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2
.github/workflows/docs-deploy-vercel.yml
vendored
2
.github/workflows/docs-deploy-vercel.yml
vendored
@ -58,7 +58,7 @@ jobs:
|
||||
|
||||
# Step 4 - Builds the site using Hugo
|
||||
- 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
|
||||
- name: Deploy to Vercel
|
||||
|
||||
2
.github/workflows/docs-preview.yml
vendored
2
.github/workflows/docs-preview.yml
vendored
@ -58,7 +58,7 @@ jobs:
|
||||
|
||||
# Step 4 - Builds the site using Hugo
|
||||
- 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
|
||||
- name: Deploy to Vercel
|
||||
|
||||
@ -3,7 +3,7 @@ FROM hugomods/hugo:0.117.0 AS builder
|
||||
WORKDIR /app
|
||||
|
||||
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
|
||||
|
||||
|
||||
BIN
docSite/assets/imgs/image-100.png
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@ -25,251 +25,6 @@ weight: 707
|
||||
"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）
|
||||
"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"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
```
|
||||
@ -118,10 +118,17 @@ services:
|
||||
```
|
||||
## 接入 FastGPT
|
||||
|
||||
参考 [ReRank模型接入](/docs/development/configuration/#rerank-接入)，host 变量为部署的域名。
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## 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)`
|
||||
|
||||
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。
|
||||
|
||||
@ -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）
|
||||
"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
|
||||
|
||||
@ -7,6 +7,13 @@ toc: true
|
||||
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
|
||||
|
||||
|
||||
@ -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。
|
||||
|
||||
### 6. 配置模型
|
||||
|
||||
[点击查看模型配置教程](/docs/development/modelConfig/intro/)
|
||||
|
||||
## FAQ
|
||||
|
||||
### Mongo 副本集自动初始化失败
|
||||
|
||||
@ -23,11 +23,11 @@ images: []
|
||||
|
||||
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:
|
||||
|
||||
|
||||
|
||||
|
||||
442
docSite/content/zh-cn/docs/development/modelConfig/intro.md
Normal file
442
docSite/content/zh-cn/docs/development/modelConfig/intro.md
Normal file
@ -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：
|
||||
|
||||
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## 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。
|
||||
|
||||
| | |
|
||||
| --- | --- |
|
||||
|  |  |
|
||||
|
||||
### 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。
|
||||
|
||||
| | |
|
||||
| --- | --- |
|
||||
|  |  |
|
||||
|
||||
### 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。
|
||||
|
||||
| | |
|
||||
| --- | --- |
|
||||
|  |  |
|
||||
|
||||
### 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。
|
||||
|
||||
| | |
|
||||
| --- | --- |
|
||||
|  |  |
|
||||
|
||||
**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。
|
||||
|
||||
|
||||
|
||||
## 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）。
|
||||
|
||||
|
||||
|
||||
#### 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：
|
||||
|
||||
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## 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
|
||||
}
|
||||
}
|
||||
```
|
||||
@ -94,70 +94,16 @@ CHAT_API_KEY=sk-xxxxxx
|
||||
|
||||
|
||||
|
||||
### 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。
|
||||
|
||||
```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
|
||||
|
||||
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
|
||||
|
||||
|
||||
@ -27,139 +27,13 @@ OPENAI_BASE_URL=https://api.siliconflow.cn/v1
|
||||
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
|
||||
{
|
||||
"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
|
||||
|
||||
|
||||
@ -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>
|
||||
|
||||
### 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。
|
||||
|
||||
@ -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
|
||||
|
||||
|
||||
|
||||
### 登录
|
||||
### 2. 登录
|
||||
|
||||
用户名：`root`
|
||||
|
||||
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。
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
{{% 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。
|
||||
[点击查看模型配置教程](/docs/development/modelConfig/intro/)
|
||||
|
||||
## 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。
|
||||
|
||||
### 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。
|
||||
|
||||
|
||||
|
||||
{{% 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
|
||||
|
||||
[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。
|
||||
@ -148,8 +149,6 @@ SYSTEM_FAVICON 可以是一个网络地址
|
||||
|
||||
|
||||
|
||||
### 管理后台(已合并到plus)
|
||||
|
||||
### 商业版镜像配置文件
|
||||
|
||||
```
|
||||
|
||||
@ -31,7 +31,6 @@ weight: 813
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
@ -56,7 +55,6 @@ weight: 813
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
|
||||
50
docSite/content/zh-cn/docs/development/upgrading/4820.md
Normal file
50
docSite/content/zh-cn/docs/development/upgrading/4820.md
Normal file
@ -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。
|
||||
@ -114,15 +114,15 @@ services:
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@ -72,15 +72,15 @@ services:
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@ -53,15 +53,15 @@ services:
|
||||
wait $$!
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.8.20 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.8.17 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.17 # 阿里云
|
||||
image: ghcr.io/labring/fastgpt:v4.8.20 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.20 # 阿里云
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
|
||||
@ -23,7 +23,6 @@ data:
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
@ -45,7 +44,6 @@ data:
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
@ -67,7 +65,6 @@ data:
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
@ -89,7 +86,6 @@ data:
|
||||
"usedInClassify": false,
|
||||
"usedInExtractFields": false,
|
||||
"usedInToolCall": false,
|
||||
"usedInQueryExtension": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
|
||||
@ -2,12 +2,22 @@ import { ErrType } from '../errorCode';
|
||||
import { i18nT } from '../../../../web/i18n/utils';
|
||||
