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v4.8.7
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v4.8.12-al
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2
.github/ISSUE_TEMPLATE/bugs.md
vendored
@@ -11,7 +11,7 @@ assignees: ''
|
||||
[//]: # '方框内填 x 表示打钩'
|
||||
|
||||
- [ ] 我已确认目前没有类似 issue
|
||||
- [ ] 我已完整查看过项目 README,以及[项目文档](https://doc.fastgpt.in/docs/intro/)
|
||||
- [ ] 我已完整查看过项目 README,以及[项目文档](https://doc.tryfastgpt.ai/docs/intro/)
|
||||
- [ ] 我使用了自己的 key,并确认我的 key 是可正常使用的
|
||||
- [ ] 我理解并愿意跟进此 issue,协助测试和提供反馈
|
||||
- [x] 我理解并认可上述内容,并理解项目维护者精力有限,**不遵循规则的 issue 可能会被无视或直接关闭**
|
||||
|
||||
2
.github/ISSUE_TEMPLATE/config.yml
vendored
@@ -1,5 +1,5 @@
|
||||
blank_issues_enabled: false
|
||||
contact_links:
|
||||
- name: 飞书话题群
|
||||
url: https://oss.laf.run/otnvvf-imgs/1719505774252.jpg
|
||||
url: https://oss.laf.run/otnvvf-imgs/fastgpt-feishu1.png
|
||||
about: FastGPT 全是问题群
|
||||
|
||||
BIN
.github/imgs/image.png
vendored
Normal file
|
After Width: | Height: | Size: 21 KiB |
BIN
.github/imgs/intro1.png
vendored
|
Before Width: | Height: | Size: 166 KiB After Width: | Height: | Size: 173 KiB |
BIN
.github/imgs/intro2.png
vendored
|
Before Width: | Height: | Size: 246 KiB After Width: | Height: | Size: 273 KiB |
BIN
.github/imgs/intro3.png
vendored
|
Before Width: | Height: | Size: 250 KiB After Width: | Height: | Size: 168 KiB |
BIN
.github/imgs/intro4.png
vendored
|
Before Width: | Height: | Size: 182 KiB After Width: | Height: | Size: 159 KiB |
5
.github/workflows/docs-deploy-kubeconfig.yml
vendored
@@ -1,4 +1,4 @@
|
||||
name: Deploy image by kubeconfig
|
||||
name: Deploy doc image by kubeconfig
|
||||
on:
|
||||
workflow_dispatch:
|
||||
push:
|
||||
@@ -16,6 +16,9 @@ jobs:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Change baseURL
|
||||
run: sed -i 's|^baseURL =.*|baseURL = "https://doc.fastgpt.cn"|g' ./docSite/hugo.toml
|
||||
|
||||
- name: Get current date and time
|
||||
id: datetime
|
||||
run: echo "datetime=$(date +'%Y%m%d%H%M%S')" >> "$GITHUB_OUTPUT"
|
||||
|
||||
2
.github/workflows/docs-deploy-vercel.yml
vendored
@@ -1,4 +1,4 @@
|
||||
name: Deploy image to vercel
|
||||
name: Deploy doc image to vercel
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
|
||||
5
.github/workflows/helm-release.yaml
vendored
@@ -24,11 +24,6 @@ jobs:
|
||||
export APP_VERSION=${{ steps.vars.outputs.tag }}
|
||||
export HELM_VERSION=${{ steps.vars.outputs.tag }}
|
||||
export HELM_REPO=ghcr.io/${{ github.repository_owner }}
|
||||
if [[ ! "$line" =~ ^v ]]
|
||||
then
|
||||
unset APP_VERSION
|
||||
unset HELM_VERSION
|
||||
fi
|
||||
helm dependency update files/helm/fastgpt
|
||||
helm package files/helm/fastgpt --version ${HELM_VERSION}-helm --app-version ${APP_VERSION} -d bin
|
||||
helm push bin/fastgpt-${HELM_VERSION}-helm.tgz oci://${HELM_REPO}
|
||||
|
||||
@@ -7,7 +7,7 @@ on:
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
build-fastgpt-images:
|
||||
preview-fastgpt-images:
|
||||
runs-on: ubuntu-20.04
|
||||
steps:
|
||||
- name: Checkout
|
||||
@@ -3,4 +3,6 @@ dist
|
||||
**/.DS_Store
|
||||
node_modules
|
||||
docSite/
|
||||
*.md
|
||||
*.md
|
||||
|
||||
cl100l_base.ts
|
||||
46
.vscode/i18n-ally-custom-framework.yml
vendored
Normal file
@@ -0,0 +1,46 @@
|
||||
# .vscode/i18n-ally-custom-framework.yml
|
||||
|
||||
# An array of strings which contain Language Ids defined by VS Code
|
||||
# You can check available language ids here: https://code.visualstudio.com/docs/languages/identifiers
|
||||
languageIds:
|
||||
- javascript
|
||||
- typescript
|
||||
- javascriptreact
|
||||
- typescriptreact
|
||||
|
||||
# An array of RegExes to find the key usage. **The key should be captured in the first match group**.
|
||||
# You should unescape RegEx strings in order to fit in the YAML file
|
||||
# To help with this, you can use https://www.freeformatter.com/json-escape.html
|
||||
usageMatchRegex:
|
||||
# The following example shows how to detect `t("your.i18n.keys")`
|
||||
# the `{key}` will be placed by a proper keypath matching regex,
|
||||
# you can ignore it and use your own matching rules as well
|
||||
- "[^\\w\\d]t\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]commonT\\(['\"`]({key})['\"`]"
|
||||
# 支持 appT("your.i18n.keys")
|
||||
- "[^\\w\\d]appT\\(['\"`]({key})['\"`]"
|
||||
# 支持 datasetT("your.i18n.keys")
|
||||
- "[^\\w\\d]datasetT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]fileT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]publishT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]workflowT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]userT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]chatT\\(['\"`]({key})['\"`]"
|
||||
- "[^\\w\\d]i18nT\\(['\"`]({key})['\"`]"
|
||||
|
||||
# A RegEx to set a custom scope range. This scope will be used as a prefix when detecting keys
|
||||
# and works like how the i18next framework identifies the namespace scope from the
|
||||
# useTranslation() hook.
|
||||
# You should unescape RegEx strings in order to fit in the YAML file
|
||||
# To help with this, you can use https://www.freeformatter.com/json-escape.html
|
||||
scopeRangeRegex: "([^:]+):"
|
||||
|
||||
# An array of strings containing refactor templates.
|
||||
# The "$1" will be replaced by the keypath specified.
|
||||
# Optional: uncomment the following two lines to use
|
||||
|
||||
# refactorTemplates:
|
||||
# - i18n.get("$1")
|
||||
|
||||
# If set to true, only enables this custom framework (will disable all built-in frameworks)
|
||||
monopoly: false
|
||||
68
.vscode/nextapi.code-snippets
vendored
@@ -50,5 +50,73 @@
|
||||
"export default ContextProvider"
|
||||
],
|
||||
"description": "FastGPT usecontext template"
|
||||
},
|
||||
|
||||
"Jest test template": {
|
||||
"scope": "typescriptreact",
|
||||
"prefix": "jesttest",
|
||||
"body": [
|
||||
"import '@/pages/api/__mocks__/base';",
|
||||
"import { root } from '@/pages/api/__mocks__/db/init';",
|
||||
"import { getTestRequest } from '@/test/utils';",
|
||||
"import { AppErrEnum } from '@fastgpt/global/common/error/code/app';",
|
||||
"import handler from './demo';",
|
||||
"",
|
||||
"// Import the schema",
|
||||
"import { MongoOutLink } from '@fastgpt/service/support/outLink/schema';",
|
||||
"",
|
||||
"beforeAll(async () => {",
|
||||
" // await MongoOutLink.create({",
|
||||
" // shareId: 'aaa',",
|
||||
" // appId: root.appId,",
|
||||
" // tmbId: root.tmbId,",
|
||||
" // teamId: root.teamId,",
|
||||
" // type: 'share',",
|
||||
" // name: 'aaa'",
|
||||
" // })",
|
||||
"});",
|
||||
"",
|
||||
"test('Should return a list of outLink', async () => {",
|
||||
" // Mock request",
|
||||
" const res = (await handler(",
|
||||
" ...getTestRequest({",
|
||||
" query: {",
|
||||
" appId: root.appId,",
|
||||
" type: 'share'",
|
||||
" },",
|
||||
" user: root",
|
||||
" })",
|
||||
" )) as any;",
|
||||
"",
|
||||
" expect(res.code).toBe(200);",
|
||||
" expect(res.data.length).toBe(2);",
|
||||
"});",
|
||||
"",
|
||||
"test('appId is required', async () => {",
|
||||
" const res = (await handler(",
|
||||
" ...getTestRequest({",
|
||||
" query: {",
|
||||
" type: 'share'",
|
||||
" },",
|
||||
" user: root",
|
||||
" })",
|
||||
" )) as any;",
|
||||
" expect(res.code).toBe(500);",
|
||||
" expect(res.error).toBe(AppErrEnum.unExist);",
|
||||
"});",
|
||||
"",
|
||||
"test('if type is not provided, return nothing', async () => {",
|
||||
" const res = (await handler(",
|
||||
" ...getTestRequest({",
|
||||
" query: {",
|
||||
" appId: root.appId",
|
||||
" },",
|
||||
" user: root",
|
||||
" })",
|
||||
" )) as any;",
|
||||
" expect(res.code).toBe(200);",
|
||||
" expect(res.data.length).toBe(0);",
|
||||
"});"
|
||||
]
|
||||
}
|
||||
}
|
||||
13
.vscode/settings.json
vendored
@@ -13,12 +13,21 @@
|
||||
"js",
|
||||
"ts"
|
||||
],
|
||||
"i18n-ally.keystyle": "nested",
|
||||
"i18n-ally.keystyle": "flat",
|
||||
"i18n-ally.sortKeys": true,
|
||||
"i18n-ally.keepFulfilled": false,
|
||||
"i18n-ally.sourceLanguage": "zh", // 根据此语言文件翻译其他语言文件的变量和内容
|
||||
"i18n-ally.displayLanguage": "zh", // 显示语言
|
||||
"i18n-ally.namespace": true,
|
||||
"i18n-ally.pathMatcher": "{locale}/{namespaces}.json",
|
||||
"i18n-ally.extract.targetPickingStrategy": "most-similar-by-key"
|
||||
"i18n-ally.extract.targetPickingStrategy": "most-similar-by-key",
|
||||
"i18n-ally.translate.engines": ["google"],
|
||||
"[typescript]": {
|
||||
"editor.defaultFormatter": "esbenp.prettier-vscode"
|
||||
},
|
||||
"markdown.copyFiles.destination": {
|
||||
"/docSite/content/**/*": "${documentWorkspaceFolder}/docSite/assets/imgs/"
|
||||
},
|
||||
"markdown.copyFiles.overwriteBehavior": "nameIncrementally",
|
||||
"markdown.copyFiles.transformPath": "const filename = uri.path.split('/').pop(); return `/imgs/${filename}`;"
|
||||
}
|
||||
54
README.md
@@ -1,6 +1,6 @@
|
||||
<div align="center">
|
||||
|
||||
<a href="https://fastgpt.in/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
<a href="https://tryfastgpt.ai/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
|
||||
# FastGPT
|
||||
|
||||
@@ -15,13 +15,13 @@ FastGPT 是一个基于 LLM 大语言模型的知识库问答系统,提供开
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://fastgpt.in/">
|
||||
<a href="https://tryfastgpt.ai/">
|
||||
<img height="21" src="https://img.shields.io/badge/在线使用-d4eaf7?style=flat-square&logo=spoj&logoColor=7d09f1" alt="cloud">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/intro">
|
||||
<a href="https://doc.tryfastgpt.ai/docs/intro">
|
||||
<img height="21" src="https://img.shields.io/badge/相关文档-7d09f1?style=flat-square" alt="document">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/development">
|
||||
<a href="https://doc.tryfastgpt.ai/docs/development">
|
||||
<img height="21" src="https://img.shields.io/badge/本地开发-%23d4eaf7?style=flat-square&logo=xcode&logoColor=7d09f1" alt="development">
|
||||
</a>
|
||||
<a href="/#-%E7%9B%B8%E5%85%B3%E9%A1%B9%E7%9B%AE">
|
||||
@@ -36,7 +36,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
## 🛸 在线使用
|
||||
|
||||
- 🌍 海外版:[fastgpt.in](https://fastgpt.in/)
|
||||
- 🌍 国际版:[tryfastgpt.ai](https://tryfastgpt.ai/)
|
||||
|
||||
| | |
|
||||
| ---------------------------------- | ---------------------------------- |
|
||||
@@ -50,22 +50,22 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
## 💡 RoadMap
|
||||
|
||||
`1` 应用编排能力
|
||||
- [x] 提供简易模式,无需操作编排
|
||||
- [x] 工作流编排
|
||||
- [x] 对话工作流、插件工作流
|
||||
- [x] 工具调用
|
||||
- [x] 插件 - 工作流封装能力
|
||||
- [x] Code sandbox
|
||||
- [ ] 循环调用
|
||||
- [x] 循环调用
|
||||
- [x] 用户选择
|
||||
- [x] 表单输入
|
||||
|
||||
`2` 知识库能力
|
||||
- [x] 多库复用,混用
|
||||
- [x] chunk 记录修改和删除
|
||||
- [x] 源文件存储
|
||||
- [x] 支持手动输入,直接分段,QA 拆分导入
|
||||
- [x] 支持 txt,md,html,pdf,docx,pptx,csv,xlsx (有需要更多可 PR file loader)
|
||||
- [x] 支持 url 读取、CSV 批量导入
|
||||
- [x] 混合检索 & 重排
|
||||
- [ ] 标签过滤
|
||||
- [ ] 自定义文件读取服务
|
||||
- [ ] 自定义分块服务
|
||||
|
||||
`3` 应用调试能力
|
||||
- [x] 知识库单点搜索测试
|
||||
@@ -77,7 +77,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
`4` OpenAPI 接口
|
||||
- [x] completions 接口 (chat 模式对齐 GPT 接口)
|
||||
- [x] 知识库 CRUD
|
||||
- [ ] 对话 CRUD
|
||||
- [x] 对话 CRUD
|
||||
|
||||
`5` 运营能力
|
||||
- [x] 免登录分享窗口
|
||||
@@ -88,7 +88,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
`6` 其他
|
||||
- [x] 支持语音输入和输出 (可配置语音输入语音回答)
|
||||
- [x] 模糊输入提示
|
||||
- [ ] 模板市场
|
||||
- [x] 模板市场
|
||||
|
||||
<a href="#readme">
|
||||
<img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
|
||||
@@ -96,23 +96,21 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
## 👨💻 开发
|
||||
|
||||
项目技术栈:NextJs + TS + ChakraUI + Mongo + Postgres (Vector 插件)
|
||||
项目技术栈:NextJs + TS + ChakraUI + MongoDB + PostgreSQL (PG Vector 插件)/Milvus
|
||||
|
||||
- **⚡ 快速部署**
|
||||
|
||||
> [Sealos](https://sealos.io) 的服务器在国外,不需要额外处理网络问题,无需服务器、无需魔法、无需域名,支持高并发 & 动态伸缩。点击以下按钮即可一键部署 👇
|
||||
> 使用 [Sealos](https://sealos.io) 服务,无需采购服务器、无需域名,支持高并发 & 动态伸缩,并且数据库应用采用 kubeblocks 的数据库,在 IO 性能方面,远超于简单的 Docker 容器部署。
|
||||
|
||||
[](https://cloud.sealos.io/?openapp=system-fastdeploy%3FtemplateName%3Dfastgpt)
|
||||
[点击查看 Sealos 一键部署 FastGPT 教程](https://doc.tryfastgpt.ai/docs/development/sealos/)
|
||||
|
||||
由于需要部署数据库,部署完后需要等待 2~4 分钟才能正常访问。默认用了最低配置,首次访问时会有些慢。相关使用教程可查看:[Sealos 部署 FastGPT](https://doc.fastgpt.in/docs/development/sealos/)
|
||||
|
||||
* [快开始本地开发](https://doc.fastgpt.in/docs/development/intro/)
|
||||
* [部署 FastGPT](https://doc.fastgpt.in/docs/development/sealos)
|
||||
* [系统配置文件说明](https://doc.fastgpt.in/docs/development/configuration/)
|
||||
* [多模型配置](https://doc.fastgpt.in/docs/development/one-api/)
|
||||
* [版本更新/升级介绍](https://doc.fastgpt.in/docs/development/upgrading)
|
||||
* [OpenAPI API 文档](https://doc.fastgpt.in/docs/development/openapi/)
|
||||
* [知识库结构详解](https://doc.fastgpt.in/docs/course/dataset_engine/)
|
||||
* [快速开始本地开发](https://doc.tryfastgpt.ai/docs/development/intro/)
|
||||
* [部署 FastGPT](https://doc.tryfastgpt.ai/docs/development/sealos)
|
||||
* [系统配置文件说明](https://doc.tryfastgpt.ai/docs/development/configuration/)
|
||||
* [多模型配置](https://doc.tryfastgpt.ai/docs/development/one-api/)
|
||||
* [版本更新/升级介绍](https://doc.tryfastgpt.ai/docs/development/upgrading)
|
||||
* [OpenAPI API 文档](https://doc.tryfastgpt.ai/docs/development/openapi/)
|
||||
* [知识库结构详解](https://doc.tryfastgpt.ai/docs/course/dataset_engine/)
|
||||
|
||||
<a href="#readme">
|
||||
<img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
|
||||
@@ -122,7 +120,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
扫码加入飞书话题群 (新开,逐渐弃用微信群):
|
||||
|
||||

|
||||

|
||||
|
||||
<a href="#readme">
|
||||
<img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
|
||||
@@ -151,7 +149,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
## 🌿 第三方生态
|
||||
|
||||
- [OnWeChat 个人微信/企微机器人](https://doc.fastgpt.in/docs/use-cases/onwechat/)
|
||||
- [OnWeChat 个人微信/企微机器人](https://doc.tryfastgpt.ai/docs/use-cases/onwechat/)
|
||||
|
||||
<a href="#readme">
|
||||
<img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
|
||||
@@ -214,4 +212,4 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
1. 允许作为后台服务直接商用,但不允许提供 SaaS 服务。
|
||||
2. 未经商业授权,任何形式的商用服务均需保留相关版权信息。
|
||||
3. 完整请查看 [FastGPT Open Source License](./LICENSE)
|
||||
4. 联系方式:yujinlong@sealos.io,[点击查看商业版定价策略](https://doc.fastgpt.in/docs/commercial)
|
||||
