md Normal file
View File

@@ -0,0 +1,3 @@
# 目录说明
该目录为 FastGPT 的依赖包,多端复用。

View File

@@ -4,6 +4,7 @@ import { ErrType } from '../errorCode';
/* dataset: 501000 */
export enum DatasetErrEnum {
unExist = 'unExistDataset',
unExistCollection = 'unExistCollection',
unAuthDataset = 'unAuthDataset',
unCreateCollection = 'unCreateCollection',
unAuthDatasetCollection = 'unAuthDatasetCollection',
@@ -28,6 +29,10 @@ const datasetErr = [
statusText: DatasetErrEnum.unExist,
message: 'core.dataset.error.unExistDataset'
},
{
statusText: DatasetErrEnum.unExistCollection,
message: i18nT('common:error_collection_not_exist')
},
{
statusText: DatasetErrEnum.unAuthDataset,
message: 'core.dataset.error.unAuthDataset'

View File

@@ -20,4 +20,4 @@ export const ReadFileBaseUrl = `${process.env.FILE_DOMAIN || process.env.FE_DOMA
export const documentFileType = '.txt, .docx, .csv, .xlsx, .pdf, .md, .html, .pptx';
export const imageFileType =
'.jpg, .jpeg, .png, .gif, .bmp, .webp, .svg, .tiff, .tif, .ico, .heic, .heif, .avif';
'.jpg, .jpeg, .png, .gif, .bmp, .webp, .svg, .tiff, .tif, .ico, .heic, .heif, .avif, .raw, .cr2, .nef, .arw, .dng, .psd, .ai, .eps, .emf, .wmf, .jfif, .exif, .pgm, .ppm, .pbm, .jp2, .j2k, .jpf, .jpx, .jpm, .mj2, .xbm, .pcx';

View File

@@ -1,5 +1,5 @@
import { detect } from 'jschardet';
import { documentFileType, imageFileType } from './constants';
import { documentFileType } from './constants';
import { ChatFileTypeEnum } from '../../core/chat/constants';
import { UserChatItemValueItemType } from '../../core/chat/type';
import * as fs from 'fs';
@@ -25,6 +25,7 @@ export const detectFileEncodingByPath = async (path: string) => {
const fd = await fs.promises.open(path, 'r');
try {
// Read file head
// @ts-ignore
const { bytesRead } = await fd.read(buffer, 0, MAX_BYTES, 0);
const actualBuffer = buffer.slice(0, bytesRead);
@@ -37,40 +38,49 @@ export const detectFileEncodingByPath = async (path: string) => {
// Url => user upload file type
export const parseUrlToFileType = (url: string): UserChatItemValueItemType['file'] | undefined => {
if (typeof url !== 'string') return;
const parseUrl = new URL(url, 'https://locaohost:3000');
const filename = (() => {
// Check base64 image
if (url.startsWith('data:image/')) {
const mime = url.split(',')[0].split(':')[1].split(';')[0];
return `image.${mime.split('/')[1]}`;
}
// Old version file url: https://xxx.com/file/read?filename=xxx.pdf
const filenameQuery = parseUrl.searchParams.get('filename');
if (filenameQuery) return filenameQuery;
// Handle base64 image
if (url.startsWith('data:')) {
const matches = url.match(/^data:([^;]+);base64,/);
if (!matches) return;
// Common file https://xxx.com/xxx.pdf?xxxx=xxx
const pathname = parseUrl.pathname;
if (pathname) return pathname.split('/').pop();
})();
const mimeType = matches[1].toLowerCase();
if (!mimeType.startsWith('image/')) return;
if (!filename) return;
const extension = filename.split('.').pop()?.toLowerCase() || '';
if (!extension) return;
if (documentFileType.includes(extension)) {
const extension = mimeType.split('/')[1];
return {
type: ChatFileTypeEnum.file,
name: filename,
type: ChatFileTypeEnum.image,
name: `image.${extension}`,
url
};
}
if (imageFileType.includes(extension)) {
try {
const parseUrl = new URL(url, 'https://localhost:3000');
// Get filename from URL
const filename = parseUrl.searchParams.get('filename') || parseUrl.pathname.split('/').pop();
const extension = filename?.split('.').pop()?.toLowerCase() || '';
// If it's a document type, return as file, otherwise treat as image
if (extension && documentFileType.includes(extension)) {
return {
type: ChatFileTypeEnum.file,
name: filename || 'null',
url
};
}
// Default to image type for non-document files
return {
type: ChatFileTypeEnum.image,
name: filename,
name: filename || 'null.png',
url
};
} catch (error) {
return {
type: ChatFileTypeEnum.image,
name: 'invalid.png',
url
};
}

View File

@@ -7,12 +7,14 @@ import { i18nT } from '../../../web/i18n/utils';
dayjs.extend(utc);
dayjs.extend(timezone);
export const formatTime2YMDHMW = (time?: Date) => dayjs(time).format('YYYY-MM-DD HH:mm:ss dddd');
export const formatTime2YMDHMS = (time?: Date) =>
export const formatTime2YMDHMW = (time?: Date | number) =>
dayjs(time).format('YYYY-MM-DD HH:mm:ss dddd');
export const formatTime2YMDHMS = (time?: Date | number) =>
time ? dayjs(time).format('YYYY-MM-DD HH:mm:ss') : '';
export const formatTime2YMDHM = (time?: Date) =>
export const formatTime2YMDHM = (time?: Date | number) =>
time ? dayjs(time).format('YYYY-MM-DD HH:mm') : '';
export const formatTime2YMD = (time?: Date) => (time ? dayjs(time).format('YYYY-MM-DD') : '');
export const formatTime2YMD = (time?: Date | number) =>
time ? dayjs(time).format('YYYY-MM-DD') : '';
export const formatTime2HM = (time: Date = new Date()) => dayjs(time).format('HH:mm');
/**

View File

@@ -41,6 +41,7 @@ export type FastGPTConfigFileType = {
};
export type FastGPTFeConfigsType = {
show_workorder?: boolean;
show_emptyChat?: boolean;
register_method?: ['email' | 'phone' | 'sync'];
login_method?: ['email' | 'phone']; // Attention: login method is diffrent with oauth
@@ -53,6 +54,7 @@ export type FastGPTFeConfigsType = {
show_promotion?: boolean;
show_team_chat?: boolean;
show_compliance_copywriting?: boolean;
show_aiproxy?: boolean;
concatMd?: string;
docUrl?: string;

View File

@@ -17,6 +17,8 @@ type BaseModelItemType = {
isActive?: boolean;
isCustom?: boolean;
isDefault?: boolean;
isDefaultDatasetTextModel?: boolean;
isDefaultDatasetImageModel?: boolean;
// If has requestUrl, it will request the model directly
requestUrl?: string;