/* team: 503000 */
|
||||
export enum UserErrEnum {
|
||||
notUser = 'notUser',
|
||||
userExist = 'userExist',
|
||||
unAuthRole = 'unAuthRole',
|
||||
account_psw_error = 'account_psw_error',
|
||||
balanceNotEnough = 'balanceNotEnough',
|
||||
unAuthSso = 'unAuthSso'
|
||||
}
|
||||
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,
|
||||
message: i18nT('common:code_error.account_error')
|
||||
|
||||
14
packages/global/common/system/types/index.d.ts
vendored
14
packages/global/common/system/types/index.d.ts
vendored
@ -3,7 +3,7 @@ import type {
|
||||
ChatModelItemType,
|
||||
FunctionModelItemType,
|
||||
LLMModelItemType,
|
||||
VectorModelItemType,
|
||||
EmbeddingModelItemType,
|
||||
AudioSpeechModels,
|
||||
STTModelType,
|
||||
ReRankModelItemType
|
||||
@ -31,11 +31,13 @@ export type FastGPTConfigFileType = {
|
||||
feConfigs: FastGPTFeConfigsType;
|
||||
systemEnv: SystemEnvType;
|
||||
subPlans?: SubPlanType;
|
||||
llmModels: ChatModelItemType[];
|
||||
vectorModels: VectorModelItemType[];
|
||||
reRankModels: ReRankModelItemType[];
|
||||
audioSpeechModels: AudioSpeechModelType[];
|
||||
whisperModel: STTModelType;
|
||||
|
||||
// Abandon
|
||||
llmModels?: ChatModelItemType[];
|
||||
vectorModels?: EmbeddingModelItemType[];
|
||||
reRankModels?: ReRankModelItemType[];
|
||||
audioSpeechModels?: TTSModelType[];
|
||||
whisperModel?: STTModelType;
|
||||
};
|
||||
|
||||
export type FastGPTFeConfigsType = {
|
||||
|
||||
@ -15,15 +15,13 @@ export enum LLMModelTypeEnum {
|
||||
all = 'all',
|
||||
classify = 'classify',
|
||||
extractFields = 'extractFields',
|
||||
toolCall = 'toolCall',
|
||||
queryExtension = 'queryExtension'
|
||||
toolCall = 'toolCall'
|
||||
}
|
||||
export const llmModelTypeFilterMap = {
|
||||
[LLMModelTypeEnum.all]: 'model',
|
||||
[LLMModelTypeEnum.classify]: 'usedInClassify',
|
||||
[LLMModelTypeEnum.extractFields]: 'usedInExtractFields',
|
||||
[LLMModelTypeEnum.toolCall]: 'usedInToolCall',
|
||||
[LLMModelTypeEnum.queryExtension]: 'usedInQueryExtension'
|
||||
[LLMModelTypeEnum.toolCall]: 'usedInToolCall'
|
||||
};
|
||||
|
||||
export enum EmbeddingTypeEnm {
|
||||
|
||||
115
packages/global/core/ai/model.d.ts
vendored
115
packages/global/core/ai/model.d.ts
vendored
@ -1,3 +1,4 @@
|
||||
import { ModelTypeEnum } from './model';
|
||||
import type { ModelProviderIdType } from './provider';
|
||||
|
||||
type PriceType = {
|
||||
@ -7,68 +8,74 @@ type PriceType = {
|
||||
inputPrice?: number; // 1k tokens=n points
|
||||
outputPrice?: number; // 1k tokens=n points
|
||||
};
|
||||
export type LLMModelItemType = PriceType & {
|
||||
type BaseModelItemType = {
|
||||
provider: ModelProviderIdType;
|
||||
model: string;
|
||||
name: string;
|
||||
avatar?: string; // model icon, from provider
|
||||
maxContext: number;
|
||||
maxResponse: number;
|
||||
quoteMaxToken: number;
|
||||
maxTemperature: number;
|
||||
|
||||
censor?: boolean;
|
||||
vision?: boolean;
|
||||
isActive?: boolean;
|
||||
isCustom?: boolean;
|
||||
isDefault?: boolean;
|
||||
|
||||
// diff function model
|
||||
datasetProcess?: boolean; // dataset
|
||||
usedInClassify?: boolean; // classify
|
||||
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>;
|
||||
// If has requestUrl, it will request the model directly
|
||||
requestUrl?: string;
|
||||
requestAuth?: string;
|
||||
};
|
||||
|
||||
export type VectorModelItemType = PriceType & {
|
||||
provider: ModelProviderIdType;
|
||||
model: string; // model name
|
||||
name: string; // show name
|
||||
avatar?: string;
|
||||
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 LLMModelItemType = PriceType &
|
||||
BaseModelItemType & {
|
||||
type: ModelTypeEnum.llm;
|
||||
maxContext: number;
|
||||
maxResponse: number;
|
||||
quoteMaxToken: number;
|
||||
maxTemperature?: number;
|
||||
|
||||
export type ReRankModelItemType = PriceType & {
|
||||
provider: ModelProviderIdType;
|
||||
model: string;
|
||||
name: string;
|
||||
requestUrl: string;
|
||||
requestAuth: string;
|
||||
};
|
||||
censor?: boolean;
|
||||
vision?: boolean;
|
||||
reasoning?: boolean;
|
||||
|
||||
export type AudioSpeechModelType = PriceType & {
|
||||
provider: ModelProviderIdType;
|
||||
model: string;
|
||||
name: string;
|
||||
voices: { label: string; value: string; bufferId: string }[];
|
||||
};
|
||||
// diff function model
|
||||
datasetProcess?: boolean; // dataset
|
||||
usedInClassify?: boolean; // classify
|
||||
usedInExtractFields?: boolean; // extract fields
|
||||
usedInToolCall?: boolean; // tool call
|
||||
|
||||
export type STTModelType = PriceType & {
|
||||
provider: ModelProviderIdType;
|
||||
model: string;
|
||||
name: string;
|
||||
};
|
||||
functionCall: boolean;
|
||||
toolChoice: boolean;
|
||||
|
||||
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;
|
||||
};
|
||||
|
||||
@ -1,9 +1,18 @@
|
||||
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';
|
||||
|
||||
export enum ModelTypeEnum {
|
||||
llm = 'llm',
|
||||
embedding = 'embedding',
|
||||
tts = 'tts',
|
||||
stt = 'stt',
|
||||
rerank = 'rerank'
|
||||
}
|
||||
|
||||
export const defaultQAModels: LLMModelItemType[] = [
|
||||
{
|
||||
type: ModelTypeEnum.llm,
|
||||
provider: 'OpenAI',
|
||||
model: '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',
|
||||
model: 'text-embedding-3-small',
|
||||
name: 'Embedding-2',
|
||||
@ -36,12 +46,15 @@ export const defaultVectorModels: VectorModelItemType[] = [
|
||||
}
|
||||
];
|
||||
|
||||
export const defaultWhisperModel: STTModelType = {
|
||||
provider: 'OpenAI',
|
||||
model: 'whisper-1',
|
||||
name: 'whisper-1',
|
||||
charsPointsPrice: 0
|
||||
};
|
||||
export const defaultSTTModels: STTModelType[] = [
|
||||
{
|
||||
type: ModelTypeEnum.stt,
|
||||
provider: 'OpenAI',
|
||||
model: 'whisper-1',
|
||||
name: 'whisper-1',
|
||||
charsPointsPrice: 0
|
||||
}
|
||||
];
|
||||
|
||||
export const getModelFromList = (
|
||||
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 = [
|
||||
{ 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.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 }
|
||||
];
|
||||
|
||||
@ -7,11 +7,12 @@ export type ModelProviderIdType =
|
||||
| 'Meta'
|
||||