4. 联系方式:Dennis@sealos.io,[点击查看商业版定价策略](https://doc.tryfastgpt.ai/docs/commercial)
|
||||
|
||||
217
README_en.md
@@ -1,9 +1,11 @@
|
||||
<div align="center">
|
||||
|
||||
<a href="https://fastgpt.in/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
<a href="https://tryfastgpt.ai/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
|
||||
# FastGPT
|
||||
|
||||

|
||||
|
||||
<p align="center">
|
||||
<a href="./README_en.md">English</a> |
|
||||
<a href="./README.md">简体中文</a> |
|
||||
@@ -12,132 +14,75 @@
|
||||
|
||||
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
|
||||
|
||||
[](https://github.com/labring/FastGPT/stargazers)
|
||||
[](https://github.com/labring/FastGPT/pulls)
|
||||
[](https://github.com/labring/FastGPT/pulls)
|
||||
[](https://github.com/labring/FastGPT/blob/main/LICENSE)
|
||||
[](https://doc.tryfastgpt.ai/docs/intro)
|
||||
[](https://doc.tryfastgpt.ai/docs/intro)
|
||||
[](https://tryfastgpt.ai/)
|
||||
|
||||
[](https://discord.gg/mp68xkZn2Q)
|
||||
[](https://oss.laf.run/otnvvf-imgs/feishu3.png)
|
||||
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://fastgpt.in/">
|
||||
<img height="21" src="https://img.shields.io/badge/Try it Online-d4eaf7?style=flat-square&logo=spoj&logoColor=7d09f1" alt="cloud">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/intro">
|
||||
<img height="21" src="https://img.shields.io/badge/Documents-7d09f1?style=flat-square" alt="document">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/development">
|
||||
<img height="21" src="https://img.shields.io/badge/Local Development-%23d4eaf7?style=flat-square&logo=xcode&logoColor=7d09f1" alt="development">
|
||||
</a>
|
||||
<a href="https://github.com/labring/FastGPT/blob/main/LICENSE">
|
||||
<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?style=flat-square&labelColor=d4eaf7&color=7d09f1" alt="license">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
|
||||
[](https://discord.gg/mp68xkZn2Q)
|
||||
|
||||
</div>
|
||||
## 🎥 Comprehensive Feature Demonstration
|
||||
|
||||
https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409bd33f6d4
|
||||
|
||||
## 🛸 Use Cloud Services
|
||||
## 🛸 Online Use
|
||||
|
||||
Cloud: [fastgpt.in](https://fastgpt.in/)
|
||||
Website: [tryfastgpt.ai](https://tryfastgpt.ai/)
|
||||
|
||||
| | |
|
||||
| ---------------------------------- | ---------------------------------- |
|
||||
| Conversational AI Setup | Workflow Automation |
|
||||
|  |  |
|
||||
| Knowledge Base Setup | Integration Process |
|
||||
|  |  |
|
||||
|
||||
<a href="#readme">
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 💡 Features
|
||||
|
||||
`1` Application Orchestration Features
|
||||
|
||||
- [x] Offers a straightforward mode, eliminating the need for complex orchestration
|
||||
- [x] Provides clear next-step instructions in dialogues
|
||||
- [x] Facilitates workflow orchestration
|
||||
- [x] Tracks references in source files
|
||||
- [x] Encapsulates modules for enhanced reuse at multiple levels
|
||||
- [x] Combines search and reordering functions
|
||||
- [ ] Includes a tool module
|
||||
- [ ] Integrates [Laf](https://github.com/labring/laf) for online HTTP module creation
|
||||
- [ ] Plugin encapsulation capabilities
|
||||
|
||||
`2` Knowledge Base Features
|
||||
|
||||
- [x] Allows for the mixed use of multiple databases
|
||||
- [x] Keeps track of modifications and deletions in data chunks
|
||||
- [x] Enables specific vector models for each knowledge base
|
||||
- [x] Stores original source files
|
||||
- [x] Supports direct input and segment-based QA import
|
||||
- [x] Compatible with a variety of file formats: pdf, docx, txt, html, md, csv
|
||||
- [x] Facilitates URL reading and bulk CSV importing
|
||||
- [ ] Supports PPT and Excel file import
|
||||
- [ ] Features a file reader
|
||||
- [ ] Offers diverse data preprocessing options
|
||||
|
||||
`3` Application Debugging Features
|
||||
|
||||
- [x] Enables targeted search testing within the knowledge base
|
||||
- [x] Allows feedback, editing, and deletion during conversations
|
||||
- [x] Presents the full context of interactions
|
||||
- [x] Displays all intermediate values within modules
|
||||
- [ ] Advanced DeBug mode for orchestration
|
||||
|
||||
`4` OpenAPI Interface
|
||||
|
||||
- [x] The completions interface (aligned with GPT's chat mode interface)
|
||||
- [x] CRUD operations for the knowledge base
|
||||
- [ ] CRUD operations for conversations
|
||||
|
||||
`5` Operational Features
|
||||
|
||||
- [x] Share without requiring login
|
||||
- [x] Easy embedding with Iframe
|
||||
- [x] Customizable chat window embedding with features like default open, drag-and-drop
|
||||
- [x] Centralizes conversation records for review and annotation
|
||||
| **Features** | **Details** |
|
||||
|--------------------------------------------|---------------------------------------------------|
|
||||
| **Application Orchestration Features** | ✅ Offers a straightforward mode, eliminating the need for complex orchestration <br> ✅ Provides clear next-step instructions in dialogues <br> ✅ Facilitates workflow orchestration <br> ✅ Tracks references in source files <br> ✅ Encapsulates modules for enhanced reuse at multiple levels <br> ✅ Combines search and reordering functions <br> 🔜 Includes a tool module <br> 🔜 Integrates [Laf](https://github.com/labring/laf) for online HTTP module creation <br> 🔜 Plugin encapsulation capabilities |
|
||||
| **Knowledge Base Features** | ✅ Allows for the mixed use of multiple databases <br> ✅ Keeps track of modifications and deletions in data chunks <br> ✅ Enables specific vector models for each knowledge base <br> ✅ Stores original source files <br> ✅ Supports direct input and segment-based QA import <br> ✅ Compatible with a variety of file formats: pdf, docx, txt, html, md, csv <br> ✅ Facilitates URL reading and bulk CSV importing <br> 🔜 Supports PPT and Excel file import <br> 🔜 Features a file reader <br> 🔜 Offers diverse data preprocessing options |
|
||||
| **Application Debugging Features** | ✅ Enables targeted search testing within the knowledge base <br> ✅ Allows feedback, editing, and deletion during conversations <br> ✅ Presents the full context of interactions <br> ✅ Displays all intermediate values within modules <br> 🔜 Advanced Debug mode for orchestration |
|
||||
| **OpenAPI Interface** | ✅ The completions interface (aligned with GPT's chat mode interface) <br> ✅ CRUD operations for the knowledge base <br> 🔜 CRUD operations for conversation |
|
||||
| **Operational Features** | ✅ Share without requiring login <br> ✅ Easy embedding with Iframe <br> ✅ Customizable chat window embedding with features like default open, drag-and-drop <br> ✅ Centralizes conversation records for review and annotation |
|
||||
|
||||
|
||||
<a href="#readme">
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 👨💻 Development
|
||||
|
||||
Project tech stack: NextJs + TS + ChakraUI + Mongo + Postgres (Vector plugin)
|
||||
Project tech stack: NextJs + TS + ChakraUI + MongoDB + PostgreSQL (PG Vector plug-in)/Milvus
|
||||
|
||||
- **⚡ Deployment**
|
||||
- **⚡ Fast Deployment**
|
||||
|
||||
> When using [Sealos](https://sealos.io) services, there is no need to purchase servers or domain names. It supports high concurrency and dynamic scaling, and the database application uses the kubeblocks database, which far exceeds the simple Docker container deployment in terms of IO performance.
|
||||
<div align="center">
|
||||
[](https://cloud.sealos.io/?openapp=system-fastdeploy%3FtemplateName%3Dfastgpt)
|
||||
</div>
|
||||
|
||||
Give it a 2-4 minute wait after deployment as it sets up the database. Initially, it might be a tad slow since we're using the basic settings.
|
||||
Give it a 2-4 minute wait after deployment as it sets up the database. Initially, it might be a too slow since we're using the basic settings.
|
||||
|
||||
- [Getting Started with Local Development](https://doc.fastgpt.in/docs/development)
|
||||
- [Deploying FastGPT](https://doc.fastgpt.in/docs/installation)
|
||||
- [Guide on System Configs](https://doc.fastgpt.in/docs/installation/reference)
|
||||
- [Configuring Multiple Models](https://doc.fastgpt.in/docs/installation/reference/models)
|
||||
- [Version Updates & Upgrades](https://doc.fastgpt.in/docs/installation/upgrading)
|
||||
[sealos one click deployment tutorial](https://doc.tryfastgpt.ai/docs/development/sealos/)
|
||||
|
||||
- [Getting Started with Local Development](https://doc.tryfastgpt.ai/docs/development)
|
||||
- [Deploying FastGPT](https://doc.tryfastgpt.ai/docs/installation)
|
||||
- [Guide on System Configs](https://doc.tryfastgpt.ai/docs/installation/reference)
|
||||
- [Configuring Multiple Models](https://doc.tryfastgpt.ai/docs/installation/reference/models)
|
||||
- [Version Updates & Upgrades](https://doc.tryfastgpt.ai/docs/installation/upgrading)
|
||||
|
||||
## 🏘️ Community & support
|
||||
|
||||
+ 🌐 Visit the [FastGPT website](https://fastgpt.in/) for full documentation and useful links.
|
||||
+ 💬 Join our [Discord server](https://discord.gg/mp68xkZn2Q) is to chat with FastGPT developers and other FastGPT users. This is a good place to learn about FastGPT, ask questions, and share your experiences.
|
||||
+ 🐞 Create [GitHub Issues](https://github.com/labring/FastGPT/issues/new/choose) for bug reports and feature requests.
|
||||
|
||||
<a href="#readme">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 👀 Others
|
||||
|
||||
- [FastGPT FAQ](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
|
||||
- [Docker Deployment Tutorial Video](https://www.bilibili.com/video/BV1jo4y147fT/)
|
||||
- [Official Account Integration Video Tutorial](https://www.bilibili.com/video/BV1xh4y1t7fy/)
|
||||
- [FastGPT Knowledge Base Demo](https://www.bilibili.com/video/BV1Wo4y1p7i1/)
|
||||
|
||||
<a href="#readme">
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
@@ -148,7 +93,7 @@ Project tech stack: NextJs + TS + ChakraUI + Mongo + Postgres (Vector plugin)
|
||||
- [One API: Multi-model management, supports Azure, Wenxin Yiyuan, etc.](https://github.com/songquanpeng/one-api)
|
||||
- [TuShan: Build a backend management system in 5 minutes](https://github.com/msgbyte/tushan)
|
||||
|
||||
<a href="#readme">
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
@@ -156,10 +101,69 @@ Project tech stack: NextJs + TS + ChakraUI + Mongo + Postgres (Vector plugin)
|
||||
|
||||
- [luolinAI: Enterprise WeChat bot, ready to use](https://github.com/luolin-ai/FastGPT-Enterprise-WeChatbot)
|
||||
|
||||
<a href="#readme">
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
|
||||
## 🏘️ Community & Support
|
||||
|
||||
+ 🌐 Visit the [FastGPT website](https://tryfastgpt.ai/) for full documentation and useful links.
|
||||
+ 💬 Join our [Discord server](https://discord.gg/mp68xkZn2Q) is to chat with FastGPT developers and other FastGPT users. This is a good place to learn about FastGPT, ask questions, and share your experiences.
|
||||
+ 🐞 Create [GitHub Issues](https://github.com/labring/FastGPT/issues/new/choose) for bug reports and feature requests.
|
||||
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 👀 Others
|
||||
|
||||
- [FastGPT FAQ](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
|
||||
- [Docker Deployment Tutorial Video](https://www.bilibili.com/video/BV1jo4y147fT/)
|
||||
- [Official Account Integration Video Tutorial](https://www.bilibili.com/video/BV1xh4y1t7fy/)
|
||||
- [FastGPT Knowledge Base Demo](https://www.bilibili.com/video/BV1Wo4y1p7i1/)
|
||||
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 🌱 Contributors
|
||||
|
||||
We welcome all forms of contributions. If you are interested in contributing code, you can check out our GitHub [Issues](https://github.com/labring/FastGPT/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc) to show us your ideas.
|
||||
|
||||
<a href="https://github.com/labring/FastGPT/graphs/contributors" target="_blank">
|
||||
<table>
|
||||
<tr>
|
||||
<th colspan="2">
|
||||
<br><img src="https://contrib.rocks/image?repo=labring/FastGPT"><br><br>
|
||||
</th>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://next.ossinsight.io/widgets/official/compose-org-active-contributors/thumbnail.png?activity=active&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=2x3&color_scheme=dark">
|
||||
<img alt="Active participants of labring - past 28 days" src="https://next.ossinsight.io/widgets/official/compose-org-active-contributors/thumbnail.png?activity=active&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=2x3&color_scheme=light">
|
||||
</picture>
|
||||
</td>
|
||||
<td rowspan="2">
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://next.ossinsight.io/widgets/official/compose-org-participants-growth/thumbnail.png?activity=new&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=4x7&color_scheme=dark">
|
||||
<img alt="New trends of labring" src="https://next.ossinsight.io/widgets/official/compose-org-participants-growth/thumbnail.png?activity=new&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=4x7&color_scheme=light">
|
||||
</picture>
|
||||
</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://next.ossinsight.io/widgets/official/compose-org-active-contributors/thumbnail.png?activity=new&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=2x3&color_scheme=dark">
|
||||
<img alt="New participants of labring - past 28 days" src="https://next.ossinsight.io/widgets/official/compose-org-active-contributors/thumbnail.png?activity=new&period=past_28_days&owner_id=102226726&repo_ids=605673387&image_size=2x3&color_scheme=light">
|
||||
</picture>
|
||||
</td>
|
||||
</tr>
|
||||
</table>
|
||||
</a>
|
||||
|
||||
|
||||
## 🌟 Star History
|
||||
|
||||
<a href="https://github.com/labring/FastGPT/stargazers" target="_blank" style="display: block" align="center">
|
||||
@@ -169,3 +173,20 @@ Project tech stack: NextJs + TS + ChakraUI + Mongo + Postgres (Vector plugin)
|
||||
<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=labring/FastGPT&type=Date" />
|
||||
</picture>
|
||||
</a>
|
||||
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
|
||||
## 📄 Usage Agreement
|
||||
|
||||
This repository complies with the [FastGPT Open Source License](./LICENSE) open source agreement.
