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Commit 42b2046f by Archer Committed by GitHub
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4.8.21 feature (#3720) 

* agent search demo

* edit form force close image select

* feat: llm params and doubao1.5

* perf: model error tip

* fix: template register path

* package
parent bb82b515
Showing with 892 additions and 103 deletions
docSite/content/zh-cn/docs/development/docker.md
......@@ -11,7 +11,7 @@ weight: 707
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
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
......@@ -211,6 +211,8 @@ docker restart oneapi
### 6. 配置模型
务必先配置至少一组模型，否则系统无法正常使用。
[点击查看模型配置教程](/docs/development/modelConfig/intro/)
## FAQ
......
docSite/content/zh-cn/docs/development/faq.md
......@@ -130,7 +130,7 @@ OneAPI 的 API Key 配置错误，需要修改`OPENAI_API_KEY`环境变量，并
## 四、常见模型问题
### 如何检查模型问题
### 如何检查模型可用性问题
1. 私有部署模型，先确认部署的模型是否正常。
2. 通过 CURL 请求，直接测试上游模型是否正常运行（云端模型或私有模型均进行测试）
......@@ -403,3 +403,7 @@ curl --location --request POST 'https://oneapi.xxxx/v1/chat/completions' \
"tool_choice": "auto"
}'
```
### 向量检索得分大于 1
由于模型没有归一化导致的。目前仅支持归一化的模型。
\ No newline at end of file
docSite/content/zh-cn/docs/development/sealos.md
......@@ -60,6 +60,10 @@ FastGPT 使用了 one-api 项目来管理模型池，其可以兼容 OpenAI 、A
### 3. 配置模型
### 4. 配置模型
务必先配置至少一组模型，否则系统无法正常使用。
[点击查看模型配置教程](/docs/development/modelConfig/intro/)
## 收费
......
docSite/content/zh-cn/docs/development/upgrading/4821.md 0 → 100644
---
title: 'V4.8.21(进行中)'
description: 'FastGPT V4.8.21 更新说明'
icon: 'upgrade'
draft: false
toc: true
weight: 804
---
## 完整更新内容
1.
2. 新增 - LLM 模型支持 top_p, response_format, json_schema 参数。
3. 新增 - Doubao1.5 模型预设。
4. 优化 - 模型未配置时错误提示。
5. 修复 - 简易模式，切换到其他非视觉模型时候，会强制关闭图片识别。
6. 修复 - o1,o3 模型，在测试时候字段映射未生效导致报错。
7. 修复 - 公众号对话空指针异常。
\ No newline at end of file
packages/global/core/ai/model.d.ts
......@@ -26,11 +26,16 @@ type BaseModelItemType = {
export type LLMModelItemType = PriceType &
BaseModelItemType & {
type: ModelTypeEnum.llm;
// Model params
maxContext: number;
maxResponse: number;
quoteMaxToken: number;
maxTemperature?: number;
showTopP?: boolean;
responseFormatList?: string[];
showStopSign?: boolean;
censor?: boolean;
vision?: boolean;
reasoning?: boolean;
......