| 'MistralAI'
|
||||
| 'Groq'
|
||||
| 'Grok'
|
||||
| 'AliCloud'
|
||||
| 'Qwen'
|
||||
| 'Doubao'
|
||||
| 'ChatGLM'
|
||||
| 'DeepSeek'
|
||||
| 'ChatGLM'
|
||||
| 'Ernie'
|
||||
| 'Moonshot'
|
||||
| 'MiniMax'
|
||||
@ -20,6 +21,7 @@ export type ModelProviderIdType =
|
||||
| 'Baichuan'
|
||||
| 'StepFun'
|
||||
| 'Yi'
|
||||
| 'Siliconflow'
|
||||
| 'Ollama'
|
||||
| 'BAAI'
|
||||
| 'FishAudio'
|
||||
@ -29,7 +31,7 @@ export type ModelProviderIdType =
|
||||
|
||||
export type ModelProviderType = {
|
||||
id: ModelProviderIdType;
|
||||
name: string;
|
||||
name: any;
|
||||
avatar: string;
|
||||
};
|
||||
|
||||
@ -59,6 +61,11 @@ export const ModelProviderList: ModelProviderType[] = [
|
||||
name: 'MistralAI',
|
||||
avatar: 'model/mistral'
|
||||
},
|
||||
{
|
||||
id: 'Grok',
|
||||
name: 'Grok',
|
||||
avatar: 'model/grok'
|
||||
},
|
||||
{
|
||||
id: 'Groq',
|
||||
name: 'Groq',
|
||||
@ -155,6 +162,11 @@ export const ModelProviderList: ModelProviderType[] = [
|
||||
name: i18nT('common:model_moka'),
|
||||
avatar: 'model/moka'
|
||||
},
|
||||
{
|
||||
id: 'Siliconflow',
|
||||
name: i18nT('common:model_siliconflow'),
|
||||
avatar: 'model/siliconflow'
|
||||
},
|
||||
{
|
||||
id: 'Other',
|
||||
name: i18nT('common:model_other'),
|
||||
@ -165,6 +177,7 @@ export const ModelProviderMap = Object.fromEntries(
|
||||
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;
|
||||
};
|
||||
|
||||
2
packages/global/core/app/type.d.ts
vendored
2
packages/global/core/app/type.d.ts
vendored
@ -80,6 +80,7 @@ export type AppSimpleEditFormType = {
|
||||
maxToken?: number;
|
||||
isResponseAnswerText: boolean;
|
||||
maxHistories: number;
|
||||
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
|
||||
};
|
||||
dataset: {
|
||||
datasets: SelectedDatasetType;
|
||||
@ -117,6 +118,7 @@ export type SettingAIDataType = {
|
||||
isResponseAnswerText?: boolean;
|
||||
maxHistories?: number;
|
||||
[NodeInputKeyEnum.aiChatVision]?: boolean; // Is open vision mode
|
||||
[NodeInputKeyEnum.aiChatReasoning]?: boolean; // Is open reasoning mode
|
||||
};
|
||||
|
||||
// variable
|
||||
|
||||
@ -16,7 +16,8 @@ export const getDefaultAppForm = (): AppSimpleEditFormType => {
|
||||
temperature: 0,
|
||||
isResponseAnswerText: true,
|
||||
maxHistories: 6,
|
||||
maxToken: 4000
|
||||
maxToken: 4000,
|
||||
aiChatReasoning: true
|
||||
},
|
||||
dataset: {
|
||||
datasets: [],
|
||||
|
||||
@ -25,7 +25,8 @@ export enum ChatItemValueTypeEnum {
|
||||
text = 'text',
|
||||
file = 'file',
|
||||
tool = 'tool',
|
||||
interactive = 'interactive'
|
||||
interactive = 'interactive',
|
||||
reasoning = 'reasoning'
|
||||
}
|
||||
|
||||
export enum ChatSourceEnum {
|
||||
@ -75,5 +76,3 @@ export enum ChatStatusEnum {
|
||||
running = 'running',
|
||||
finish = 'finish'
|
||||
}
|
||||
|
||||
export const MARKDOWN_QUOTE_SIGN = 'QUOTE SIGN';
|
||||
|
||||
11
packages/global/core/chat/type.d.ts
vendored
11
packages/global/core/chat/type.d.ts
vendored
@ -70,14 +70,23 @@ export type SystemChatItemType = {
|
||||
obj: ChatRoleEnum.System;
|
||||
value: SystemChatItemValueItemType[];
|
||||
};
|
||||
|
||||
export type AIChatItemValueItemType = {
|
||||
type: ChatItemValueTypeEnum.text | ChatItemValueTypeEnum.tool | ChatItemValueTypeEnum.interactive;
|
||||
type:
|
||||
| ChatItemValueTypeEnum.text
|
||||
| ChatItemValueTypeEnum.reasoning
|
||||
| ChatItemValueTypeEnum.tool
|
||||
| ChatItemValueTypeEnum.interactive;
|
||||
text?: {
|
||||
content: string;
|
||||
};
|
||||
reasoning?: {
|
||||
content: string;
|
||||
};
|
||||
tools?: ToolModuleResponseItemType[];
|
||||
interactive?: WorkflowInteractiveResponseType;
|
||||
};
|
||||
|
||||
export type AIChatItemType = {
|
||||
obj: ChatRoleEnum.AI;
|
||||
value: AIChatItemValueItemType[];
|
||||
|
||||
8
packages/global/core/dataset/type.d.ts
vendored
8
packages/global/core/dataset/type.d.ts
vendored
@ -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 { PushDatasetDataChunkProps } from './api';
|
||||
import {
|
||||
@ -152,7 +152,7 @@ export type DatasetSimpleItemType = {
|
||||
_id: string;
|
||||
avatar: string;
|
||||
name: string;
|
||||
vectorModel: VectorModelItemType;
|
||||
vectorModel: EmbeddingModelItemType;
|
||||
};
|
||||
export type DatasetListItemType = {
|
||||
_id: string;
|
||||
@ -163,14 +163,14 @@ export type DatasetListItemType = {
|
||||
intro: string;
|
||||
type: `${DatasetTypeEnum}`;
|
||||
permission: DatasetPermission;
|
||||
vectorModel: VectorModelItemType;
|
||||
vectorModel: EmbeddingModelItemType;
|
||||
inheritPermission: boolean;
|
||||
private?: boolean;
|
||||
sourceMember?: SourceMemberType;
|
||||
};
|
||||
|
||||
export type DatasetItemType = Omit<DatasetSchemaType, 'vectorModel' | 'agentModel'> & {
|
||||
vectorModel: VectorModelItemType;
|
||||
vectorModel: EmbeddingModelItemType;
|
||||
agentModel: LLMModelItemType;
|
||||
permission: DatasetPermission;
|
||||
};
|
||||
|
||||
2
packages/global/core/workflow/api.d.ts
vendored
2
packages/global/core/workflow/api.d.ts
vendored
@ -1,4 +1,4 @@
|
||||
import { VectorModelItemType } from '../ai/model.d';
|
||||
import { EmbeddingModelItemType } from '../ai/model.d';
|
||||
import { NodeInputKeyEnum } from './constants';
|
||||
|
||||
export type SelectedDatasetType = { datasetId: string }[];
|
||||
|
||||
@ -141,6 +141,7 @@ export enum NodeInputKeyEnum {
|
||||
aiChatDatasetQuote = 'quoteQA',
|
||||
aiChatVision = 'aiChatVision',
|
||||
stringQuoteText = 'stringQuoteText',
|
||||
aiChatReasoning = 'aiChatReasoning',
|
||||
|
||||
// dataset
|
||||
datasetSelectList = 'datasets',
|
||||
@ -220,7 +221,8 @@ export enum NodeOutputKeyEnum {
|
||||
// common
|
||||
userChatInput = 'userChatInput',
|
||||
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',
|
||||
failed = 'failed',
|
||||
error = 'error',
|
||||
|
||||
@ -220,6 +220,7 @@ export type AIChatNodeProps = {
|
||||
[NodeInputKeyEnum.aiChatMaxToken]?: number;
|
||||
[NodeInputKeyEnum.aiChatIsResponseText]: boolean;
|
||||
[NodeInputKeyEnum.aiChatVision]?: boolean;
|
||||
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
|
||||
|
||||
[NodeInputKeyEnum.aiChatQuoteRole]?: AiChatQuoteRoleType;
|
||||
[NodeInputKeyEnum.aiChatQuoteTemplate]?: string;