|
||||
|
||||
1. Direct commercial use as a backend service is allowed, but provision of SaaS services is not allowed.
|
||||
2. Without commercial authorization, any form of commercial service must retain relevant copyright information.
|
||||
3. For full details, please see [FastGPT Open Source License](./LICENSE)
|
||||
4. Contact: Dennis@sealos.io , [click to view commercial version pricing strategy](https://doc.tryfastgpt.ai/docs/commercial)
|
||||
|
||||
<a href="#FastGPT">
|
||||
<img src="https://img.shields.io/badge/-Back_to_Top-7d09f1.svg" alt="#" align="right">
|
||||
</a>
|
||||
20
README_ja.md
@@ -1,6 +1,6 @@
|
||||
<div align="center">
|
||||
|
||||
<a href="https://fastgpt.in/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
<a href="https://tryfastgpt.ai/"><img src="/.github/imgs/logo.svg" width="120" height="120" alt="fastgpt logo"></a>
|
||||
|
||||
# FastGPT
|
||||
|
||||
@@ -15,13 +15,13 @@ FastGPT は、LLM 上 に 構築 された 知識 ベースの Q&A システム
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://fastgpt.in/">
|
||||
<a href="https://tryfastgpt.ai/">
|
||||
<img height="21" src="https://img.shields.io/badge/在线使用-d4eaf7?style=flat-square&logo=spoj&logoColor=7d09f1" alt="cloud">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/intro">
|
||||
<a href="https://doc.tryfastgpt.ai/docs/intro">
|
||||
<img height="21" src="https://img.shields.io/badge/相关文档-7d09f1?style=flat-square" alt="document">
|
||||
</a>
|
||||
<a href="https://doc.fastgpt.in/docs/development">
|
||||
<a href="https://doc.tryfastgpt.ai/docs/development">
|
||||
<img height="21" src="https://img.shields.io/badge/本地开发-%23d4eaf7?style=flat-square&logo=xcode&logoColor=7d09f1" alt="development">
|
||||
</a>
|
||||
<a href="/#-%E7%9B%B8%E5%85%B3%E9%A1%B9%E7%9B%AE">
|
||||
@@ -36,7 +36,7 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
## 🛸 クラウドサービスの 利用
|
||||
|
||||
[fastgpt.in](https://fastgpt.in/)
|
||||
[tryfastgpt.ai](https://tryfastgpt.ai/)
|
||||
|
||||
| | |
|
||||
| ---------------------------------- | ---------------------------------- |
|
||||
@@ -98,11 +98,11 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
|
||||
|
||||
デプロイ 後、データベースをセットアップするので、2~4分待 ってください。基本設定 を 使 っているので、最初 は 少 し 遅 いかもしれません。
|
||||
|
||||
- [ローカル 開発入門](https://doc.fastgpt.in/docs/development)
|
||||
- [FastGPT のデプロイ](https://doc.fastgpt.in/docs/installation)
|
||||
- [システム 設定 ガイド](https://doc.fastgpt.in/docs/installation/reference)
|
||||
- [複数 モデルの 設定](https://doc.fastgpt.in/docs/installation/reference/models)
|
||||
- [バージョン 更新 とアップグレード](https://doc.fastgpt.in/docs/installation/upgrading)
|
||||
- [ローカル 開発入門](https://doc.tryfastgpt.ai/docs/development)
|
||||
- [FastGPT のデプロイ](https://doc.tryfastgpt.ai/docs/installation)
|
||||
- [システム 設定 ガイド](https://doc.tryfastgpt.ai/docs/installation/reference)
|
||||
- [複数 モデルの 設定](https://doc.tryfastgpt.ai/docs/installation/reference/models)
|
||||
- [バージョン 更新 とアップグレード](https://doc.tryfastgpt.ai/docs/installation/upgrading)
|
||||
|
||||
<!-- ## :point_right: ロードマップ
|
||||
- [FastGPT ロードマップ](https://kjqvjse66l.feishu.cn/docx/RVUxdqE2WolDYyxEKATcM0XXnte) -->
|
||||
|
||||
BIN
bin/fastgpt-v1.0.0-helm.tgz
Normal file
76
dev.md
@@ -23,6 +23,81 @@ pnpm dev
|
||||
make dev name=app
|
||||
```
|
||||
|
||||
Note: If the Node version is >= 20, you need to pass the `--no-node-snapshot` parameter to Node when running `pnpm i`
|
||||
|
||||
```sh
|
||||
NODE_OPTIONS=--no-node-snapshot pnpm i
|
||||
```
|
||||
|
||||
### Jest
|
||||
|
||||
https://fael3z0zfze.feishu.cn/docx/ZOI1dABpxoGhS7xzhkXcKPxZnDL
|
||||
|
||||
## I18N
|
||||
|
||||
### Install i18n-ally Plugin
|
||||
|
||||
1. Open the Extensions Marketplace in VSCode, search for and install the `i18n Ally` plugin.
|
||||
|
||||
### Code Optimization Examples
|
||||
|
||||
#### Fetch Specific Namespace Translations in `getServerSideProps`
|
||||
|
||||
```typescript
|
||||
// pages/yourPage.tsx
|
||||
export async function getServerSideProps(context: any) {
|
||||
return {
|
||||
props: {
|
||||
currentTab: context?.query?.currentTab || TabEnum.info,
|
||||
...(await serverSideTranslations(context.locale, ['publish', 'user']))
|
||||
}
|
||||
};
|
||||
}
|
||||
```
|
||||
|
||||
#### Use useTranslation Hook in Page
|
||||
|
||||
```typescript
|
||||
// pages/yourPage.tsx
|
||||
import { useTranslation } from 'next-i18next';
|
||||
|
||||
const YourComponent = () => {
|
||||
const { t } = useTranslation();
|
||||
|
||||
return (
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
mr={2}
|
||||
onClick={() => setShowSelected(false)}
|
||||
>
|
||||
{t('common:close')}
|
||||
</Button>
|
||||
);
|
||||
};
|
||||
|
||||
export default YourComponent;
|
||||
```
|
||||
|
||||
#### Handle Static File Translations
|
||||
|
||||
```typescript
|
||||
// utils/i18n.ts
|
||||
import { i18nT } from '@fastgpt/web/i18n/utils';
|
||||
|
||||
const staticContent = {
|
||||
id: 'simpleChat',
|
||||
avatar: 'core/workflow/template/aiChat',
|
||||
name: i18nT('app:template.simple_robot'),
|
||||
};
|
||||
|
||||
export default staticContent;
|
||||
```
|
||||
|
||||
### Standardize Translation Format
|
||||
|
||||
- Use the t(namespace:key) format to ensure consistent naming.
|
||||
- Translation keys should use lowercase letters and underscores, e.g., common.close.
|
||||
|
||||
## Build
|
||||
|
||||
@@ -37,4 +112,3 @@ docker build -f ./projects/app/Dockerfile -t registry.cn-hangzhou.aliyuncs.com/f
|
||||
# Make cmd: Build image with proxy
|
||||
make build name=app image=registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.1 proxy=taobao
|
||||
```
|
||||
|
||||
|
||||
5
docSite/assets/images/social/lark.svg
Normal file
@@ -0,0 +1,5 @@
|
||||
<svg t="1728884315234" class="icon" viewBox="0 0 1224 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4847" width="28" height="28" fill="currentColor">
|
||||
|
||||
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|
||||
|
||||
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|
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@@ -11,7 +11,7 @@ FastGPT 项目在 Apache License 2.0 许可下开源,同时包含以下附加
|
||||
|
||||
+ FastGPT 允许被用于商业化,例如作为其他应用的“后端即服务”使用,或者作为应用开发平台提供给企业。然而,当满足以下条件时,必须联系作者获得商业许可:
|
||||
|
||||
+ 多租户 SaaS 服务:除非获得 FastGPT 的明确书面授权,否则不得使用 fastgpt.in 的源码来运营与 fastgpt.in 服务类似的多租户 SaaS 服务。
|
||||
+ 多租户 SaaS 服务:除非获得 FastGPT 的明确书面授权,否则不得使用 tryfastgpt.ai 的源码来运营与 tryfastgpt.ai 服务类似的多租户 SaaS 服务。
|
||||
+ LOGO 及版权信息:在使用 FastGPT 的过程中,不得移除或修改 FastGPT 控制台内的 LOGO 或版权信息。
|
||||
|
||||
请通过电子邮件 yujinlong@sealos.io 联系我们咨询许可事宜。
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
weight: 1100
|
||||
title: '商业版介绍'
|
||||
description: 'FastGPT 商业版介绍'
|
||||
title: '收费说明'
|
||||
description: 'FastGPT 收费说明'
|
||||
icon: 'shopping_cart'
|
||||
draft: false
|
||||
images: []
|
||||
|
||||
@@ -29,8 +29,8 @@ FastGPT 商业版是基于 FastGPT 开源版的增强版本,增加了一些独
|
||||
| web站点同步 | ❌ | ✅ | ✅ |
|
||||
| 管理后台 | ❌ | ✅ | 不需要 |
|
||||
| 增强训练模式 | ❌ | ✅ | ✅ |
|
||||
| 第三方应用快速接入(飞书、公众号) | ❌ | ✅ | ✅ |
|
||||
| 图片知识库 | ❌ | 设计中 | 设计中 |
|
||||
| 自动规划召回 | ❌ | 设计中 | 设计中 |
|
||||
| 对话日志运营分析 | ❌ | 设计中 | 设计中 |
|
||||
| 完整商业授权 | ❌ | ✅ | ✅ |
|
||||
{{< /table >}}
|
||||
|
||||
12
docSite/content/zh-cn/docs/commercial/saas.md
Normal file
@@ -0,0 +1,12 @@
|
||||
---
|
||||
title: '线上版定价'
|
||||
description: 'FastGPT 线上版定价'
|
||||
icon: 'currency_yen'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 1002
|
||||
type: redirect
|
||||
target: https://cloud.tryfastgpt.ai/price
|
||||
---
|
||||
|
||||
线上版价格请查看:[https://cloud.tryfastgpt.ai/price](https://cloud.tryfastgpt.ai/price)
|
||||
@@ -11,6 +11,6 @@ FastGPT 是一个由用户和贡献者参与推动的开源项目,如果您对
|
||||
|
||||
+ 📱 扫码加入社区微信交流群👇
|
||||
|
||||
<img width="400px" src="https://oss.laf.run/htr4n1-images/fastgpt-qr-code.jpg" class="medium-zoom-image" />
|
||||
<img width="400px" src="https://oss.laf.run/otnvvf-imgs/fastgpt-feishu1.png" class="medium-zoom-image" />
|
||||
|
||||
+ 🐞 请将任何 FastGPT 的 Bug、问题和需求提交到 [GitHub Issue](https://github.com/labring/fastgpt/issues/new/choose)。
|
||||
@@ -60,6 +60,8 @@ Tips: 可以通过点击上下文按键查看完整的上下文组成,便于
|
||||
|
||||
### 引用模板和提示词设计
|
||||
|
||||
简易模式已移除该功能,仅在工作流中可配置,可点击工作流中`AI对话节点`内,知识库引用旁边的`setting icon`进行配置。随着模型的增强,这部分功能将逐步弱化。
|
||||
|
||||
引用模板和引用提示词通常是成对出现,引用提示词依赖引用模板。
|
||||
|
||||
FastGPT 知识库采用 QA 对(不一定都是问答格式,仅代表两个变量)的格式存储,在转义成字符串时候会根据**引用模板**来进行格式化。知识库包含多个可用变量: q, a, sourceId(数据的ID), index(第n个数据), source(数据的集合名、文件名),score(距离得分,0-1) 可以通过 {{q}} {{a}} {{sourceId}} {{index}} {{source}} {{score}} 按需引入。下面一个模板例子:
|
||||
|
||||
@@ -4,7 +4,7 @@ description: "FastGPT 对话问题引导"
|
||||
icon: "code"
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 350
|
||||
weight: 108
|
||||
---
|
||||
|
||||

|
||||
|
||||
50
docSite/content/zh-cn/docs/course/collection_tags.md
Normal file
@@ -0,0 +1,50 @@
|
||||
---
|
||||
title: "知识库集合标签"
|
||||
description: "FastGPT 知识库集合标签使用说明"
|
||||
icon: "developer_guide"
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 109
|
||||
---
|
||||
|
||||
知识库集合标签是 FastGPT 商业版特有功能。它允许你对知识库中的数据集合添加标签进行分类,更高效地管理知识库数据。
|
||||
|
||||
而进一步可以在问答中,搜索知识库时添加集合过滤,实现更精确的搜索。
|
||||
|
||||
| | | |
|
||||
| --------------------- | --------------------- | --------------------- |
|
||||
|  |  |  |
|
||||
|
||||
## 标签基础操作说明
|
||||
|
||||
在知识库详情页面,可以对标签进行管理,可执行的操作有
|
||||
|
||||
- 创建标签
|
||||
- 修改标签名
|
||||
- 删除标签
|
||||
- 将一个标签赋给多个数据集合
|
||||
- 给一个数据集合添加多个标签
|
||||
|
||||
也可以利用标签对数据集合进行筛选
|
||||
|
||||
## 知识库搜索-集合过滤说明
|
||||
|
||||
利用标签可以在知识库搜索时,通过填写「集合过滤」这一栏来实现更精确的搜索,具体的填写示例如下
|
||||
|
||||
```json
|
||||
{
|
||||
"tags": {
|
||||
"$and": ["标签 1","标签 2"],
|
||||
"$or": ["有 $and 标签时,and 生效,or 不生效"]
|
||||
},
|
||||
"createTime": {
|
||||
"$gte": "YYYY-MM-DD HH:mm 格式即可,集合的创建时间大于该时间",
|
||||
"$lte": "YYYY-MM-DD HH:mm 格式即可,集合的创建时间小于该时间,可和 $gte 共同使用"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
在填写时有两个注意的点,
|
||||
|
||||
- 标签值可以为 `string` 类型的标签名,也可以为 `null`,而 `null` 代表着未设置标签的数据集合
|
||||
- 标签过滤有 `$and` 和 `$or` 两种条件类型,在同时设置了 `$and` 和 `$or` 的情况下,只有 `$and` 会生效
|
||||
@@ -42,7 +42,7 @@ FastGPT 采用了 RAG 中的 Embedding 方案构建知识库,要使用好 Fast
|
||||
|
||||
FastGPT 采用了`PostgresSQL`的`PG Vector`插件作为向量检索器,索引为`HNSW`。且`PostgresSQL`仅用于向量检索(该引擎可以替换成其它数据库),`MongoDB`用于其他数据的存取。
|
||||
|
||||
在`MongoDB`的`dataset.datas`表中,会存储向量原数据的信息,同时有一个`indexes`字段,会记录其对应的向量ID,这是一个数组,也就是说,一组向量可以对应多组数据。
|
||||
在`MongoDB`的`dataset.datas`表中,会存储向量原数据的信息,同时有一个`indexes`字段,会记录其对应的向量ID,这是一个数组,也就是说,一组数据可以对应多个向量。
|
||||
|
||||
在`PostgresSQL`的表中,设置一个`vector`字段用于存储向量。在检索时,会先召回向量,再根据向量的ID,去`MongoDB`中寻找原数据内容,如果对应了同一组原数据,则进行合并,向量得分取最高得分。
|
||||
|
||||
|
||||
97
docSite/content/zh-cn/docs/course/feishu.md