View File

@@ -22,6 +22,7 @@ export type ModelProviderIdType =
| 'StepFun'
| 'Yi'
| 'Siliconflow'
| 'PPIO'
| 'Ollama'
| 'BAAI'
| 'FishAudio'
@@ -71,11 +72,6 @@ export const ModelProviderList: ModelProviderType[] = [
name: 'Groq',
avatar: 'model/groq'
},
{
id: 'AliCloud',
name: i18nT('common:model_alicloud'),
avatar: 'model/alicloud'
},
{
id: 'Qwen',
name: i18nT('common:model_qwen'),
@@ -86,6 +82,11 @@ export const ModelProviderList: ModelProviderType[] = [
name: i18nT('common:model_doubao'),
avatar: 'model/doubao'
},
{
id: 'DeepSeek',
name: 'DeepSeek',
avatar: 'model/deepseek'
},
{
id: 'ChatGLM',
name: i18nT('common:model_chatglm'),
@@ -96,11 +97,6 @@ export const ModelProviderList: ModelProviderType[] = [
name: i18nT('common:model_ernie'),
avatar: 'model/ernie'
},
{
id: 'DeepSeek',
name: 'DeepSeek',
avatar: 'model/deepseek'
},
{
id: 'Moonshot',
name: i18nT('common:model_moonshot'),
@@ -162,11 +158,21 @@ export const ModelProviderList: ModelProviderType[] = [
name: i18nT('common:model_moka'),
avatar: 'model/moka'
},
{
id: 'AliCloud',
name: i18nT('common:model_alicloud'),
avatar: 'model/alicloud'
},
{
id: 'Siliconflow',
name: i18nT('common:model_siliconflow'),
avatar: 'model/siliconflow'
},
{
id: 'PPIO',
name: i18nT('common:model_ppio'),
avatar: 'model/ppio'
},
{
id: 'Other',
name: i18nT('common:model_other'),

View File

@@ -1,14 +1,12 @@
import openai from 'openai';
import type {
ChatCompletionMessageToolCall,
ChatCompletionChunk,
ChatCompletionMessageParam as SdkChatCompletionMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionContentPart as SdkChatCompletionContentPart,
ChatCompletionUserMessageParam as SdkChatCompletionUserMessageParam,
ChatCompletionToolMessageParam as SdkChatCompletionToolMessageParam,
ChatCompletionAssistantMessageParam as SdkChatCompletionAssistantMessageParam,
ChatCompletionContentPartText
ChatCompletionAssistantMessageParam as SdkChatCompletionAssistantMessageParam
} from 'openai/resources';
import { ChatMessageTypeEnum } from './constants';
import { WorkflowInteractiveResponseType } from '../workflow/template/system/interactive/type';
@@ -48,6 +46,7 @@ export type ChatCompletionMessageParam = (
| CustomChatCompletionToolMessageParam
| CustomChatCompletionAssistantMessageParam
) & {
reasoning_text?: string;
dataId?: string;
hideInUI?: boolean;
};
@@ -71,7 +70,8 @@ export type ChatCompletionMessageFunctionCall =
};
// Stream response
export type StreamChatType = Stream<ChatCompletionChunk>;
export type StreamChatType = Stream<openai.Chat.Completions.ChatCompletionChunk>;
export type UnStreamChatType = openai.Chat.Completions.ChatCompletion;
export default openai;
export * from 'openai';

View File

@@ -46,7 +46,16 @@ export const chats2GPTMessages = ({
messages.forEach((item) => {
const dataId = reserveId ? item.dataId : undefined;
if (item.obj === ChatRoleEnum.Human) {
if (item.obj === ChatRoleEnum.System) {
const content = item.value?.[0]?.text?.content;
if (content) {
results.push({
dataId,
role: ChatCompletionRequestMessageRoleEnum.System,
content
});
}
} else if (item.obj === ChatRoleEnum.Human) {
const value = item.value
.map((item) => {
if (item.type === ChatItemValueTypeEnum.text) {
@@ -80,15 +89,6 @@ export const chats2GPTMessages = ({
role: ChatCompletionRequestMessageRoleEnum.User,
content: simpleUserContentPart(value)
});
} else if (item.obj === ChatRoleEnum.System) {
const content = item.value?.[0]?.text?.content;
if (content) {
results.push({
dataId,
role: ChatCompletionRequestMessageRoleEnum.System,
content
});
}
} else {
const aiResults: ChatCompletionMessageParam[] = [];
@@ -349,7 +349,7 @@ export const chatValue2RuntimePrompt = (value: ChatItemValueItemType[]): Runtime
};
value.forEach((item) => {
if (item.type === 'file' && item.file) {
prompt.files?.push(item.file);
prompt.files.push(item.file);
} else if (item.text) {
prompt.text += item.text.content;
}

View File

@@ -192,6 +192,7 @@ export type DatasetCollectionItemType = CollectionWithDatasetType & {
sourceId?: string;
file?: DatasetFileSchema;
permission: DatasetPermission;
indexAmount: number;
};
/* ================= data ===================== */

View File

@@ -10,6 +10,7 @@ import { FlowNodeOutputItemType, ReferenceValueType } from '../type/io';
import { ChatItemType, NodeOutputItemType } from '../../../core/chat/type';
import { ChatItemValueTypeEnum, ChatRoleEnum } from '../../../core/chat/constants';
import { replaceVariable, valToStr } from '../../../common/string/tools';
import { ChatCompletionChunk } from 'openai/resources';
export const getMaxHistoryLimitFromNodes = (nodes: StoreNodeItemType[]): number => {
let limit = 10;

View File

@@ -1,5 +1,9 @@
import { MemberGroupSchemaType, MemberGroupType } from 'support/permission/memberGroup/type';
import { OAuthEnum } from './constant';
import { TrackRegisterParams } from './login/api';
import { TeamMemberStatusEnum } from './team/constant';
import { OrgType } from './team/org/type';
import { TeamMemberItemType } from './team/type';
export type PostLoginProps = {
username: string;
@@ -21,3 +25,9 @@ export type FastLoginProps = {
token: string;
code: string;
};
export type SearchResult = {
members: Omit<TeamMemberItemType, 'teamId' | 'permission'>[];
orgs: Omit<OrgType, 'permission' | 'members'>[];
groups: MemberGroupSchemaType[];
};

View File

@@ -13,6 +13,7 @@ export type CreateTeamProps = {
defaultTeam?: boolean;
memberName?: string;
memberAvatar?: string;
notificationAccount?: string;
};
export type UpdateTeamProps = Omit<ThirdPartyAccountType, 'externalWorkflowVariable'> & {
name?: string;
@@ -39,6 +40,12 @@ export type UpdateInviteProps = {
tmbId: string;
status: TeamMemberSchema['status'];
};
export type UpdateStatusProps = {
tmbId: string;
status: TeamMemberSchema['status'];
};
export type InviteMemberResponse = Record<
'invite' | 'inValid' | 'inTeam',
{ username: string; userId: string }[]

View File

@@ -34,6 +34,7 @@ export type TeamTagSchema = TeamTagItemType & {
_id: string;
teamId: string;
createTime: Date;
updateTime?: Date;
};
export type TeamMemberSchema = {
@@ -41,6 +42,7 @@ export type TeamMemberSchema = {
teamId: string;
userId: string;
createTime: Date;
updateTime?: Date;
name: string;
role: `${TeamMemberRoleEnum}`;
status: `${TeamMemberStatusEnum}`;
@@ -79,6 +81,9 @@ export type TeamMemberItemType = {
role: `${TeamMemberRoleEnum}`;
status: `${TeamMemberStatusEnum}`;
permission: TeamPermission;
contact?: string;
createTime: Date;
updateTime?: Date;
};
export type TeamTagItemType = {