packages/global/core/app/type.d.ts
......@@ -74,13 +74,17 @@ export type AppDetailType = AppSchema & {
export type AppSimpleEditFormType = {
// templateId: string;
aiSettings: {
model: string;
systemPrompt?: string | undefined;
temperature?: number;
maxToken?: number;
isResponseAnswerText: boolean;
[NodeInputKeyEnum.aiModel]: string;
[NodeInputKeyEnum.aiSystemPrompt]?: string | undefined;
[NodeInputKeyEnum.aiChatTemperature]?: number;
[NodeInputKeyEnum.aiChatMaxToken]?: number;
[NodeInputKeyEnum.aiChatIsResponseText]: boolean;
maxHistories: number;
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
[NodeInputKeyEnum.aiChatReasoning]?: boolean; // Is open reasoning mode
[NodeInputKeyEnum.aiChatTopP]?: number;
[NodeInputKeyEnum.aiChatStopSign]?: string;
[NodeInputKeyEnum.aiChatResponseFormat]?: string;
[NodeInputKeyEnum.aiChatJsonSchema]?: string;
};
dataset: {
datasets: SelectedDatasetType;
......@@ -119,6 +123,10 @@ export type SettingAIDataType = {
maxHistories?: number;
[NodeInputKeyEnum.aiChatVision]?: boolean; // Is open vision mode
[NodeInputKeyEnum.aiChatReasoning]?: boolean; // Is open reasoning mode
[NodeInputKeyEnum.aiChatTopP]?: number;
[NodeInputKeyEnum.aiChatStopSign]?: string;
[NodeInputKeyEnum.aiChatResponseFormat]?: string;
[NodeInputKeyEnum.aiChatJsonSchema]?: string;
};
// variable
......
packages/global/core/workflow/constants.ts
......@@ -142,6 +142,10 @@ export enum NodeInputKeyEnum {
aiChatVision = 'aiChatVision',
stringQuoteText = 'stringQuoteText',
aiChatReasoning = 'aiChatReasoning',
aiChatTopP = 'aiChatTopP',
aiChatStopSign = 'aiChatStopSign',
aiChatResponseFormat = 'aiChatResponseFormat',
aiChatJsonSchema = 'aiChatJsonSchema',
// dataset
datasetSelectList = 'datasets',
......
packages/global/core/workflow/runtime/type.d.ts
......@@ -221,6 +221,10 @@ export type AIChatNodeProps = {
[NodeInputKeyEnum.aiChatIsResponseText]: boolean;
[NodeInputKeyEnum.aiChatVision]?: boolean;
[NodeInputKeyEnum.aiChatReasoning]?: boolean;
[NodeInputKeyEnum.aiChatTopP]?: number;
[NodeInputKeyEnum.aiChatStopSign]?: string;
[NodeInputKeyEnum.aiChatResponseFormat]?: string;
[NodeInputKeyEnum.aiChatJsonSchema]?: string;
[NodeInputKeyEnum.aiChatQuoteRole]?: AiChatQuoteRoleType;
[NodeInputKeyEnum.aiChatQuoteTemplate]?: string;
......
packages/global/core/workflow/template/system/aiChat/index.ts
......@@ -63,14 +63,12 @@ export const AiChatModule: FlowNodeTemplateType = {
key: NodeInputKeyEnum.aiChatTemperature,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '',
value: undefined,
valueType: WorkflowIOValueTypeEnum.number
},
{
key: NodeInputKeyEnum.aiChatMaxToken,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '',
value: undefined,
valueType: WorkflowIOValueTypeEnum.number
},
......@@ -98,6 +96,30 @@ export const AiChatModule: FlowNodeTemplateType = {
valueType: WorkflowIOValueTypeEnum.boolean,
value: true
},
{
key: NodeInputKeyEnum.aiChatTopP,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.number
},
{
key: NodeInputKeyEnum.aiChatStopSign,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
{
key: NodeInputKeyEnum.aiChatResponseFormat,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
{
key: NodeInputKeyEnum.aiChatJsonSchema,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
// settings modal ---
{
...Input_Template_System_Prompt,
......@@ -108,7 +130,6 @@ export const AiChatModule: FlowNodeTemplateType = {
Input_Template_History,
Input_Template_Dataset_Quote,
Input_Template_File_Link_Prompt,
{ ...Input_Template_UserChatInput, toolDescription: i18nT('workflow:user_question') }
],
outputs: [
......