Normal file
@@ -0,0 +1,97 @@
|
||||
---
|
||||
title: "接入飞书机器人教程"
|
||||
description: "FastGPT 接入飞书机器人教程"
|
||||
icon: "chat"
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 111
|
||||
---
|
||||
|
||||
从 4.8.10 版本起,FastGPT 商业版支持直接接入飞书机器人,无需额外的 API。
|
||||
|
||||
## 1. 申请飞书应用
|
||||
|
||||
开一个免费的测试企业更方便进行调试。
|
||||
|
||||
1. 在[飞书开放平台](https://open.feishu.cn/app)的开发者后台申请企业自建应用。
|
||||
|
||||

|
||||
|
||||
添加一个**机器人**应用。
|
||||
|
||||
## 2. 在 FastGPT 新建发布渠道
|
||||
|
||||
在fastgpt中选择想要接入的应用,在 发布渠道 页面,新建一个接入飞书机器人的发布渠道,填写好基础信息。
|
||||
|
||||

|
||||
|
||||
## 3. 获取应用的 App ID, App Secret 两个凭证
|
||||
|
||||
在飞书开放平台开发者后台,刚刚创建的企业自建应用中,找到 App ID 和 App Secret,填入 FastGPT 新建发布渠道的对话框里面。
|
||||
|
||||

|
||||
|
||||
填入两个参数到 FastGPT 配置弹窗中。
|
||||
|
||||

|
||||
|
||||
(可选)在飞书开放平台开发者后台,点击事件与回调 -> 加密策略 获取 Encrypt Key,并填入飞书机器人接入的对话框里面
|
||||
|
||||

|
||||
|
||||
Encrypt Key 用于加密飞书服务器与 FastGPT 之间通信。
|
||||
建议如果使用 Https 协议,则不需要 Encrypt Key。如果使用 Http 协议通信,则建议使用 Encrypt Key
|
||||
Verification Token 默认生成的这个 Token 用于校验来源。但我们使用飞书官方推荐的另一种更为安全的校验方式,因此可以忽略这个配置项。
|
||||
## 4. 配置回调地址
|
||||
|
||||
新建好发布渠道后,点击**请求地址**,复制对应的请求地址。
|
||||
|
||||
在飞书控制台,点击左侧的 `事件与回调` ,点击`配置订阅方式`旁边的编辑 icon,粘贴刚刚复制的请求地址到输入框中。
|
||||
|
||||
| | | |
|
||||
| --- | --- | --- |
|
||||
|  |  |  |
|
||||
|
||||
## 5. 配置机器人回调事件和权限
|
||||
|
||||
* 添加 `接收消息` 事件
|
||||
|
||||
在`事件与回调`页面,点击`添加事件`。
|
||||
|
||||
搜索`接收消息`,或者直接搜索 `im.message.receive_v1` ,找到`接收消息 v2.0`的时间,勾选上并点击`确认添加`。
|
||||
|
||||
添加事件后,增加两个权限:点击对应权限,会有弹窗提示添加权限,添加上图两个权限。
|
||||
|
||||
| | |
|
||||
| --- | --- |
|
||||
|  |  |
|
||||
|
||||
不推荐启用上图中的两个“历史版本”,而是使用新版本的权限。
|
||||
- 若开启 “读取用户发给机器人的单聊消息”, 则单聊发送给机器人的消息将被送到 FastGPT
|
||||
- 若开启 “接收群聊中@机器人消息事件”, 则群聊中@机器人的消息将被送到 FastGPT
|
||||
- 若开启(不推荐开启)“获取群组中所有消息”,则群聊中所有消息都将被送到 FastGPT
|
||||
|
||||
## 6. 配置回复消息权限
|
||||
|
||||
在飞书控制台,点击左侧的 `权限管理` ,搜索框中输入`发消息`,找到`以应用的身份发消息`的权限,点击开通权限。
|
||||
|
||||

|
||||
|
||||
## 7. 发布机器人
|
||||
|
||||
点击飞书控制台左侧的`版本管理与发布`,即可发布机器人。
|
||||
|
||||

|
||||
|
||||
然后就可以在工作台里找到你的机器人啦。接下来就是把机器人拉进群组,或者单独与它对话。
|
||||
|
||||

|
||||
|
||||
## FAQ
|
||||
|
||||
### 发送了消息,没响应
|
||||
|
||||
1. 检查飞书机器人回调地址、权限等是否正确。
|
||||
2. 查看 FastGPT 对话日志,是否有对应的提问记录
|
||||
3. 如果有记录,飞书没回应,则是没给机器人开权限。
|
||||
4. 如果没记录,则可能是应用运行报错了,可以先试试最简单的机器人。(飞书机器人无法输入全局变量、文件、图片内容)
|
||||
132
docSite/content/zh-cn/docs/course/fileInput.md
Normal file
@@ -0,0 +1,132 @@
|
||||
---
|
||||
title: '文件输入功能介绍'
|
||||
description: 'FastGPT 文件输入功能介绍'
|
||||
icon: 'description'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 110
|
||||
---
|
||||
|
||||
从 4.8.9 版本起,FastGPT 支持在`简易模式`和`工作流`中,配置用户上传文件、图片功能。下面先简单介绍下如何使用文件输入功能,最后是介绍下文件解析的工作原理。
|
||||
|
||||
|
||||
## 简易模式中使用
|
||||
|
||||
简易模式打开文件上传后,会使用工具调用模式,也就是由模型自行决策,是否需要读取文件内容。
|
||||
|
||||
可以找到左侧文件上传的配置项,点击其右侧的`开启`/`关闭`按键,即可打开配置弹窗。
|
||||
|
||||

|
||||
|
||||
随后,你的调试对话框中,就会出现一个文件选择的 icon,可以点击文件选择 icon,选择你需要上传的文件。
|
||||
|
||||
由于采用的是工具调用模式,所以在提问时候,可能需要加上适当的引导,让模型知道,你需要读取`文档`。
|
||||
|
||||

|
||||
|
||||
## 工作流中使用
|
||||
|
||||
工作流中,可以在系统配置中,找到`文件输入`配置项,点击其右侧的`开启`/`关闭`按键,即可打开配置弹窗。
|
||||
|
||||

|
||||
|
||||
在工作流中,使用文件的方式很多,最简单的就是类似下图中,直接通过工具调用接入文档解析,实现和简易模式一样的效果。
|
||||
|
||||

|
||||
|
||||
也可以更简单点,强制每轮对话都携带上文档内容进行回答,这样就不需要调用两次 AI 才能读取文档内容了。
|
||||
|
||||

|
||||
|
||||
当然,你也可以在工作流中,对文档进行内容提取、内容分析等,然后将分析的结果传递给 HTTP 或者其他模块,从而实现文件处理的 SOP。不过目前版本,`插件`中并未支持文件处理,所以在构建 SOP 的话可能还是有一些麻烦。
|
||||
|
||||
|
||||
## 文档解析工作原理
|
||||
|
||||
不同于图片识别,LLM 模型目前没有支持直接解析文档的能力,所有的文档“理解”都是通过文档转文字后拼接 prompt 实现。这里通过几个 FAQ 来解释文档解析的工作原理,理解文档解析的原理,可以更好的在工作流中使用文档解析功能。
|
||||
|
||||
### 上传的文件如何存储在数据库中
|
||||
|
||||
FastGPT 的对话记录存储结构中,role=user 的消息,value 值会按以下结构存储:
|
||||
|
||||
```ts
|
||||
type UserChatItemValueItemType = {
|
||||
type: 'text' | 'file'
|
||||
text?: {
|
||||
content: string;
|
||||
};
|
||||
file?: {
|
||||
type: 'img' | 'doc'
|
||||
name?: string;
|
||||
url: string;
|
||||
};
|
||||
};
|
||||
```
|
||||
|
||||
也就是说,上传的图片和文档,都会以 URL 的形式存储在库中,并不会存储`解析后的文档内容`。
|
||||
|
||||
### 图片如何处理
|
||||
|
||||
文档解析节点不会处理图片,图片链接会被过滤,图片识别请直接使用支持图片识别的 LLM 模型。
|
||||
|
||||
### 文档解析节点如何工作
|
||||
|
||||
文档解析依赖文档解析节点,这个节点会接收一个`array<string>`类型的输入,对应的是文件输入的 URL;输出的是一个`string`,对应的是文档解析后的内容。
|
||||
|
||||

|
||||
|
||||
* 在文档解析节点中,只会解析`文档`类型的 URL,它是通过文件 URL 解析出来的`文名件后缀`去判断的。如果你同时选择了文档和图片,图片会被忽略。
|
||||
* 文档解析节点,除了解析本轮工作流接收的文件外,还会把历史记录中的文档 URL 进行解析。最终会解析至多 n 个文档,n 取决于你配置文件上传时,允许的最大文件数量。
|
||||
|
||||
{{% alert icon="🤖" context="success" %}}
|
||||
举例:
|
||||
|
||||
配置了最多允许 5 个文件上传
|
||||
|
||||
1. 第一轮对话,上传 3 个文档和 1 个图片:文档解析节点,返回 3 个文档内容。
|
||||
2. 第二轮对话,不上传任何文件:文档解析节点,返回 3 个文档内容。
|
||||
3. 第三轮对话,上传 2 个文档:文档解析节点,返回 5 个文档内容。
|
||||
4. 第四轮对话,上传 1 个文档:文档解析节点,返回 5 个文档内容,第一轮对话中的第三个文档会被过滤掉。
|
||||
|
||||
{{% /alert %}}
|
||||
|
||||
* 多个文档内容如何拼接的
|
||||
|
||||
按下列的模板,对多个文件进行拼接,即文件名+文件内容的形式组成一个字符串,不同文档之间通过分隔符:`\n******\n` 进行分割。
|
||||
|
||||
```
|
||||
File: ${filename}
|
||||
<Content>
|
||||
${content}
|
||||
</Content>
|
||||
```
|
||||
|
||||
### 工具调用如何使用文档解析
|
||||
|
||||
在工具调用中,文档解析节点的调用提示词为:`解析对话中所有上传的文档,并返回对应文档内容`。
|
||||
|
||||
作为工具被执行后,文档解析节点会返回解析后的文档内容作为工具响应。
|
||||
|
||||
### AI对话中如何使用文档解析
|
||||
|
||||
在 AI 对话节点中,新增了一个文档引用的输入,可以直接引用文档解析节点的输出,从而实现文档内容的引用。
|
||||
|
||||
它接收一个`string`类型的输入,除了可以引用文档解析结果外,还可以实现自定义内容引用,最终会进行提示词拼接,放置在 role=system 的消息中。提示词模板如下:
|
||||
|
||||
```
|
||||
将 <Quote></Quote> 中的内容作为本次对话的参考:
|
||||
<Quote>
|
||||
{{quote}}
|
||||
</Quote>
|
||||
```
|
||||
|
||||
quote 为引用的内容。
|
||||
|
||||

|
||||
|
||||
## 文件输入后续更新
|
||||
|
||||
* 插件支持配置文件输入。
|
||||
* 子应用和插件调用,支持传递文件输入。
|
||||
* 文档解析,结构化解析结果。
|
||||
* 更多的文件类型输入以及解析器。
|
||||
@@ -1,133 +0,0 @@
|
||||
---
|
||||
title: " 打造高质量 AI 知识库(过期)"
|
||||
description: " 利用 FastGPT 打造高质量 AI 知识库"
|
||||
icon: "school"
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 300
|
||||
---
|
||||
|
||||
## 前言
|
||||
|
||||
自从去年 12 月 ChatGPT 发布后,带动了新的一轮应用交互革命。尤其是 GPT-3.5 接口全面放开后,LLM 应用雨后春笋般快速涌现,但因为 GPT 的可控性、随机性和合规性等问题,很多应用场景都没法落地。
|
||||
|
||||
3 月时候,在 Twitter 上刷到一个老哥使用 GPT 训练自己的博客记录,并且成本非常低(比起 FT)。他给出了一个完整的流程图:
|
||||
|
||||

|
||||
|
||||
看到这个推文后,我灵机一动,应用场景就十分清晰了。直接上手开干,在经过不到 1 个月时间,FastGPT 在原来多助手管理基础上,加入了向量搜索。于是便有了最早的一期视频:
|
||||
|
||||
{{< bilibili BV1Wo4y1p7i1 >}}
|
||||
|
||||
3 个月过去了,FastGPT 延续着早期的思路去完善和扩展,目前在向量搜索 + LLM 线性问答方面的功能基本上完成了。不过我们始终没有出一期关于如何构建知识库的教程,趁着 V4 在开发中,我们计划介绍一期《如何在 FastGPT 上构建高质量知识库》,以便大家更好的使用。
|
||||
|
||||
## FastGPT 知识库完整逻辑
|
||||
|
||||
在正式构建知识库前,我们先来了解下 FastGPT 是如何进行知识库检索的。首先了解几个基本概念:
|
||||
|
||||
1. 向量:将人类直观的语言(文字、图片、视频等)转成计算机可识别的语言(数组)。
|
||||
2. 向量相似度:两个向量之间可以进行计算,得到一个相似度,即代表:两个语言相似的程度。
|
||||
3. 语言大模型的一些特点:上下文理解、总结和推理。
|
||||
|
||||
结合上述 3 个概念,便有了 “向量搜索 + 大模型 = 知识库问答” 的公式。下图是 FastGPT V3 中知识库问答功能的完整逻辑:
|
||||
|
||||

|
||||
|
||||
与大部分其他知识库问答产品不一样的是, FastGPT 采用了 QA 问答对进行存储,而不是仅进行 chunk(文本分块)处理。目的是为了减少向量化内容的长度,让向量能更好的表达文本的含义,从而提高搜索精准度。
|
||||
此外 FastGPT 还提供了搜索测试和对话测试两种途径对数据进行调整,从而方便用户调整自己的数据。根据上述流程和方式,我们以构建一个 FastGPT 常见问题机器人为例,展示如何构建一个高质量的 AI 知识库。
|
||||
|
||||
## 构建知识库应用
|
||||
|
||||
首先,先创建一个 FastGPT 常见问题知识库
|
||||
|
||||

|
||||
|
||||
### 通过 QA 拆分,获取基础知识
|
||||
|
||||
我们先直接把 FastGPT Git 上一些已有文档,进行 QA 拆分,从而获取一些 FastGPT 基础的知识。下面是 README 例子。
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
### 修正 QA
|
||||
|
||||
通过 README 我们一共得到了 11 组数据,整体的质量还是不错的,图片和链接都提取出来了。不过最后一个知识点出现了一些截断,我们需要手动的修正一下。
|
||||
|
||||
此外,我们观察到第一列第三个知识点。这个知识点是介绍了 FastGPT 一些资源链接,但是 QA 拆分将答案放置在了 A 中,但通常来说用户的提问并不会直接问“有哪些链接”,通常会问:“部署教程”,“问题文档”之类的。因此,我们需要将这个知识点进行简单的一个处理,如下图:
|
||||
|
||||

|
||||
|
||||
我们先来创建一个应用,看看效果如何。 首先需要去创建一个应用,并且在知识库中关联相关的知识库。另外还需要在配置页的提示词中,告诉 GPT:“知识库的范围”。
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
整体的效果还是不错的,链接和对应的图片都可以顺利的展示。
|
||||
|
||||
### 录入社区常见问题
|
||||
|
||||
接着,我们再把 FastGPT 常见问题的文档导入,由于平时整理不当,我们只能手动的录入对应的问答。
|
||||
|
||||

|
||||
|
||||
导入结果如上图。可以看到,我们均采用的是问答对的格式,而不是粗略的直接导入。目的就是为了模拟用户问题,进一步的提高向量搜索的匹配效果。可以为同一个问题设置多种问法,效果更佳。
|
||||
FastGPT 还提供了 openapi 功能,你可以在本地对特殊格式的文件进行处理后,再上传到 FastGPT,具体可以参考:[FastGPT Api Docs](https://doc.fastgpt.in/docs/development/openapi)
|
||||
|
||||
## 知识库微调和参数调整
|
||||
|
||||
FastGPT 提供了搜索测试和对话测试两种途径对知识库进行微调,我们先来使用搜索测试对知识库进行调整。我们建议你提前收集一些用户问题进行测试,根据预期效果进行跳转。可以先进行搜索测试调整,判断知识点是否合理。
|
||||
|
||||
### 搜索测试
|
||||
|
||||

|
||||
|
||||
你可能会遇到下面这种情况,由于“知识库”这个关键词导致一些无关内容的相似度也被搜索进去,此时就需要给第四条记录也增加一个“知识库”关键词,从而去提高它的相似度。
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
### 提示词设置
|
||||
|
||||
提示词的作用是引导模型对话的方向。在设置提示词时,遵守 2 个原则:
|
||||
|
||||
1. 告诉 Gpt 回答什么方面内容。
|
||||
2. 给知识库一个基本描述,从而让 Gpt 更好的判断用户的问题是否属于知识库范围。
|
||||
|
||||

|
||||
|
||||
### 更好的限定模型聊天范围
|
||||
|
||||
首先,你可以通过调整知识库搜索时的相似度和最大搜索数量,实现从知识库层面限制聊天范围。通常我们可以设置相似度为 0.82,并设置空搜索回复内容。这意味着,如果用户的问题无法在知识库中匹配时,会直接回复预设的内容。
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
由于 openai 向量模型并不是针对中文,所以当问题中有一些知识库内容的关键词时,相似度
|
||||
会较高,此时无法从知识库层面进行限定。需要通过限定词进行调整,例如:
|
||||
|
||||
> 我的问题如果不是关于 FastGPT 的,请直接回复:“我不确定”。你仅需要回答知识库中的内容,不在其中的内容,不需要回答。
|
||||
|
||||
效果如下:
|
||||
|
||||

|
||||
|
||||
当然,gpt35 在一定情况下依然是不可控的。
|
||||
|
||||
### 通过对话调整知识库
|
||||
|
||||
与搜索测试类似,你可以直接在对话页里,点击“引用”,来随时修改知识库内容。
|
||||
|
||||

|
||||
|
||||
## 总结
|
||||
|
||||
1. 向量搜索是一种可以比较文本相似度的技术。
|
||||
2. 大模型具有总结和推理能力,可以从给定的文本中回答问题。
|
||||
3. 最有效的知识库构建方式是 QA 和手动构建。
|
||||
4. Q 的长度不宜过长。
|
||||
5. 需要调整提示词,来引导模型回答知识库内容。
|
||||
6. 可以通过调整搜索相似度、最大搜索数量和限定词来控制模型回复的范围。
|
||||
106
docSite/content/zh-cn/docs/course/official_account.md
Normal file
@@ -0,0 +1,106 @@
|
||||
---
|
||||
title: '接入微信公众号教程'
|
||||
description: 'FastGPT 接入微信公众号教程'
|
||||
icon: 'description'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 113
|
||||
---
|
||||
|
||||
从 4.8.10 版本起,FastGPT 商业版支持直接接入微信公众号,无需额外的 API。
|
||||
|
||||
**注意⚠️: 目前只支持通过验证的公众号(服务号和订阅号都可以)**
|
||||
|
||||
## 1. 在 FastGPT 新建发布渠道
|
||||
|
||||
在 FastGPT 中选择想要接入的应用,在 *发布渠道* 页面,新建一个接入微信公众号的发布渠道,填写好基础信息。
|
||||
|
||||

|
||||
|
||||
## 2. 登录微信公众平台,获取 AppID 、 Secret和Token
|
||||
|
||||
### 1. https://mp.weixin.qq.com 登录微信公众平台,选择您的公众号。
|
||||
|
||||
**只支持通过验证的公众号,未通过验证的公众号暂不支持。**
|
||||
|
||||
开发者可以从这个链接申请微信公众号的测试号进行测试,测试号可以正常使用,但不能配置 AES Key
|
||||
|
||||

|
||||
|
||||
### 2. 把3个参数填入 FastGPT 配置弹窗中。
|
||||

|
||||
|
||||
## 3. 在 IP 白名单中加入 FastGPT 的 IP
|
||||
|
||||

|
||||
|
||||
私有部署的用户可自行查阅自己的 IP 地址。
|
||||
|
||||
海外版用户(cloud.tryfastgpt.ai)可以填写下面的 IP 白名单:
|
||||
|
||||
```
|
||||
34.87.20.17
|
||||
35.247.161.35
|
||||
34.87.51.146
|
||||
34.87.110.152
|
||||
35.247.163.68
|
||||
34.126.163.205
|
||||
34.87.20.189
|
||||
34.87.102.86
|
||||
35.240.227.100
|
||||
35.198.192.104
|
||||
34.143.149.171
|
||||
34.87.152.33
|
||||
34.124.237.188
|
||||
35.197.149.75
|
||||
34.87.44.74
|
||||
34.124.189.116
|
||||
34.87.79.202
|
||||
34.87.173.252
|
||||
34.143.240.160
|
||||
34.87.180.104
|
||||
34.142.157.52
