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V4.8.20 feature (#3686)

Browse Source 
* Aiproxy (#3649)

* model config

* feat: model config ui

* perf: rename variable

* feat: custom request url

* perf: model buffer

* perf: init model

* feat: json model config

* auto login

* fix: ts

* update packages

* package

* fix: dockerfile

* feat: usage filter & export & dashbord (#3538)

* feat: usage filter & export & dashbord

* adjust ui

* fix tmb scroll

* fix code & selecte all

* merge

* perf: usages list；perf: move components (#3654)

* perf: usages list

* team sub plan load

* perf: usage dashboard code

* perf: dashboard ui

* perf: move components

* add default model config (#3653)

* 4.8.20 test (#3656)

* provider

* perf: model config

* model perf (#3657)

* fix: model

* dataset quote

* perf: model config

* model tag

* doubao model config

* perf: config model

* feat: model test

* fix: POST 500 error on dingtalk bot (#3655)

* feat: default model (#3662)

* move model config

* feat: default model

* fix: false triggerd org selection (#3661)

* export usage csv i18n (#3660)

* export usage csv i18n

* fix build

* feat: markdown extension (#3663)

* feat: markdown extension

* media cros

* rerank test

* default price

* perf: default model

* fix: cannot custom provider

* fix: default model select

* update bg

* perf: default model selector

* fix: usage export

* i18n

* fix: rerank

* update init extension

* perf: ip limit check

* doubao model order

* web default modle

* perf: tts selector

* perf: tts error

* qrcode package

* reload buffer (#3665)

* reload buffer

* reload buffer

* tts selector

* fix: err tip (#3666)

* fix: err tip

* perf: training queue

* doc

* fix interactive edge (#3659)

* fix interactive edge

* fix

* comment

* add gemini model

* fix: chat model select

* perf: supplement assistant empty response (#3669)

* perf: supplement assistant empty response

* check array

* perf: max_token count;feat: support resoner output;fix: member scroll (#3681)

* perf: supplement assistant empty response

* check array

* perf: max_token count

* feat: support resoner output

* member scroll

* update provider order

* i18n

* fix: stream response (#3682)

* perf: supplement assistant empty response

* check array

* fix: stream response

* fix: model config cannot set to null

* fix: reasoning response (#3684)

* perf: supplement assistant empty response

* check array

* fix: reasoning response

* fix: reasoning response

* doc (#3685)

* perf: supplement assistant empty response

* check array

* doc

* lock

* animation

* update doc

* update compose

* doc

* doc

---------

Co-authored-by: heheer <heheer@sealos.io>
Co-authored-by: a.e. <49438478+I-Info@users.noreply.github.com>
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# Step 4 - Builds the site using Hugo # Step 4 - Builds the site using Hugo
- name: Build - name: Build
run: cd docSite && hugo mod get -u github.com/colinwilson/lotusdocs && hugo -v --minify run: cd docSite && hugo mod get -u github.com/colinwilson/lotusdocs@6d0568e” && hugo -v --minify
# Step 5 - Push our generated site to Vercel # Step 5 - Push our generated site to Vercel
- name: Deploy to Vercel - name: Deploy to Vercel

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# Step 4 - Builds the site using Hugo # Step 4 - Builds the site using Hugo
- name: Build - name: Build
run: cd docSite && hugo mod get -u github.com/colinwilson/lotusdocs && hugo -v --minify run: cd docSite && hugo mod get -u github.com/colinwilson/lotusdocs@6d0568e” && hugo -v --minify
# Step 5 - Push our generated site to Vercel # Step 5 - Push our generated site to Vercel
- name: Deploy to Vercel - name: Deploy to Vercel

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WORKDIR /app WORKDIR /app
ADD ./docSite hugo ADD ./docSite hugo
RUN cd /app/hugo && hugo mod get -u github.com/colinwilson/lotusdocs && hugo -v --minify RUN cd /app/hugo && hugo mod get -u github.com/colinwilson/lotusdocs@6d0568e” && hugo -v --minify
FROM fholzer/nginx-brotli:latest FROM fholzer/nginx-brotli:latest

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docSite/content/zh-cn/docs/development/configuration.md
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@ -25,251 +25,6 @@ weight: 707
"qaMaxProcess": 15, // 问答拆分线程数量 "qaMaxProcess": 15, // 问答拆分线程数量
"tokenWorkers": 50, // Token 计算线程保持数，会持续占用内存，不能设置太大。 "tokenWorkers": 50, // Token 计算线程保持数，会持续占用内存，不能设置太大。
"pgHNSWEfSearch": 100 // 向量搜索参数。越大，搜索越精确，但是速度越慢。设置为100，有99%+精度。 "pgHNSWEfSearch": 100 // 向量搜索参数。越大，搜索越精确，但是速度越慢。设置为100，有99%+精度。
},
"llmModels": [
{
"provider": "OpenAI", // 模型提供商，主要用于分类展示，目前已经内置提供商包括：https://github.com/labring/FastGPT/blob/main/packages/global/core/ai/provider.ts, 可 pr 提供新的提供商，或直接填写 Other
"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
"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）
"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, // 是否设置为文本理解模型（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。）
"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）
"fieldMap": {} // 字段映射（o1 模型需要把 max_tokens 映射为 max_completion_tokens）
},
{
"provider": "OpenAI",
"model": "gpt-4o",
"name": "gpt-4o",
"maxContext": 125000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 1.2,
"charsPointsPrice": 0,
"censor": false,
"vision": true,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": true,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"defaultConfig": {},
"fieldMap": {}
},
{
"provider": "OpenAI",
"model": "o1-mini",
"name": "o1-mini",
"maxContext": 125000,
"maxResponse": 65000,
"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
}
},
{
"provider": "OpenAI",
"model": "o1-preview",
"name": "o1-preview",
"maxContext": 125000,
"maxResponse": 32000,
"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": [
{
"provider": "OpenAI",
"model": "text-embedding-3-small",
"name": "text-embedding-3-small",
"charsPointsPrice": 0,
"defaultToken": 512,
"maxToken": 3000,
"weight": 100
},
{
"provider": "OpenAI",
"model": "text-embedding-3-large",
"name": "text-embedding-3-large",
"charsPointsPrice": 0,
"defaultToken": 512,
"maxToken": 3000,
"weight": 100,
"defaultConfig": {
"dimensions": 1024
}
},
{
"provider": "OpenAI",
"model": "text-embedding-ada-002", // 模型名（与OneAPI对应）
"name": "Embedding-2", // 模型展示名
"charsPointsPrice": 0, // n积分/1k token
"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）
"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
}
],
"reRankModels": [],
"audioSpeechModels": [
{
"provider": "OpenAI",
"model": "tts-1",
"name": "OpenAI TTS1",
"charsPointsPrice": 0,
"voices": [
{ "label": "Alloy", "value": "alloy", "bufferId": "openai-Alloy" },
{ "label": "Echo", "value": "echo", "bufferId": "openai-Echo" },
{ "label": "Fable", "value": "fable", "bufferId": "openai-Fable" },
{ "label": "Onyx", "value": "onyx", "bufferId": "openai-Onyx" },
{ "label": "Nova", "value": "nova", "bufferId": "openai-Nova" },
{ "label": "Shimmer", "value": "shimmer", "bufferId": "openai-Shimmer" }
]
}
],
"whisperModel": {
"provider": "OpenAI",
"model": "whisper-1",
"name": "Whisper1",
"charsPointsPrice": 0
} }
} }
``` ```
## 内置的模型提供商ID
为了方便模型分类展示，FastGPT 内置了部分模型提供商的名字和 Logo。如果你期望补充提供商，可[提交 Issue](https://github.com/labring/FastGPT/issues)，并提供几个信息：
1. 厂商官网地址
2. 厂商 SVG logo，建议是正方形图片。
目前已支持的提供商, 复制 "-" 之前的字符串，作为 provider 的值。
- OpenAI
- Claude
- Gemini
- Meta
- MistralAI
- AliCloud - 阿里云
- Qwen - 通义千问
- Doubao - 豆包
- ChatGLM - 智谱
- DeepSeek - 深度求索
- Moonshot - 月之暗面
- MiniMax
- SparkDesk - 讯飞星火
- Hunyuan - 腾讯混元
- Baichuan - 百川
- Yi - 零一万物
- Ernie - 文心一言
- StepFun - 阶跃星辰
- Ollama
- BAAI - 智源研究院
- FishAudio
- Intern - 书生
- Moka - Moka-AI
- Other - 其他
## ReRank 模型接入
由于 OneAPI 不支持 Rerank 模型，所以需要单独配置接入，这里
### 使用硅基流动的在线模型
有免费的 `bge-reranker-v2-m3` 模型可以使用。
1. [点击注册硅基流动账号](https://cloud.siliconflow.cn/i/TR9Ym0c4)
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"
}
]
}
```
### 私有部署模型
请使用 4.6.6-alpha 以上版本，配置文件中的 `reRankModels` 为重排模型，虽然是数组，不过目前仅有第1个生效。
1. [部署 ReRank 模型](/docs/development/custom-models/bge-rerank/)
1. 找到 FastGPT 的配置文件中的 `reRankModels`， 4.6.6 以前是 `ReRankModels`。
2. 修改对应的值：
```json
{
"reRankModels": [
{
"model": "bge-reranker-base", // 随意
"name": "检索重排-base", // 随意
"charsPointsPrice": 0,
"requestUrl": "{{host}}/v1/rerank",
"requestAuth": "安全凭证，已自动补 Bearer"
}
]
}
```