View File

@@ -17,6 +17,7 @@ export type UserModelSchema = {
fastgpt_sem?: {
keyword: string;
};
contact?: string;
};
export type UserType = {
@@ -26,9 +27,9 @@ export type UserType = {
timezone: string;
promotionRate: UserModelSchema['promotionRate'];
team: TeamTmbItemType;
standardInfo?: standardInfoType;
notificationAccount?: string;
permission: TeamPermission;
contact?: string;
};
export type SourceMemberType = {

View File

@@ -0,0 +1,4 @@
export const generateCsv = (headers: string[], data: string[][]) => {
const csv = [headers.join(','), ...data.map((row) => row.join(','))].join('\n');
return csv;
};

View File

@@ -18,10 +18,10 @@ export function getGFSCollection(bucket: `${BucketNameEnum}`) {
MongoDatasetFileSchema;
MongoChatFileSchema;
return connectionMongo.connection.db.collection(`${bucket}.files`);
return connectionMongo.connection.db!.collection(`${bucket}.files`);
}
export function getGridBucket(bucket: `${BucketNameEnum}`) {
return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db, {
return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db!, {
bucketName: bucket,
// @ts-ignore
readPreference: ReadPreference.SECONDARY_PREFERRED // Read from secondary node

View File

@@ -26,15 +26,18 @@ export async function uploadMongoImg({
const [base64Mime, base64Data] = base64Img.split(',');
// Check if mime type is valid
if (!base64MimeRegex.test(base64Mime)) {
return Promise.reject('Invalid image mime type');
return Promise.reject('Invalid image base64');
}
const mime = `image/${base64Mime.match(base64MimeRegex)?.[1] ?? 'image/jpeg'}`;
const binary = Buffer.from(base64Data, 'base64');
const extension = mime.split('/')[1];
let extension = mime.split('/')[1];
if (extension.startsWith('x-')) {
extension = extension.substring(2); // Remove 'x-' prefix
}
if (!imageFileType.includes(`.${extension}`)) {
return Promise.reject('Invalid image file type');
if (!extension || !imageFileType.includes(`.${extension}`)) {
return Promise.reject(`Invalid image file type: ${mime}`);
}
const { _id } = await MongoImage.create({
@@ -115,7 +118,7 @@ export async function delImgByRelatedId({
}: {
teamId: string;
relateIds: string[];
session: ClientSession;
session?: ClientSession;
}) {
if (relateIds.length === 0) return;

View File

@@ -111,15 +111,21 @@ export const readRawContentByFileBuffer = async ({
// markdown data format
if (imageList) {
await batchRun(imageList, async (item) => {
const src = await uploadMongoImg({
base64Img: `data:${item.mime};base64,${item.base64}`,
teamId,
// expiredTime: addHours(new Date(), 1),
metadata: {
...metadata,
mime: item.mime
const src = await (async () => {
try {
return await uploadMongoImg({
base64Img: `data:${item.mime};base64,${item.base64}`,
teamId,
// expiredTime: addHours(new Date(), 1),
metadata: {
...metadata,
mime: item.mime
}
});
} catch (error) {
return '';
}
});
})();
rawText = rawText.replace(item.uuid, src);
if (formatText) {
formatText = formatText.replace(item.uuid, src);

View File

@@ -38,10 +38,12 @@ const addCommonMiddleware = (schema: mongoose.Schema) => {
schema.post(op, function (this: any, result: any, next) {
if (this._startTime) {
const duration = Date.now() - this._startTime;
const warnLogData = {
query: this._query,
op,
collectionName: this.collection?.name,
op: this.op,
...(this._query && { query: this._query }),
...(this._update && { update: this._update }),
...(this._delete && { delete: this._delete }),
duration
};

View File

@@ -16,16 +16,30 @@ export async function connectMongo(): Promise<Mongoose> {
console.log('mongo start connect');
try {
connectionMongo.set('strictQuery', true);
// Remove existing listeners to prevent duplicates
connectionMongo.connection.removeAllListeners('error');
connectionMongo.connection.removeAllListeners('disconnected');
connectionMongo.set('strictQuery', false);
connectionMongo.connection.on('error', async (error) => {
console.log('mongo error', error);
await connectionMongo.disconnect();
await delay(1000);
connectMongo();
try {
if (connectionMongo.connection.readyState !== 0) {
await connectionMongo.disconnect();
await delay(1000);
await connectMongo();
}
} catch (error) {}
});
connectionMongo.connection.on('disconnected', () => {
connectionMongo.connection.on('disconnected', async () => {
console.log('mongo disconnected');
try {
if (connectionMongo.connection.readyState !== 0) {
await connectionMongo.disconnect();
await delay(1000);
await connectMongo();
}
} catch (error) {}
});
await connectionMongo.connect(process.env.MONGODB_URI as string, {

View File

@@ -25,7 +25,7 @@ export const countGptMessagesTokens = async (
number
>({
name: WorkerNameEnum.countGptMessagesTokens,
maxReservedThreads: global.systemEnv?.tokenWorkers || 50
maxReservedThreads: global.systemEnv?.tokenWorkers || 30
});
const total = await workerController.run({ messages, tools, functionCall });

View File

@@ -1 +1,4 @@
export const FastGPTProUrl = process.env.PRO_URL ? `${process.env.PRO_URL}/api` : '';
export const isFastGPTMainService = !!process.env.PRO_URL;
// @ts-ignore
export const isFastGPTProService = () => !!global.systemConfig;

View File

@@ -21,6 +21,7 @@ export const recallFromVectorStore = Vector.embRecall;
export const getVectorDataByTime = Vector.getVectorDataByTime;
export const getVectorCountByTeamId = Vector.getVectorCountByTeamId;
export const getVectorCountByDatasetId = Vector.getVectorCountByDatasetId;
export const getVectorCountByCollectionId = Vector.getVectorCountByCollectionId;
export const insertDatasetDataVector = async ({
model,

View File

@@ -321,6 +321,23 @@ export class MilvusCtrl {
return total;
};
getVectorCountByCollectionId = async (
teamId: string,
datasetId: string,
collectionId: string
) => {
const client = await this.getClient();
const result = await client.query({
collection_name: DatasetVectorTableName,
output_fields: ['count(*)'],
filter: `(teamId == "${String(teamId)}") and (datasetId == "${String(datasetId)}") and (collectionId == "${String(collectionId)}")`
});
const total = result.data?.[0]?.['count(*)'] as number;
return total;
};
getVectorDataByTime = async (start: Date, end: Date) => {
const client = await this.getClient();

View File

@@ -240,6 +240,23 @@ export class PgVectorCtrl {
where: [['team_id', String(teamId)], 'and', ['dataset_id', String(datasetId)]]
});
return total;
};
getVectorCountByCollectionId = async (
teamId: string,
datasetId: string,
collectionId: string
) => {
const total = await PgClient.count(DatasetVectorTableName, {
where: [
['team_id', String(teamId)],
'and',
['dataset_id', String(datasetId)],
'and',
['collection_id', String(collectionId)]
]
});
return total;
};
}