|
||||
```
|
||||
|
||||
国内版用户(fastgpt.cn)可以填写下面的 IP 白名单:
|
||||
|
||||
```
|
||||
47.97.59.172
|
||||
121.43.108.48
|
||||
121.41.75.88
|
||||
121.41.178.7
|
||||
121.40.65.187
|
||||
121.196.235.183
|
||||
120.55.195.90
|
||||
120.55.193.112
|
||||
120.26.229.115
|
||||
112.124.41.79
|
||||
101.37.205.32
|
||||
47.98.190.173
|
||||
```
|
||||
|
||||
## 4. 获取AES Key,选择加密方式
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
1. 随机生成AESKey,填入 FastGPT 配置弹窗中。
|
||||
|
||||
2. 选择加密方式为安全模式。
|
||||
|
||||
## 5. 获取 URL
|
||||
|
||||
1. 在FastGPT确认创建,获取URL。
|
||||
|
||||

|
||||
|
||||
2. 填入微信公众平台的 URL 处,然后提交保存
|
||||

|
||||
|
||||
## 6. 启用服务器配置(如已自动启用,请忽略)
|
||||

|
||||
|
||||
## 7. 开始使用
|
||||
|
||||
现在用户向公众号发消息,消息则会被转发到 FastGPT,通过公众号返回对话结果。
|
||||
@@ -1,13 +1,15 @@
|
||||
---
|
||||
title: "对接第三方 GPT 应用"
|
||||
description: "通过与 OpenAI 兼容的 API 对接第三方应用"
|
||||
title: "通过 API 访问应用"
|
||||
description: "通过 API 访问 FastGPT 应用"
|
||||
icon: "model_training"
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 505
|
||||
weight: 112
|
||||
---
|
||||
|
||||
## 获取 API 秘钥
|
||||
在 FastGPT 中,你可以为每一个应用创建多个 API 密钥,用于访问应用的 API 接口。每个密钥仅能访问一个应用。完整的接口可以[查看应用对话接口](/docs/development/openapi/chat)。
|
||||
|
||||
## 获取 API 密钥
|
||||
|
||||
依次选择应用 -> 「API访问」,然后点击「API 密钥」来创建密钥。
|
||||
|
||||
@@ -15,7 +17,7 @@ weight: 505
|
||||
密钥需要自己保管好,一旦关闭就无法再复制密钥,只能创建新密钥再复制。
|
||||
{{% /alert %}}
|
||||
|
||||

|
||||

|
||||
|
||||
{{% 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。
|
||||
@@ -26,7 +28,7 @@ Tips: 安全起见,你可以设置一个额度或者过期时间,放置 key
|
||||
|
||||
```bash
|
||||
OPENAI_API_BASE_URL: https://api.fastgpt.in/api (改成自己部署的域名)
|
||||
OPENAI_API_KEY = 上一步获取到的秘钥
|
||||
OPENAI_API_KEY = 上一步获取到的密钥
|
||||
```
|
||||
|
||||
**[ChatGPT Next Web](https://github.com/Yidadaa/ChatGPT-Next-Web) 示例:**
|
||||
@@ -18,7 +18,7 @@ Web 站点同步利用爬虫的技术,可以通过一个入口网站,自动
|
||||
Tips: 国内的媒体站点基本不可用,公众号、csdn、知乎等。可以通过终端发送`curl`请求检测是否为静态站点,例如:
|
||||
|
||||
```bash
|
||||
curl https://doc.fastgpt.in/docs/intro/
|
||||
curl https://doc.tryfastgpt.ai/docs/intro/
|
||||
```
|
||||
|
||||
## 如何使用
|
||||
|
||||
@@ -13,9 +13,7 @@ weight: 708
|
||||
|
||||
这个配置文件中包含了系统参数和各个模型配置:
|
||||
|
||||
## 4.6.8+ 版本新配置文件
|
||||
|
||||
llm模型全部合并
|
||||
## 4.6.8+ 版本新配置文件示例
|
||||
|
||||
```json
|
||||
{
|
||||
@@ -29,16 +27,16 @@ llm模型全部合并
|
||||
},
|
||||
"llmModels": [
|
||||
{
|
||||
"model": "gpt-3.5-turbo", // 模型名(对应OneAPI中渠道的模型名)
|
||||
"name": "gpt-3.5-turbo", // 别名
|
||||
"model": "gpt-4o-mini", // 模型名(对应OneAPI中渠道的模型名)
|
||||
"name": "gpt-4o-mini", // 模型别名
|
||||
"avatar": "/imgs/model/openai.svg", // 模型的logo
|
||||
"maxContext": 16000, // 最大上下文
|
||||
"maxResponse": 4000, // 最大回复
|
||||
"quoteMaxToken": 13000, // 最大引用内容
|
||||
"maxContext": 125000, // 最大上下文
|
||||
"maxResponse": 16000, // 最大回复
|
||||
"quoteMaxToken": 120000, // 最大引用内容
|
||||
"maxTemperature": 1.2, // 最大温度
|
||||
"charsPointsPrice": 0, // n积分/1k token(商业版)
|
||||
"charsPointsPrice": 0, // n积分/1k token(商业版)
|
||||
"censor": false, // 是否开启敏感校验(商业版)
|
||||
"vision": false, // 是否支持图片输入
|
||||
"vision": true, // 是否支持图片输入
|
||||
"datasetProcess": true, // 是否设置为知识库处理模型(QA),务必保证至少有一个为true,否则知识库会报错
|
||||
"usedInClassify": true, // 是否用于问题分类(务必保证至少有一个为true)
|
||||
"usedInExtractFields": true, // 是否用于内容提取(务必保证至少有一个为true)
|
||||
@@ -49,20 +47,20 @@ llm模型全部合并
|
||||
"customCQPrompt": "", // 自定义文本分类提示词(不支持工具和函数调用的模型
|
||||
"customExtractPrompt": "", // 自定义内容提取提示词
|
||||
"defaultSystemChatPrompt": "", // 对话默认携带的系统提示词
|
||||
"defaultConfig":{} // 请求API时,挟带一些默认配置(比如 GLM4 的 top_p)
|
||||
"defaultConfig": {} // 请求API时,挟带一些默认配置(比如 GLM4 的 top_p)
|
||||
},
|
||||
{
|
||||
"model": "gpt-4-0125-preview",
|
||||
"name": "gpt-4-turbo",
|
||||
"model": "gpt-4o",
|
||||
"name": "gpt-4o",
|
||||
"avatar": "/imgs/model/openai.svg",
|
||||
"maxContext": 125000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 100000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": 1.2,
|
||||
"charsPointsPrice": 0,
|
||||
"censor": false,
|
||||
"vision": false,
|
||||
"datasetProcess": false,
|
||||
"vision": true,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
@@ -72,30 +70,61 @@ llm模型全部合并
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"defaultConfig":{}
|
||||
"defaultConfig": {}
|
||||
},
|
||||
{
|
||||
"model": "gpt-4-vision-preview",
|
||||
"name": "gpt-4-vision",
|
||||
"model": "o1-mini",
|
||||
"name": "o1-mini",
|
||||
"avatar": "/imgs/model/openai.svg",
|
||||
"maxContext": 128000,
|
||||
"maxContext": 125000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 100000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": 1.2,
|
||||
"charsPointsPrice": 0,
|
||||
"censor": false,
|
||||
"vision": true,
|
||||
"datasetProcess": false,
|
||||
"usedInClassify": false,
|
||||
"usedInExtractFields": false,
|
||||
"usedInToolCall": false,
|
||||
"usedInQueryExtension": false,
|
||||
"toolChoice": true,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"defaultConfig":{}
|
||||
"defaultConfig": {
|
||||
"temperature": 1,
|
||||
"max_tokens": null,
|
||||
"stream": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"model": "o1-preview",
|
||||
"name": "o1-preview",
|
||||
"avatar": "/imgs/model/openai.svg",
|
||||
"maxContext": 125000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": 1.2,
|
||||
"charsPointsPrice": 0,
|
||||
"censor": false,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"defaultConfig": {
|
||||
"temperature": 1,
|
||||
"max_tokens": null,
|
||||
"stream": false
|
||||
}
|
||||
}
|
||||
],
|
||||
"vectorModels": [
|
||||
@@ -107,9 +136,30 @@ llm模型全部合并
|
||||
"defaultToken": 700, // 默认文本分割时候的 token
|
||||
"maxToken": 3000, // 最大 token
|
||||
"weight": 100, // 优先训练权重
|
||||
"defaultConfig":{}, // 自定义额外参数。例如,如果希望使用 embedding3-large 的话,可以传入 dimensions:1024,来返回1024维度的向量。(目前必须小于1536维度)
|
||||
"defaultConfig": {}, // 自定义额外参数。例如,如果希望使用 embedding3-large 的话,可以传入 dimensions:1024,来返回1024维度的向量。(目前必须小于1536维度)
|
||||
"dbConfig": {}, // 存储时的额外参数(非对称向量模型时候需要用到)
|
||||
"queryConfig": {} // 参训时的额外参数
|
||||
},
|
||||
{
|
||||
"model": "text-embedding-3-large",
|
||||
"name": "text-embedding-3-large",
|
||||
"avatar": "/imgs/model/openai.svg",
|
||||
"charsPointsPrice": 0,
|
||||
"defaultToken": 512,
|
||||
"maxToken": 3000,
|
||||
"weight": 100,
|
||||
"defaultConfig": {
|
||||
"dimensions": 1024
|
||||
}
|
||||
},
|
||||
{
|
||||
"model": "text-embedding-3-small",
|
||||
"name": "text-embedding-3-small",
|
||||
"avatar": "/imgs/model/openai.svg",
|
||||
"charsPointsPrice": 0,
|
||||
"defaultToken": 512,
|
||||
"maxToken": 3000,
|
||||
"weight": 100
|
||||
}
|
||||
],
|
||||
"reRankModels": [],
|
||||
@@ -138,19 +188,22 @@ llm模型全部合并
|
||||
|
||||
## 关于模型 logo
|
||||
|
||||
统一放置在项目的`public/imgs/model/xxx`目录中,目前内置了以下几种,如果有需要,可以PR增加。默认头像为 Hugging face 的 logo~
|
||||
统一放置在项目的`public/imgs/model/xxx`目录中,目前内置了以下几种,如果有需要,可以PR增加。默认logo为 Hugging face 的 logo~
|
||||
|
||||
- /imgs/model/baichuan.svg - 百川
|
||||
- /imgs/model/chatglm.svg - 智谱
|
||||
- /imgs/model/calude.svg - calude
|
||||
- /imgs/model/baichuan.svg - 百川智能
|
||||
- /imgs/model/chatglm.svg - 智谱清言
|
||||
- /imgs/model/claude.svg - claude
|
||||
- /imgs/model/deepseek.svg - deepseek
|
||||
- /imgs/model/doubao.svg - 火山豆包
|
||||
- /imgs/model/ernie.svg - 文心一言
|
||||
- /imgs/model/gemini.svg - gemini
|
||||
- /imgs/model/huggingface.svg - Hugging face【默认logo】
|
||||
- /imgs/model/minimax.svg - minimax
|
||||
- /imgs/model/moonshot.svg - 月之暗面
|
||||
- /imgs/model/openai.svg - OpenAI GPT
|
||||
- /imgs/model/qwen.svg - 通义千问
|
||||
- /imgs/model/sparkDesk.svg - 讯飞星火
|
||||
- /imgs/model/yi.svg - 零一万物
|
||||
- /imgs/model/gemini.svg - gemini
|
||||
- /imgs/model/deepseek.svg - deepseek
|
||||
- /imgs/model/minimax.svg - minimax
|
||||
-
|
||||
|
||||
## 特殊模型
|
||||
@@ -177,6 +230,27 @@ llm模型全部合并
|
||||
}
|
||||
```
|
||||
|
||||
### ReRank 接入(硅基流动)
|
||||
|
||||
有免费的 `bge-reranker-v2-m3` 模型可以使用。
|
||||
|
||||
1. 注册硅基流动账号: https://siliconflow.cn/
|
||||
2. 进入控制台,获取 API key: https://cloud.siliconflow.cn/account/ak
|
||||
3. 修改 FastGPT 配置文件
|
||||
|
||||
```json
|
||||
{
|
||||
"reRankModels": [
|
||||
{
|
||||
"model": "BAAI/bge-reranker-v2-m3", // 这里的model需要对应 siliconflow 的模型名
|
||||
"name": "BAAI/bge-reranker-v2-m3",
|
||||
"requestUrl": "https://api.siliconflow.cn/v1/rerank",
|
||||
"requestAuth": "siliconflow 上申请的 key"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### ReRank 接入(Cohere)
|
||||
|
||||
这个重排模型对中文不是很好,不如 bge 的好用。
|
||||
@@ -189,7 +263,7 @@ llm模型全部合并
|
||||
"reRankModels": [
|
||||
{
|
||||
"model": "rerank-multilingual-v2.0", // 这里的model需要对应 cohere 的模型名
|
||||
"name": "检索重排", // 随意
|
||||
"name": "rerank-multilingual-v2.0",
|
||||
"requestUrl": "https://api.cohere.ai/v1/rerank",
|
||||
"requestAuth": "Coherer上申请的key"
|
||||
}
|
||||
|
||||
@@ -14,9 +14,9 @@ weight: 920
|
||||
{{< table "table-hover table-striped-columns" >}}
|
||||
| 模型名 | 内存 | 显存 | 硬盘空间 | 启动命令 |
|
||||
|------|---------|---------|----------|--------------------------|
|
||||
| bge-rerank-base | >=4GB | >=4GB | >=8GB | python app.py |
|
||||
| bge-rerank-large | >=8GB | >=8GB | >=8GB | python app.py |
|
||||
| bge-rerank-v2-m3 | >=8GB | >=8GB | >=8GB | python app.py |
|
||||
| bge-reranker-base | >=4GB | >=4GB | >=8GB | python app.py |
|
||||
| bge-reranker-large | >=8GB | >=8GB | >=8GB | python app.py |
|
||||
| bge-reranker-v2-m3 | >=8GB | >=8GB | >=8GB | python app.py |
|
||||
{{< /table >}}
|
||||
|
||||
## 源码部署
|
||||
@@ -33,7 +33,7 @@ weight: 920
|
||||
|
||||
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-rerank-v2-m3](https://github.com/labring/FastGPT/tree/main/python/bge-rerank/bge-rerank-v2-m3)
|
||||
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)
|
||||
|
||||
### 3. 安装依赖
|
||||
|
||||
@@ -47,7 +47,7 @@ pip install -r requirements.txt
|
||||
|
||||
1. [https://huggingface.co/BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)
|
||||
2. [https://huggingface.co/BAAI/bge-reranker-large](https://huggingface.co/BAAI/bge-reranker-large)
|
||||
3. [https://huggingface.co/BAAI/bge-rerank-v2-m3](https://huggingface.co/BAAI/bge-rerank-v2-m3)
|
||||
3. [https://huggingface.co/BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)
|
||||
|
||||
在对应代码目录下 clone 模型。目录结构:
|
||||
|
||||
@@ -119,3 +119,19 @@ services:
|
||||
## 接入 FastGPT
|
||||
|
||||
参考 [ReRank模型接入](/docs/development/configuration/#rerank-接入),host 变量为部署的域名。
|
||||
|
||||
## QA
|
||||
|
||||
### Docker 运行提示 `Bus error (core dumped)`
|
||||
|
||||
尝试增加 `docker-compose.yml` 配置项 `shm_size` ,以增加容器中的共享内存目录大小。
|
||||
|
||||
```
|
||||
...