packages/global/core/workflow/template/system/tools.ts
......@@ -43,14 +43,12 @@ export const ToolModule: FlowNodeTemplateType = {
key: NodeInputKeyEnum.aiChatTemperature,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '',
value: undefined,
valueType: WorkflowIOValueTypeEnum.number
},
{
key: NodeInputKeyEnum.aiChatMaxToken,
renderTypeList: [FlowNodeInputTypeEnum.hidden], // Set in the pop-up window
label: '',
value: undefined,
valueType: WorkflowIOValueTypeEnum.number
},
{
......@@ -60,6 +58,30 @@ export const ToolModule: FlowNodeTemplateType = {
valueType: WorkflowIOValueTypeEnum.boolean,
value: true
},
{
key: NodeInputKeyEnum.aiChatTopP,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.number
},
{
key: NodeInputKeyEnum.aiChatStopSign,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
{
key: NodeInputKeyEnum.aiChatResponseFormat,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
{
key: NodeInputKeyEnum.aiChatJsonSchema,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string
},
{
...Input_Template_System_Prompt,
......
packages/service/core/ai/config/provider/DeepSeek.json
......@@ -5,7 +5,7 @@
"model": "deepseek-chat",
"name": "Deepseek-chat",
"maxContext": 64000,
"maxResponse": 4096,
"maxResponse": 8000,
"quoteMaxToken": 60000,
"maxTemperature": 1.5,
"vision": false,
......@@ -25,7 +25,7 @@
"model": "deepseek-reasoner",
"name": "Deepseek-reasoner",
"maxContext": 64000,
"maxResponse": 4096,
"maxResponse": 8000,
"quoteMaxToken": 60000,
"maxTemperature": null,
"vision": false,
......
packages/service/core/ai/config/provider/Doubao.json
......@@ -2,6 +2,94 @@
"provider": "Doubao",
"list": [
{
"model": "Doubao-1.5-lite-32k",
"name": "Doubao-1.5-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-1.5-pro-32k",
"name": "Doubao-1.5-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-1.5-pro-256k",
"name": "Doubao-1.5-pro-256k",
"maxContext": 256000,
"maxResponse": 12000,
"quoteMaxToken": 256000,
"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-1.5-vision-pro-32k",
"name": "Doubao-1.5-vision-pro-32k",
"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": "Doubao-lite-4k",
"name": "Doubao-lite-4k",
"maxContext": 4000,
......
packages/service/core/ai/config/provider/OpenAI.json
......@@ -8,6 +8,9 @@
"maxResponse": 16000,
"quoteMaxToken": 60000,
"maxTemperature": 1.2,
"showTopP": true,
"responseFormatList": ["text", "json_object", "json_schema"],
"showStopSign": true,
"vision": true,
"toolChoice": true,
"functionCall": true,
......
packages/service/core/ai/config/utils.ts
......@@ -31,10 +31,12 @@ import { delay } from '@fastgpt/global/common/system/utils';
export const loadSystemModels = async (init = false) => {
const getProviderList = () => {
const currentFileUrl = new URL(import.meta.url);
const modelsPath = path.join(
path.dirname(currentFileUrl.pathname.replace(/^\/+/, '')),
'provider'
const filePath = decodeURIComponent(
process.platform === 'win32'
? currentFileUrl.pathname.substring(1) // Remove leading slash on Windows
: currentFileUrl.pathname
);
const modelsPath = path.join(path.dirname(filePath), 'provider');
return fs.readdirSync(modelsPath) as string[];
};
......@@ -150,6 +152,7 @@ export const loadSystemModels = async (init = false) => {
console.error('Load models error', error);
// @ts-ignore
global.systemModelList = undefined;
return Promise.reject(error);
}
};
......