|
||||
|
||||
@ -176,6 +176,7 @@ export const checkNodeRunStatus = ({
|
||||
}
|
||||
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);
|
||||
return nextEdges.some((nextEdge) => checkIsCircular(nextEdge, new Set(visited)));
|
||||
};
|
||||
@ -207,7 +208,23 @@ export const checkNodeRunStatus = ({
|
||||
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')) {
|
||||
return 'skip';
|
||||
}
|
||||
@ -215,14 +232,6 @@ export const checkNodeRunStatus = ({
|
||||
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';
|
||||
};
|
||||
|
||||
@ -355,12 +364,14 @@ export function replaceEditorVariable({
|
||||
|
||||
export const textAdaptGptResponse = ({
|
||||
text,
|
||||
reasoning_content,
|
||||
model = '',
|
||||
finish_reason = null,
|
||||
extraData = {}
|
||||
}: {
|
||||
model?: string;
|
||||
text: string | null;
|
||||
text?: string | null;
|
||||
reasoning_content?: string | null;
|
||||
finish_reason?: null | 'stop';
|
||||
extraData?: Object;
|
||||
}) => {
|
||||
@ -372,10 +383,11 @@ export const textAdaptGptResponse = ({
|
||||
model,
|
||||
choices: [
|
||||
{
|
||||
delta:
|
||||
text === null
|
||||
? {}
|
||||
: { role: ChatCompletionRequestMessageRoleEnum.Assistant, content: text },
|
||||
delta: {
|
||||
role: ChatCompletionRequestMessageRoleEnum.Assistant,
|
||||
content: text,
|
||||
...(reasoning_content && { reasoning_content })
|
||||
},
|
||||
index: 0,
|
||||
finish_reason
|
||||
}
|
||||
|
||||
@ -63,14 +63,14 @@ export const AiChatModule: FlowNodeTemplateType = {
|
||||
key: NodeInputKeyEnum.aiChatTemperature,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
|
||||
label: '',
|
||||
value: 0,
|
||||
value: undefined,
|
||||
valueType: WorkflowIOValueTypeEnum.number
|
||||
},
|
||||
{
|
||||
key: NodeInputKeyEnum.aiChatMaxToken,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
|
||||
label: '',
|
||||
value: 2000,
|
||||
value: undefined,
|
||||
valueType: WorkflowIOValueTypeEnum.number
|
||||
},
|
||||
|
||||
@ -91,6 +91,13 @@ export const AiChatModule: FlowNodeTemplateType = {
|
||||
valueType: WorkflowIOValueTypeEnum.boolean,
|
||||
value: true
|
||||
},
|
||||
{
|
||||
key: NodeInputKeyEnum.aiChatReasoning,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden],
|
||||
label: '',
|
||||
valueType: WorkflowIOValueTypeEnum.boolean,
|
||||
value: true
|
||||
},
|
||||
// settings modal ---
|
||||
{
|
||||
...Input_Template_System_Prompt,
|
||||
|
||||
@ -31,10 +31,7 @@ export const AiQueryExtension: FlowNodeTemplateType = {
|
||||
showStatus: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_SelectAIModel,
|
||||
llmModelType: LLMModelTypeEnum.queryExtension
|
||||
},
|
||||
Input_Template_SelectAIModel,
|
||||
{
|
||||
key: NodeInputKeyEnum.aiSystemPrompt,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
|
||||
|
||||
@ -43,14 +43,14 @@ export const ToolModule: FlowNodeTemplateType = {
|
||||
key: NodeInputKeyEnum.aiChatTemperature,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
|
||||
label: '',
|
||||
value: 0,
|
||||
value: undefined,
|
||||
valueType: WorkflowIOValueTypeEnum.number
|
||||
},
|
||||
{
|
||||
key: NodeInputKeyEnum.aiChatMaxToken,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
|
||||
label: '',
|
||||
value: 2000,
|
||||
value: undefined,
|
||||
valueType: WorkflowIOValueTypeEnum.number
|
||||
},
|
||||
{
|
||||
|
||||
16
packages/global/support/wallet/usage/api.d.ts
vendored
16
packages/global/support/wallet/usage/api.d.ts
vendored
@ -6,6 +6,22 @@ export type CreateTrainingUsageProps = {
|
||||
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 & {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
|
||||
@ -18,30 +18,30 @@ export const UsageSourceMap = {
|
||||
label: i18nT('common:core.chat.logs.online')
|
||||
},
|
||||
[UsageSourceEnum.api]: {
|
||||
label: 'Api'
|
||||
label: 'API'
|
||||
},
|
||||
[UsageSourceEnum.shareLink]: {
|
||||
label: i18nT('common:core.chat.logs.free_login')
|
||||
},
|
||||
[UsageSourceEnum.training]: {
|
||||
label: 'dataset.Training Name'
|
||||
label: i18nT('common:dataset.Training Name')
|
||||
},
|
||||
[UsageSourceEnum.cronJob]: {
|
||||
label: i18nT('common:cron_job_run_app')
|
||||
},
|
||||
[UsageSourceEnum.feishu]: {
|
||||
label: i18nT('user:usage.feishu')
|
||||
label: i18nT('account_usage:feishu')
|
||||
},
|
||||
[UsageSourceEnum.official_account]: {
|
||||
label: i18nT('user:usage.official_account')
|
||||
label: i18nT('account_usage:official_account')
|
||||
},
|
||||
[UsageSourceEnum.share]: {
|
||||
label: i18nT('user:usage.share')
|
||||
label: i18nT('account_usage:share')
|
||||
},
|
||||
[UsageSourceEnum.wecom]: {
|
||||
label: i18nT('user:usage.wecom')
|
||||
label: i18nT('account_usage:wecom')
|
||||
},
|
||||
[UsageSourceEnum.dingtalk]: {
|
||||
label: i18nT('user:usage.dingtalk')
|
||||
label: i18nT('account_usage:dingtalk')
|
||||
}
|
||||
};
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
import { SourceMemberType } from '../../../support/user/type';
|
||||
import { CreateUsageProps } from './api';
|
||||
import { UsageSourceEnum } from './constants';
|
||||
|
||||
@ -10,6 +11,7 @@ export type UsageListItemCountType = {
|
||||
// deprecated
|
||||
tokens?: number;
|
||||
};
|
||||
|
||||
export type UsageListItemType = UsageListItemCountType & {
|
||||
moduleName: string;
|
||||
amount: number;
|
||||
@ -28,4 +30,5 @@ export type UsageItemType = {
|
||||
source: UsageSchemaType['source'];
|
||||
totalPoints: number;
|
||||
list: UsageSchemaType['list'];
|
||||
sourceMember: SourceMemberType;
|
||||
};
|
||||
|
||||
@ -40,7 +40,7 @@ export async function uploadMongoImg({
|
||||
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) => {
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
import { ApiRequestProps } from '../../type/next';
|
||||
import requestIp from 'request-ip';
|
||||
import { ERROR_ENUM } from '@fastgpt/global/common/error/errorCode';
|
||||
import { authFrequencyLimit } from '../system/frequencyLimit/utils';
|
||||
import { addSeconds } from 'date-fns';
|
||||
import { NextApiResponse } from 'next';
|
||||
@ -9,7 +8,17 @@ import { jsonRes } from '../response';
|
||||
// unit: times/s
|
||||
// how to use?