|
||||
services:
|
||||
reranker:
|
||||
...
|
||||
container_name: reranker
|
||||
shm_size: '2gb'
|
||||
...
|
||||
```
|
||||
|
||||
@@ -124,53 +124,36 @@ curl --location --request POST 'https://<oneapi_url>/v1/chat/completions' \
|
||||
|
||||
## 将本地模型接入 FastGPT
|
||||
|
||||
修改 FastGPT 的 `config.json` 配置文件,其中 chatModels(对话模型)用于聊天对话,cqModels(问题分类模型)用来对问题进行分类,extractModels(内容提取模型)则用来进行工具选择。我们分别在 chatModels、cqModels 和 extractModels 中加入 qwen-chat 模型:
|
||||
修改 FastGPT 的 `config.json` 配置文件的 llmModels 部分加入 qwen-chat 模型:
|
||||
|
||||
```json
|
||||
{
|
||||
"chatModels": [
|
||||
...
|
||||
{
|
||||
"model": "qwen-chat",
|
||||
"name": "Qwen",
|
||||
"maxContext": 2048,
|
||||
"maxResponse": 2048,
|
||||
"quoteMaxToken": 2000,
|
||||
"maxTemperature": 1,
|
||||
"vision": false,
|
||||
"defaultSystemChatPrompt": ""
|
||||
}
|
||||
...
|
||||
...
|
||||
"llmModels": [
|
||||
{
|
||||
"model": "qwen-chat", // 模型名(对应OneAPI中渠道的模型名)
|
||||
"name": "Qwen", // 模型别名
|
||||
"avatar": "/imgs/model/Qwen.svg", // 模型的logo
|
||||
"maxContext": 125000, // 最大上下文
|
||||
"maxResponse": 4000, // 最大回复
|
||||
"quoteMaxToken": 120000, // 最大引用内容
|
||||
"maxTemperature": 1.2, // 最大温度
|
||||
"charsPointsPrice": 0, // n积分/1k token(商业版)
|
||||
"censor": false, // 是否开启敏感校验(商业版)
|
||||
"vision": true, // 是否支持图片输入
|
||||
"datasetProcess": true, // 是否设置为知识库处理模型(QA),务必保证至少有一个为true,否则知识库会报错
|
||||
"usedInClassify": true, // 是否用于问题分类(务必保证至少有一个为true)
|
||||
"usedInExtractFields": true, // 是否用于内容提取(务必保证至少有一个为true)
|
||||
"usedInToolCall": true, // 是否用于工具调用(务必保证至少有一个为true)
|
||||
"usedInQueryExtension": true, // 是否用于问题优化(务必保证至少有一个为true)
|
||||
"toolChoice": true, // 是否支持工具选择(分类,内容提取,工具调用会用到。目前只有gpt支持)
|
||||
"functionCall": false, // 是否支持函数调用(分类,内容提取,工具调用会用到。会优先使用 toolChoice,如果为false,则使用 functionCall,如果仍为 false,则使用提示词模式)
|
||||
"customCQPrompt": "", // 自定义文本分类提示词(不支持工具和函数调用的模型
|
||||
"customExtractPrompt": "", // 自定义内容提取提示词
|
||||
"defaultSystemChatPrompt": "", // 对话默认携带的系统提示词
|
||||
"defaultConfig": {} // 请求API时,挟带一些默认配置(比如 GLM4 的 top_p)
|
||||
}
|
||||
],
|
||||
"cqModels": [
|
||||
...
|
||||
{
|
||||
"model": "qwen-chat",
|
||||
"name": "Qwen",
|
||||
"maxContext": 2048,
|
||||
"maxResponse": 2048,
|
||||
"inputPrice": 0,
|
||||
"outputPrice": 0,
|
||||
"toolChoice": true,
|
||||
"functionPrompt": ""
|
||||
}
|
||||
...
|
||||
],
|
||||
"extractModels": [
|
||||
...
|
||||
{
|
||||
"model": "qwen-chat",
|
||||
"name": "Qwen",
|
||||
"maxContext": 2048,
|
||||
"maxResponse": 2048,
|
||||
"inputPrice": 0,
|
||||
"outputPrice": 0,
|
||||
"toolChoice": true,
|
||||
"functionPrompt": ""
|
||||
}
|
||||
...
|
||||
]
|
||||
}
|
||||
...
|
||||
```
|
||||
|
||||
然后重启 FastGPT 就可以在应用配置中选择 Qwen 模型进行对话:
|
||||
|
||||
@@ -35,6 +35,8 @@ weight: 707
|
||||
|
||||
### Milvus版本
|
||||
|
||||
暂不推荐,部分系统存在精度丢失,等待修复。
|
||||
|
||||
对于千万级以上向量性能更优秀。
|
||||
|
||||
[点击查看 Milvus 官方推荐配置](https://milvus.io/docs/prerequisite-docker.md)
|
||||
@@ -49,6 +51,8 @@ weight: 707
|
||||
|
||||
### zilliz cloud版本
|
||||
|
||||
暂不推荐,部分系统存在精度丢失,等待修复。
|
||||
|
||||
亿级以上向量首选。
|
||||
|
||||
由于向量库使用了 Cloud,无需占用本地资源,无需太关注。
|
||||
@@ -110,7 +114,7 @@ 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`和`fastgpt`,并在docker配置文件中注释掉`sandbox`和`fastgpt`的部分
|
||||
|
||||
- [config.json](https://github.com/labring/FastGPT/blob/main/projects/app/data/config.json)
|
||||
- [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)
|
||||
|
||||
{{% alert icon="🤖" context="success" %}}
|
||||
|
||||
@@ -121,4 +121,148 @@ OneAPI 的 API Key 配置错误,需要修改`OPENAI_API_KEY`环境变量,并
|
||||
|
||||
1. 模型服务不可用
|
||||
2. 模型接口参数异常(温度、max token等可能不适配)
|
||||
3. ....
|
||||
3. ....
|
||||
|
||||
|
||||
## 四、常见模型问题
|
||||
|
||||
### 报错 - 模型响应为空
|
||||
|
||||
该错误是由于 stream 模式下,oneapi 直接结束了流请求,并且未返回任何内容导致。
|
||||
|
||||
4.8.10 版本新增了错误日志,报错时,会在日志中打印出实际发送的 Body 参数,可以复制该参数后,通过 curl 向 oneapi 发起请求测试。
|
||||
|
||||
由于 oneapi 在 stream 模式下,无法正确捕获错误,可以设置成 `stream=false` 后进行测试。
|
||||
|
||||
### 如何测试模型是否支持工具调用
|
||||
|
||||
需要模型提供商和 oneapi 同时支持工具调用才可使用,测试方法如下:
|
||||
|
||||
1. 通过 `curl` 向 `oneapi` 发起第一轮 stream 模式的 tool 测试。
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://oneapi.xxx/v1/chat/completions' \
|
||||
--header 'Authorization: Bearer sk-xxxx' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"model": "gpt-4o-mini",
|
||||
"temperature": 0.01,
|
||||
"max_tokens": 8000,
|
||||
"stream": true,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "几点了"
|
||||
}
|
||||
],
|
||||
"tools": [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "hCVbIY",
|
||||
"description": "获取用户当前时区的时间。",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {},
|
||||
"required": []
|
||||
}
|
||||
}
|
||||
}
|
||||
],
|
||||
"tool_choice": "auto"
|
||||
}'
|
||||
```
|
||||
|
||||
2. 检查响应参数
|
||||
|
||||
如果能正常调用工具,会返回对应 `tool_calls` 参数。
|
||||
|
||||
```json
|
||||
{
|
||||
"id": "chatcmpl-A7kwo1rZ3OHYSeIFgfWYxu8X2koN3",
|
||||
"object": "chat.completion.chunk",
|
||||
"created": 1726412126,
|
||||
"model": "gpt-4o-mini-2024-07-18",
|
||||
"system_fingerprint": "fp_483d39d857",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"delta": {
|
||||
"role": "assistant",
|
||||
"content": null,
|
||||
"tool_calls": [
|
||||
{
|
||||
"index": 0,
|
||||
"id": "call_0n24eiFk8OUyIyrdEbLdirU7",
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "mEYIcFl84rYC",
|
||||
"arguments": ""
|
||||
}
|
||||
}
|
||||
],
|
||||
"refusal": null
|
||||
},
|
||||
"logprobs": null,
|
||||
"finish_reason": null
|
||||
}
|
||||
],
|
||||
"usage": null
|
||||
}
|
||||
```
|
||||
|
||||
3. 通过 `curl` 向 `oneapi` 发起第二轮 stream 模式的 tool 测试。
|
||||
|
||||
第二轮请求是把工具结果发送给模型。发起后会得到模型回答的结果。
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://oneapi.xxxx/v1/chat/completions' \
|
||||
--header 'Authorization: Bearer sk-xxx' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"model": "gpt-4o-mini",
|
||||
"temperature": 0.01,
|
||||
"max_tokens": 8000,
|
||||
"stream": true,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "几点了"
|
||||
},
|
||||
{
|
||||
"role": "assistant",
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "kDia9S19c4RO",
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "hCVbIY",
|
||||
"arguments": "{}"
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"tool_call_id": "kDia9S19c4RO",
|
||||
"role": "tool",
|
||||
"name": "hCVbIY",
|
||||
"content": "{\n \"time\": \"2024-09-14 22:59:21 Sunday\"\n}"
|
||||
}
|
||||
],
|
||||
"tools": [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "hCVbIY",
|
||||
"description": "获取用户当前时区的时间。",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {},
|
||||
"required": []
|
||||
}
|
||||
}
|
||||
}
|
||||
],
|
||||
"tool_choice": "auto"
|
||||
}'
|
||||
```
|
||||
@@ -7,11 +7,11 @@ toc: true
|
||||
weight: 705
|
||||
---
|
||||
|
||||
本文档介绍了如何设置开发环境以构建和测试 [FastGPT](https://fastgpt.in),。
|
||||
本文档介绍了如何设置开发环境以构建和测试 [FastGPT](https://tryfastgpt.ai),。
|
||||
|
||||
## 前置依赖项
|
||||
|
||||
您需要在计算机上安装和配置以下依赖项才能构建 [FastGPT](https://fastgpt.in):
|
||||
您需要在计算机上安装和配置以下依赖项才能构建 [FastGPT](https://tryfastgpt.ai):
|
||||
|
||||
- [Git](http://git-scm.com/)
|
||||
- [Docker](https://www.docker.com/)(构建镜像)
|
||||
@@ -150,7 +150,7 @@ FastGPT 在`pnpm i`后会执行`postinstall`脚本,用于自动生成`ChakraUI
|
||||
|
||||
遇到困难了吗?有任何问题吗? 加入微信群与开发者和用户保持沟通。
|
||||
|
||||
<img width="400px" src="https://oss.laf.run/htr4n1-images/fastgpt-qr-code.jpg" class="medium-zoom-image" />
|
||||
<img width="400px" src="https://oss.laf.run/otnvvf-imgs/fastgpt-feishu1.png" class="medium-zoom-image" />
|
||||
|
||||
## 代码结构说明
|
||||
|
||||
|
||||
@@ -172,7 +172,7 @@ docker exec -it mongo mongorestore -u "username" -p "password" --authenticationD
|
||||
5.重启容器 【C环境】
|
||||
```
|
||||
docker compose restart
|
||||
docker logs -f mongo **强烈建议先检查mongo运行情况,在去做登陆动作,如果mongo报错,访问web也会报错”
|
||||
docker logs -f mongo **强烈建议先检查mongo运行情况,在去做登录动作,如果mongo报错,访问web也会报错”
|
||||
```
|
||||
|
||||
如果mongo启动正常,显示的是类似这样的,而不是 “mongo is restarting”,后者就是错误
|
||||
@@ -182,5 +182,5 @@ docker logs -f mongo **强烈建议先检查mongo运行情况,在去做登陆
|
||||
<img width="508" alt="iShot_2024-05-09_19 23 13" src="https://github.com/labring/FastGPT/assets/103937568/2e2afc9f-484c-4b63-93ee-1c14aef03de0">
|
||||
|
||||
|
||||
6. 启动fastgpt容器服务后,登陆新fastgpt web,能看到原来的数据库内容完整显示,说明已经导入系统了。
|
||||
6. 启动fastgpt容器服务后,登录新fastgpt web,能看到原来的数据库内容完整显示,说明已经导入系统了。
|
||||
<img width="1728" alt="iShot_2024-05-09_19 23 51" src="https://github.com/labring/FastGPT/assets/103937568/846b6157-6b6a-4468-a1d9-c44d681ebf7c">
|
||||
|
||||
@@ -135,7 +135,7 @@ CHAT_API_KEY=sk-xxxxxx
|
||||
"charsPointsPrice": 0,
|
||||
"censor": false,
|
||||
"vision": false, // 是否支持图片输入
|
||||
"datasetProcess": false, // 是否设置为知识库处理模型
|
||||
"datasetProcess": true, // 是否设置为知识库处理模型
|
||||
"usedInClassify": true, // 是否用于问题分类
|
||||
"usedInExtractFields": true, // 是否用于字段提取
|
||||
"usedInToolCall": true, // 是否用于工具调用
|
||||
|
||||
@@ -7,29 +7,31 @@ toc: true
|
||||
weight: 852
|
||||
---
|
||||
|
||||
{{% alert icon="🤖 " context="success" %}}
|
||||
该接口的 API Key 需使用`应用特定的 key`,否则会报错。
|
||||
# 发起对话
|
||||
|
||||
有些包调用时,`BaseUrl`需要添加`v1`路径,有些不需要,如果出现404情况,可补充`v1`重试。
|
||||
{{% alert icon="🤖 " context="success" %}}
|
||||
* 该接口的 API Key 需使用`应用特定的 key`,否则会报错。
|
||||
|
||||
* 有些包调用时,`BaseUrl`需要添加`v1`路径,有些不需要,如果出现404情况,可补充`v1`重试。
|
||||
{{% /alert %}}
|
||||
|
||||
## 发起对话(简易应用和工作流)
|
||||
## 请求简易应用和工作流
|
||||
|
||||
对话接口兼容`GPT`的接口!如果你的项目使用的是标准的`GPT`官方接口,可以直接通过修改`BaseUrl`和 `Authorization`来访问 FastGpt 应用,不过需要注意下面几个规则:
|
||||
|
||||
{{% alert icon="🤖 " context="success" %}}
|
||||
* 传入的`model`,`temperature`等参数字段均无效,这些字段由编排决定。
|
||||
* 传入的`model`,`temperature`等参数字段均无效,这些字段由编排决定,不会根据 API 参数改变。
|
||||
* 不会返回实际消耗`Token`值,如果需要,可以设置`detail=true`,并手动计算 `responseData` 里的`tokens`值。
|
||||
{{% /alert %}}
|
||||
|
||||
### 请求
|
||||
|
||||
{{< tabs tabTotal="2" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="基础请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://api.fastgpt.in/api/v1/chat/completions' \
|
||||
curl --location --request POST 'http://localhost:3000/api/v1/chat/completions' \
|
||||
--header 'Authorization: Bearer fastgpt-xxxxxx' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
@@ -42,8 +44,49 @@ curl --location --request POST 'https://api.fastgpt.in/api/v1/chat/completions'
|
||||
},
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "导演是谁",
|
||||
"role": "user"
|
||||
}
|
||||
]
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="图片/文件请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
* 仅`messages`有部分区别,其他参数一致。
|
||||
* 目前不支持上次文件,需上传到自己的对象存储中,获取对应的文件链接。
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/v1/chat/completions' \
|
||||
--header 'Authorization: Bearer fastgpt-xxxxxx' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"chatId": "abcd",
|
||||
"stream": false,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "导演是谁"
|
||||
},
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {
|
||||
"url": "图片链接"
|
||||
}
|
||||
},
|
||||
{
|
||||
"type": "file_url",
|
||||
"name": "文件名",
|
||||
"url": "文档链接,支持 txt md html word pdf ppt csv excel"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}'