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@ -118,10 +118,17 @@ services:
``` ```
## 接入 FastGPT ## 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。 1. 打开 FastGPT 模型配置，新增一个重排模型。
2. 填写模型配置表单：模型 ID 为`bge-reranker-base`，地址填写`{{host}}/v1/rerank`，host 为你部署的域名/IP:Port。
![alt text](/imgs/image-102.png)
## QA ## QA
### 403报错
FastGPT中，自定义请求 Token 和环境变量的 ACCESS_TOKEN 不一致。
### Docker 运行提示 `Bus error (core dumped)` ### 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。 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。

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@ -144,7 +144,6 @@ curl --location --request POST 'https://<oneapi_url>/v1/chat/completions' \
"usedInClassify": true, // 是否用于问题分类（务必保证至少有一个为true） "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） "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） "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。） "toolChoice": true, // 是否支持工具选择（分类，内容提取，工具调用会用到。）
"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） "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 "customCQPrompt": "", // 自定义文本分类提示词（不支持工具和函数调用的模型

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@ -7,6 +7,13 @@ toc: true
weight: 707 weight: 707
--- ---
## 前置知识
1. 基础的网络知识：端口，防火墙……
2. Docker 和 Docker Compose 基础知识
3. 大模型相关接口和参数
4. RAG 相关知识：向量模型，向量数据库，向量检索
## 部署架构图 ## 部署架构图
![](/imgs/sealos-fastgpt.webp) ![](/imgs/sealos-fastgpt.webp)
@ -202,6 +209,10 @@ docker restart oneapi
首次运行，会自动初始化 root 用户，密码为 `1234`（与环境变量中的`DEFAULT_ROOT_PSW`一致），日志里会提示一次`MongoServerError: Unable to read from a snapshot due to pending collection catalog changes;`可忽略。 首次运行，会自动初始化 root 用户，密码为 `1234`（与环境变量中的`DEFAULT_ROOT_PSW`一致），日志里会提示一次`MongoServerError: Unable to read from a snapshot due to pending collection catalog changes;`可忽略。
### 6. 配置模型
[点击查看模型配置教程](/docs/development/modelConfig/intro/)
## FAQ ## FAQ
### Mongo 副本集自动初始化失败 ### Mongo 副本集自动初始化失败

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@ -23,11 +23,11 @@ images: []
![](/imgs/faq1.png) ![](/imgs/faq1.png)
这是索引模型的长度限制，通过任何方式部署都一样的，但不同索引模型的配置不一样，可以在后台修改参数。 这是索引模型的长度限制，通过任何方式部署都一样的，但不同索引模型的配置不一样，可以在后台修改参数。
### sealos怎么挂载 小程序配置文件 ### 怎么挂载小程序配置文件
新增配置文件：/app/projects/app/public/xxxx.txt 将验证文件，挂载到指定位置：/app/projects/app/public/xxxx.txt
如图: 然后重启。例如:
![](/imgs/faq2.png) ![](/imgs/faq2.png)

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@ -0,0 +1,442 @@
---
title: 'FastGPT 模型配置说明'
description: 'FastGPT 模型配置说明'
icon: 'api'
draft: false
toc: true
weight: 744
---
在 4.8.20 版本以前，FastGPT 模型配置在 `config.json` 文件中声明，你可以在 https://github.com/labring/FastGPT/blob/main/projects/app/data/model.json 中找到旧版的配置文件示例。
从 4.8.20 版本开始，你可以直接在 FastGPT 页面中进行模型配置，并且系统内置了大量模型，无需从 0 开始配置。下面介绍模型配置的基本流程：
## 1. 使用 OneAPI 对接模型提供商
可以使用 [OneAPI 接入教程](/docs/development/modelconfig/one-api) 来进行模型聚合，从而可以对接更多模型提供商。你需要先在各服务商申请好 API 接入 OneAPI 后，才能在 FastGPT 中使用这些模型。示例流程如下：
![alt text](/imgs/image-95.png)
除了各模型官方的服务外，还有一些第三方服务商提供模型接入服务，当然你也可以用 Ollama 等来部署本地模型，最终都需要接入 OneAPI，下面是一些第三方服务商：
{{% alert icon=" " context="info" %}}
- [SiliconCloud(硅基流动)](https://cloud.siliconflow.cn/i/TR9Ym0c4): 提供开源模型调用的平台。
- [Sealos AIProxy](https://hzh.sealos.run/?openapp=system-aiproxy): 提供国内各家模型代理，无需逐一申请 api。
{{% /alert %}}
在 OneAPI 配置好模型后，你就可以打开 FastGPT 页面，启用对应模型了。
## 2. 登录 root 用户
仅 root 用户可以进行模型配置。
## 3. 进入模型配置页面
登录 root 用户后，在`账号-模型提供商-模型配置`中，你可以看到所有内置的模型和自定义模型，以及哪些模型启用了。
![alt text](/image-90.png)
## 4. 配置介绍
{{% alert icon="🤖 " context="success" %}}
注意：目前语音识别模型和重排模型仅会生效一个，所以配置时候，只需要配置一个即可。
{{% /alert %}}
### 核心配置
- 模型 ID：接口请求时候，Body 中`model`字段的值，全局唯一。
- 自定义请求地址/Key：如果需要绕过`OneAPI`，可以设置自定义请求地址和 Token。一般情况下不需要，如果 OneAPI 不支持某些模型，可以使用该特性。
### 模型类型
1. 语言模型 - 进行文本对话，多模态模型支持图片识别。
2. 索引模型 - 对文本块进行索引，用于相关文本检索。
3. 语音合成 - 将文本转换为语音。
4. 语音识别 - 将语音转换为文本。
5. 重排模型 - 对文本进行重排，用于优化文本质量。
### 启用模型
系统内置了目前主流厂商的模型，如果你不熟悉配置，直接点击`启用`即可，需要注意到是，模型 ID 需要和 OneAPI 中渠道的`模型`一致。
| | |
| --- | --- |
| ![alt text](/imgs/image-91.png) | ![alt text](/imgs/image-92.png) |
### 修改模型配置
点击模型右侧的齿轮即可进行模型配置，不同类型模型的配置有区别。
| | |
| --- | --- |
| ![alt text](/imgs/image-93.png) | ![alt text](/imgs/image-94.png) |
### 新增自定义模型
如果系统内置的模型无法满足你的需求，你可以添加自定义模型。自定义模型中，如果`模型 ID`与系统内置的模型 ID 一致，则会被认为是修改系统模型。
| | |
| --- | --- |
| ![alt text](/imgs/image-96.png) | ![alt text](/imgs/image-97.png) |
### 通过配置文件配置
如果你觉得通过页面配置模型比较麻烦，你也可以通过配置文件来配置模型。或者希望快速将一个系统的配置，复制到另一个系统，也可以通过配置文件来实现。
| | |
| --- | --- |
| ![alt text](/imgs/image-98.png) | ![alt text](/imgs/image-99.png) |
**语言模型字段说明：**
```json
{
"model": "模型 ID",
"metadata": {
"isCustom": true, // 是否为自定义模型
"isActive": true, // 是否启用
"provider": "OpenAI", // 模型提供商，主要用于分类展示，目前已经内置提供商包括：https://github.com/labring/FastGPT/blob/main/packages/global/core/ai/provider.ts, 可 pr 提供新的提供商，或直接填写 Other
"model": "gpt-4o-mini", // 模型ID(对应OneAPI中渠道的模型名)
"name": "gpt-4o-mini", // 模型别名
"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）
"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, // 是否设置为文本理解模型（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）
"toolChoice": true, // 是否支持工具选择（分类，内容提取，工具调用会用到。）
"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）
"fieldMap": {} // 字段映射（o1 模型需要把 max_tokens 映射为 max_completion_tokens）
}
}
```
**索引模型字段说明:**
```json
{
"model": "模型 ID",
"metadata": {
"isCustom": true, // 是否为自定义模型
"isActive": true, // 是否启用
"provider": "OpenAI", // 模型提供商
"model": "text-embedding-3-small", // 模型ID
"name": "text-embedding-3-small", // 模型别名
"charsPointsPrice": 0, // n积分/1k token
"defaultToken": 512, // 默认文本分割时候的 token
"maxToken": 3000 // 最大 token
}
}
```
**重排模型字段说明:**
```json
{
"model": "模型 ID",
"metadata": {
"isCustom": true, // 是否为自定义模型
"isActive": true, // 是否启用
"provider": "BAAI", // 模型提供商
"model": "bge-reranker-v2-m3", // 模型ID
"name": "ReRanker-Base", // 模型别名
"requestUrl": "", // 自定义请求地址
"requestAuth": "", // 自定义请求认证
"type": "rerank" // 模型类型
}
}
```
**语音合成模型字段说明:**
```json
{
"model": "模型 ID",
"metadata": {
"isActive": true, // 是否启用
"isCustom": true, // 是否为自定义模型
"type": "tts", // 模型类型
"provider": "FishAudio", // 模型提供商
"model": "fishaudio/fish-speech-1.5", // 模型ID
"name": "fish-speech-1.5", // 模型别名
"voices": [ // 音色
{
"label": "fish-alex", // 音色名称
"value": "fishaudio/fish-speech-1.5:alex", // 音色ID
},
{
"label": "fish-anna", // 音色名称
"value": "fishaudio/fish-speech-1.5:anna", // 音色ID
}
],
"charsPointsPrice": 0 // n积分/1k token
}
}
```
**语音识别模型字段说明:**
```json
{
"model": "whisper-1",
"metadata": {
"isActive": true, // 是否启用
"isCustom": true, // 是否为自定义模型
"provider": "OpenAI", // 模型提供商
"model": "whisper-1", // 模型ID
"name": "whisper-1", // 模型别名
"charsPointsPrice": 0, // n积分/1k token
"type": "stt" // 模型类型
}
}
```
## 模型测试
FastGPT 页面上提供了每类模型的简单测试，可以初步检查模型是否正常工作，会实际按模板发送一个请求。
![alt text](/imgs/image-105.png)
## 特殊接入示例
### ReRank 模型接入
由于 OneAPI 不支持 Rerank 模型，所以需要单独配置。FastGPT 中，模型配置支持自定义请求地址，可以绕过 OneAPI，直接向提供商发起请求，可以利用这个特性来接入 Rerank 模型。
#### 使用硅基流动的在线模型
有免费的 `bge-reranker-v2-m3` 模型可以使用。
1. [点击注册硅基流动账号](https://cloud.siliconflow.cn/i/TR9Ym0c4)
2. 进入控制台，获取 API key: https://cloud.siliconflow.cn/account/ak
3. 打开 FastGPT 模型配置，新增一个`BAAI/bge-reranker-v2-m3`的重排模型（如果系统内置了，也可以直接变更,无需新增）。
![alt text](/imgs/image-101.png)
#### 私有部署模型
[点击查看部署 ReRank 模型教程](/docs/development/custom-models/bge-rerank/)
### 接入语音识别模型
OneAPI 的语言识别接口，无法正确的识别其他模型（会始终识别成 whisper-1），所以如果想接入其他模型，可以通过自定义请求地址来实现。例如，接入硅基流动的 `FunAudioLLM/SenseVoiceSmall` 模型，可以参考如下配置：
点击模型编辑：
![alt text](/imgs/image-106.png)
填写硅基流动的地址：`https://api.siliconflow.cn/v1/audio/transcriptions`，并填写硅基流动的 API Key。
![alt text](/imgs/image-107.png)
## 其他配置项说明
### 自定义请求地址
如果填写了该值，则可以允许你绕过 OneAPI，直接向自定义请求地址发起请求。需要填写完整的请求地址，例如：
- LLM: {{host}}/v1/chat/completions
- Embedding: {{host}}/v1/embeddings
- STT: {{host}}/v1/audio/transcriptions
- TTS: {{host}}/v1/audio/speech
- Rerank: {{host}}/v1/rerank
自定义请求 Key，则是向自定义请求地址发起请求时候，携带请求头：Authorization: Bearer xxx 进行请求。
所有接口均遵循 OpenAI 提供的模型格式，可参考 [OpenAI API 文档](https://platform.openai.com/docs/api-reference/introduction) 进行配置。
由于 OpenAI 没有提供 ReRank 模型，遵循的是 Cohere 的格式。[点击查看接口请求示例](/docs/development/faq/#如何检查模型问题)
## 旧版模型配置说明
配置好 OneAPI 后，需要在`config.json`文件中，手动的增加模型配置，并重启。