|
||||
// 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) => {
|
||||
const ip = requestIp.getClientIp(req);
|
||||
if (!ip || (process.env.USE_IP_LIMIT !== 'true' && !force)) {
|
||||
@ -17,14 +26,14 @@ export function useReqFrequencyLimit(seconds: number, limit: number, force = fal
|
||||
}
|
||||
try {
|
||||
await authFrequencyLimit({
|
||||
eventId: 'ip-qps-limit' + ip,
|
||||
eventId: `ip-qps-limit-${id}-` + ip,
|
||||
maxAmount: limit,
|
||||
expiredTime: addSeconds(new Date(), seconds)
|
||||
});
|
||||
} catch (_) {
|
||||
jsonRes(res, {
|
||||
code: 429,
|
||||
error: ERROR_ENUM.tooManyRequest
|
||||
error: `Too many request, request ${limit} times every ${seconds} seconds`
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
@ -33,7 +33,15 @@ export const jsonRes = <T = any>(
|
||||
|
||||
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
|
||||
|
||||
@ -6,8 +6,7 @@ import { FastGPTProUrl } from '../constants';
|
||||
export const getFastGPTConfigFromDB = async () => {
|
||||
if (!FastGPTProUrl) {
|
||||
return {
|
||||
config: {} as FastGPTConfigFileType,
|
||||
configId: undefined
|
||||
config: {} as FastGPTConfigFileType
|
||||
};
|
||||
}
|
||||
|
||||
@ -18,9 +17,35 @@ export const getFastGPTConfigFromDB = async () => {
|
||||
});
|
||||
|
||||
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 {
|
||||
configId: res ? String(res._id) : undefined,
|
||||
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();
|
||||
};
|
||||
|
||||
@ -13,15 +13,6 @@ export const initFastGPTConfig = (config?: FastGPTConfigFileType) => {
|
||||
global.feConfigs = config.feConfigs;
|
||||
global.systemEnv = config.systemEnv;
|
||||
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 = () => {
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
import { PgVectorCtrl } from './pg/class';
|
||||
import { getVectorsByText } from '../../core/ai/embedding';
|
||||
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 { MilvusCtrl } from './milvus/class';
|
||||
|
||||
@ -28,7 +28,7 @@ export const insertDatasetDataVector = async ({
|
||||
...props
|
||||
}: InsertVectorProps & {
|
||||
query: string;
|
||||
model: VectorModelItemType;
|
||||
model: EmbeddingModelItemType;
|
||||
}) => {
|
||||
const { vectors, tokens } = await getVectorsByText({
|
||||
model,
|
||||
|
||||
@ -1,5 +1,6 @@
|
||||
import type { NextApiResponse } from 'next';
|
||||
import { getAIApi } from '../config';
|
||||
import { getTTSModel } from '../model';
|
||||
|
||||
export async function text2Speech({
|
||||
res,
|
||||
@ -18,15 +19,26 @@ export async function text2Speech({
|
||||
voice: string;
|
||||
speed?: number;
|
||||
}) {
|
||||
const modelData = getTTSModel(model)!;
|
||||
const ai = getAIApi();
|
||||
const response = await ai.audio.speech.create({
|
||||
model,
|
||||
// @ts-ignore
|
||||
voice,
|
||||
input,
|
||||
response_format: 'mp3',
|
||||
speed
|
||||
});
|
||||
const response = await ai.audio.speech.create(
|
||||
{
|
||||
model,
|
||||
// @ts-ignore
|
||||
voice,
|
||||
input,
|
||||
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;
|
||||
readableStream.pipe(res);
|
||||
|
||||
@ -2,6 +2,7 @@ import fs from 'fs';
|
||||
import { getAxiosConfig } from '../config';
|
||||
import axios from 'axios';
|
||||
import FormData from 'form-data';
|
||||
import { getSTTModel } from '../model';
|
||||
|
||||
export const aiTranscriptions = async ({
|
||||
model,
|
||||
@ -14,13 +15,21 @@ export const aiTranscriptions = async ({
|
||||
data.append('model', model);
|
||||
data.append('file', fileStream);
|
||||
|
||||
const modelData = getSTTModel(model);
|
||||
const aiAxiosConfig = getAxiosConfig();
|
||||
|
||||
const { data: result } = await axios<{ text: string }>({
|
||||
method: 'post',
|
||||
baseURL: aiAxiosConfig.baseUrl,
|
||||
url: '/audio/transcriptions',
|
||||
...(modelData.requestUrl
|
||||
? { url: modelData.requestUrl }
|
||||
: {
|
||||
baseURL: aiAxiosConfig.baseUrl,
|
||||
url: modelData.requestUrl || '/audio/transcriptions'
|
||||
}),
|
||||
headers: {
|
||||
Authorization: aiAxiosConfig.authorization,
|
||||
Authorization: modelData.requestAuth
|
||||
? `Bearer ${modelData.requestAuth}`
|
||||
: aiAxiosConfig.authorization,
|
||||
...data.getHeaders()
|
||||
},
|
||||
data: data
|
||||
|
||||
@ -7,14 +7,14 @@ import { getErrText } from '@fastgpt/global/common/error/utils';
|
||||
import { addLog } from '../../common/system/log';
|
||||
import { i18nT } from '../../../web/i18n/utils';
|
||||
import { OpenaiAccountType } from '@fastgpt/global/support/user/team/type';
|
||||
import { getLLMModel } from './model';
|
||||
|
||||
export const openaiBaseUrl = process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1';
|
||||
|
||||
export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number }) => {
|
||||
const { userKey, timeout } = props || {};
|
||||
|
||||
const baseUrl =
|
||||
userKey?.baseUrl || global?.systemEnv?.oneapiUrl || process.env.ONEAPI_URL || openaiBaseUrl;
|
||||
const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
|
||||
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
|
||||
|
||||
return new OpenAI({
|
||||
@ -29,8 +29,7 @@ export const getAIApi = (props?: { userKey?: OpenaiAccountType; timeout?: number
|
||||
export const getAxiosConfig = (props?: { userKey?: OpenaiAccountType }) => {
|
||||
const { userKey } = props || {};
|
||||
|
||||
const baseUrl =
|
||||
userKey?.baseUrl || global?.systemEnv?.oneapiUrl || process.env.ONEAPI_URL || openaiBaseUrl;
|
||||
const baseUrl = userKey?.baseUrl || global?.systemEnv?.oneapiUrl || openaiBaseUrl;
|
||||
const apiKey = userKey?.key || global?.systemEnv?.chatApiKey || process.env.CHAT_API_KEY || '';
|
||||
|
||||
return {
|
||||
@ -63,12 +62,23 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
|
||||
getEmptyResponseTip: () => string;
|
||||
}> => {
|
||||
try {
|
||||
const modelConstantsData = getLLMModel(body.model);
|
||||
|
||||
const formatTimeout = timeout ? timeout : body.stream ? 60000 : 600000;
|
||||
const ai = getAIApi({
|
||||
userKey,
|
||||
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 =
|
||||
typeof response === 'object' &&
|
||||
|
||||
@ -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
|
||||
}
|
||||
@ -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
4
packages/service/core/ai/config/provider/AliCloud.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "AliCloud",
|
||||
"list": []
|
||||
}
|
||||
17
packages/service/core/ai/config/provider/BAAI.json
Normal file
17
packages/service/core/ai/config/provider/BAAI.json
Normal 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
4
packages/service/core/ai/config/provider/Baichuan.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Baichuan",
|
||||
"list": []
|
||||
}
|
||||
147
packages/service/core/ai/config/provider/ChatGLM.json
Normal file
147
packages/service/core/ai/config/provider/ChatGLM.json
Normal 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
93
packages/service/core/ai/config/provider/Claude.json
Normal 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
48
packages/service/core/ai/config/provider/DeepSeek.json
Normal 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
195
packages/service/core/ai/config/provider/Doubao.json
Normal 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": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "Doubao-pro-4k",