|
||||
@@ -269,7 +312,6 @@ event取值:
|
||||
{{< /tabs >}}
|
||||
|
||||
|
||||
|
||||
## 请求插件
|
||||
|
||||
插件的接口与对话接口一致,仅请求参数略有区别,有以下规定:
|
||||
@@ -332,7 +374,7 @@ curl --location --request POST 'http://localhost:3000/api/v1/chat/completions' \
|
||||
},
|
||||
{
|
||||
"nodeId": "pluginOutput",
|
||||
"moduleName": "自定义插件输出",
|
||||
"moduleName": "插件输出",
|
||||
"moduleType": "pluginOutput",
|
||||
"totalPoints": 0,
|
||||
"pluginOutput": {
|
||||
@@ -430,7 +472,7 @@ event: answer
|
||||
data: [DONE]
|
||||
|
||||
event: flowResponses
|
||||
data: [{"nodeId":"fdDgXQ6SYn8v","moduleName":"AI 对话","moduleType":"chatNode","totalPoints":0.033,"model":"FastAI-3.5","tokens":33,"query":"你好","maxToken":2000,"historyPreview":[{"obj":"Human","value":"你好"},{"obj":"AI","value":"你好!有什么可以帮助你的吗?"}],"contextTotalLen":2,"runningTime":1.42},{"nodeId":"pluginOutput","moduleName":"自定义插件输出","moduleType":"pluginOutput","totalPoints":0,"pluginOutput":{"result":"你好!有什么可以帮助你的吗?"},"runningTime":0}]
|
||||
data: [{"nodeId":"fdDgXQ6SYn8v","moduleName":"AI 对话","moduleType":"chatNode","totalPoints":0.033,"model":"FastAI-3.5","tokens":33,"query":"你好","maxToken":2000,"historyPreview":[{"obj":"Human","value":"你好"},{"obj":"AI","value":"你好!有什么可以帮助你的吗?"}],"contextTotalLen":2,"runningTime":1.42},{"nodeId":"pluginOutput","moduleName":"插件输出","moduleType":"pluginOutput","totalPoints":0,"pluginOutput":{"result":"你好!有什么可以帮助你的吗?"},"runningTime":0}]
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
@@ -455,8 +497,728 @@ event取值:
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
## 使用案例
|
||||
|
||||
- [接入 NextWeb/ChatGPT web 等应用](/docs/use-cases/openapi)
|
||||
- [接入 onwechat](/docs/use-cases/onwechat)
|
||||
- [接入 飞书](/docs/use-cases/feishu)
|
||||
|
||||
# 对话 CRUD
|
||||
|
||||
{{% alert icon="🤖 " context="success" %}}
|
||||
* 以下接口可使用任意`API Key`调用。
|
||||
* 4.8.12 以上版本才能使用
|
||||
{{% /alert %}}
|
||||
|
||||
**重要字段**
|
||||
|
||||
* chatId - 指一个应用下,某一个对话窗口的 ID
|
||||
* dataId - 指一个对话窗口下,某一个对话记录的 ID
|
||||
|
||||
## 历史记录
|
||||
|
||||
### 获取某个应用历史记录
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/getHistories' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"offset": 0,
|
||||
"pageSize": 20
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- offset - 偏移量,即从第几条数据开始取
|
||||
- pageSize - 记录数量
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": {
|
||||
"list": [
|
||||
{
|
||||
"chatId": "usdAP1GbzSGu",
|
||||
"updateTime": "2024-10-13T03:29:05.779Z",
|
||||
"appId": "66e29b870b24ce35330c0f08",
|
||||
"customTitle": "",
|
||||
"title": "你好",
|
||||
"top": false
|
||||
},
|
||||
{
|
||||
"chatId": "lC0uTAsyNBlZ",
|
||||
"updateTime": "2024-10-13T03:22:19.950Z",
|
||||
"appId": "66e29b870b24ce35330c0f08",
|
||||
"customTitle": "",
|
||||
"title": "测试",
|
||||
"top": false
|
||||
}
|
||||
],
|
||||
"total": 2
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 修改某个对话的标题
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/updateHistory' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"chatId": "chatId",
|
||||
"customTitle": "自定义标题"
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
- customTitle - 自定义对话名
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 置顶 / 取消置顶
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/updateHistory' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"chatId": "chatId",
|
||||
"top": true
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用Id
|
||||
- chatId - 历史记录 Id
|
||||
- top - 是否置顶,ture 置顶,false 取消置顶
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 删除某个历史记录
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request DELETE 'http://localhost:3000/api/core/chat/delHistory?chatId={{chatId}}&appId={{appId}}' \
|
||||
--header 'Authorization: Bearer {{apikey}}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 清空所有历史记录
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request DELETE 'http://localhost:3000/api/core/chat/clearHistories?appId={{appId}}' \
|
||||
--header 'Authorization: Bearer {{apikey}}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
## 对话记录
|
||||
|
||||
指的是某个 chatId 下的对话记录操作。
|
||||
|
||||
### 获取单个对话初始化信息
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request GET 'http://localhost:3000/api/core/chat/init?appId={{appId}}&chatId={{chatId}}' \
|
||||
--header 'Authorization: Bearer {{apikey}}'
|
||||
```
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": {
|
||||
"chatId": "sPVOuEohjo3w",
|
||||
"appId": "66e29b870b24ce35330c0f08",
|
||||
"variables": {
|
||||
|
||||
},
|
||||
"app": {
|
||||
"chatConfig": {
|
||||
"questionGuide": true,
|
||||
"ttsConfig": {
|
||||
"type": "web"
|
||||
},
|
||||
"whisperConfig": {
|
||||
"open": false,
|
||||
"autoSend": false,
|
||||
"autoTTSResponse": false
|
||||
},
|
||||
"chatInputGuide": {
|
||||
"open": false,
|
||||
"textList": [
|
||||
|
||||
],
|
||||
"customUrl": ""
|
||||
},
|
||||
"instruction": "",
|
||||
"variables": [
|
||||
|
||||
],
|
||||
"fileSelectConfig": {
|
||||
"canSelectFile": true,
|
||||
"canSelectImg": true,
|
||||
"maxFiles": 10
|
||||
},
|
||||
"_id": "66f1139aaab9ddaf1b5c596d",
|
||||
"welcomeText": ""
|
||||
},
|
||||
"chatModels": [
|
||||
"GPT-4o-mini"
|
||||
],
|
||||
"name": "测试",
|
||||
"avatar": "/imgs/app/avatar/workflow.svg",
|
||||
"intro": "",
|
||||
"type": "advanced",
|
||||
"pluginInputs": [
|
||||
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 获取对话记录列表
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/getPaginationRecords' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"chatId": "chatId",
|
||||
"offset": 0,
|
||||
"pageSize": 10,
|
||||
"loadCustomFeedbacks": true
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
- offset - 偏移量
|
||||
- pageSize - 记录数量
|
||||
- loadCustomFeedbacks - 是否读取自定义反馈(可选)
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": {
|
||||
"list": [
|
||||
{
|
||||
"_id": "670b84e6796057dda04b0fd2",
|
||||
"dataId": "jzqdV4Ap1u004rhd2WW8yGLn",
|
||||
"obj": "Human",
|
||||
"value": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": {
|
||||
"content": "你好"
|
||||
}
|
||||
}
|
||||
],
|
||||
"customFeedbacks": [
|
||||
|
||||
]
|
||||
},
|
||||
{
|
||||
"_id": "670b84e6796057dda04b0fd3",
|
||||
"dataId": "x9KQWcK9MApGdDQH7z7bocw1",
|
||||
"obj": "AI",
|
||||
"value": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": {
|
||||
"content": "你好!有什么我可以帮助你的吗?"
|
||||
}
|
||||
}
|
||||
],
|
||||
"customFeedbacks": [
|
||||
|
||||
],
|
||||
"llmModuleAccount": 1,
|
||||
"totalQuoteList": [
|
||||
|
||||
],
|
||||
"totalRunningTime": 2.42,
|
||||
"historyPreviewLength": 2
|
||||
}
|
||||
],
|
||||
"total": 2
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 获取单个对话记录运行详情
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request GET 'http://localhost:3000/api/core/chat/getResData?appId={{appId}}&chatId={{chatId}}&dataId={{dataId}}' \
|
||||
--header 'Authorization: Bearer {{apikey}}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 对话 Id
|
||||
- dataId - 对话记录 Id
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": [
|
||||
{
|
||||
"id": "mVlxkz8NfyfU",
|
||||
"nodeId": "448745",
|
||||
"moduleName": "common:core.module.template.work_start",
|
||||
"moduleType": "workflowStart",
|
||||
"runningTime": 0
|
||||
},
|
||||
{
|
||||
"id": "b3FndAdHSobY",
|
||||
"nodeId": "z04w8JXSYjl3",
|
||||
"moduleName": "AI 对话",
|
||||
"moduleType": "chatNode",
|
||||
"runningTime": 1.22,
|
||||
"totalPoints": 0.02475,
|
||||
"model": "GPT-4o-mini",
|
||||
"tokens": 75,
|
||||
"query": "测试",
|
||||
"maxToken": 2000,
|
||||
"historyPreview": [
|
||||
{
|
||||
"obj": "Human",
|
||||
"value": "你好"
|
||||
},
|
||||
{
|
||||
"obj": "AI",
|
||||
"value": "你好!有什么我可以帮助你的吗?"
|
||||
},
|
||||
{
|
||||
"obj": "Human",
|
||||
"value": "测试"
|
||||
},
|
||||
{
|
||||
"obj": "AI",
|
||||
"value": "测试成功!请问你有什么具体的问题或者需要讨论的话题吗?"
|
||||
}
|
||||
],
|
||||
"contextTotalLen": 4
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
|
||||
### 删除对话记录
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request DELETE 'http://localhost:3000/api/core/chat/item/delete?contentId={{contentId}}&chatId={{chatId}}&appId={{appId}}' \
|
||||
--header 'Authorization: Bearer {{apikey}}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
- contentId - 对话记录 Id
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 点赞 / 取消点赞
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/feedback/updateUserFeedback' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"chatId": "chatId",
|
||||
"dataId": "dataId",
|
||||
"userGoodFeedback": "yes"
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
- dataId - 对话记录 Id
|
||||
- userGoodFeedback - 用户点赞时的信息(可选),取消点赞时不填此参数即可
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
### 点踩 / 取消点踩
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/chat/feedback/updateUserFeedback' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"appId": "appId",
|
||||
"chatId": "chatId",
|
||||
"dataId": "dataId",
|
||||
"userBadFeedback": "yes"
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- appId - 应用 Id
|
||||
- chatId - 历史记录 Id
|
||||
- dataId - 对话记录 Id
|
||||
- userBadFeedback - 用户点踩时的信息(可选),取消点踩时不填此参数即可
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": null
|
||||
}
|
||||
```
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
## 猜你想问
|
||||
|
||||
{{< tabs tabTotal="3" >}}
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/ai/agent/createQuestionGuide' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"messages":[
|
||||
{
|
||||
"role": "user",
|
||||
"content": "你好"
|
||||
},
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": "你好!有什么我可以帮助你的吗?"
|
||||
}
|
||||
]
|
||||
}'
|
||||
```
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="参数说明" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- messages - 对话消息,提供给 AI 的消息记录
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
|
||||
{{< tab tabName="响应示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 200,
|
||||
"statusText": "",
|
||||
"message": "",
|
||||
"data": [
|
||||
"你对AI有什么看法?",
|
||||
"想了解AI的应用吗?",
|
||||
"你希望AI能做什么?"
|
||||
]
|
||||
}
|
||||
```
|
||||
{{< /markdownify >}}
|
||||
{{< /tab >}}
|
||||
{{< /tabs >}}
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -22,7 +22,7 @@ weight: 853
|
||||
**新例子**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://api.fastgpt.in/api/support/wallet/usage/createTrainingUsage' \
|
||||
curl --location --request POST 'http://localhost:3000/api/support/wallet/usage/createTrainingUsage' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
@@ -34,7 +34,7 @@ curl --location --request POST 'https://api.fastgpt.in/api/support/wallet/usage/
|
||||
**x例子**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://api.fastgpt.in/api/support/wallet/bill/createTrainingBill' \
|
||||
curl --location --request POST 'http://localhost:3000/api/support/wallet/bill/createTrainingBill' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
@@ -312,6 +312,8 @@ curl --location --request DELETE 'http://localhost:3000/api/core/dataset/delete?