由于环境变量不利于配置复杂的内容，FastGPT 采用了 ConfigMap 的形式挂载配置文件，你可以在 `projects/app/data/config.json` 看到默认的配置文件。可以参考 [docker-compose 快速部署](/docs/development/docker/) 来挂载配置文件。
**开发环境下**，你需要将示例配置文件 `config.json` 复制成 `config.local.json` 文件才会生效。
**Docker部署**，修改`config.json` 文件，需要重启容器。
下面配置文件示例中包含了系统参数和各个模型配置：
```json
{
"feConfigs": {
"lafEnv": "https://laf.dev" // laf环境。 https://laf.run （杭州阿里云） ,或者私有化的laf环境。如果使用 Laf openapi 功能，需要最新版的 laf 。
},
"systemEnv": {
"vectorMaxProcess": 15, // 向量处理线程数量
"qaMaxProcess": 15, // 问答拆分线程数量
"tokenWorkers": 50, // Token 计算线程保持数，会持续占用内存，不能设置太大。
"pgHNSWEfSearch": 100 // 向量搜索参数。越大，搜索越精确，但是速度越慢。设置为100，有99%+精度。
},
"llmModels": [
{
"provider": "OpenAI", // 模型提供商，主要用于分类展示，目前已经内置提供商包括：https://github.com/labring/FastGPT/blob/main/packages/global/core/ai/provider.ts, 可 pr 提供新的提供商，或直接填写 Other
"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
"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）
"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, // 是否设置为文本理解模型（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）
"toolChoice": true, // 是否支持工具选择（分类，内容提取，工具调用会用到。）
"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）
"fieldMap": {} // 字段映射（o1 模型需要把 max_tokens 映射为 max_completion_tokens）
},
{
"provider": "OpenAI",
"model": "gpt-4o",
"name": "gpt-4o",
"maxContext": 125000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 1.2,
"charsPointsPrice": 0,
"censor": false,
"vision": true,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"toolChoice": true,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"defaultConfig": {},
"fieldMap": {}
},
{
"provider": "OpenAI",
"model": "o1-mini",
"name": "o1-mini",
"maxContext": 125000,
"maxResponse": 65000,
"quoteMaxToken": 120000,
"maxTemperature": 1.2,
"charsPointsPrice": 0,
"censor": false,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"defaultConfig": {
"temperature": 1,
"max_tokens": null,
"stream": false
}
},
{
"provider": "OpenAI",
"model": "o1-preview",
"name": "o1-preview",
"maxContext": 125000,
"maxResponse": 32000,
"quoteMaxToken": 120000,
"maxTemperature": 1.2,
"charsPointsPrice": 0,
"censor": false,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"defaultConfig": {
"temperature": 1,
"max_tokens": null,
"stream": false
}
}
],
"vectorModels": [
{
"provider": "OpenAI",
"model": "text-embedding-3-small",
"name": "text-embedding-3-small",
"charsPointsPrice": 0,
"defaultToken": 512,
"maxToken": 3000,
"weight": 100
},
{
"provider": "OpenAI",
"model": "text-embedding-3-large",
"name": "text-embedding-3-large",
"charsPointsPrice": 0,
"defaultToken": 512,
"maxToken": 3000,
"weight": 100,
"defaultConfig": {
"dimensions": 1024
}
},
{
"provider": "OpenAI",
"model": "text-embedding-ada-002", // 模型名（与OneAPI对应）
"name": "Embedding-2", // 模型展示名
"charsPointsPrice": 0, // n积分/1k token
"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）
"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
}
],
"reRankModels": [],
"audioSpeechModels": [
{
"provider": "OpenAI",
"model": "tts-1",
"name": "OpenAI TTS1",
"charsPointsPrice": 0,
"voices": [
{ "label": "Alloy", "value": "alloy", "bufferId": "openai-Alloy" },
{ "label": "Echo", "value": "echo", "bufferId": "openai-Echo" },
{ "label": "Fable", "value": "fable", "bufferId": "openai-Fable" },
{ "label": "Onyx", "value": "onyx", "bufferId": "openai-Onyx" },
{ "label": "Nova", "value": "nova", "bufferId": "openai-Nova" },
{ "label": "Shimmer", "value": "shimmer", "bufferId": "openai-Shimmer" }
]
}
],
"whisperModel": {
"provider": "OpenAI",
"model": "whisper-1",
"name": "Whisper1",
"charsPointsPrice": 0
}
}
```

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@ -94,70 +94,16 @@ CHAT_API_KEY=sk-xxxxxx
![](/imgs/oneapi-demo1.png) ![](/imgs/oneapi-demo1.png)
### 2. 修改 FastGPT 配置文件 ### 2. 修改 FastGPT 模型配置
可以在 `/projects/app/src/data/config.json` 里找到配置文件（本地开发需要复制成 config.local.json）,按下面内容修改配置文件，最新/更具体的配置说明，可查看[FastGPT 配置文件说明](/docs/development/configuration)。 打开 FastGPT 模型配置，启动文心千帆模型，如果希望未内置，可以通过新增模型来配置。
配置模型关键点在于`model` 需要与 OneAPI 渠道中的模型一致。 ![alt text](/imgs/image-103.png)
```json
{
"llmModels": [ // 语言模型配置
{
"model": "ERNIE-Bot", // 这里的模型需要对应 One API 的模型
"name": "文心一言", // 对外展示的名称
"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
"maxTemperature": 1.2, // 最大温度
"charsPointsPrice": 0,
"censor": false,
"vision": false, // 是否支持图片输入
"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
"usedInQueryExtension": true, // 是否用于问题优化
"toolChoice": true, // 是否支持工具选择
"functionCall": false, // 是否支持函数调用
"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）
}
],
"vectorModels": [ // 向量模型配置
{
"model": "text-embedding-ada-002",
"name": "Embedding-2",
"avatar": "/imgs/model/openai.svg",
"charsPointsPrice": 0,
"defaultToken": 700,
"maxToken": 3000,
"weight": 100
},
]
}
```
### 3. 重启 FastGPT
**Docker 版本**
```bash
docker-compose down
docker-compose up -d
```
**Sealos 版本**
直接找到 FastGPT 服务，点击重启即可。
## 其他服务商接入参考 ## 其他服务商接入参考
这章介绍一些提供商接入 OneAPI 的教程，配置后不要忘记修改 FastGPT 配置文件。 这章介绍一些提供商接入 OneAPI 的教程，配置后不要忘记在 FastGPT 模型配置中启用。
### 阿里通义千问 ### 阿里通义千问

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@ -27,139 +27,13 @@ OPENAI_BASE_URL=https://api.siliconflow.cn/v1
CHAT_API_KEY=sk-xxxxxx CHAT_API_KEY=sk-xxxxxx
``` ```
## 3. 修改 FastGPT 配置文件 ## 3. 修改 FastGPT 模型配置
我们选取 SiliconCloud 中的模型作为 FastGPT 配置。这里配置了 `Qwen2.5 72b` 的纯语言和视觉模型；选择 `bge-m3` 作为向量模型；选择 `bge-reranker-v2-m3` 作为重排模型。选择 `fish-speech-1.5` 作为语音模型；选择 `SenseVoiceSmall` 作为语音输入模型。 系统内置了几个硅基流动的模型进行体验，如果需要其他模型，可以手动添加。
注意：ReRank 模型仍需配置一次 Api Key 这里启动了 `Qwen2.5 72b` 的纯语言和视觉模型；选择 `bge-m3` 作为向量模型；选择 `bge-reranker-v2-m3` 作为重排模型。选择 `fish-speech-1.5` 作为语音模型；选择 `SenseVoiceSmall` 作为语音输入模型。
```json ![alt text](/imgs/image-104.png)
{
"llmModels": [
{
"provider": "Other", // 模型提供商，主要用于分类展示，目前已经内置提供商包括：https://github.com/labring/FastGPT/blob/main/packages/global/core/ai/provider.ts, 可 pr 提供新的提供商，或直接填写 Other
"model": "Qwen/Qwen2.5-72B-Instruct", // 模型名(对应OneAPI中渠道的模型名)
"name": "Qwen2.5-72B-Instruct", // 模型别名
"maxContext": 32000, // 最大上下文
"maxResponse": 4000, // 最大回复
"quoteMaxToken": 30000, // 最大引用内容
"maxTemperature": 1, // 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": false, // 是否支持图片输入
"datasetProcess": true, // 是否设置为文本理解模型（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。）
"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）
"fieldMap": {} // 字段映射（o1 模型需要把 max_tokens 映射为 max_completion_tokens）
},
{
"provider": "Other",
"model": "Qwen/Qwen2-VL-72B-Instruct",
"name": "Qwen2-VL-72B-Instruct",
"maxContext": 32000,
"maxResponse": 4000,
"quoteMaxToken": 30000,
"maxTemperature": 1,
"charsPointsPrice": 0,
"censor": false,
"vision": true,
"datasetProcess": false,
"usedInClassify": false,
"usedInExtractFields": false,
"usedInToolCall": false,
"usedInQueryExtension": false,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"defaultConfig": {}
}
],
"vectorModels": [
{
"provider": "Other",
"model": "Pro/BAAI/bge-m3",
"name": "Pro/BAAI/bge-m3",
"charsPointsPrice": 0,
"defaultToken": 512,
"maxToken": 5000,
"weight": 100
}
],
"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"
}
],
"audioSpeechModels": [
{
"model": "fishaudio/fish-speech-1.5",
"name": "fish-speech-1.5",
"voices": [
{
"label": "fish-alex",
"value": "fishaudio/fish-speech-1.5:alex",
"bufferId": "fish-alex"
},
{
"label": "fish-anna",
"value": "fishaudio/fish-speech-1.5:anna",
"bufferId": "fish-anna"
},
{
"label": "fish-bella",
"value": "fishaudio/fish-speech-1.5:bella",
"bufferId": "fish-bella"
},
{
"label": "fish-benjamin",
"value": "fishaudio/fish-speech-1.5:benjamin",
"bufferId": "fish-benjamin"
},
{
"label": "fish-charles",
"value": "fishaudio/fish-speech-1.5:charles",
"bufferId": "fish-charles"
},
{
"label": "fish-claire",
"value": "fishaudio/fish-speech-1.5:claire",
"bufferId": "fish-claire"
},
{
"label": "fish-david",
"value": "fishaudio/fish-speech-1.5:david",
"bufferId": "fish-david"
},
{
"label": "fish-diana",
"value": "fishaudio/fish-speech-1.5:diana",
"bufferId": "fish-diana"
}
]
}
],
"whisperModel": {
"model": "FunAudioLLM/SenseVoiceSmall",
"name": "SenseVoiceSmall",
"charsPointsPrice": 0
}
}
```
## 4. 重启 FastGPT
## 5. 体验测试 ## 5. 体验测试