|
||||
"name": "Doubao-pro-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-pro-32k",
|
||||
"name": "Doubao-pro-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-pro-128k",
|
||||
"name": "Doubao-pro-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-pro-32k",
|
||||
"name": "Doubao-vision-pro-32k",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 32000,
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"model": "Doubao-embedding-large",
|
||||
"name": "Doubao-embedding-large",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 4096,
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "Doubao-embedding",
|
||||
"name": "Doubao-embedding",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 4096,
|
||||
"type": "embedding"
|
||||
}
|
||||
]
|
||||
}
|
||||
107
packages/service/core/ai/config/provider/Ernie.json
Normal file
107
packages/service/core/ai/config/provider/Ernie.json
Normal file
@ -0,0 +1,107 @@
|
||||
{
|
||||
"provider": "Ernie",
|
||||
"list": [
|
||||
{
|
||||
"model": "ERNIE-4.0-8K",
|
||||
"name": "ERNIE-4.0-8K",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 2048,
|
||||
"quoteMaxToken": 5000,
|
||||
"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": "ERNIE-4.0-Turbo-8K",
|
||||
"name": "ERNIE-4.0-Turbo-8K",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 2048,
|
||||
"quoteMaxToken": 5000,
|
||||
"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": "ERNIE-Lite-8K",
|
||||
"name": "ERNIE-lite-8k",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 2048,
|
||||
"quoteMaxToken": 6000,
|
||||
"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": "ERNIE-Speed-128K",
|
||||
"name": "ERNIE-Speed-128K",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4096,
|
||||
"quoteMaxToken": 120000,
|
||||
"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": "Embedding-V1",
|
||||
"name": "Embedding-V1",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 1000,
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "tao-8k",
|
||||
"name": "tao-8k",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"type": "embedding"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/FishAudio.json
Normal file
4
packages/service/core/ai/config/provider/FishAudio.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "FishAudio",
|
||||
"list": []
|
||||
}
|
||||
144
packages/service/core/ai/config/provider/Gemini.json
Normal file
144
packages/service/core/ai/config/provider/Gemini.json
Normal file
@ -0,0 +1,144 @@
|
||||
{
|
||||
"provider": "Gemini",
|
||||
"list": [
|
||||
{
|
||||
"model": "gemini-1.5-flash",
|
||||
"name": "gemini-1.5-flash",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gemini-1.5-pro",
|
||||
"name": "gemini-1.5-pro",
|
||||
"maxContext": 2000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gemini-2.0-flash-exp",
|
||||
"name": "gemini-2.0-flash-exp",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gemini-2.0-flash-thinking-exp-1219",
|
||||
"name": "gemini-2.0-flash-thinking-exp-1219",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gemini-2.0-flash-thinking-exp-01-21",
|
||||
"name": "gemini-2.0-flash-thinking-exp-01-21",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gemini-exp-1206",
|
||||
"name": "gemini-exp-1206",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 120000,
|
||||
"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": "text-embedding-004",
|
||||
"name": "text-embedding-004",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 2000,
|
||||
"type": "embedding"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/Grok.json
Normal file
4
packages/service/core/ai/config/provider/Grok.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Grok",
|
||||
"list": []
|
||||
}
|
||||
47
packages/service/core/ai/config/provider/Groq.json
Normal file
47
packages/service/core/ai/config/provider/Groq.json
Normal file
@ -0,0 +1,47 @@
|
||||
{
|
||||
"provider": "Groq",
|
||||
"list": [
|
||||
{
|
||||
"model": "llama-3.1-8b-instant",
|
||||
"name": "Groq-llama-3.1-8b-instant",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "llama-3.3-70b-versatile",
|
||||
"name": "Groq-llama-3.3-70b-versatile",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"type": "llm"
|
||||
}
|
||||
]
|
||||
}
|
||||
166
packages/service/core/ai/config/provider/Hunyuan.json
Normal file
166
packages/service/core/ai/config/provider/Hunyuan.json
Normal file
@ -0,0 +1,166 @@
|
||||
{
|
||||
"provider": "Hunyuan",
|
||||
"list": [
|
||||
{
|
||||
"model": "hunyuan-large",
|
||||
"name": "hunyuan-large",
|
||||
"maxContext": 28000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 20000,
|
||||
"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": "hunyuan-lite",
|
||||
"name": "hunyuan-lite",
|
||||
"maxContext": 250000,
|
||||
"maxResponse": 6000,
|
||||
"quoteMaxToken": 100000,
|
||||
"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": "hunyuan-pro",
|
||||
"name": "hunyuan-pro",
|
||||
"maxContext": 28000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 28000,
|
||||
"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": "hunyuan-standard",
|
||||
"name": "hunyuan-standard",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 2000,
|
||||
"quoteMaxToken": 20000,
|
||||
"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": "hunyuan-turbo-vision",
|
||||
"name": "hunyuan-turbo-vision",
|
||||
"maxContext": 6000,
|
||||
"maxResponse": 2000,
|
||||
"quoteMaxToken": 6000,
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"model": "hunyuan-turbo",
|
||||
"name": "hunyuan-turbo",
|
||||
"maxContext": 28000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 20000,
|
||||
"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": "hunyuan-vision",
|
||||
"name": "hunyuan-vision",
|
||||
"maxContext": 6000,
|
||||
"maxResponse": 2000,
|
||||
"quoteMaxToken": 4000,
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"model": "hunyuan-embedding",
|
||||
"name": "hunyuan-embedding",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 1024,
|
||||
"type": "embedding"
|
||||
}
|
||||
]
|
||||
}
|
||||
49
packages/service/core/ai/config/provider/Intern.json
Normal file
49
packages/service/core/ai/config/provider/Intern.json
Normal file
@ -0,0 +1,49 @@
|
||||
{
|
||||
"provider": "Intern",
|
||||
"list": [
|
||||
{
|
||||
"model": "internlm2-pro-chat",
|
||||
"name": "internlm2-pro-chat",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 8000,
|
||||
"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": "internlm3-8b-instruct",
|
||||
"name": "internlm3-8b-instruct",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 8000,
|
||||
"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"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/Meta.json
Normal file
4
packages/service/core/ai/config/provider/Meta.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Meta",
|
||||
"list": []
|
||||
}
|
||||
240
packages/service/core/ai/config/provider/MiniMax.json
Normal file
240
packages/service/core/ai/config/provider/MiniMax.json
Normal file
@ -0,0 +1,240 @@
|
||||
{
|
||||
"provider": "MiniMax",
|
||||
"list": [
|
||||
{
|
||||
"model": "MiniMax-Text-01",
|
||||
"name": "MiniMax-Text-01",
|
||||
"maxContext": 1000000,
|
||||
"maxResponse": 1000000,
|
||||
"quoteMaxToken": 100000,
|
||||
"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": "abab6.5s-chat",