View File

@@ -1,7 +1,9 @@
import OpenAI from '@fastgpt/global/core/ai';
import {
ChatCompletionCreateParamsNonStreaming,
ChatCompletionCreateParamsStreaming
ChatCompletionCreateParamsStreaming,
StreamChatType,
UnStreamChatType
} from '@fastgpt/global/core/ai/type';
import { getErrText } from '@fastgpt/global/common/error/utils';
import { addLog } from '../../common/system/log';
@@ -9,14 +11,17 @@ import { i18nT } from '../../../web/i18n/utils';
import { OpenaiAccountType } from '@fastgpt/global/support/user/team/type';
import { getLLMModel } from './model';
export const openaiBaseUrl = process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1';
const aiProxyBaseUrl = process.env.AIPROXY_API_ENDPOINT
? `${process.env.AIPROXY_API_ENDPOINT}/v1`
: undefined;
const openaiBaseUrl = aiProxyBaseUrl || process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1';
const openaiBaseKey = process.env.AIPROXY_API_TOKEN || process.env.CHAT_API_KEY || '';
export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number }) => {
const { userKey, timeout } = props || {};
const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || openaiBaseKey;
return new OpenAI({
baseURL: baseUrl,
apiKey,
@@ -30,7 +35,7 @@ export const getAxiosConfig = (props?: { userKey?: OpenaiAccountType }) => {
const { userKey } = props || {};
const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || openaiBaseKey;
return {
baseUrl,
@@ -38,29 +43,30 @@ export const getAxiosConfig = (props?: { userKey?: OpenaiAccountType }) => {
};
};
type CompletionsBodyType =
| ChatCompletionCreateParamsNonStreaming
| ChatCompletionCreateParamsStreaming;
type InferResponseType<T extends CompletionsBodyType> =
T extends ChatCompletionCreateParamsStreaming
? OpenAI.Chat.Completions.ChatCompletionChunk
: OpenAI.Chat.Completions.ChatCompletion;
export const createChatCompletion = async <T extends CompletionsBodyType>({
export const createChatCompletion = async ({
body,
userKey,
timeout,
options
}: {
body: T;
body: ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming;
userKey?: OpenaiAccountType;
timeout?: number;
options?: OpenAI.RequestOptions;
}): Promise<{
response: InferResponseType<T>;
isStreamResponse: boolean;
getEmptyResponseTip: () => string;
}> => {
}): Promise<
{
getEmptyResponseTip: () => string;
} & (
| {
response: StreamChatType;
isStreamResponse: true;
}
| {
response: UnStreamChatType;
isStreamResponse: false;
}
)
> => {
try {
const modelConstantsData = getLLMModel(body.model);
@@ -69,6 +75,7 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
userKey,
timeout: formatTimeout
});
const response = await ai.chat.completions.create(body, {
...options,
...(modelConstantsData.requestUrl ? { path: modelConstantsData.requestUrl } : {}),
@@ -96,9 +103,17 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
return i18nT('chat:LLM_model_response_empty');
};
if (isStreamResponse) {
return {
response,
isStreamResponse: true,
getEmptyResponseTip
};
}
return {
response: response as InferResponseType<T>,
isStreamResponse,
response,
isStreamResponse: false,
getEmptyResponseTip
};
} catch (error) {

View File

@@ -1,4 +1,10 @@
{
"provider": "AliCloud",
"list": []
}
"list": [
{
"model": "SenseVoiceSmall",
"name": "SenseVoiceSmall",
"type": "stt"
}
]
}

View File

@@ -1,6 +1,30 @@
{
"provider": "Claude",
"list": [
{
"model": "claude-3-7-sonnet-20250219",
"name": "claude-3-7-sonnet-20250219",
"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-3-5-haiku-20241022",
"name": "claude-3-5-haiku-20241022",
@@ -10,7 +34,7 @@
"maxTemperature": 1,
"showTopP": true,
"showStopSign": true,
"vision": false,
"vision": true,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
@@ -98,4 +122,4 @@
"type": "llm"
}
]
}
}

View File

@@ -1,6 +1,54 @@
{
"provider": "Gemini",
"list": [
{
"model": "gemini-2.0-flash",
"name": "gemini-2.0-flash",
"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-pro-exp",
"name": "gemini-2.0-pro-exp",
"maxContext": 2000000,
"maxResponse": 8000,
"quoteMaxToken": 100000,
"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-1.5-flash",
"name": "gemini-1.5-flash",
@@ -153,4 +201,4 @@
"type": "embedding"
}
]
}
}

View File

@@ -1,4 +1,29 @@
{
"provider": "Grok",
"list": []
}
"list": [
{
"model": "grok-3",
"name": "grok-3",
"maxContext": 128000,
"maxResponse": 8000,
"quoteMaxToken": 128000,
"maxTemperature": 1,
"showTopP": true,
"showStopSign": true,
"vision": false,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
}
]
}

View File

@@ -0,0 +1,4 @@
{
"provider": "PPIO",
"list": []
}

View File

@@ -52,6 +52,12 @@ export const loadSystemModels = async (init = false) => {
if (model.isDefault) {
global.systemDefaultModel.llm = model;
}
if (model.isDefaultDatasetTextModel) {
global.systemDefaultModel.datasetTextLLM = model;
}
if (model.isDefaultDatasetImageModel) {
global.systemDefaultModel.datasetImageLLM = model;
}
} else if (model.type === ModelTypeEnum.embedding) {
global.embeddingModelMap.set(model.model, model);
global.embeddingModelMap.set(model.name, model);
@@ -134,6 +140,16 @@ export const loadSystemModels = async (init = false) => {
if (!global.systemDefaultModel.llm) {
global.systemDefaultModel.llm = Array.from(global.llmModelMap.values())[0];
}
if (!global.systemDefaultModel.datasetTextLLM) {
global.systemDefaultModel.datasetTextLLM = Array.from(global.llmModelMap.values()).find(
(item) => item.datasetProcess
);
}
if (!global.systemDefaultModel.datasetImageLLM) {
global.systemDefaultModel.datasetImageLLM = Array.from(global.llmModelMap.values()).find(
(item) => item.vision
);
}
if (!global.systemDefaultModel.embedding) {
global.systemDefaultModel.embedding = Array.from(global.embeddingModelMap.values())[0];
}

View File

@@ -22,6 +22,9 @@ export type SystemModelItemType =
export type SystemDefaultModelType = {
[ModelTypeEnum.llm]?: LLMModelItemType;
datasetTextLLM?: LLMModelItemType;
datasetImageLLM?: LLMModelItemType;
[ModelTypeEnum.embedding]?: EmbeddingModelItemType;
[ModelTypeEnum.tts]?: TTSModelType;
[ModelTypeEnum.stt]?: STTModelType;