35
docSite/content/zh-cn/docs/development/sealos.md
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@ -34,7 +34,7 @@ FastGPT 使用了 one-api 项目来管理模型池，其可以兼容 OpenAI 、A
<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> <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 ### 1. 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。 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。
@ -52,27 +52,15 @@ FastGPT 使用了 one-api 项目来管理模型池，其可以兼容 OpenAI 、A
![](/imgs/sealos2.png) ![](/imgs/sealos2.png)
### 登录 ### 2. 登录
用户名：`root` 用户名：`root`
密码是刚刚一键部署时设置的`root_password` 密码是刚刚一键部署时设置的`root_password`
### 修改配置文件和环境变量 ### 3. 配置模型
在 Sealos 中，你可以打开`应用管理`（App Launchpad）看到部署的 FastGPT，可以打开`数据库`（Database）看到对应的数据库。 [点击查看模型配置教程](/docs/development/modelConfig/intro/)
在`应用管理`中，选中 FastGPT，点击变更，可以看到对应的环境变量和配置文件。
![](/imgs/fastgptonsealos1.png)
{{% alert icon="🤖 " context="success" %}}
在 Sealos 上，FastGPT 一共运行了 1 个服务和 2 个数据库，如暂停和删除请注意数据库一同操作。（你可以白天启动，晚上暂停它们，省钱大法）
{{% /alert %}}
### 更新
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 ## 收费
@ -88,7 +76,20 @@ 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。 点击右侧的详情，可以查看对应应用的详细信息。
### 修改配置文件和环境变量
在 Sealos 中，你可以打开`应用管理`（App Launchpad）看到部署的 FastGPT，可以打开`数据库`（Database）看到对应的数据库。
在`应用管理`中，选中 FastGPT，点击变更，可以看到对应的环境变量和配置文件。
![](/imgs/fastgptonsealos1.png)
{{% alert icon="🤖 " context="success" %}}
在 Sealos 上，FastGPT 一共运行了 1 个服务和 2 个数据库，如暂停和删除请注意数据库一同操作。（你可以白天启动，晚上暂停它们，省钱大法）
{{% /alert %}}
### 如何更新/升级 FastGPT ### 如何更新/升级 FastGPT
[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！！！！！ [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。 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。
@ -148,8 +149,6 @@ SYSTEM_FAVICON 可以是一个网络地址
![](/imgs/onsealos8.png) ![](/imgs/onsealos8.png)
### 管理后台(已合并到plus)
### 商业版镜像配置文件 ### 商业版镜像配置文件
``` ```

2
docSite/content/zh-cn/docs/development/upgrading/4811.md
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@ -31,7 +31,6 @@ weight: 813
"usedInClassify": true, "usedInClassify": true,
"usedInExtractFields": true, "usedInExtractFields": true,
"usedInToolCall": true, "usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false, "toolChoice": false,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",
@ -56,7 +55,6 @@ weight: 813
"usedInClassify": true, "usedInClassify": true,
"usedInExtractFields": true, "usedInExtractFields": true,
"usedInToolCall": true, "usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false, "toolChoice": false,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",

50
docSite/content/zh-cn/docs/development/upgrading/4820.md Normal file
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@ -0,0 +1,50 @@
---
title: 'V4.8.20(进行中)'
description: 'FastGPT V4.8.20 更新说明'
icon: 'upgrade'
draft: false
toc: true
weight: 804
---
## 更新指南
### 1. 做好数据库备份
### 2. 更新环境变量
如果有很早版本用户，配置了`ONEAPI_URL`的，需要统一改成`OPENAI_BASE_URL`
### 3. 更新镜像：
- 更新 fastgpt 镜像 tag: v4.8.20
- 更新 fastgpt-pro 商业版镜像 tag: v4.8.20
- Sandbox 镜像无需更新
### 4. 运行升级脚本
从任意终端，发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`；{{host}} 替换成**FastGPT 域名**。
```bash
curl --location --request POST 'https://{{host}}/api/admin/initv4820' \
--header 'rootkey: {{rootkey}}' \
--header 'Content-Type: application/json'
```
脚本会自动把原配置文件的模型加载到新版模型配置中。
## 完整更新内容
1. 新增 - 可视化模型参数配置。预设超过 100 个模型配置。同时支持所有类型模型的一键测试。（预计下个版本会完全支持在页面上配置渠道）。
2. 新增 - DeepSeek resoner 模型支持输出思考过程。
3. 新增 - 使用记录导出和仪表盘。
4. 新增 - markdown 语法扩展，支持音视频（代码块 audio 和 video）。
5. 新增 - 调整 max_tokens 计算逻辑。优先保证 max_tokens 为配置值，如超出最大上下文，则减少历史记录。例如：如果申请 8000 的 max_tokens，则上下文长度会减少 8000。
6. 优化 - 问题优化增加上下文过滤，避免超出上下文。
7. 优化 - 页面组件抽离，减少页面组件路由。
8. 优化 - 全文检索，忽略大小写。
9. 优化 - 问答生成和增强索引改成流输出，避免部分模型超时。
10. 优化 - 自动给 assistant 空 content，补充 null，同时合并连续的 text assistant，避免部分模型抛错。
11. 优化 - 调整图片 Host， 取消上传时补充 FE_DOMAIN，改成发送对话前补充，避免替换域名后原图片无法正常使用。
12. 修复 - 部分场景成员列表无法触底加载。
13. 修复 - 工作流递归执行，部分条件下无法正常运行。

8
files/docker/docker-compose-milvus.yml
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@ -114,15 +114,15 @@ services:
# fastgpt # fastgpt
sandbox: sandbox:
container_name: sandbox container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
networks: networks:
- fastgpt - fastgpt
restart: always restart: always
fastgpt: fastgpt:
container_name: fastgpt container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.17 # git image: ghcr.io/labring/fastgpt:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
ports: ports:
- 3000:3000 - 3000:3000
networks: networks:

8
files/docker/docker-compose-pgvector.yml
View File

@ -72,15 +72,15 @@ services:
# fastgpt # fastgpt
sandbox: sandbox:
container_name: sandbox container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
networks: networks:
- fastgpt - fastgpt
restart: always restart: always
fastgpt: fastgpt:
container_name: fastgpt container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.17 # git image: ghcr.io/labring/fastgpt:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
ports: ports:
- 3000:3000 - 3000:3000
networks: networks:

8
files/docker/docker-compose-zilliz.yml
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@ -53,15 +53,15 @@ services:
wait $$! wait $$!
sandbox: sandbox:
container_name: sandbox container_name: sandbox
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
networks: networks:
- fastgpt - fastgpt
restart: always restart: always
fastgpt: fastgpt:
container_name: fastgpt container_name: fastgpt
image: ghcr.io/labring/fastgpt:v4.8.17 # git image: ghcr.io/labring/fastgpt:v4.8.20 # git
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云 # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
ports: ports:
- 3000:3000 - 3000:3000
networks: networks:

4
files/helm/fastgpt/templates/configmap-config.yaml
View File

@ -23,7 +23,6 @@ data:
"usedInClassify": true, "usedInClassify": true,
"usedInExtractFields": true, "usedInExtractFields": true,
"usedInToolCall": true, "usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": true, "toolChoice": true,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",
@ -45,7 +44,6 @@ data:
"usedInClassify": true, "usedInClassify": true,
"usedInExtractFields": true, "usedInExtractFields": true,
"usedInToolCall": true, "usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": true, "toolChoice": true,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",
@ -67,7 +65,6 @@ data:
"usedInClassify": true, "usedInClassify": true,
"usedInExtractFields": true, "usedInExtractFields": true,
"usedInToolCall": true, "usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": true, "toolChoice": true,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",
@ -89,7 +86,6 @@ data:
"usedInClassify": false, "usedInClassify": false,
"usedInExtractFields": false, "usedInExtractFields": false,
"usedInToolCall": false, "usedInToolCall": false,
"usedInQueryExtension": false,
"toolChoice": true, "toolChoice": true,
"functionCall": false, "functionCall": false,
"customCQPrompt": "", "customCQPrompt": "",

10
packages/global/common/error/code/user.ts
View File

@ -2,12 +2,22 @@ import { ErrType } from '../errorCode';
import { i18nT } from '../../../../web/i18n/utils'; import { i18nT } from '../../../../web/i18n/utils';
/* team: 503000 */ /* team: 503000 */
export enum UserErrEnum { export enum UserErrEnum {
notUser = 'notUser',
userExist = 'userExist',
unAuthRole = 'unAuthRole', unAuthRole = 'unAuthRole',
account_psw_error = 'account_psw_error', account_psw_error = 'account_psw_error',
balanceNotEnough = 'balanceNotEnough', balanceNotEnough = 'balanceNotEnough',
unAuthSso = 'unAuthSso' unAuthSso = 'unAuthSso'
} }
const errList = [ const errList = [
{
statusText: UserErrEnum.notUser,
message: i18nT('common:code_error.account_not_found')
},
{
statusText: UserErrEnum.userExist,
message: i18nT('common:code_error.account_exist')
},
{ {
statusText: UserErrEnum.account_psw_error, statusText: UserErrEnum.account_psw_error,
message: i18nT('common:code_error.account_error') message: i18nT('common:code_error.account_error')

14
packages/global/common/system/types/index.d.ts vendored
View File

@ -3,7 +3,7 @@ import type {
ChatModelItemType, ChatModelItemType,
FunctionModelItemType, FunctionModelItemType,
LLMModelItemType, LLMModelItemType,
VectorModelItemType, EmbeddingModelItemType,
AudioSpeechModels, AudioSpeechModels,
STTModelType, STTModelType,
ReRankModelItemType ReRankModelItemType
@ -31,11 +31,13 @@ export type FastGPTConfigFileType = {
feConfigs: FastGPTFeConfigsType; feConfigs: FastGPTFeConfigsType;
systemEnv: SystemEnvType; systemEnv: SystemEnvType;
subPlans?: SubPlanType; subPlans?: SubPlanType;
llmModels: ChatModelItemType[];
vectorModels: VectorModelItemType[]; // Abandon
reRankModels: ReRankModelItemType[]; llmModels?: ChatModelItemType[];
audioSpeechModels: AudioSpeechModelType[]; vectorModels?: EmbeddingModelItemType[];
whisperModel: STTModelType; reRankModels?: ReRankModelItemType[];
audioSpeechModels?: TTSModelType[];
whisperModel?: STTModelType;
}; };
export type FastGPTFeConfigsType = { export type FastGPTFeConfigsType = {

6
packages/global/core/ai/constants.ts
View File

@ -15,15 +15,13 @@ export enum LLMModelTypeEnum {
all = 'all', all = 'all',
classify = 'classify', classify = 'classify',
extractFields = 'extractFields', extractFields = 'extractFields',
toolCall = 'toolCall', toolCall = 'toolCall'
queryExtension = 'queryExtension'
} }
export const llmModelTypeFilterMap = { export const llmModelTypeFilterMap = {
[LLMModelTypeEnum.all]: 'model', [LLMModelTypeEnum.all]: 'model',
[LLMModelTypeEnum.classify]: 'usedInClassify', [LLMModelTypeEnum.classify]: 'usedInClassify',
[LLMModelTypeEnum.extractFields]: 'usedInExtractFields', [LLMModelTypeEnum.extractFields]: 'usedInExtractFields',
[LLMModelTypeEnum.toolCall]: 'usedInToolCall', [LLMModelTypeEnum.toolCall]: 'usedInToolCall'
[LLMModelTypeEnum.queryExtension]: 'usedInQueryExtension'
}; };
export enum EmbeddingTypeEnm { export enum EmbeddingTypeEnm {

115
packages/global/core/ai/model.d.ts vendored
View File

@ -1,3 +1,4 @@
import { ModelTypeEnum } from './model';
import type { ModelProviderIdType } from './provider'; import type { ModelProviderIdType } from './provider';
type PriceType = { type PriceType = {
@ -7,68 +8,74 @@ type PriceType = {
inputPrice?: number; // 1k tokens=n points inputPrice?: number; // 1k tokens=n points
outputPrice?: number; // 1k tokens=n points outputPrice?: number; // 1k tokens=n points
}; };
export type LLMModelItemType = PriceType & { type BaseModelItemType = {
provider: ModelProviderIdType; provider: ModelProviderIdType;
model: string; model: string;
name: string; name: string;
avatar?: string; // model icon, from provider avatar?: string; // model icon, from provider
maxContext: number;
maxResponse: number;
quoteMaxToken: number;
maxTemperature: number;
censor?: boolean; isActive?: boolean;
vision?: boolean; isCustom?: boolean;
isDefault?: boolean;
// diff function model // If has requestUrl, it will request the model directly
datasetProcess?: boolean; // dataset requestUrl?: string;
usedInClassify?: boolean; // classify requestAuth?: string;
usedInExtractFields?: boolean; // extract fields
usedInToolCall?: boolean; // tool call
usedInQueryExtension?: boolean; // query extension
functionCall: boolean;
toolChoice: boolean;
customCQPrompt: string;
customExtractPrompt: string;
defaultSystemChatPrompt?: string;
defaultConfig?: Record<string, any>;
fieldMap?: Record<string, string>;
}; };
export type VectorModelItemType = PriceType & { export type LLMModelItemType = PriceType &
provider: ModelProviderIdType; BaseModelItemType & {
model: string; // model name type: ModelTypeEnum.llm;
name: string; // show name maxContext: number;
avatar?: string; maxResponse: number;
defaultToken: number; // split text default token quoteMaxToken: number;
maxToken: number; // model max token maxTemperature?: number;
weight: number; // training weight
hidden?: boolean; // Disallow creation
defaultConfig?: Record<string, any>; // post request config
dbConfig?: Record<string, any>; // Custom parameters for storage
queryConfig?: Record<string, any>; // Custom parameters for query
};
export type ReRankModelItemType = PriceType & { censor?: boolean;
provider: ModelProviderIdType; vision?: boolean;
model: string; reasoning?: boolean;
name: string;
requestUrl: string;
requestAuth: string;
};
export type AudioSpeechModelType = PriceType & { // diff function model
provider: ModelProviderIdType; datasetProcess?: boolean; // dataset
model: string; usedInClassify?: boolean; // classify
name: string; usedInExtractFields?: boolean; // extract fields
voices: { label: string; value: string; bufferId: string }[]; usedInToolCall?: boolean; // tool call
};