|
||||
"name": "MiniMax-abab6.5s",
|
||||
"maxContext": 245000,
|
||||
"maxResponse": 10000,
|
||||
"quoteMaxToken": 240000,
|
||||
"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": "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"
|
||||
}
|
||||
]
|
||||
}
|
||||
93
packages/service/core/ai/config/provider/MistralAI.json
Normal file
93
packages/service/core/ai/config/provider/MistralAI.json
Normal file
@ -0,0 +1,93 @@
|
||||
{
|
||||
"provider": "MistralAI",
|
||||
"list": [
|
||||
{
|
||||
"model": "ministral-3b-latest",
|
||||
"name": "Ministral-3b-latest",
|
||||
"maxContext": 130000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "ministral-8b-latest",
|
||||
"name": "Ministral-8b-latest",
|
||||
"maxContext": 130000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "mistral-large-latest",
|
||||
"name": "Mistral-large-latest",
|
||||
"maxContext": 130000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "mistral-small-latest",
|
||||
"name": "Mistral-small-latest",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 32000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/Moka.json
Normal file
4
packages/service/core/ai/config/provider/Moka.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Moka",
|
||||
"list": []
|
||||
}
|
||||
71
packages/service/core/ai/config/provider/Moonshot.json
Normal file
71
packages/service/core/ai/config/provider/Moonshot.json
Normal file
@ -0,0 +1,71 @@
|
||||
{
|
||||
"provider": "Moonshot",
|
||||
"list": [
|
||||
{
|
||||
"model": "moonshot-v1-8k",
|
||||
"name": "moonshot-v1-8k",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 6000,
|
||||
"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": "moonshot-v1-32k",
|
||||
"name": "moonshot-v1-32k",
|
||||
"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": "moonshot-v1-128k",
|
||||
"name": "moonshot-v1-128k",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 60000,
|
||||
"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"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/Ollama.json
Normal file
4
packages/service/core/ai/config/provider/Ollama.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Ollama",
|
||||
"list": []
|
||||
}
|
||||
252
packages/service/core/ai/config/provider/OpenAI.json
Normal file
252
packages/service/core/ai/config/provider/OpenAI.json
Normal file
@ -0,0 +1,252 @@
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"list": [
|
||||
{
|
||||
"model": "gpt-4o-mini",
|
||||
"name": "GPT-4o-mini",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 16000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": true,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gpt-4o",
|
||||
"name": "GPT-4o",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": true,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "o3-mini",
|
||||
"name": "o3-mini",
|
||||
"maxContext": 200000,
|
||||
"maxResponse": 100000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": null,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {
|
||||
"stream": false
|
||||
},
|
||||
"fieldMap": {
|
||||
"max_tokens": "max_completion_tokens"
|
||||
},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "o1-mini",
|
||||
"name": "o1-mini",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": null,
|
||||
"vision": false,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {
|
||||
"stream": false
|
||||
},
|
||||
"fieldMap": {
|
||||
"max_tokens": "max_completion_tokens"
|
||||
},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "o1",
|
||||
"name": "o1",
|
||||
"maxContext": 195000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": null,
|
||||
"vision": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {
|
||||
"stream": false
|
||||
},
|
||||
"fieldMap": {
|
||||
"max_tokens": "max_completion_tokens"
|
||||
},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "o1-preview",
|
||||
"name": "o1-preview",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 120000,
|
||||
"maxTemperature": null,
|
||||
"vision": false,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {
|
||||
"stream": false
|
||||
},
|
||||
"fieldMap": {
|
||||
"max_tokens": "max_completion_tokens"
|
||||
},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"name": "gpt-3.5-turbo",
|
||||
"maxContext": 16000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 13000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": false,
|
||||
"toolChoice": true,
|
||||
"functionCall": true,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "gpt-4-turbo",
|
||||
"name": "gpt-4-turbo",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 60000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": true,
|
||||
"functionCall": true,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "text-embedding-3-large",
|
||||
"name": "text-embedding-3-large",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"defaultConfig": {
|
||||
"dimensions": 1024
|
||||
},
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "text-embedding-3-small",
|
||||
"name": "text-embedding-3-small",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "text-embedding-ada-002",
|
||||
"name": "text-embedding-ada-002",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "tts-1",
|
||||
"name": "TTS1",
|
||||
"voices": [
|
||||
{
|
||||
"label": "Alloy",
|
||||
"value": "alloy"
|
||||
},
|
||||
{
|
||||
"label": "Echo",
|
||||
"value": "echo"
|
||||
},
|
||||
{
|
||||
"label": "Fable",
|
||||
"value": "fable"
|
||||
},
|
||||
{
|
||||
"label": "Onyx",
|
||||
"value": "onyx"
|
||||
},
|
||||
{
|
||||
"label": "Nova",
|
||||
"value": "nova"
|
||||
},
|
||||
{
|
||||
"label": "Shimmer",
|
||||
"value": "shimmer"
|
||||
}
|
||||
],
|
||||
"type": "tts"
|
||||
},
|
||||
{
|
||||
"model": "whisper-1",
|
||||
"name": "whisper-1",
|
||||
"type": "stt"
|
||||
}
|
||||
]
|
||||
}
|
||||
4
packages/service/core/ai/config/provider/Other.json
Normal file
4
packages/service/core/ai/config/provider/Other.json
Normal file
@ -0,0 +1,4 @@
|
||||
{
|
||||
"provider": "Other",
|
||||
"list": []
|
||||
}
|
||||
223
packages/service/core/ai/config/provider/Qwen.json
Normal file
223
packages/service/core/ai/config/provider/Qwen.json
Normal file
@ -0,0 +1,223 @@
|
||||
{
|
||||
"provider": "Qwen",
|
||||
"list": [
|
||||
{
|
||||
"model": "qwen-turbo",
|
||||
"name": "Qwen-turbo",
|
||||
"maxContext": 128000,
|
||||
"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": "qwen-plus",
|
||||
"name": "Qwen-plus",
|
||||
"maxContext": 64000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 60000,
|
||||
"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": "qwen-vl-plus",
|
||||
"name": "qwen-vl-plus",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 2000,
|
||||
"quoteMaxToken": 20000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "qwen-max",
|
||||
"name": "Qwen-max",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 6000,
|
||||
"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": "qwen-vl-max",
|
||||
"name": "qwen-vl-max",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 2000,
|
||||
"quoteMaxToken": 20000,
|
||||
"maxTemperature": 1.2,
|
||||
"vision": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"defaultSystemChatPrompt": "",
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"customCQPrompt": "",
|
||||
"usedInExtractFields": true,