View File

@@ -37,25 +37,26 @@ export const computedTemperature = ({
return temperature;
};
type CompletionsBodyType = (
type CompletionsBodyType =
| ChatCompletionCreateParamsNonStreaming
| ChatCompletionCreateParamsStreaming
) & {
response_format?: any;
json_schema?: string;
stop?: string;
};
| ChatCompletionCreateParamsStreaming;
type InferCompletionsBody<T> = T extends { stream: true }
? ChatCompletionCreateParamsStreaming
: ChatCompletionCreateParamsNonStreaming;
: T extends { stream: false }
? ChatCompletionCreateParamsNonStreaming
: ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming;
export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
body: T,
body: T & {
response_format?: any;
json_schema?: string;
stop?: string;
},
model: string | LLMModelItemType
): InferCompletionsBody<T> => {
const modelData = typeof model === 'string' ? getLLMModel(model) : model;
if (!modelData) {
return body as InferCompletionsBody<T>;
return body as unknown as InferCompletionsBody<T>;
}
const response_format = body.response_format;
@@ -91,16 +92,148 @@ export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
});
}
// console.log(requestBody);
return requestBody as InferCompletionsBody<T>;
return requestBody as unknown as InferCompletionsBody<T>;
};
export const llmStreamResponseToText = async (response: StreamChatType) => {
export const llmStreamResponseToAnswerText = async (response: StreamChatType) => {
let answer = '';
for await (const part of response) {
const content = part.choices?.[0]?.delta?.content || '';
answer += content;
}
return answer;
return parseReasoningContent(answer)[1];
};
// Parse <think></think> tags to think and answer - unstream response
export const parseReasoningContent = (text: string): [string, string] => {
const regex = /<think>([\s\S]*?)<\/think>/;
const match = text.match(regex);
if (!match) {
return ['', text];
}
const thinkContent = match[1].trim();
// Add answer (remaining text after think tag)
const answerContent = text.slice(match.index! + match[0].length);
return [thinkContent, answerContent];
};
// Parse <think></think> tags to think and answer - stream response
export const parseReasoningStreamContent = () => {
let isInThinkTag: boolean | undefined;
const startTag = '<think>';
let startTagBuffer = '';
const endTag = '</think>';
let endTagBuffer = '';
/*
parseReasoning - 只控制是否主动解析 <think></think>,如果接口已经解析了,仍然会返回 think 内容。
*/
const parsePart = (
part: {
choices: {
delta: {
content?: string;
reasoning_content?: string;
};
}[];
},
parseReasoning = false
): [string, string] => {
const content = part.choices?.[0]?.delta?.content || '';
// @ts-ignore
const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
if (reasoningContent || !parseReasoning) {
isInThinkTag = false;
return [reasoningContent, content];
}
if (!content) {
return ['', ''];
}
// 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 ['', 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 < startTag.length) {
return ['', ''];
}
if (startTagBuffer.startsWith(startTag)) {
isInThinkTag = true;
return [startTagBuffer.slice(startTag.length), ''];
}
// 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 ['', 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:
abc - 完全未命中尾标签
abc<th - 命中一部分尾标签
abc</think> - 完全命中尾标签
abc</think>abc - 完全命中尾标签
</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(endTag)) {
isInThinkTag = false;
const answer = endTagBuffer.slice(endTag.length);
return ['', answer];
} else if (endTagBuffer.length >= endTag.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 [tmp, ''];
}
return ['', ''];
} else if (content.includes(endTag)) {
// 返回内容,完整命中</think>,直接结束
isInThinkTag = false;
const [think, answer] = content.split(endTag);
return [think, answer];
} else {
// 无 buffer且未命中 </think>,开始疑似 </think> 检测。
for (let i = 1; i < endTag.length; i++) {
const partialEndTag = endTag.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 [think, ''];
}
}
}
// 完全未命中尾标签,还是 think 阶段。
return [content, ''];
};
const getStartTagBuffer = () => startTagBuffer;
return {
parsePart,
getStartTagBuffer
};
};

View File

@@ -1,7 +1,7 @@
import { connectionMongo, getMongoModel } from '../../common/mongo';
const { Schema } = connectionMongo;
import { ChatSchema as ChatType } from '@fastgpt/global/core/chat/type.d';
import { ChatSourceMap } from '@fastgpt/global/core/chat/constants';
import { ChatSourceEnum, ChatSourceMap } from '@fastgpt/global/core/chat/constants';
import {
TeamCollectionName,
TeamMemberCollectionName
@@ -52,8 +52,10 @@ const ChatSchema = new Schema({
},
source: {
type: String,
required: true
required: true,
enum: Object.values(ChatSourceEnum)
},
sourceName: String,
shareId: {
type: String
},

View File

@@ -1,6 +1,10 @@
import type { AIChatItemType, UserChatItemType } from '@fastgpt/global/core/chat/type.d';
import { MongoApp } from '../app/schema';
import { ChatItemValueTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
import {
ChatItemValueTypeEnum,
ChatRoleEnum,
ChatSourceEnum
} from '@fastgpt/global/core/chat/constants';
import { MongoChatItem } from './chatItemSchema';
import { MongoChat } from './chatSchema';
import { addLog } from '../../common/system/log';
@@ -22,7 +26,8 @@ type Props = {
variables?: Record<string, any>;
isUpdateUseTime: boolean;
newTitle: string;
source: string;
source: `${ChatSourceEnum}`;
sourceName?: string;
shareId?: string;
outLinkUid?: string;
content: [UserChatItemType & { dataId?: string }, AIChatItemType & { dataId?: string }];
@@ -40,6 +45,7 @@ export async function saveChat({
isUpdateUseTime,
newTitle,
source,
sourceName,
shareId,
outLinkUid,
content,
@@ -96,6 +102,7 @@ export async function saveChat({
pluginInputs,
title: newTitle,
source,
sourceName,
shareId,
outLinkUid,
metadata: metadataUpdate,

View File

@@ -197,7 +197,11 @@ export const loadRequestMessages = async ({
addLog.info(`Filter invalid image: ${imgUrl}`);
return;
}
} catch (error) {
} catch (error: any) {
if (error?.response?.status === 405) {
return item;
}
addLog.warn(`Filter invalid image: ${imgUrl}`, { error });
return;
}
}