packages/service/core/ai/utils.ts
......@@ -37,9 +37,14 @@ export const computedTemperature = ({
return temperature;
};
type CompletionsBodyType =
type CompletionsBodyType = (
| ChatCompletionCreateParamsNonStreaming
| ChatCompletionCreateParamsStreaming;
| ChatCompletionCreateParamsStreaming
) & {
response_format?: any;
json_schema?: string;
stop?: string;
};
type InferCompletionsBody<T> = T extends { stream: true }
? ChatCompletionCreateParamsStreaming
: ChatCompletionCreateParamsNonStreaming;
......@@ -53,6 +58,10 @@ export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
return body as InferCompletionsBody<T>;
}
const response_format = body.response_format;
const json_schema = body.json_schema ?? undefined;
const stop = body.stop ?? undefined;
const requestBody: T = {
...body,
temperature:
......@@ -62,7 +71,14 @@ export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
temperature: body.temperature
})
: undefined,
...modelData?.defaultConfig
...modelData?.defaultConfig,
response_format: response_format
? {
type: response_format,
json_schema
}
: undefined,
stop: stop?.split('|')
};
// field map
......
packages/service/core/dataset/search/agent.ts 0 → 100644
import { chats2GPTMessages } from '@fastgpt/global/core/chat/adapt';
import { ChatItemType } from '@fastgpt/global/core/chat/type';
import { DatasetSearchModeEnum } from '@fastgpt/global/core/dataset/constants';
import { getLLMModel } from '../../ai/model';
import { filterGPTMessageByMaxContext } from '../../chat/utils';
import { replaceVariable } from '@fastgpt/global/common/string/tools';
import { createChatCompletion } from '../../ai/config';
import { llmCompletionsBodyFormat } from '../../ai/utils';
import { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
import { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
import { searchDatasetData } from './controller';
type SearchDatasetDataProps = {
queries: string[];
histories: ChatItemType[];
teamId: string;
model: string;
similarity?: number; // min distance
limit: number; // max Token limit
datasetIds: string[];
searchMode?: `${DatasetSearchModeEnum}`;
usingReRank?: boolean;
reRankQuery: string;
/*
{
tags: {
$and: ["str1","str2"],
$or: ["str1","str2",null] null means no tags
},
createTime: {
$gte: 'xx',
$lte: 'xxx'
}
}
*/
collectionFilterMatch?: string;
};
const analyzeQuery = async ({ query, histories }: { query: string; histories: ChatItemType[] }) => {
const modelData = getLLMModel('gpt-4o-mini');
const systemFewShot = `
## 知识背景
FastGPT 是低代码AI应用构建平台，支持通过语义相似度实现精准数据检索。用户正在利用该功能开发数据检索应用。
## 任务目标
基于用户历史对话和知识背景，生成多维度检索方案，确保覆盖核心语义及潜在关联维度。
## 工作流程
1. 问题解构阶段
[意图识别] 提取用户问题的核心实体和关系：
- 显性需求：直接提及的关键词
- 隐性需求：可能涉及的关联概念
[示例] 若问题为"推荐手机"，需考虑价格、品牌、使用场景等维度
2. 完整性校验阶段
[完整性评估] 检查是否缺失核心实体和关系：
- 主语完整
- 多实体关系准确
[维度扩展] 检查是否需要补充：
□ 时间范围 □ 地理限定 □ 比较维度
□ 专业术语 □ 同义词替换 □ 场景参数
3. 检索生成阶段
[组合策略] 生成包含以下要素的查询序列：
① 基础查询（核心关键词）
② 扩展查询（核心+同义词）
③ 场景查询（核心+场景限定词）
④ 逆向查询（相关技术/对比对象）
## 输出规范
格式要求：
1. 每个查询为完整陈述句
2. 包含至少1个核心词+1个扩展维度
3. 按查询范围从宽到窄排序
禁止项：
- 使用问句形式
- 包含解决方案描述
- 超出话题范围的假设
## 执行示例
用户问题："如何优化数据检索速度"
查询内容：
1. FastGPT 数据检索速度优化的常用方法
2. FastGPT 大数据量下的语义检索性能提升方案
3. FastGPT API 响应时间的优化指标
## 任务开始
`.trim();