|
||||
"usedInQueryExtension": true,
|
||||
"customExtractPrompt": "",
|
||||
"usedInToolCall": true,
|
||||
"defaultConfig": {},
|
||||
"fieldMap": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "qwen-coder-turbo",
|
||||
"name": "qwen-coder-turbo",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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": "qwen2.5-7b-instruct",
|
||||
"name": "qwen2.5-7b-instruct",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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": "qwen2.5-14b-instruct",
|
||||
"name": "qwen2.5-14b-instruct",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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": "qwen2.5-32b-instruct",
|
||||
"name": "qwen2.5-32b-instruct",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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": "qwen2.5-72b-instruct",
|
||||
"name": "Qwen2.5-72B-instruct",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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"
|
||||
}
|
||||
]
|
||||
}
|
||||
204
packages/service/core/ai/config/provider/Siliconflow.json
Normal file
204
packages/service/core/ai/config/provider/Siliconflow.json
Normal file
@ -0,0 +1,204 @@
|
||||
{
|
||||
"provider": "Siliconflow",
|
||||
"list": [
|
||||
{
|
||||
"model": "Qwen/Qwen2.5-72B-Instruct",
|
||||
"name": "Qwen/Qwen2.5-72B-Instruct",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 50000,
|
||||
"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": "Qwen/Qwen2-VL-72B-Instruct",
|
||||
"name": "Qwen/Qwen2-VL-72B-Instruct",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 32000,
|
||||
"maxTemperature": 1,
|
||||
"censor": false,
|
||||
"vision": true,
|
||||
"datasetProcess": false,
|
||||
"usedInClassify": false,
|
||||
"usedInExtractFields": false,
|
||||
"usedInToolCall": false,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"defaultConfig": {},
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "deepseek-ai/DeepSeek-V2.5",
|
||||
"name": "deepseek-ai/DeepSeek-V2.5",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 32000,
|
||||
"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": "BAAI/bge-m3",
|
||||
"name": "BAAI/bge-m3",
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"type": "embedding"
|
||||
},
|
||||
{
|
||||
"model": "FunAudioLLM/CosyVoice2-0.5B",
|
||||
"name": "FunAudioLLM/CosyVoice2-0.5B",
|
||||
"voices": [
|
||||
{
|
||||
"label": "alex",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:alex"
|
||||
},
|
||||
{
|
||||
"label": "anna",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:anna"
|
||||
},
|
||||
{
|
||||
"label": "bella",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:bella"
|
||||
},
|
||||
{
|
||||
"label": "benjamin",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:benjamin"
|
||||
},
|
||||
{
|
||||
"label": "charles",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:charles"
|
||||
},
|
||||
{
|
||||
"label": "claire",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:claire"
|
||||
},
|
||||
{
|
||||
"label": "david",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:david"
|
||||
},
|
||||
{
|
||||
"label": "diana",
|
||||
"value": "FunAudioLLM/CosyVoice2-0.5B:diana"
|
||||
}
|
||||
],
|
||||
"type": "tts"
|
||||
},
|
||||
{
|
||||
"model": "RVC-Boss/GPT-SoVITS",
|
||||
"name": "RVC-Boss/GPT-SoVITS",
|
||||
"voices": [
|
||||
{
|
||||
"label": "alex",
|
||||
"value": "RVC-Boss/GPT-SoVITS:alex"
|
||||
},
|
||||
{
|
||||
"label": "anna",
|
||||
"value": "RVC-Boss/GPT-SoVITS:anna"
|
||||
},
|
||||
{
|
||||
"label": "bella",
|
||||
"value": "RVC-Boss/GPT-SoVITS:bella"
|
||||
},
|
||||
{
|
||||
"label": "benjamin",
|
||||
"value": "RVC-Boss/GPT-SoVITS:benjamin"
|
||||
},
|
||||
{
|
||||
"label": "charles",
|
||||
"value": "RVC-Boss/GPT-SoVITS:charles"
|
||||
},
|
||||
{
|
||||
"label": "claire",
|
||||
"value": "RVC-Boss/GPT-SoVITS:claire"
|
||||
},
|
||||
{
|
||||
"label": "david",
|
||||
"value": "RVC-Boss/GPT-SoVITS:david"
|
||||
},
|
||||
{
|
||||
"label": "diana",
|
||||
"value": "RVC-Boss/GPT-SoVITS:diana"
|
||||
}
|
||||
],
|
||||
"type": "tts"
|
||||
},
|
||||
{
|
||||
"model": "fishaudio/fish-speech-1.5",
|
||||
"name": "fish-speech-1.5",
|
||||
"voices": [
|
||||
{
|
||||
"label": "alex",
|
||||
"value": "fishaudio/fish-speech-1.5:alex"
|
||||
},
|
||||
{
|
||||
"label": "anna",
|
||||
"value": "fishaudio/fish-speech-1.5:anna"
|
||||
},
|
||||
{
|
||||
"label": "bella",
|
||||
"value": "fishaudio/fish-speech-1.5:bella"
|
||||
},
|
||||
{
|
||||
"label": "benjamin",
|
||||
"value": "fishaudio/fish-speech-1.5:benjamin"
|
||||
},
|
||||
{
|
||||
"label": "charles",
|
||||
"value": "fishaudio/fish-speech-1.5:charles"
|
||||
},
|
||||
{
|
||||
"label": "claire",
|
||||
"value": "fishaudio/fish-speech-1.5:claire"
|
||||
},
|
||||
{
|
||||
"label": "david",
|
||||
"value": "fishaudio/fish-speech-1.5:david"
|
||||
},
|
||||
{
|
||||
"label": "diana",
|
||||
"value": "fishaudio/fish-speech-1.5:diana"
|
||||
}
|
||||
],
|
||||
"type": "tts"
|
||||
},
|
||||
{
|
||||
"model": "FunAudioLLM/SenseVoiceSmall",
|
||||
"name": "FunAudioLLM/SenseVoiceSmall",
|
||||
"type": "stt"
|
||||
},
|
||||
{
|
||||
"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
129
packages/service/core/ai/config/provider/SparkDesk.json
Normal file
@ -0,0 +1,129 @@
|
||||
{
|
||||
"provider": "SparkDesk",
|
||||
"list": [
|
||||
{
|
||||
"model": "lite",
|
||||
"name": "SparkDesk-lite",
|
||||
"maxContext": 32000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 32000,
|
||||
"maxTemperature": 1,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "generalv3",
|
||||
"name": "SparkDesk-Pro",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 8000,
|
||||
"maxTemperature": 1,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "pro-128k",
|
||||
"name": "SparkDesk-Pro-128k",
|
||||
"maxContext": 128000,
|
||||
"maxResponse": 4000,
|
||||
"quoteMaxToken": 128000,
|
||||
"maxTemperature": 1,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"toolChoice": false,
|
||||
"functionCall": false,
|
||||
"customCQPrompt": "",
|
||||
"customExtractPrompt": "",
|
||||
"defaultSystemChatPrompt": "",
|
||||
"type": "llm"
|
||||
},
|
||||
{
|
||||
"model": "generalv3.5",
|
||||
"name": "SparkDesk-max",
|
||||
"maxContext": 8000,
|
||||
"maxResponse": 8000,
|
||||
"quoteMaxToken": 8000,
|
||||
"maxTemperature": 1,
|
||||
"vision": false,
|
||||
"datasetProcess": true,
|
||||
"usedInClassify": true,
|
||||
"usedInExtractFields": true,
|
||||
"usedInToolCall": true,
|
||||
"usedInQueryExtension": true,
|
||||
"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
308
packages/service/core/ai/config/provider/StepFun.json
Normal 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
49
packages/service/core/ai/config/provider/Yi.json
Normal 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"
|
||||
}
|
||||
]
|
||||
}
|
||||
@ -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
21
packages/service/core/ai/config/schema.ts
Normal 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
|
||||
);
|
||||
@ -1,6 +0,0 @@
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"model": "whisper-1",
|
||||
"name": "whisper-1",
|
||||
"charsPointsPrice": 0
|
||||
}
|
||||
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Reference in New Issue
Block a user