View File

@@ -25,6 +25,7 @@ import { MongoImage } from '../../../common/file/image/schema';
import { hashStr } from '@fastgpt/global/common/string/tools';
import { addDays } from 'date-fns';
import { MongoDatasetDataText } from '../data/dataTextSchema';
import { delay, retryFn } from '@fastgpt/global/common/system/utils';
export const createCollectionAndInsertData = async ({
dataset,
@@ -216,7 +217,7 @@ export async function createOneCollection({
nextSyncTime
}
],
{ session }
{ session, ordered: true }
);
return collection;
@@ -227,8 +228,14 @@ export const delCollectionRelatedSource = async ({
collections,
session
}: {
collections: DatasetCollectionSchemaType[];
session: ClientSession;
collections: {
teamId: string;
fileId?: string;
metadata?: {
relatedImgId?: string;
};
}[];
session?: ClientSession;
}) => {
if (collections.length === 0) return;
@@ -259,11 +266,13 @@ export const delCollectionRelatedSource = async ({
export async function delCollection({
collections,
session,
delRelatedSource
delImg = true,
delFile = true
}: {
collections: DatasetCollectionSchemaType[];
session: ClientSession;
delRelatedSource: boolean;
delImg: boolean;
delFile: boolean;
}) {
if (collections.length === 0) return;
@@ -274,83 +283,55 @@ export async function delCollection({
const datasetIds = Array.from(new Set(collections.map((item) => String(item.datasetId))));
const collectionIds = collections.map((item) => String(item._id));
// Delete training data
await MongoDatasetTraining.deleteMany({
teamId,
datasetIds: { $in: datasetIds },
collectionId: { $in: collectionIds }
await retryFn(async () => {
await Promise.all([
// Delete training data
MongoDatasetTraining.deleteMany({
teamId,
datasetId: { $in: datasetIds },
collectionId: { $in: collectionIds }
}),
// Delete dataset_data_texts
MongoDatasetDataText.deleteMany({
teamId,
datasetId: { $in: datasetIds },
collectionId: { $in: collectionIds }
}),
// Delete dataset_datas
MongoDatasetData.deleteMany({
teamId,
datasetId: { $in: datasetIds },
collectionId: { $in: collectionIds }
}),
...(delImg
? [
delImgByRelatedId({
teamId,
relateIds: collections
.map((item) => item?.metadata?.relatedImgId || '')
.filter(Boolean)
})
]
: []),
...(delFile
? [
delFileByFileIdList({
bucketName: BucketNameEnum.dataset,
fileIdList: collections.map((item) => item?.fileId || '').filter(Boolean)
})
]
: []),
// Delete vector data
deleteDatasetDataVector({ teamId, datasetIds, collectionIds })
]);
// delete collections
await MongoDatasetCollection.deleteMany(
{
teamId,
_id: { $in: collectionIds }
},
{ session }
);
});
/* file and imgs */
if (delRelatedSource) {
await delCollectionRelatedSource({ collections, session });
}
// Delete dataset_datas
await MongoDatasetData.deleteMany(
{ teamId, datasetIds: { $in: datasetIds }, collectionId: { $in: collectionIds } },
{ session }
);
// Delete dataset_data_texts
await MongoDatasetDataText.deleteMany(
{ teamId, datasetIds: { $in: datasetIds }, collectionId: { $in: collectionIds } },
{ session }
);
// delete collections
await MongoDatasetCollection.deleteMany(
{
teamId,
_id: { $in: collectionIds }
},
{ session }
);
// no session delete: delete files, vector data
await deleteDatasetDataVector({ teamId, datasetIds, collectionIds });
}
/**
* delete delOnlyCollection
*/
export async function delOnlyCollection({
collections,
session
}: {
collections: DatasetCollectionSchemaType[];
session: ClientSession;
}) {
if (collections.length === 0) return;
const teamId = collections[0].teamId;
if (!teamId) return Promise.reject('teamId is not exist');
const datasetIds = Array.from(new Set(collections.map((item) => String(item.datasetId))));
const collectionIds = collections.map((item) => String(item._id));
// delete training data
await MongoDatasetTraining.deleteMany({
teamId,
datasetIds: { $in: datasetIds },
collectionId: { $in: collectionIds }
});
// delete dataset.datas
await MongoDatasetData.deleteMany(
{ teamId, datasetIds: { $in: datasetIds }, collectionId: { $in: collectionIds } },
{ session }
);
// delete collections
await MongoDatasetCollection.deleteMany(
{
teamId,
_id: { $in: collectionIds }
},
{ session }
);
// no session delete: delete files, vector data
await deleteDatasetDataVector({ teamId, datasetIds, collectionIds });
}

View File

@@ -97,7 +97,7 @@ export const createOrGetCollectionTags = async ({
datasetId,
tag: tagContent
})),
{ session }
{ session, ordered: true }
);
return [...existingTags.map((tag) => tag._id), ...newTags.map((tag) => tag._id)];
@@ -174,6 +174,14 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
}
await mongoSessionRun(async (session) => {
// Delete old collection
await delCollection({
collections: [collection],
delImg: false,
delFile: false,
session
});
// Create new collection
await createCollectionAndInsertData({
session,
@@ -208,13 +216,6 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
updateTime: new Date()
}
});
// Delete old collection
await delCollection({
collections: [collection],
delRelatedSource: false,
session
});
});
return DatasetCollectionSyncResultEnum.success;

View File

@@ -7,6 +7,8 @@ import { MongoDatasetTraining } from './training/schema';
import { MongoDatasetData } from './data/schema';
import { deleteDatasetDataVector } from '../../common/vectorStore/controller';
import { MongoDatasetDataText } from './data/dataTextSchema';
import { DatasetErrEnum } from '@fastgpt/global/common/error/code/dataset';
import { retryFn } from '@fastgpt/global/common/system/utils';
/* ============= dataset ========== */
/* find all datasetId by top datasetId */
@@ -54,7 +56,7 @@ export async function getCollectionWithDataset(collectionId: string) {
.populate<{ dataset: DatasetSchemaType }>('dataset')
.lean();
if (!data) {
return Promise.reject('Collection is not exist');
return Promise.reject(DatasetErrEnum.unExistCollection);
}
return data;
}
@@ -77,40 +79,39 @@ export async function delDatasetRelevantData({
const datasetIds = datasets.map((item) => item._id);
// delete training data
await MongoDatasetTraining.deleteMany({
teamId,
datasetId: { $in: datasetIds }
});
// Get _id, teamId, fileId, metadata.relatedImgId for all collections
const collections = await MongoDatasetCollection.find(
{
teamId,
datasetId: { $in: datasetIds }
},
'_id teamId datasetId fileId metadata',
{ session }
'_id teamId datasetId fileId metadata'
).lean();
// Delete Image and file
await delCollectionRelatedSource({ collections, session });
await retryFn(async () => {
await Promise.all([
// delete training data
MongoDatasetTraining.deleteMany({
teamId,
datasetId: { $in: datasetIds }
}),
//Delete dataset_data_texts
MongoDatasetDataText.deleteMany({
teamId,
datasetId: { $in: datasetIds }
}),
//delete dataset_datas
MongoDatasetData.deleteMany({ teamId, datasetId: { $in: datasetIds } }),
// Delete Image and file
delCollectionRelatedSource({ collections }),
// Delete vector data
deleteDatasetDataVector({ teamId, datasetIds })
]);
});
// delete collections
await MongoDatasetCollection.deleteMany({
teamId,
datasetId: { $in: datasetIds }
}).session(session);
// No session delete:
// Delete dataset_data_texts
await MongoDatasetDataText.deleteMany({
teamId,
datasetId: { $in: datasetIds }
});
// delete dataset_datas
await MongoDatasetData.deleteMany({ teamId, datasetId: { $in: datasetIds } });
// Delete vector data
await deleteDatasetDataVector({ teamId, datasetIds });
}

View File

@@ -1,6 +1,6 @@
import { connectionMongo, getMongoModel } from '../../../common/mongo';
const { Schema } = connectionMongo;
import { DatasetDataSchemaType } from '@fastgpt/global/core/dataset/type.d';
import { DatasetDataTextSchemaType } from '@fastgpt/global/core/dataset/type.d';
import { TeamCollectionName } from '@fastgpt/global/support/user/team/constant';
import { DatasetCollectionName } from '../schema';
import { DatasetColCollectionName } from '../collection/schema';
@@ -40,12 +40,13 @@ try {
default_language: 'none'
}
);
DatasetDataTextSchema.index({ teamId: 1, datasetId: 1, collectionId: 1 });
DatasetDataTextSchema.index({ dataId: 1 }, { unique: true });
} catch (error) {
console.log(error);
}
export const MongoDatasetDataText = getMongoModel<DatasetDataSchemaType>(
export const MongoDatasetDataText = getMongoModel<DatasetDataTextSchemaType>(
DatasetDataTextCollectionName,
DatasetDataTextSchema
);