export type STTModelType = PriceType & { functionCall: boolean;
provider: ModelProviderIdType; toolChoice: boolean;
model: string;
name: string; customCQPrompt: string;
}; customExtractPrompt: string;
defaultSystemChatPrompt?: string;
defaultConfig?: Record<string, any>;
fieldMap?: Record<string, string>;
};
export type EmbeddingModelItemType = PriceType &
BaseModelItemType & {
type: ModelTypeEnum.embedding;
defaultToken: number; // split text default token
maxToken: number; // model max token
weight: number; // training weight
hidden?: boolean; // Disallow creation
defaultConfig?: Record<string, any>; // post request config
dbConfig?: Record<string, any>; // Custom parameters for storage
queryConfig?: Record<string, any>; // Custom parameters for query
};
export type ReRankModelItemType = PriceType &
BaseModelItemType & {
type: ModelTypeEnum.rerank;
};
export type TTSModelType = PriceType &
BaseModelItemType & {
type: ModelTypeEnum.tts;
voices: { label: string; value: string }[];
};
export type STTModelType = PriceType &
BaseModelItemType & {
type: ModelTypeEnum.stt;
};

40
packages/global/core/ai/model.ts
View File

@ -1,9 +1,18 @@
import { i18nT } from '../../../web/i18n/utils'; import { i18nT } from '../../../web/i18n/utils';
import type { LLMModelItemType, STTModelType, VectorModelItemType } from './model.d'; import type { LLMModelItemType, STTModelType, EmbeddingModelItemType } from './model.d';
import { getModelProvider, ModelProviderIdType } from './provider'; import { getModelProvider, ModelProviderIdType } from './provider';
export enum ModelTypeEnum {
llm = 'llm',
embedding = 'embedding',
tts = 'tts',
stt = 'stt',
rerank = 'rerank'
}
export const defaultQAModels: LLMModelItemType[] = [ export const defaultQAModels: LLMModelItemType[] = [
{ {
type: ModelTypeEnum.llm,
provider: 'OpenAI', provider: 'OpenAI',
model: 'gpt-4o-mini', model: 'gpt-4o-mini',
name: 'gpt-4o-mini', name: 'gpt-4o-mini',
@ -24,8 +33,9 @@ export const defaultQAModels: LLMModelItemType[] = [
} }
]; ];
export const defaultVectorModels: VectorModelItemType[] = [ export const defaultVectorModels: EmbeddingModelItemType[] = [
{ {
type: ModelTypeEnum.embedding,
provider: 'OpenAI', provider: 'OpenAI',
model: 'text-embedding-3-small', model: 'text-embedding-3-small',
name: 'Embedding-2', name: 'Embedding-2',
@ -36,12 +46,15 @@ export const defaultVectorModels: VectorModelItemType[] = [
} }
]; ];
export const defaultWhisperModel: STTModelType = { export const defaultSTTModels: STTModelType[] = [
provider: 'OpenAI', {
model: 'whisper-1', type: ModelTypeEnum.stt,
name: 'whisper-1', provider: 'OpenAI',
charsPointsPrice: 0 model: 'whisper-1',
}; name: 'whisper-1',
charsPointsPrice: 0
}
];
export const getModelFromList = ( export const getModelFromList = (
modelList: { provider: ModelProviderIdType; name: string; model: string }[], modelList: { provider: ModelProviderIdType; name: string; model: string }[],
@ -55,15 +68,10 @@ export const getModelFromList = (
}; };
}; };
export enum ModelTypeEnum {
chat = 'chat',
embedding = 'embedding',
tts = 'tts',
stt = 'stt'
}
export const modelTypeList = [ export const modelTypeList = [
{ label: i18nT('common:model.type.chat'), value: ModelTypeEnum.chat }, { label: i18nT('common:model.type.chat'), value: ModelTypeEnum.llm },
{ label: i18nT('common:model.type.embedding'), value: ModelTypeEnum.embedding }, { label: i18nT('common:model.type.embedding'), value: ModelTypeEnum.embedding },
{ label: i18nT('common:model.type.tts'), value: ModelTypeEnum.tts }, { label: i18nT('common:model.type.tts'), value: ModelTypeEnum.tts },
{ label: i18nT('common:model.type.stt'), value: ModelTypeEnum.stt } { label: i18nT('common:model.type.stt'), value: ModelTypeEnum.stt },
{ label: i18nT('common:model.type.reRank'), value: ModelTypeEnum.rerank }
]; ];

19
packages/global/core/ai/provider.ts
View File

@ -7,11 +7,12 @@ export type ModelProviderIdType =
| 'Meta' | 'Meta'
| 'MistralAI' | 'MistralAI'
| 'Groq' | 'Groq'
| 'Grok'
| 'AliCloud' | 'AliCloud'
| 'Qwen' | 'Qwen'
| 'Doubao' | 'Doubao'
| 'ChatGLM'
| 'DeepSeek' | 'DeepSeek'
| 'ChatGLM'
| 'Ernie' | 'Ernie'
| 'Moonshot' | 'Moonshot'
| 'MiniMax' | 'MiniMax'
@ -20,6 +21,7 @@ export type ModelProviderIdType =
| 'Baichuan' | 'Baichuan'
| 'StepFun' | 'StepFun'
| 'Yi' | 'Yi'
| 'Siliconflow'
| 'Ollama' | 'Ollama'
| 'BAAI' | 'BAAI'
| 'FishAudio' | 'FishAudio'
@ -29,7 +31,7 @@ export type ModelProviderIdType =
export type ModelProviderType = { export type ModelProviderType = {
id: ModelProviderIdType; id: ModelProviderIdType;
name: string; name: any;
avatar: string; avatar: string;
}; };
@ -59,6 +61,11 @@ export const ModelProviderList: ModelProviderType[] = [
name: 'MistralAI', name: 'MistralAI',
avatar: 'model/mistral' avatar: 'model/mistral'
}, },
{
id: 'Grok',
name: 'Grok',
avatar: 'model/grok'
},
{ {
id: 'Groq', id: 'Groq',
name: 'Groq', name: 'Groq',
@ -155,6 +162,11 @@ export const ModelProviderList: ModelProviderType[] = [
name: i18nT('common:model_moka'), name: i18nT('common:model_moka'),
avatar: 'model/moka' avatar: 'model/moka'
}, },
{
id: 'Siliconflow',
name: i18nT('common:model_siliconflow'),
avatar: 'model/siliconflow'
},
{ {
id: 'Other', id: 'Other',
name: i18nT('common:model_other'), name: i18nT('common:model_other'),
@ -165,6 +177,7 @@ export const ModelProviderMap = Object.fromEntries(
ModelProviderList.map((item, index) => [item.id, { ...item, order: index }]) ModelProviderList.map((item, index) => [item.id, { ...item, order: index }])
); );
export const getModelProvider = (provider: ModelProviderIdType) => { export const getModelProvider = (provider?: ModelProviderIdType) => {
if (!provider) return ModelProviderMap.Other;
return ModelProviderMap[provider] ?? ModelProviderMap.Other; return ModelProviderMap[provider] ?? ModelProviderMap.Other;
}; };

2
packages/global/core/app/type.d.ts vendored
View File

@ -80,6 +80,7 @@ export type AppSimpleEditFormType = {
maxToken?: number; maxToken?: number;
isResponseAnswerText: boolean; isResponseAnswerText: boolean;
maxHistories: number; maxHistories: number;
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
}; };
dataset: { dataset: {
datasets: SelectedDatasetType; datasets: SelectedDatasetType;
@ -117,6 +118,7 @@ export type SettingAIDataType = {
isResponseAnswerText?: boolean; isResponseAnswerText?: boolean;
maxHistories?: number; maxHistories?: number;
[NodeInputKeyEnum.aiChatVision]?: boolean; // Is open vision mode [NodeInputKeyEnum.aiChatVision]?: boolean; // Is open vision mode
[NodeInputKeyEnum.aiChatReasoning]?: boolean; // Is open reasoning mode
}; };
// variable // variable

3
packages/global/core/app/utils.ts
View File

@ -16,7 +16,8 @@ export const getDefaultAppForm = (): AppSimpleEditFormType => {
temperature: 0, temperature: 0,
isResponseAnswerText: true, isResponseAnswerText: true,
maxHistories: 6, maxHistories: 6,
maxToken: 4000 maxToken: 4000,
aiChatReasoning: true
}, },
dataset: { dataset: {
datasets: [], datasets: [],

5
packages/global/core/chat/constants.ts
View File

@ -25,7 +25,8 @@ export enum ChatItemValueTypeEnum {
text = 'text', text = 'text',
file = 'file', file = 'file',
tool = 'tool', tool = 'tool',
interactive = 'interactive' interactive = 'interactive',
reasoning = 'reasoning'
} }
export enum ChatSourceEnum { export enum ChatSourceEnum {
@ -75,5 +76,3 @@ export enum ChatStatusEnum {
running = 'running', running = 'running',
finish = 'finish' finish = 'finish'
} }
export const MARKDOWN_QUOTE_SIGN = 'QUOTE SIGN';

11
packages/global/core/chat/type.d.ts vendored
View File

@ -70,14 +70,23 @@ export type SystemChatItemType = {
obj: ChatRoleEnum.System; obj: ChatRoleEnum.System;
value: SystemChatItemValueItemType[]; value: SystemChatItemValueItemType[];
}; };
export type AIChatItemValueItemType = { export type AIChatItemValueItemType = {
type: ChatItemValueTypeEnum.text | ChatItemValueTypeEnum.tool | ChatItemValueTypeEnum.interactive; type:
| ChatItemValueTypeEnum.text
| ChatItemValueTypeEnum.reasoning
| ChatItemValueTypeEnum.tool
| ChatItemValueTypeEnum.interactive;
text?: { text?: {
content: string; content: string;
}; };
reasoning?: {
content: string;
};
tools?: ToolModuleResponseItemType[]; tools?: ToolModuleResponseItemType[];
interactive?: WorkflowInteractiveResponseType; interactive?: WorkflowInteractiveResponseType;
}; };
export type AIChatItemType = { export type AIChatItemType = {
obj: ChatRoleEnum.AI; obj: ChatRoleEnum.AI;
value: AIChatItemValueItemType[]; value: AIChatItemValueItemType[];

8
packages/global/core/dataset/type.d.ts vendored
View File

@ -1,4 +1,4 @@
import type { LLMModelItemType, VectorModelItemType } from '../../core/ai/model.d'; import type { LLMModelItemType, EmbeddingModelItemType } from '../../core/ai/model.d';
import { PermissionTypeEnum } from '../../support/permission/constant'; import { PermissionTypeEnum } from '../../support/permission/constant';
import { PushDatasetDataChunkProps } from './api'; import { PushDatasetDataChunkProps } from './api';
import { import {
@ -152,7 +152,7 @@ export type DatasetSimpleItemType = {
_id: string; _id: string;
avatar: string; avatar: string;
name: string; name: string;
vectorModel: VectorModelItemType; vectorModel: EmbeddingModelItemType;
}; };
export type DatasetListItemType = { export type DatasetListItemType = {
_id: string; _id: string;
@ -163,14 +163,14 @@ export type DatasetListItemType = {
intro: string; intro: string;
type: `${DatasetTypeEnum}`; type: `${DatasetTypeEnum}`;
permission: DatasetPermission; permission: DatasetPermission;
vectorModel: VectorModelItemType; vectorModel: EmbeddingModelItemType;
inheritPermission: boolean; inheritPermission: boolean;
private?: boolean; private?: boolean;
sourceMember?: SourceMemberType; sourceMember?: SourceMemberType;
}; };
export type DatasetItemType = Omit<DatasetSchemaType, 'vectorModel' | 'agentModel'> & { export type DatasetItemType = Omit<DatasetSchemaType, 'vectorModel' | 'agentModel'> & {
vectorModel: VectorModelItemType; vectorModel: EmbeddingModelItemType;
agentModel: LLMModelItemType; agentModel: LLMModelItemType;
permission: DatasetPermission; permission: DatasetPermission;
}; };

2
packages/global/core/workflow/api.d.ts vendored
View File

@ -1,4 +1,4 @@
import { VectorModelItemType } from '../ai/model.d'; import { EmbeddingModelItemType } from '../ai/model.d';
import { NodeInputKeyEnum } from './constants'; import { NodeInputKeyEnum } from './constants';
export type SelectedDatasetType = { datasetId: string }[]; export type SelectedDatasetType = { datasetId: string }[];

4
packages/global/core/workflow/constants.ts
View File

@ -141,6 +141,7 @@ export enum NodeInputKeyEnum {
aiChatDatasetQuote = 'quoteQA', aiChatDatasetQuote = 'quoteQA',
aiChatVision = 'aiChatVision', aiChatVision = 'aiChatVision',
stringQuoteText = 'stringQuoteText', stringQuoteText = 'stringQuoteText',
aiChatReasoning = 'aiChatReasoning',
// dataset // dataset
datasetSelectList = 'datasets', datasetSelectList = 'datasets',
@ -220,7 +221,8 @@ export enum NodeOutputKeyEnum {
// common // common
userChatInput = 'userChatInput', userChatInput = 'userChatInput',
history = 'history', history = 'history',
answerText = 'answerText', // module answer. the value will be show and save to history answerText = 'answerText', // node answer. the value will be show and save to history
reasoningText = 'reasoningText', // node reasoning. the value will be show but not save to history
success = 'success', success = 'success',
failed = 'failed', failed = 'failed',
error = 'error', error = 'error',

1
packages/global/core/workflow/runtime/type.d.ts vendored
View File

@ -220,6 +220,7 @@ export type AIChatNodeProps = {
[NodeInputKeyEnum.aiChatMaxToken]?: number; [NodeInputKeyEnum.aiChatMaxToken]?: number;
[NodeInputKeyEnum.aiChatIsResponseText]: boolean; [NodeInputKeyEnum.aiChatIsResponseText]: boolean;
[NodeInputKeyEnum.aiChatVision]?: boolean; [NodeInputKeyEnum.aiChatVision]?: boolean;
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
[NodeInputKeyEnum.aiChatQuoteRole]?: AiChatQuoteRoleType; [NodeInputKeyEnum.aiChatQuoteRole]?: AiChatQuoteRoleType;
[NodeInputKeyEnum.aiChatQuoteTemplate]?: string; [NodeInputKeyEnum.aiChatQuoteTemplate]?: string;

40
packages/global/core/workflow/runtime/utils.ts
View File

@ -176,6 +176,7 @@ export const checkNodeRunStatus = ({
} }
visited.add(edge.source); visited.add(edge.source);
// 递归检测后面的 edge，如果有其中一个成环，则返回 true
const nextEdges = allEdges.filter((item) => item.target === edge.source); const nextEdges = allEdges.filter((item) => item.target === edge.source);
return nextEdges.some((nextEdge) => checkIsCircular(nextEdge, new Set(visited))); return nextEdges.some((nextEdge) => checkIsCircular(nextEdge, new Set(visited)));