|
||||
| chunkSize | 预估块大小 | |
|
||||
| chunkSplitter | 自定义最高优先分割符号 | |
|
||||
| qaPrompt | qa拆分提示词 | |
|
||||
| tags | 集合标签(字符串数组) | |
|
||||
| createTime | 文件创建时间(Date / String) | |
|
||||
|
||||
**出参**
|
||||
|
||||
@@ -466,7 +468,7 @@ curl --location --request POST 'http://localhost:3000/api/core/dataset/collectio
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"link":"https://doc.fastgpt.in/docs/course/quick-start/",
|
||||
"link":"https://doc.tryfastgpt.ai/docs/course/quick-start/",
|
||||
"datasetId":"6593e137231a2be9c5603ba7",
|
||||
"parentId": null,
|
||||
|
||||
@@ -531,6 +533,8 @@ data 为集合的 ID。
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
使用代码上传时,请注意中文 filename 需要进行 encode 处理,否则容易乱码。
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/dataset/collection/create/localFile' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
@@ -602,9 +606,11 @@ curl --location --request POST 'http://localhost:3000/api/proApi/core/dataset/co
|
||||
--data-raw '{
|
||||
"externalFileUrl":"https://image.xxxxx.com/fastgpt-dev/%E6%91%82.pdf",
|
||||
"externalFileId":"1111",
|
||||
"filename":"自定义文件名",
|
||||
"createTime": "2024-05-01T00:00:00.000Z",
|
||||
"filename":"自定义文件名.pdf",
|
||||
"datasetId":"6642d105a5e9d2b00255b27b",
|
||||
"parentId": null,
|
||||
"tags": ["tag1","tag2"],
|
||||
|
||||
"trainingType": "chunk",
|
||||
"chunkSize":512,
|
||||
@@ -623,7 +629,8 @@ curl --location --request POST 'http://localhost:3000/api/proApi/core/dataset/co
|
||||
| --- | --- | --- |
|
||||
| externalFileUrl | 文件访问链接(可以是临时链接) | ✅ |
|
||||
| externalFileId | 外部文件ID | |
|
||||
| filename | 自定义文件名 | |
|
||||
| filename | 自定义文件名,需要带后缀 | |
|
||||
| createTime | 文件创建时间(Date ISO 字符串都 ok) | |
|
||||
|
||||
|
||||
{{< /markdownify >}}
|
||||
@@ -708,7 +715,21 @@ curl --location --request POST 'http://localhost:3000/api/core/dataset/collectio
|
||||
"updateTime": "2099-01-01T00:00:00.000Z",
|
||||
"dataAmount": 3,
|
||||
"trainingAmount": 0,
|
||||
"canWrite": true
|
||||
"externalFileId": "1111",
|
||||
"tags": [
|
||||
"11",
|
||||
"测试的"
|
||||
],
|
||||
"forbid": false,
|
||||
"trainingType": "chunk",
|
||||
"permission": {
|
||||
"value": 4294967295,
|
||||
"isOwner": true,
|
||||
"hasManagePer": true,
|
||||
"hasWritePer": true,
|
||||
"hasReadPer": true
|
||||
}
|
||||
|
||||
},
|
||||
{
|
||||
"_id": "65abd0ad9d1448617cba6031",
|
||||
@@ -716,11 +737,23 @@ curl --location --request POST 'http://localhost:3000/api/core/dataset/collectio
|
||||
"tmbId": "65422be6aa44b7da77729ec9",
|
||||
"type": "link",
|
||||
"name": "快速上手 | FastGPT",
|
||||
"rawLink": "https://doc.fastgpt.in/docs/course/quick-start/",
|
||||
"rawLink": "https://doc.tryfastgpt.ai/docs/course/quick-start/",
|
||||
"updateTime": "2024-01-20T13:54:53.031Z",
|
||||
"dataAmount": 3,
|
||||
"trainingAmount": 0,
|
||||
"canWrite": true
|
||||
"externalFileId": "222",
|
||||
"tags": [
|
||||
"测试的"
|
||||
],
|
||||
"forbid": false,
|
||||
"trainingType": "chunk",
|
||||
"permission": {
|
||||
"value": 4294967295,
|
||||
"isOwner": true,
|
||||
"hasManagePer": true,
|
||||
"hasWritePer": true,
|
||||
"hasReadPer": true
|
||||
}
|
||||
}
|
||||
],
|
||||
"total": 93
|
||||
@@ -811,14 +844,36 @@ curl --location --request GET 'http://localhost:3000/api/core/dataset/collection
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
**通过集合 ID 修改集合信息**
|
||||
|
||||
```bash
|
||||
curl --location --request PUT 'http://localhost:3000/api/core/dataset/collection/update' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"id":"65abcfab9d1448617cba5f0d",
|
||||
"parentId":null,
|
||||
"name":"测2222试"
|
||||
"parentId": null,
|
||||
"name": "测2222试",
|
||||
"tags": ["tag1", "tag2"],
|
||||
"forbid": false,
|
||||
"createTime": "2024-01-01T00:00:00.000Z"
|
||||
}'
|
||||
```
|
||||
|
||||
**通过外部文件 ID 修改集合信息**, 只需要把 id 换成 datasetId 和 externalFileId。
|
||||
|
||||
```bash
|
||||
curl --location --request PUT 'http://localhost:3000/api/core/dataset/collection/update' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"datasetId":"6593e137231a2be9c5603ba7",
|
||||
"externalFileId":"1111",
|
||||
"parentId": null,
|
||||
"name": "测2222试",
|
||||
"tags": ["tag1", "tag2"],
|
||||
"forbid": false,
|
||||
"createTime": "2024-01-01T00:00:00.000Z"
|
||||
}'
|
||||
```
|
||||
|
||||
@@ -832,6 +887,9 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/collection
|
||||
- id: 集合的ID
|
||||
- parentId: 修改父级ID(可选)
|
||||
- name: 修改集合名称(可选)
|
||||
- tags: 修改集合标签(可选)
|
||||
- forbid: 修改集合禁用状态(可选)
|
||||
- createTime: 修改集合创建时间(可选)
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
@@ -1035,6 +1093,22 @@ A2:
|
||||
{{< tab tabName="请求示例" >}}
|
||||
{{< markdownify >}}
|
||||
|
||||
**4.8.11+**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/dataset/data/v2/list' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"offset": 0,
|
||||
"pageSize": 10,
|
||||
"collectionId":"65abd4ac9d1448617cba6171",
|
||||
"searchText":""
|
||||
}'
|
||||
```
|
||||
|
||||
**4.6.7+**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'http://localhost:3000/api/core/dataset/data/list' \
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
@@ -1054,10 +1128,13 @@ curl --location --request POST 'http://localhost:3000/api/core/dataset/data/list
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
|
||||
- pageNum: 偏移量(选填)
|
||||
- pageNum: 页码(选填)
|
||||
- pageSize: 每页数量,最大30(选填)
|
||||
- collectionId: 集合的ID(必填)
|
||||
- searchText: 模糊搜索词(选填)
|
||||
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
@@ -1173,7 +1250,7 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/data/updat
|
||||
--header 'Authorization: Bearer {{authorization}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"id":"65abd4b29d1448617cba61db",
|
||||
"dataId":"65abd4b29d1448617cba61db",
|
||||
"q":"测试111",
|
||||
"a":"sss",
|
||||
"indexes":[
|
||||
@@ -1196,7 +1273,7 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/data/updat
|
||||
{{< markdownify >}}
|
||||
|
||||
{{% alert icon=" " context="success" %}}
|
||||
- id: 数据的id
|
||||
- dataId: 数据的id
|
||||
- q: 主要数据(选填)
|
||||
- a: 辅助数据(选填)
|
||||
- indexes: 自定义索引(选填),类型参考`为集合批量添加添加数据`。如果创建时候有自定义索引,
|
||||
|
||||
@@ -53,9 +53,9 @@ weight: 860
|
||||
|
||||
在分享链接的地址中,增加一个额外的参数: authToken。例如:
|
||||
|
||||
原始的链接:`https://share.fastgpt.in/chat/share?shareId=648aaf5ae121349a16d62192`
|
||||
原始的链接:`https://share.tryfastgpt.ai/chat/share?shareId=648aaf5ae121349a16d62192`
|
||||
|
||||
完整链接: `https://share.fastgpt.in/chat/share?shareId=648aaf5ae121349a16d62192&authToken=userid12345`
|
||||
完整链接: `https://share.tryfastgpt.ai/chat/share?shareId=648aaf5ae121349a16d62192&authToken=userid12345`
|
||||
|
||||
这个`authToken`通常是你系统生成的用户唯一凭证(Token之类的)。FastGPT 会在鉴权接口的`body`中携带 token={{authToken}} 的参数。
|
||||
|
||||
@@ -227,7 +227,7 @@ curl --location --request POST '{{host}}/shareAuth/finish' \
|
||||
"historyPreview": [
|
||||
{
|
||||
"obj": "Human",
|
||||
"value": "使用 <Data></Data> 标记中的内容作为你的知识:\n\n<Data>\n导演是谁?\n电影《铃芽之旅》的导演是新海诚。\n------\n电影《铃芽之旅》的编剧是谁?22\n新海诚是本片的编剧。\n------\n电影《铃芽之旅》的女主角是谁?\n电影的女主角是铃芽。\n------\n电影《铃芽之旅》的制作团队中有哪位著名人士?2\n川村元气是本片的制作团队成员之一。\n------\n你是谁?\n我是电影《铃芽之旅》助手\n------\n电影《铃芽之旅》男主角是谁?\n电影《铃芽之旅》男主角是宗像草太,由松村北斗配音。\n------\n电影《铃芽之旅》的作者新海诚写了一本小说,叫什么名字?\n小说名字叫《铃芽之旅》。\n------\n电影《铃芽之旅》的女主角是谁?\n电影《铃芽之旅》的女主角是岩户铃芽,由原菜乃华配音。\n------\n电影《铃芽之旅》的故事背景是什么?\n日本\n------\n谁担任电影《铃芽之旅》中岩户环的配音?\n深津绘里担任电影《铃芽之旅》中岩户环的配音。\n</Data>\n\n回答要求:\n- 如果你不清楚答案,你需要澄清。\n- 避免提及你是从 <Data></Data> 获取的知识。\n- 保持答案与 <Data></Data> 中描述的一致。\n- 使用 Markdown 语法优化回答格式。\n- 使用与问题相同的语言回答。\n\n问题:\"\"\"导演是谁\"\"\""
|
||||
"value": "使用 <Data></Data> 标记中的内容作为本次对话的参考:\n\n<Data>\n导演是谁?\n电影《铃芽之旅》的导演是新海诚。\n------\n电影《铃芽之旅》的编剧是谁?22\n新海诚是本片的编剧。\n------\n电影《铃芽之旅》的女主角是谁?\n电影的女主角是铃芽。\n------\n电影《铃芽之旅》的制作团队中有哪位著名人士?2\n川村元气是本片的制作团队成员之一。\n------\n你是谁?\n我是电影《铃芽之旅》助手\n------\n电影《铃芽之旅》男主角是谁?\n电影《铃芽之旅》男主角是宗像草太,由松村北斗配音。\n------\n电影《铃芽之旅》的作者新海诚写了一本小说,叫什么名字?\n小说名字叫《铃芽之旅》。\n------\n电影《铃芽之旅》的女主角是谁?\n电影《铃芽之旅》的女主角是岩户铃芽,由原菜乃华配音。\n------\n电影《铃芽之旅》的故事背景是什么?\n日本\n------\n谁担任电影《铃芽之旅》中岩户环的配音?\n深津绘里担任电影《铃芽之旅》中岩户环的配音。\n</Data>\n\n回答要求:\n- 如果你不清楚答案,你需要澄清。\n- 避免提及你是从 <Data></Data> 获取的知识。\n- 保持答案与 <Data></Data> 中描述的一致。\n- 使用 Markdown 语法优化回答格式。\n- 使用与问题相同的语言回答。\n\n问题:\"\"\"导演是谁\"\"\""
|
||||
},
|
||||
{
|
||||
"obj": "AI",
|
||||
@@ -387,9 +387,9 @@ export default async function (ctx: FunctionContext) {
|
||||
|
||||
### 3. 修改分享链接参数
|
||||
|
||||
源分享链接:`https://share.fastgpt.in/chat/share?shareId=64be36376a438af0311e599c`
|
||||
源分享链接:`https://share.tryfastgpt.ai/chat/share?shareId=64be36376a438af0311e599c`
|
||||
|
||||
修改后:`https://share.fastgpt.in/chat/share?shareId=64be36376a438af0311e599c&authToken=fastgpt`
|
||||
修改后:`https://share.tryfastgpt.ai/chat/share?shareId=64be36376a438af0311e599c&authToken=fastgpt`
|
||||
|
||||
### 4. 测试效果
|
||||
|
||||
|
||||
@@ -19,15 +19,36 @@ FastGPT 使用了 one-api 项目来管理模型池,其可以兼容 OpenAI 、A
|
||||
|
||||
|
||||
## 一键部署
|
||||
Sealos 的服务器在国外,不需要额外处理网络问题,无需服务器、无需魔法、无需域名,支持高并发 & 动态伸缩。点击以下按钮即可一键部署 👇
|
||||
|
||||
使用 Sealos 服务,无需采购服务器、无需域名,支持高并发 & 动态伸缩,并且数据库应用采用 kubeblocks 的数据库,在 IO 性能方面,远超于简单的 Docker 容器部署。可以根据需求,再下面两个区域选择部署。
|
||||
|
||||
### 新加坡区
|
||||
|
||||
新加披区的服务器在国外,可以直接访问 OpenAI,但国内用户需要梯子才可以正常访问新加坡区。国际区价格稍贵,点击下面按键即可部署👇
|
||||
|
||||
<a href="https://template.cloud.sealos.io/deploy?templateName=fastgpt" rel="external" target="_blank"><img src="https://cdn.jsdelivr.net/gh/labring-actions/templates@main/Deploy-on-Sealos.svg" alt="Deploy on Sealos"/></a>
|
||||
|
||||
### 北京区
|
||||
|
||||
北京区服务提供商为火山云,国内用户可以稳定访问,但无法访问 OpenAI 等境外服务,价格约为新加坡区的 1/4。点击下面按键即可部署👇
|
||||
|
||||
<a href="https://bja.sealos.run/?openapp=system-template%3FtemplateName%3Dfastgpt" rel="external" target="_blank"><img src="https://raw.githubusercontent.com/labring-actions/templates/main/Deploy-on-Sealos.svg" alt="Deploy on Sealos"/></a>
|
||||
|
||||
### 开始部署
|
||||
|
||||
由于需要部署数据库,部署完后需要等待 2~4 分钟才能正常访问。默认用了最低配置,首次访问时会有些慢。
|
||||
|
||||
根据提示,输入`root_password`,和 `openai`/`oneapi` 的地址和密钥。
|
||||
|
||||

|
||||
|
||||
点击 Sealos 提供的外网地址即可打开 FastGPT 的可视化界面。
|
||||
点击部署后,会跳转到应用管理页面。可以点击`fastgpt`主应用右侧的详情按键(名字为 fastgpt-xxxx), 如下图所示。
|
||||
|
||||

|
||||
|
||||
点击详情后,会跳转到 fastgpt 的部署管理页面,点击外网访问地址中的链接,即可打开 fastgpt 服务。
|
||||
|
||||
如需绑定自定义域名、修改部署参数,可以点击右上角变更,根据 sealos 的指引完成。
|
||||
|
||||

|
||||
|
||||
@@ -53,6 +74,10 @@ Sealos 的服务器在国外,不需要额外处理网络问题,无需服务
|
||||
|
||||
点击变更或重启会自动拉取镜像更新,请确保镜像`tag`正确。建议不要使用`latest`,改成固定版本号。
|
||||
|
||||
## 收费
|
||||
|
||||
Sealos 采用按量计费的方式,也就是申请了多少 cpu、内存、磁盘,就按该申请量进行计费。具体的计费标准,可以打开`sealos`控制面板中的`费用中心`进行查看。
|
||||
|
||||
## Sealos 使用
|
||||
|
||||
### 简介
|
||||
@@ -64,7 +89,7 @@ FastGPT 商业版共包含了2个应用(fastgpt, fastgpt-plus)和2个数据
|
||||
点击右侧的详情,可以查看对应应用的详细信息。
|
||||
|
||||
### 如何更新/升级 FastGPT
|
||||
[升级脚本文档](https://doc.fastgpt.in/docs/development/upgrading/)先看下文档,看下需要升级哪个版本。注意,不要跨版本升级!!!!!
|
||||
[升级脚本文档](https://doc.tryfastgpt.ai/docs/development/upgrading/)先看下文档,看下需要升级哪个版本。注意,不要跨版本升级!!!!!
|
||||
|
||||
例如,目前是4.5 版本,要升级到4.5.1,就先把镜像版本改成v4.5.1,执行一下升级脚本,等待完成后再继续升级。如果目标版本不需要执行初始化,则可以跳过。
|
||||
|
||||
@@ -99,7 +124,7 @@ FastGPT 商业版共包含了2个应用(fastgpt, fastgpt-plus)和2个数据
|
||||
|
||||

|
||||
|
||||
[配置文件参考](https://doc.fastgpt.in/docs/development/configuration/)
|
||||
[配置文件参考](https://doc.tryfastgpt.ai/docs/development/configuration/)
|
||||
|
||||
### 修改站点名称以及 favicon
|
||||
修改应用的环境变量,增加
|
||||
|
||||
@@ -77,7 +77,7 @@ docker-compose up -d
|
||||
|
||||
商业版用户需要执行一个初始化,格式化团队信息。
|
||||
|
||||
发起 1 个 HTTP 请求 ({{rootkey}} 替换成环境变量里的 `rootkey`,{{host}} 替换成自己域名)
|
||||
发起 1 个 HTTP 请求 ({{rootkey}} 替换成环境变量里的 `rootkey`,{{host}} 替换成商业版域名)
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://{{host}}/api/init/v468' \
|
||||
|
||||