View File

@@ -200,6 +200,7 @@ export async function searchDatasetData(
forbidCollectionIdList: collections.map((item) => String(item._id))
};
};
/*
Collection metadata filter
标签过滤:
@@ -207,6 +208,63 @@ export async function searchDatasetData(
2. and 标签和 null 不能共存,否则返回空数组
*/
const filterCollectionByMetadata = async (): Promise<string[] | undefined> => {
const getAllCollectionIds = async ({
parentCollectionIds
}: {
parentCollectionIds?: string[];
}): Promise<string[] | undefined> => {
if (!parentCollectionIds) return;
if (parentCollectionIds.length === 0) {
return [];
}
const collections = await MongoDatasetCollection.find(
{
teamId,
datasetId: { $in: datasetIds },
_id: { $in: parentCollectionIds }
},
'_id type',
{
...readFromSecondary
}
).lean();
const resultIds = new Set<string>();
collections.forEach((item) => {
if (item.type !== 'folder') {
resultIds.add(String(item._id));
}
});
const folderIds = collections
.filter((item) => item.type === 'folder')
.map((item) => String(item._id));
// Get all child collection ids
if (folderIds.length) {
const childCollections = await MongoDatasetCollection.find(
{
teamId,
datasetId: { $in: datasetIds },
parentId: { $in: folderIds }
},
'_id type',
{
...readFromSecondary
}
).lean();
const childIds = await getAllCollectionIds({
parentCollectionIds: childCollections.map((item) => String(item._id))
});
childIds?.forEach((id) => resultIds.add(id));
}
return Array.from(resultIds);
};
if (!collectionFilterMatch || !global.feConfigs.isPlus) return;
let tagCollectionIdList: string[] | undefined = undefined;
@@ -326,13 +384,19 @@ export async function searchDatasetData(
}
// Concat tag and time
if (tagCollectionIdList && createTimeCollectionIdList) {
return tagCollectionIdList.filter((id) => createTimeCollectionIdList!.includes(id));
} else if (tagCollectionIdList) {
return tagCollectionIdList;
} else if (createTimeCollectionIdList) {
return createTimeCollectionIdList;
}
const collectionIds = (() => {
if (tagCollectionIdList && createTimeCollectionIdList) {
return tagCollectionIdList.filter((id) =>
(createTimeCollectionIdList as string[]).includes(id)
);
}
return tagCollectionIdList || createTimeCollectionIdList;
})();
return await getAllCollectionIds({
parentCollectionIds: collectionIds
});
} catch (error) {}
};
const embeddingRecall = async ({
@@ -383,6 +447,7 @@ export async function searchDatasetData(
).lean()
]);
const set = new Map<string, number>();
const formatResult = results
.map((item, index) => {
const collection = collections.find((col) => String(col._id) === String(item.collectionId));
@@ -398,8 +463,6 @@ export async function searchDatasetData(
return;
}
const score = item?.score || 0;
const result: SearchDataResponseItemType = {
id: String(data._id),
updateTime: data.updateTime,
@@ -409,12 +472,24 @@ export async function searchDatasetData(
datasetId: String(data.datasetId),
collectionId: String(data.collectionId),
...getCollectionSourceData(collection),
score: [{ type: SearchScoreTypeEnum.embedding, value: score, index }]
score: [{ type: SearchScoreTypeEnum.embedding, value: item?.score || 0, index }]
};
return result;
})
.filter(Boolean) as SearchDataResponseItemType[];
.filter((item) => {
if (!item) return false;
if (set.has(item.id)) return false;
set.set(item.id, 1);
return true;
})
.map((item, index) => {
if (!item) return;
return {
...item,
score: item.score.map((item) => ({ ...item, index }))
};
}) as SearchDataResponseItemType[];
return {
embeddingRecallResults: formatResult,
@@ -717,11 +792,12 @@ export const defaultSearchDatasetData = async ({
? getLLMModel(datasetSearchExtensionModel)
: undefined;
const { concatQueries, rewriteQuery, aiExtensionResult } = await datasetSearchQueryExtension({
query,
extensionModel,
extensionBg: datasetSearchExtensionBg
});
const { concatQueries, extensionQueries, rewriteQuery, aiExtensionResult } =
await datasetSearchQueryExtension({
query,
extensionModel,
extensionBg: datasetSearchExtensionBg
});
const result = await searchDatasetData({
...props,
@@ -736,7 +812,7 @@ export const defaultSearchDatasetData = async ({
model: aiExtensionResult.model,
inputTokens: aiExtensionResult.inputTokens,
outputTokens: aiExtensionResult.outputTokens,
query: concatQueries.join('\n')
query: extensionQueries.join('\n')
}
: undefined
};

View File

@@ -72,12 +72,15 @@ Human: ${query}
if (result.extensionQueries?.length === 0) return;
return result;
})();
const extensionQueries = filterSamQuery(aiExtensionResult?.extensionQueries || []);
if (aiExtensionResult) {
queries = filterSamQuery(queries.concat(aiExtensionResult.extensionQueries));
queries = filterSamQuery(queries.concat(extensionQueries));
rewriteQuery = queries.join('\n');
}
return {
extensionQueries,
concatQueries: queries,
rewriteQuery,
aiExtensionResult

View File

@@ -334,7 +334,7 @@ const getMultiInput = async ({
return {
documentQuoteText: text,
userFiles: fileLinks.map((url) => parseUrlToFileType(url))
userFiles: fileLinks.map((url) => parseUrlToFileType(url)).filter(Boolean)
};
};