}; };
@ -207,7 +208,23 @@ export const checkNodeRunStatus = ({
currentNode: node currentNode: node
}); });
// check skip（其中一组边，全 skip） // check active（其中一组边，至少有一个 active，且没有 waiting 即可运行）
if (
commonEdges.length > 0 &&
commonEdges.some((item) => item.status === 'active') &&
commonEdges.every((item) => item.status !== 'waiting')
) {
return 'run';
}
if (
recursiveEdges.length > 0 &&
recursiveEdges.some((item) => item.status === 'active') &&
recursiveEdges.every((item) => item.status !== 'waiting')
) {
return 'run';
}
// check skip（其中一组边，全是 skiped 则跳过运行）
if (commonEdges.length > 0 && commonEdges.every((item) => item.status === 'skipped')) { if (commonEdges.length > 0 && commonEdges.every((item) => item.status === 'skipped')) {
return 'skip'; return 'skip';
} }
@ -215,14 +232,6 @@ export const checkNodeRunStatus = ({
return 'skip'; return 'skip';
} }
// check active（有一类边，不全是 wait 即可运行）
if (commonEdges.length > 0 && commonEdges.every((item) => item.status !== 'waiting')) {
return 'run';
}
if (recursiveEdges.length > 0 && recursiveEdges.every((item) => item.status !== 'waiting')) {
return 'run';
}
return 'wait'; return 'wait';
}; };
@ -355,12 +364,14 @@ export function replaceEditorVariable({
export const textAdaptGptResponse = ({ export const textAdaptGptResponse = ({
text, text,
reasoning_content,
model = '', model = '',
finish_reason = null, finish_reason = null,
extraData = {} extraData = {}
}: { }: {
model?: string; model?: string;
text: string | null; text?: string | null;
reasoning_content?: string | null;
finish_reason?: null | 'stop'; finish_reason?: null | 'stop';
extraData?: Object; extraData?: Object;
}) => { }) => {
@ -372,10 +383,11 @@ export const textAdaptGptResponse = ({
model, model,
choices: [ choices: [
{ {
delta: delta: {
text === null role: ChatCompletionRequestMessageRoleEnum.Assistant,
? {} content: text,
: { role: ChatCompletionRequestMessageRoleEnum.Assistant, content: text }, ...(reasoning_content && { reasoning_content })
},
index: 0, index: 0,
finish_reason finish_reason
} }

11
packages/global/core/workflow/template/system/aiChat/index.ts
View File

@ -63,14 +63,14 @@ export const AiChatModule: FlowNodeTemplateType = {
key: NodeInputKeyEnum.aiChatTemperature, key: NodeInputKeyEnum.aiChatTemperature,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '', label: '',
value: 0, value: undefined,
valueType: WorkflowIOValueTypeEnum.number valueType: WorkflowIOValueTypeEnum.number
}, },
{ {
key: NodeInputKeyEnum.aiChatMaxToken, key: NodeInputKeyEnum.aiChatMaxToken,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '', label: '',
value: 2000, value: undefined,
valueType: WorkflowIOValueTypeEnum.number valueType: WorkflowIOValueTypeEnum.number
}, },
@ -91,6 +91,13 @@ export const AiChatModule: FlowNodeTemplateType = {
valueType: WorkflowIOValueTypeEnum.boolean, valueType: WorkflowIOValueTypeEnum.boolean,
value: true value: true
}, },
{
key: NodeInputKeyEnum.aiChatReasoning,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.boolean,
value: true
},
// settings modal --- // settings modal ---
{ {
...Input_Template_System_Prompt, ...Input_Template_System_Prompt,

5
packages/global/core/workflow/template/system/queryExtension.ts
View File

@ -31,10 +31,7 @@ export const AiQueryExtension: FlowNodeTemplateType = {
showStatus: true, showStatus: true,
version: '481', version: '481',
inputs: [ inputs: [
{ Input_Template_SelectAIModel,
...Input_Template_SelectAIModel,
llmModelType: LLMModelTypeEnum.queryExtension
},
{ {
key: NodeInputKeyEnum.aiSystemPrompt, key: NodeInputKeyEnum.aiSystemPrompt,
renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference], renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],

4
packages/global/core/workflow/template/system/tools.ts
View File

@ -43,14 +43,14 @@ export const ToolModule: FlowNodeTemplateType = {
key: NodeInputKeyEnum.aiChatTemperature, key: NodeInputKeyEnum.aiChatTemperature,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '', label: '',
value: 0, value: undefined,
valueType: WorkflowIOValueTypeEnum.number valueType: WorkflowIOValueTypeEnum.number
}, },
{ {
key: NodeInputKeyEnum.aiChatMaxToken, key: NodeInputKeyEnum.aiChatMaxToken,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '', label: '',
value: 2000, value: undefined,
valueType: WorkflowIOValueTypeEnum.number valueType: WorkflowIOValueTypeEnum.number
}, },
{ {

16
packages/global/support/wallet/usage/api.d.ts vendored
View File

@ -6,6 +6,22 @@ export type CreateTrainingUsageProps = {
datasetId: string; datasetId: string;
}; };
export type GetUsageProps = {
dateStart: Date;
dateEnd: Date;
sources?: UsageSourceEnum[];
teamMemberIds?: string[];
projectName?: string;
};
export type GetUsageDashboardProps = GetUsageProps & {
unit: 'day' | 'month';
};
export type GetUsageDashboardResponseItem = {
date: Date;
totalPoints: number;
};
export type ConcatUsageProps = UsageListItemCountType & { export type ConcatUsageProps = UsageListItemCountType & {
teamId: string; teamId: string;
tmbId: string; tmbId: string;

14
packages/global/support/wallet/usage/constants.ts
View File

@ -18,30 +18,30 @@ export const UsageSourceMap = {
label: i18nT('common:core.chat.logs.online') label: i18nT('common:core.chat.logs.online')
}, },
[UsageSourceEnum.api]: { [UsageSourceEnum.api]: {
label: 'Api' label: 'API'
}, },
[UsageSourceEnum.shareLink]: { [UsageSourceEnum.shareLink]: {
label: i18nT('common:core.chat.logs.free_login') label: i18nT('common:core.chat.logs.free_login')
}, },
[UsageSourceEnum.training]: { [UsageSourceEnum.training]: {
label: 'dataset.Training Name' label: i18nT('common:dataset.Training Name')
}, },
[UsageSourceEnum.cronJob]: { [UsageSourceEnum.cronJob]: {
label: i18nT('common:cron_job_run_app') label: i18nT('common:cron_job_run_app')
}, },
[UsageSourceEnum.feishu]: { [UsageSourceEnum.feishu]: {
label: i18nT('user:usage.feishu') label: i18nT('account_usage:feishu')
}, },
[UsageSourceEnum.official_account]: { [UsageSourceEnum.official_account]: {
label: i18nT('user:usage.official_account') label: i18nT('account_usage:official_account')
}, },
[UsageSourceEnum.share]: { [UsageSourceEnum.share]: {
label: i18nT('user:usage.share') label: i18nT('account_usage:share')
}, },
[UsageSourceEnum.wecom]: { [UsageSourceEnum.wecom]: {
label: i18nT('user:usage.wecom') label: i18nT('account_usage:wecom')
}, },
[UsageSourceEnum.dingtalk]: { [UsageSourceEnum.dingtalk]: {
label: i18nT('user:usage.dingtalk') label: i18nT('account_usage:dingtalk')
} }
}; };

3
packages/global/support/wallet/usage/type.d.ts vendored
View File

@ -1,3 +1,4 @@
import { SourceMemberType } from '../../../support/user/type';
import { CreateUsageProps } from './api'; import { CreateUsageProps } from './api';
import { UsageSourceEnum } from './constants'; import { UsageSourceEnum } from './constants';
@ -10,6 +11,7 @@ export type UsageListItemCountType = {
// deprecated // deprecated
tokens?: number; tokens?: number;
}; };
export type UsageListItemType = UsageListItemCountType & { export type UsageListItemType = UsageListItemCountType & {
moduleName: string; moduleName: string;
amount: number; amount: number;
@ -28,4 +30,5 @@ export type UsageItemType = {
source: UsageSchemaType['source']; source: UsageSchemaType['source'];
totalPoints: number; totalPoints: number;
list: UsageSchemaType['list']; list: UsageSchemaType['list'];
sourceMember: SourceMemberType;
}; };

2
packages/service/common/file/image/controller.ts
View File

@ -40,7 +40,7 @@ export async function uploadMongoImg({
expiredTime: forever ? undefined : addHours(new Date(), 1) expiredTime: forever ? undefined : addHours(new Date(), 1)
}); });
return `${process.env.FE_DOMAIN || ''}${process.env.NEXT_PUBLIC_BASE_URL || ''}${imageBaseUrl}${String(_id)}.${extension}`; return `${process.env.NEXT_PUBLIC_BASE_URL || ''}${imageBaseUrl}${String(_id)}.${extension}`;
} }
const getIdFromPath = (path?: string) => { const getIdFromPath = (path?: string) => {

17
packages/service/common/middle/reqFrequencyLimit.ts
View File

@ -1,6 +1,5 @@
import { ApiRequestProps } from '../../type/next'; import { ApiRequestProps } from '../../type/next';
import requestIp from 'request-ip'; import requestIp from 'request-ip';
import { ERROR_ENUM } from '@fastgpt/global/common/error/errorCode';
import { authFrequencyLimit } from '../system/frequencyLimit/utils'; import { authFrequencyLimit } from '../system/frequencyLimit/utils';
import { addSeconds } from 'date-fns'; import { addSeconds } from 'date-fns';
import { NextApiResponse } from 'next'; import { NextApiResponse } from 'next';
@ -9,7 +8,17 @@ import { jsonRes } from '../response';
// unit: times/s // unit: times/s
// how to use? // how to use?
// export default NextAPI(useQPSLimit(10), handler); // limit 10 times per second for a ip // export default NextAPI(useQPSLimit(10), handler); // limit 10 times per second for a ip
export function useReqFrequencyLimit(seconds: number, limit: number, force = false) { export function useIPFrequencyLimit({
id,
seconds,
limit,
force = false
}: {
id: string;
seconds: number;
limit: number;
force?: boolean;
}) {
return async (req: ApiRequestProps, res: NextApiResponse) => { return async (req: ApiRequestProps, res: NextApiResponse) => {
const ip = requestIp.getClientIp(req); const ip = requestIp.getClientIp(req);
if (!ip || (process.env.USE_IP_LIMIT !== 'true' && !force)) { if (!ip || (process.env.USE_IP_LIMIT !== 'true' && !force)) {
@ -17,14 +26,14 @@ export function useReqFrequencyLimit(seconds: number, limit: number, force = fal
} }
try { try {
await authFrequencyLimit({ await authFrequencyLimit({
eventId: 'ip-qps-limit' + ip, eventId: `ip-qps-limit-${id}-` + ip,
maxAmount: limit, maxAmount: limit,
expiredTime: addSeconds(new Date(), seconds) expiredTime: addSeconds(new Date(), seconds)
}); });
} catch (_) { } catch (_) {
jsonRes(res, { jsonRes(res, {
code: 429, code: 429,
error: ERROR_ENUM.tooManyRequest error: `Too many request, request ${limit} times every ${seconds} seconds`
}); });
} }
}; };

10
packages/service/common/response/index.ts
View File

@ -33,7 +33,15 @@ export const jsonRes = <T = any>(
addLog.error(`Api response error: ${url}`, ERROR_RESPONSE[errResponseKey]); addLog.error(`Api response error: ${url}`, ERROR_RESPONSE[errResponseKey]);
return res.status(code).json(ERROR_RESPONSE[errResponseKey]); res.status(code);
if (message) {
res.send(message);
} else {
res.json(ERROR_RESPONSE[errResponseKey]);
}
return;
} }
// another error // another error

31
packages/service/common/system/config/controller.ts
View File

@ -6,8 +6,7 @@ import { FastGPTProUrl } from '../constants';
export const getFastGPTConfigFromDB = async () => { export const getFastGPTConfigFromDB = async () => {
if (!FastGPTProUrl) { if (!FastGPTProUrl) {
return { return {
config: {} as FastGPTConfigFileType, config: {} as FastGPTConfigFileType
configId: undefined
}; };
} }
@ -18,9 +17,35 @@ export const getFastGPTConfigFromDB = async () => {
}); });
const config = res?.value || {}; const config = res?.value || {};
// 利用配置文件的创建时间（更新时间）来做缓存，如果前端命中缓存，则不需要再返回配置文件
global.systemInitBufferId = res ? res.createTime.getTime().toString() : undefined;
return { return {
configId: res ? String(res._id) : undefined,
config: config as FastGPTConfigFileType config: config as FastGPTConfigFileType
}; };
}; };
export const updateFastGPTConfigBuffer = async () => {
const res = await MongoSystemConfigs.findOne({
type: SystemConfigsTypeEnum.fastgpt
}).sort({
createTime: -1
});
if (!res) return;
res.createTime = new Date();
await res.save();
global.systemInitBufferId = res.createTime.getTime().toString();
};
export const reloadFastGPTConfigBuffer = async () => {
const res = await MongoSystemConfigs.findOne({
type: SystemConfigsTypeEnum.fastgpt
}).sort({
createTime: -1
});
if (!res) return;
global.systemInitBufferId = res.createTime.getTime().toString();
};

9
packages/service/common/system/tools.ts
View File

@ -13,15 +13,6 @@ export const initFastGPTConfig = (config?: FastGPTConfigFileType) => {
global.feConfigs = config.feConfigs; global.feConfigs = config.feConfigs;
global.systemEnv = config.systemEnv; global.systemEnv = config.systemEnv;
global.subPlans = config.subPlans; global.subPlans = config.subPlans;
global.llmModels = config.llmModels;
global.llmModelPriceType = global.llmModels.some((item) => typeof item.inputPrice === 'number')
? 'IO'
: 'Tokens';
global.vectorModels = config.vectorModels;
global.audioSpeechModels = config.audioSpeechModels;
global.whisperModel = config.whisperModel;
global.reRankModels = config.reRankModels;
}; };
export const systemStartCb = () => { export const systemStartCb = () => {