View File

@@ -4,12 +4,9 @@ import type { ChatItemType, UserChatItemValueItemType } from '@fastgpt/global/co
import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
import { SseResponseEventEnum } from '@fastgpt/global/core/workflow/runtime/constants';
import { textAdaptGptResponse } from '@fastgpt/global/core/workflow/runtime/utils';
import { parseReasoningContent, parseReasoningStreamContent } from '../../../ai/utils';
import { createChatCompletion } from '../../../ai/config';
import type {
ChatCompletion,
ChatCompletionMessageParam,
StreamChatType
} from '@fastgpt/global/core/ai/type.d';
import type { ChatCompletionMessageParam, StreamChatType } from '@fastgpt/global/core/ai/type.d';
import { formatModelChars2Points } from '../../../../support/wallet/usage/utils';
import type { LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
import { postTextCensor } from '../../../../common/api/requestPlusApi';
@@ -195,7 +192,13 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
});
const { answerText, reasoningText } = await (async () => {
if (res && isStreamResponse) {
if (isStreamResponse) {
if (!res) {
return {
answerText: '',
reasoningText: ''
};
}
// sse response
const { answer, reasoning } = await streamResponse({
res,
@@ -210,34 +213,49 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
reasoningText: reasoning
};
} else {
const unStreamResponse = response as ChatCompletion;
const answer = unStreamResponse.choices?.[0]?.message?.content || '';
// @ts-ignore
const reasoning = unStreamResponse.choices?.[0]?.message?.reasoning_content || '';
const { content, reasoningContent } = (() => {
const content = response.choices?.[0]?.message?.content || '';
// @ts-ignore
const reasoningContent: string = response.choices?.[0]?.message?.reasoning_content || '';
// API already parse reasoning content
if (reasoningContent || !aiChatReasoning) {
return {
content,
reasoningContent
};
}
const [think, answer] = parseReasoningContent(content);
return {
content: answer,
reasoningContent: think
};
})();
// Some models do not support streaming
if (stream) {
if (isResponseAnswerText && answer) {
if (aiChatReasoning && reasoningContent) {
workflowStreamResponse?.({
event: SseResponseEventEnum.fastAnswer,
data: textAdaptGptResponse({
text: answer
reasoning_content: reasoningContent
})
});
}
if (aiChatReasoning && reasoning) {
if (isResponseAnswerText && content) {
workflowStreamResponse?.({
event: SseResponseEventEnum.fastAnswer,
data: textAdaptGptResponse({
reasoning_content: reasoning
text: content
})
});
}
}
return {
answerText: answer,
reasoningText: reasoning
answerText: content,
reasoningText: reasoningContent
};
}
})();
@@ -249,7 +267,8 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
const AIMessages: ChatCompletionMessageParam[] = [
{
role: ChatCompletionRequestMessageRoleEnum.Assistant,
content: answerText
content: answerText,
reasoning_text: reasoningText // reasoning_text is only recorded for response, but not for request
}
];
@@ -267,7 +286,7 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
});
return {
answerText,
answerText: answerText.trim(),
reasoningText,
[DispatchNodeResponseKeyEnum.nodeResponse]: {
totalPoints: externalProvider.openaiAccount?.key ? 0 : totalPoints,
@@ -386,7 +405,7 @@ async function getMultiInput({
return {
documentQuoteText: text,
userFiles: fileLinks.map((url) => parseUrlToFileType(url))
userFiles: fileLinks.map((url) => parseUrlToFileType(url)).filter(Boolean)
};
}
@@ -500,26 +519,18 @@ async function streamResponse({
});
let answer = '';
let reasoning = '';
const { parsePart, getStartTagBuffer } = parseReasoningStreamContent();
for await (const part of stream) {
if (res.closed) {
stream.controller?.abort();
break;
}
const content = part.choices?.[0]?.delta?.content || '';
const [reasoningContent, content] = parsePart(part, aiChatReasoning);
answer += content;
if (isResponseAnswerText && content) {
workflowStreamResponse?.({
write,
event: SseResponseEventEnum.answer,
data: textAdaptGptResponse({
text: content
})
});
}
const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
reasoning += reasoningContent;
if (aiChatReasoning && reasoningContent) {
workflowStreamResponse?.({
write,
@@ -529,6 +540,21 @@ async function streamResponse({
})
});
}
if (isResponseAnswerText && content) {
workflowStreamResponse?.({
write,
event: SseResponseEventEnum.answer,
data: textAdaptGptResponse({
text: content
})
});
}
}
// if answer is empty, try to get value from startTagBuffer. (Cause: The response content is too short to exceed the minimum parse length)
if (answer === '') {
answer = getStartTagBuffer();
}
return { answer, reasoning };

View File

@@ -232,9 +232,14 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
chatNodeUsages = chatNodeUsages.concat(nodeDispatchUsages);
}
if (toolResponses !== undefined) {
if (toolResponses !== undefined && toolResponses !== null) {
if (Array.isArray(toolResponses) && toolResponses.length === 0) return;
if (typeof toolResponses === 'object' && Object.keys(toolResponses).length === 0) return;
if (
!Array.isArray(toolResponses) &&
typeof toolResponses === 'object' &&
Object.keys(toolResponses).length === 0
)
return;
toolRunResponse = toolResponses;
}
@@ -243,12 +248,17 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
chatAssistantResponse = chatAssistantResponse.concat(assistantResponses);
} else {
if (reasoningText) {
chatAssistantResponse.push({
type: ChatItemValueTypeEnum.reasoning,
reasoning: {
content: reasoningText
}
});
const isResponseReasoningText = inputs.find(
(item) => item.key === NodeInputKeyEnum.aiChatReasoning
)?.value;
if (isResponseReasoningText) {
chatAssistantResponse.push({
type: ChatItemValueTypeEnum.reasoning,
reasoning: {
content: reasoningText
}
});
}
}
if (answerText) {
// save assistant text response

View File

@@ -53,7 +53,7 @@ export const dispatchRunAppNode = async (props: Props): Promise<Response> => {
const userInputFiles = (() => {
if (fileUrlList) {
return fileUrlList.map((url) => parseUrlToFileType(url));
return fileUrlList.map((url) => parseUrlToFileType(url)).filter(Boolean);
}
// Adapt version 4.8.13 upgrade
return files;

View File

@@ -398,41 +398,6 @@ async function fetchData({
};
}
// function replaceVariable(text: string, obj: Record<string, any>) {
// for (const [key, value] of Object.entries(obj)) {
// if (value === undefined) {
// text = text.replace(new RegExp(`{{(${key})}}`, 'g'), UNDEFINED_SIGN);
// } else {
// const replacement = JSON.stringify(value);
// const unquotedReplacement =
// replacement.startsWith('"') && replacement.endsWith('"')
// ? replacement.slice(1, -1)
// : replacement;
// text = text.replace(new RegExp(`{{(${key})}}`, 'g'), () => unquotedReplacement);
// }
// }
// return text || '';
// }
// function removeUndefinedSign(obj: Record<string, any>) {
// for (const key in obj) {
// if (obj[key] === UNDEFINED_SIGN) {
// obj[key] = undefined;
// } else if (Array.isArray(obj[key])) {
// obj[key] = obj[key].map((item: any) => {
// if (item === UNDEFINED_SIGN) {
// return undefined;
// } else if (typeof item === 'object') {
// removeUndefinedSign(item);
// }
// return item;
// });
// } else if (typeof obj[key] === 'object') {
// removeUndefinedSign(obj[key]);
// }
// }
// return obj;
// }
// Replace some special response from system plugin
async function replaceSystemPluginResponse({
response,

View File

@@ -24,7 +24,7 @@
"jsonwebtoken": "^9.0.2",
"lodash": "^4.17.21",
"mammoth": "^1.6.0",
"mongoose": "^7.0.2",
"mongoose": "^8.10.1",
"multer": "1.4.5-lts.1",
"next": "14.2.5",
"nextjs-cors": "^2.2.0",

View File

@@ -178,7 +178,7 @@ export const getClbsAndGroupsWithInfo = async ({
]);
export const delResourcePermissionById = (id: string) => {
return MongoResourcePermission.findByIdAndRemove(id);
return MongoResourcePermission.findByIdAndDelete(id);
};
export const delResourcePermission = ({
session,

View File

@@ -196,7 +196,8 @@ export async function syncCollaborators({
permission: item.permission
})),
{
session
session,
ordered: true
}
);
}

Some files were not shown because too many files have changed in this diff Show More