4
packages/service/common/vectorStore/controller.ts
View File

@ -2,7 +2,7 @@
import { PgVectorCtrl } from './pg/class'; import { PgVectorCtrl } from './pg/class';
import { getVectorsByText } from '../../core/ai/embedding'; import { getVectorsByText } from '../../core/ai/embedding';
import { InsertVectorProps } from './controller.d'; import { InsertVectorProps } from './controller.d';
import { VectorModelItemType } from '@fastgpt/global/core/ai/model.d'; import { EmbeddingModelItemType } from '@fastgpt/global/core/ai/model.d';
import { MILVUS_ADDRESS, PG_ADDRESS } from './constants'; import { MILVUS_ADDRESS, PG_ADDRESS } from './constants';
import { MilvusCtrl } from './milvus/class'; import { MilvusCtrl } from './milvus/class';
@ -28,7 +28,7 @@ export const insertDatasetDataVector = async ({
...props ...props
}: InsertVectorProps & { }: InsertVectorProps & {
query: string; query: string;
model: VectorModelItemType; model: EmbeddingModelItemType;
}) => { }) => {
const { vectors, tokens } = await getVectorsByText({ const { vectors, tokens } = await getVectorsByText({
model, model,

28
packages/service/core/ai/audio/speech.ts
View File

@ -1,5 +1,6 @@
import type { NextApiResponse } from 'next'; import type { NextApiResponse } from 'next';
import { getAIApi } from '../config'; import { getAIApi } from '../config';
import { getTTSModel } from '../model';
export async function text2Speech({ export async function text2Speech({
res, res,
@ -18,15 +19,26 @@ export async function text2Speech({
voice: string; voice: string;
speed?: number; speed?: number;
}) { }) {
const modelData = getTTSModel(model)!;
const ai = getAIApi(); const ai = getAIApi();
const response = await ai.audio.speech.create({ const response = await ai.audio.speech.create(
model, {
// @ts-ignore model,
voice, // @ts-ignore
input, voice,
response_format: 'mp3', input,
speed response_format: 'mp3',
}); speed
},
modelData.requestUrl && modelData.requestAuth
? {
path: modelData.requestUrl,
headers: {
Authorization: `Bearer ${modelData.requestAuth}`
}
}
: {}
);
const readableStream = response.body as unknown as NodeJS.ReadableStream; const readableStream = response.body as unknown as NodeJS.ReadableStream;
readableStream.pipe(res); readableStream.pipe(res);

15
packages/service/core/ai/audio/transcriptions.ts
View File

@ -2,6 +2,7 @@ import fs from 'fs';
import { getAxiosConfig } from '../config'; import { getAxiosConfig } from '../config';
import axios from 'axios'; import axios from 'axios';
import FormData from 'form-data'; import FormData from 'form-data';
import { getSTTModel } from '../model';
export const aiTranscriptions = async ({ export const aiTranscriptions = async ({
model, model,
@ -14,13 +15,21 @@ export const aiTranscriptions = async ({
data.append('model', model); data.append('model', model);
data.append('file', fileStream); data.append('file', fileStream);
const modelData = getSTTModel(model);
const aiAxiosConfig = getAxiosConfig(); const aiAxiosConfig = getAxiosConfig();
const { data: result } = await axios<{ text: string }>({ const { data: result } = await axios<{ text: string }>({
method: 'post', method: 'post',
baseURL: aiAxiosConfig.baseUrl, ...(modelData.requestUrl
url: '/audio/transcriptions', ? { url: modelData.requestUrl }
: {
baseURL: aiAxiosConfig.baseUrl,
url: modelData.requestUrl || '/audio/transcriptions'
}),
headers: { headers: {
Authorization: aiAxiosConfig.authorization, Authorization: modelData.requestAuth
? `Bearer ${modelData.requestAuth}`
: aiAxiosConfig.authorization,
...data.getHeaders() ...data.getHeaders()
}, },
data: data data: data

20
packages/service/core/ai/config.ts
View File

@ -7,14 +7,14 @@ import { getErrText } from '@fastgpt/global/common/error/utils';
import { addLog } from '../../common/system/log'; import { addLog } from '../../common/system/log';
import { i18nT } from '../../../web/i18n/utils'; import { i18nT } from '../../../web/i18n/utils';
import { OpenaiAccountType } from '@fastgpt/global/support/user/team/type'; import { OpenaiAccountType } from '@fastgpt/global/support/user/team/type';
import { getLLMModel } from './model';
export const openaiBaseUrl = process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1'; export const openaiBaseUrl = process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1';
export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number }) => { export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number }) => {
const { userKey, timeout } = props || {}; const { userKey, timeout } = props || {};
const baseUrl = const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
userKey?.baseUrl || global?.systemEnv?.oneapiUrl || process.env.ONEAPI_URL || openaiBaseUrl;
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || ''; const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
return new OpenAI({ return new OpenAI({
@ -29,8 +29,7 @@ export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number
export const getAxiosConfig = (props?: { userKey?: OpenaiAccountType }) => { export const getAxiosConfig = (props?: { userKey?: OpenaiAccountType }) => {
const { userKey } = props || {}; const { userKey } = props || {};
const baseUrl = const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
userKey?.baseUrl || global?.systemEnv?.oneapiUrl || process.env.ONEAPI_URL || openaiBaseUrl;
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || ''; const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
return { return {
@ -63,12 +62,23 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
getEmptyResponseTip: () => string; getEmptyResponseTip: () => string;
}> => { }> => {
try { try {
const modelConstantsData = getLLMModel(body.model);
const formatTimeout = timeout ? timeout : body.stream ? 60000 : 600000; const formatTimeout = timeout ? timeout : body.stream ? 60000 : 600000;
const ai = getAIApi({ const ai = getAIApi({
userKey, userKey,
timeout: formatTimeout timeout: formatTimeout
}); });
const response = await ai.chat.completions.create(body, options); const response = await ai.chat.completions.create(body, {
...options,
...(modelConstantsData.requestUrl ? { path: modelConstantsData.requestUrl } : {}),
headers: {
...options?.headers,
...(modelConstantsData.requestAuth
? { Authorization: `Bearer ${modelConstantsData.requestAuth}` }
: {})
}
});
const isStreamResponse = const isStreamResponse =
typeof response === 'object' && typeof response === 'object' &&

11
packages/service/core/ai/config/embedding/text-embedding-ada-002.json
View File

@ -1,11 +0,0 @@
{
"provider": "OpenAI",
"model": "text-embedding-ada-002",
"name": "text-embedding-ada-002",
"defaultToken": 512, // 默认分块 token
"maxToken": 3000, // 最大分块 token
"weight": 0, // 权重
"charsPointsPrice": 0 // 积分/1k token
}

33
packages/service/core/ai/config/llm/gpt-4o-mini.json
View File

@ -1,33 +0,0 @@
{
"provider": "OpenAI",
"model": "gpt-4o-mini",
"name": "GPT-4o-mini", // alias
"maxContext": 125000, // 最大上下文
"maxResponse": 16000, // 最大回复
"quoteMaxToken": 60000, // 最大引用
"maxTemperature": 1.2, // 最大温度
"presencePenaltyRange": [-2, 2], // 惩罚系数范围
"frequencyPenaltyRange": [-2, 2], // 频率惩罚系数范围
"responseFormatList": ["text", "json_object", "json_schema"], // 响应格式
"showStopSign": true, // 是否显示停止符号
"vision": true, // 是否支持图片识别
"toolChoice": true, // 是否支持工具调用
"functionCall": false, // 是否支持函数调用（一般都可以 false 了，基本不用了）
"defaultSystemChatPrompt": "", // 默认系统提示
"datasetProcess": true, // 用于知识库文本处理
"usedInClassify": true, // 用于问题分类
"customCQPrompt": "", // 自定义问题分类提示
"usedInExtractFields": true, // 用于提取字段
"customExtractPrompt": "", // 自定义提取提示
"usedInToolCall": true, // 用于工具调用
"usedInQueryExtension": true, // 用于问题优化
"defaultConfig": {}, // 额外的自定义 body
"fieldMap": {}, // body 字段映射
"censor": false, // 是否开启敏感词过滤
"charsPointsPrice": 0 // n 积分/1k token
}

4
packages/service/core/ai/config/provider/AliCloud.json Normal file
View File

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

17
packages/service/core/ai/config/provider/BAAI.json Normal file
View File

@ -0,0 +1,17 @@
{
"provider": "BAAI",
"list": [
{
"model": "bge-m3",
"name": "bge-m3",
"defaultToken": 512,
"maxToken": 8000,
"type": "embedding"
},
{
"model": "bge-reranker-v2-m3",
"name": "bge-reranker-v2-m3",
"type": "rerank"
}
]
}

4
packages/service/core/ai/config/provider/Baichuan.json Normal file
View File

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

147
packages/service/core/ai/config/provider/ChatGLM.json Normal file
View File

@ -0,0 +1,147 @@
{
"provider": "ChatGLM",
"list": [
{
"model": "glm-4-air",
"name": "glm-4-air",
"maxContext": 128000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 0.99,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "glm-4-flash",
"name": "glm-4-flash",
"maxContext": 128000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 0.99,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "glm-4-long",
"name": "glm-4-long",
"maxContext": 1000000,
"maxResponse": 4000,
"quoteMaxToken": 900000,
"maxTemperature": 0.99,
"vision": false,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "glm-4-plus",
"name": "GLM-4-plus",
"maxContext": 128000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 0.99,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "glm-4v-flash",
"name": "glm-4v-flash",
"maxContext": 8000,
"maxResponse": 1000,
"quoteMaxToken": 6000,
"maxTemperature": 0.99,
"vision": true,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "glm-4v-plus",
"name": "GLM-4v-plus",
"maxContext": 8000,
"maxResponse": 1000,
"quoteMaxToken": 6000,
"maxTemperature": 0.99,
"vision": true,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "embedding-3",
"name": "embedding-3",
"defaultToken": 512,
"maxToken": 8000,
"defaultConfig": {
"dimensions": 1024
},
"type": "embedding"
}
]
}

93
packages/service/core/ai/config/provider/Claude.json Normal file
View File

@ -0,0 +1,93 @@
{
"provider": "Claude",
"list": [
{
"model": "claude-3-5-haiku-20241022",
"name": "claude-3-5-haiku-20241022",
"maxContext": 200000,
"maxResponse": 8000,
"quoteMaxToken": 100000,
"maxTemperature": 1,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "claude-3-5-sonnet-20240620",
"name": "Claude-3-5-sonnet-20240620",
"maxContext": 200000,
"maxResponse": 8000,
"quoteMaxToken": 100000,
"maxTemperature": 1,
"vision": true,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "claude-3-5-sonnet-20241022",
"name": "Claude-3-5-sonnet-20241022",
"maxContext": 200000,
"maxResponse": 8000,
"quoteMaxToken": 100000,
"maxTemperature": 1,
"vision": true,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "claude-3-opus-20240229",
"name": "claude-3-opus-20240229",
"maxContext": 200000,
"maxResponse": 4096,
"quoteMaxToken": 100000,
"maxTemperature": 1,
"vision": true,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
}
]
}

48
packages/service/core/ai/config/provider/DeepSeek.json Normal file
View File

@ -0,0 +1,48 @@
{
"provider": "DeepSeek",
"list": [
{
"model": "deepseek-chat",
"name": "Deepseek-chat",
"maxContext": 64000,
"maxResponse": 4096,
"quoteMaxToken": 60000,
"maxTemperature": 1.5,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"type": "llm"
},
{
"model": "deepseek-reasoner",
"name": "Deepseek-reasoner",
"maxContext": 64000,
"maxResponse": 4096,
"quoteMaxToken": 60000,
"maxTemperature": null,
"vision": false,
"reasoning": true,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
}
]
}

195
packages/service/core/ai/config/provider/Doubao.json Normal file
View File

@ -0,0 +1,195 @@
{
"provider": "Doubao",
"list": [
{
"model": "Doubao-lite-4k",
"name": "Doubao-lite-4k",
"maxContext": 4000,
"maxResponse": 4000,
"quoteMaxToken": 4000,
"maxTemperature": 1,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "Doubao-lite-32k",
"name": "Doubao-lite-32k",
"maxContext": 32000,
"maxResponse": 4000,
"quoteMaxToken": 32000,
"maxTemperature": 1,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "Doubao-lite-128k",
"name": "Doubao-lite-128k",
"maxContext": 128000,
"maxResponse": 4000,
"quoteMaxToken": 120000,
"maxTemperature": 1,
"vision": false,
"toolChoice": true,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "Doubao-vision-lite-32k",
"name": "Doubao-vision-lite-32k",
"maxContext": 32000,
"maxResponse": 4000,
"quoteMaxToken": 32000,
"maxTemperature": 1,
"vision": true,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
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}

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{
"provider": "Ernie",
"list": [
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{
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{
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]
}

4
packages/service/core/ai/config/provider/FishAudio.json Normal file
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{
"provider": "FishAudio",
"list": []
}

144
packages/service/core/ai/config/provider/Gemini.json Normal file
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{
"provider": "Gemini",
"list": [
{
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{
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{
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]
}

4
packages/service/core/ai/config/provider/Grok.json Normal file
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{
"provider": "Grok",
"list": []
}

47
packages/service/core/ai/config/provider/Groq.json Normal file
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{
"provider": "Groq",
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}
]
}

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packages/service/core/ai/config/provider/Hunyuan.json Normal file
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{
"provider": "Hunyuan",
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]
}

49
packages/service/core/ai/config/provider/Intern.json Normal file
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{
"provider": "Intern",
"list": [
{
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]
}

4
packages/service/core/ai/config/provider/Meta.json Normal file
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{
"provider": "Meta",
"list": []
}

240
packages/service/core/ai/config/provider/MiniMax.json Normal file
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{
"provider": "MiniMax",
"list": [
{
"model": "MiniMax-Text-01",
"name": "MiniMax-Text-01",
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{
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"defaultConfig": {},
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{
"model": "speech-01-turbo",
"name": "speech-01-turbo",
"voices": [
{
"label": "male-qn-qingse",
"value": "male-qn-qingse"
},
{
"label": "male-qn-jingying",
"value": "male-qn-jingying"
},
{
"label": "male-qn-badao",
"value": "male-qn-badao"
},
{
"label": "male-qn-daxuesheng",
"value": "male-qn-daxuesheng"
},
{
"label": "female-shaonv",
"value": "female-shaonv"
},
{
"label": "female-yujie",
"value": "female-yujie"
},
{
"label": "female-chengshu",
"value": "female-chengshu"
},
{
"label": "female-tianmei",
"value": "female-tianmei"
},
{
"label": "presenter_male",
"value": "presenter_male"
},
{
"label": "presenter_female",
"value": "presenter_female"
},
{
"label": "audiobook_male_1",
"value": "audiobook_male_1"
},
{
"label": "audiobook_male_2",
"value": "audiobook_male_2"
},
{
"label": "audiobook_female_1",
"value": "audiobook_female_1"
},
{
"label": "audiobook_female_2",
"value": "audiobook_female_2"
},
{
"label": "male-qn-qingse-jingpin",
"value": "male-qn-qingse-jingpin"
},
{
"label": "male-qn-jingying-jingpin",
"value": "male-qn-jingying-jingpin"
},
{
"label": "male-qn-badao-jingpin",
"value": "male-qn-badao-jingpin"
},
{
"label": "male-qn-daxuesheng-jingpin",
"value": "male-qn-daxuesheng-jingpin"
},
{
"label": "female-shaonv-jingpin",
"value": "female-shaonv-jingpin"
},
{
"label": "female-yujie-jingpin",
"value": "female-yujie-jingpin"
},
{
"label": "female-chengshu-jingpin",
"value": "female-chengshu-jingpin"
},
{
"label": "female-tianmei-jingpin",
"value": "female-tianmei-jingpin"
},
{
"label": "clever_boy",
"value": "clever_boy"
},
{
"label": "cute_boy",
"value": "cute_boy"
},
{
"label": "lovely_girl",
"value": "lovely_girl"
},
{
"label": "cartoon_pig",
"value": "cartoon_pig"
},
{
"label": "bingjiao_didi",
"value": "bingjiao_didi"
},
{
"label": "junlang_nanyou",
"value": "junlang_nanyou"
},
{
"label": "chunzhen_xuedi",
"value": "chunzhen_xuedi"
},
{
"label": "lengdan_xiongzhang",
"value": "lengdan_xiongzhang"
},
{
"label": "badao_shaoye",
"value": "badao_shaoye"
},
{
"label": "tianxin_xiaoling",
"value": "tianxin_xiaoling"
},
{
"label": "qiaopi_mengmei",
"value": "qiaopi_mengmei"
},
{
"label": "wumei_yujie",
"value": "wumei_yujie"
},
{
"label": "diadia_xuemei",
"value": "diadia_xuemei"
},
{
"label": "danya_xuejie",
"value": "danya_xuejie"
},
{
"label": "Santa_Claus",
"value": "Santa_Claus"
},
{
"label": "Grinch",
"value": "Grinch"
},
{
"label": "Rudolph",
"value": "Rudolph"
},
{
"label": "Arnold",
"value": "Arnold"
},
{
"label": "Charming_Santa",
"value": "Charming_Santa"
},
{
"label": "Charming_Lady",
"value": "Charming_Lady"
},
{
"label": "Sweet_Girl",
"value": "Sweet_Girl"
},
{
"label": "Cute_Elf",
"value": "Cute_Elf"
},
{
"label": "Attractive_Girl",
"value": "Attractive_Girl"
},
{
"label": "Serene_Woman",
"value": "Serene_Woman"
}
],
"type": "tts"
}
]
}

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packages/service/core/ai/config/provider/MistralAI.json Normal file
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{
"provider": "MistralAI",
"list": [
{
"model": "ministral-3b-latest",
"name": "Ministral-3b-latest",
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"maxResponse": 8000,
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"vision": false,
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"functionCall": false,
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"usedInQueryExtension": true,
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"defaultConfig": {},
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}

4
packages/service/core/ai/config/provider/Moka.json Normal file
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{
"provider": "Moka",
"list": []
}

71
packages/service/core/ai/config/provider/Moonshot.json Normal file
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{
"provider": "Moonshot",
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}

4
packages/service/core/ai/config/provider/Ollama.json Normal file
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{
"provider": "Ollama",
"list": []
}

252
packages/service/core/ai/config/provider/OpenAI.json Normal file
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{
"provider": "OpenAI",
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{
"model": "whisper-1",
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}

4
packages/service/core/ai/config/provider/Other.json Normal file
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{
"provider": "Other",
"list": []
}

223
packages/service/core/ai/config/provider/Qwen.json Normal file
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{
"provider": "Qwen",
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{
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}

204
packages/service/core/ai/config/provider/Siliconflow.json Normal file
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{
"provider": "Siliconflow",
"list": [
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{
"model": "BAAI/bge-reranker-v2-m3",
"name": "BAAI/bge-reranker-v2-m3",
"type": "rerank"
}
]
}

129
packages/service/core/ai/config/provider/SparkDesk.json Normal file
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{
"provider": "SparkDesk",
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"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "max-32k",
"name": "SparkDesk-max-32k",
"maxContext": 32000,
"maxResponse": 8000,
"quoteMaxToken": 32000,
"maxTemperature": 1,
"vision": false,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "4.0Ultra",
"name": "SparkDesk-v4.0 Ultra",
"maxContext": 8000,
"maxResponse": 8000,
"quoteMaxToken": 8000,
"maxTemperature": 1,
"vision": false,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
}
]
}

308
packages/service/core/ai/config/provider/StepFun.json Normal file
View File

@ -0,0 +1,308 @@
{
"provider": "StepFun",
"list": [
{
"model": "step-1-flash",
"name": "step-1-flash",
"maxContext": 8000,
"maxResponse": 4000,
"quoteMaxToken": 6000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1-8k",
"name": "step-1-8k",
"maxContext": 8000,
"maxResponse": 8000,
"quoteMaxToken": 8000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1-32k",
"name": "step-1-32k",
"maxContext": 32000,
"maxResponse": 8000,
"quoteMaxToken": 32000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1-128k",
"name": "step-1-128k",
"maxContext": 128000,
"maxResponse": 8000,
"quoteMaxToken": 128000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1-256k",
"name": "step-1-256k",
"maxContext": 256000,
"maxResponse": 8000,
"quoteMaxToken": 256000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1o-vision-32k",
"name": "step-1o-vision-32k",
"maxContext": 32000,
"quoteMaxToken": 32000,
"maxResponse": 8000,
"maxTemperature": 2,
"vision": true,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1v-8k",
"name": "step-1v-8k",
"maxContext": 8000,
"maxResponse": 8000,
"quoteMaxToken": 8000,
"maxTemperature": 2,
"vision": true,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-1v-32k",
"name": "step-1v-32k",
"maxContext": 32000,
"quoteMaxToken": 32000,
"maxResponse": 8000,
"maxTemperature": 2,
"vision": true,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-2-mini",
"name": "step-2-mini",
"maxContext": 8000,
"maxResponse": 4000,
"quoteMaxToken": 6000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-2-16k",
"name": "step-2-16k",
"maxContext": 16000,
"maxResponse": 4000,
"quoteMaxToken": 4000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-2-16k-exp",
"name": "step-2-16k-exp",
"maxContext": 16000,
"maxResponse": 4000,
"quoteMaxToken": 4000,
"maxTemperature": 2,
"vision": false,
"datasetProcess": true,
"usedInClassify": true,
"usedInExtractFields": true,
"usedInToolCall": true,
"usedInQueryExtension": true,
"toolChoice": false,
"functionCall": false,
"customCQPrompt": "",
"customExtractPrompt": "",
"defaultSystemChatPrompt": "",
"type": "llm"
},
{
"model": "step-tts-mini",
"name": "step-tts-mini",
"voices": [
{
"label": "cixingnansheng",
"value": "cixingnansheng"
},
{
"label": "zhengpaiqingnian",
"value": "zhengpaiqingnian"
},
{
"label": "yuanqinansheng",
"value": "yuanqinansheng"
},
{
"label": "qingniandaxuesheng",
"value": "qingniandaxuesheng"
},
{
"label": "boyinnansheng",
"value": "boyinnansheng"
},
{
"label": "ruyananshi",
"value": "ruyananshi"
},
{
"label": "shenchennanyin",
"value": "shenchennanyin"
},
{
"label": "qinqienvsheng",
"value": "qinqienvsheng"
},
{
"label": "wenrounvsheng",
"value": "wenrounvsheng"
},
{
"label": "jilingshaonv",
"value": "jilingshaonv"
},
{
"label": "yuanqishaonv",
"value": "yuanqishaonv"
},
{
"label": "ruanmengnvsheng",
"value": "ruanmengnvsheng"
},
{
"label": "youyanvsheng",
"value": "youyanvsheng"
},
{
"label": "lengyanyujie",
"value": "lengyanyujie"
},
{
"label": "shuangkuaijiejie",
"value": "shuangkuaijiejie"
},
{
"label": "wenjingxuejie",
"value": "wenjingxuejie"
},
{
"label": "linjiajiejie",
"value": "linjiajiejie"
},
{
"label": "linjiameimei",
"value": "linjiameimei"
},
{
"label": "zhixingjiejie",
"value": "zhixingjiejie"
}
],
"type": "tts"
}
]
}

49
packages/service/core/ai/config/provider/Yi.json Normal file
View File

@ -0,0 +1,49 @@
{
"provider": "Yi",
"list": [
{
"model": "yi-lightning",
"name": "yi-lightning",
"maxContext": 16000,
"maxResponse": 4000,
"quoteMaxToken": 12000,
"maxTemperature": 1,
"vision": false,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
},
{
"model": "yi-vision-v2",
"name": "yi-vision-v2",
"maxContext": 16000,
"maxResponse": 4000,
"quoteMaxToken": 12000,
"maxTemperature": 1,
"vision": true,
"toolChoice": false,
"functionCall": false,
"defaultSystemChatPrompt": "",
"datasetProcess": true,
"usedInClassify": true,
"customCQPrompt": "",
"usedInExtractFields": true,
"usedInQueryExtension": true,
"customExtractPrompt": "",
"usedInToolCall": true,
"defaultConfig": {},
"fieldMap": {},
"type": "llm"
}
]
}

6
packages/service/core/ai/config/rerank/bge-reranker-v2-m3.json
View File

@ -1,6 +0,0 @@
{
"provider": "BAAI",
"model": "bge-reranker-v2-m3",
"name": "bge-reranker-v2-m3",
"charsPointsPrice": 0
}

21
packages/service/core/ai/config/schema.ts Normal file
View File

@ -0,0 +1,21 @@
import { connectionMongo, getMongoModel } from '../../../common/mongo';
const { Schema } = connectionMongo;
import type { SystemModelSchemaType } from '../type';
const SystemModelSchema = new Schema({
model: {
type: String,
required: true,
unique: true
},
metadata: {
type: Object,
required: true,
default: {}
}
});
export const MongoSystemModel = getMongoModel<SystemModelSchemaType>(
'system_models',
SystemModelSchema
);

6
packages/service/core/ai/config/stt/whisper-1.json
View File

@ -1,6 +0,0 @@
{
"provider": "OpenAI",
"model": "whisper-1",
"name": "whisper-1",
"charsPointsPrice": 0
}

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