const filterHistories = await filterGPTMessageByMaxContext({
messages: chats2GPTMessages({ messages: histories, reserveId: false }),
maxContext: modelData.maxContext - 1000
});
const messages = [
{
role: 'system',
content: systemFewShot
},
...filterHistories,
{
role: 'user',
content: query
}
] as any;
const { response: result } = await createChatCompletion({
body: llmCompletionsBodyFormat(
{
stream: false,
model: modelData.model,
temperature: 0.1,
messages
},
modelData
)
});
let answer = result.choices?.[0]?.message?.content || '';
// Extract queries from the answer by line number
const queries = answer
.split('\n')
.map((line) => {
const match = line.match(/^\d+\.\s*(.+)$/);
return match ? match[1].trim() : null;
})
.filter(Boolean) as string[];
if (queries.length === 0) {
return [answer];
}
return queries;
};
const checkQuery = async ({
queries,
histories,
searchResult
}: {
queries: string[];
histories: ChatItemType[];
searchResult: SearchDataResponseItemType[];
}) => {
const modelData = getLLMModel('gpt-4o-mini');
const systemFewShot = `
## 知识背景
FastGPT 是低代码AI应用构建平台，支持通过语义相似度实现精准数据检索。用户正在利用该功能开发数据检索应用。
## 查询结果
${searchResult.map((item) => item.q + item.a).join('---\n---')}
## 任务目标
检查"检索结果"是否覆盖用户的问题，如果无法覆盖用户问题，则再次生成检索方案。
## 工作流程
1. 检查检索结果是否覆盖用户的问题
2. 如果检索结果覆盖用户问题，则直接输出："Done"
3. 如果无法覆盖用户问题，则结合用户问题和检索结果，生成进一步的检索方案，进行深度检索
## 输出规范
1. 每个查询均为完整的查询语句
2. 通过序号来表示多个检索内容
## 输出示例1
Done
## 输出示例2
1. 环界云计算的办公地址
2. 环界云计算的注册地址在哪里
## 任务开始
`.trim();
const filterHistories = await filterGPTMessageByMaxContext({
messages: chats2GPTMessages({ messages: histories, reserveId: false }),
maxContext: modelData.maxContext - 1000
});
const messages = [
{
role: 'system',
content: systemFewShot
},
...filterHistories,
{
role: 'user',
content: queries.join('\n')
}
] as any;
console.log(messages);
const { response: result } = await createChatCompletion({
body: llmCompletionsBodyFormat(
{
stream: false,
model: modelData.model,
temperature: 0.1,
messages
},
modelData
)
});
let answer = result.choices?.[0]?.message?.content || '';
console.log(answer);
if (answer.includes('Done')) {
return [];
}
const nextQueries = answer
.split('\n')
.map((line) => {
const match = line.match(/^\d+\.\s*(.+)$/);
return match ? match[1].trim() : null;
})
.filter(Boolean) as string[];
return nextQueries;
};
export const agentSearchDatasetData = async ({
searchRes = [],
tokens = 0,
...props
}: SearchDatasetDataProps & {
searchRes?: SearchDataResponseItemType[];
tokens?: number;
}) => {
const query = props.queries[0];
const searchResultList: SearchDataResponseItemType[] = [];
let searchQueries: string[] = [];
// 1. agent 分析问题
searchQueries = await analyzeQuery({ query, histories: props.histories });
// 2. 检索内容 + 检查
let retryTimes = 3;
while (true) {
retryTimes--;
if (retryTimes < 0) break;
console.log(searchQueries, '--');
const { searchRes: searchRes2, tokens: tokens2 } = await searchDatasetData({
...props,
queries: searchQueries
});
// console.log(searchRes2.map((item) => item.q));
// deduplicate and merge search results
const uniqueResults = searchRes2.filter((item) => {
return !searchResultList.some((existingItem) => existingItem.id === item.id);
});
searchResultList.push(...uniqueResults);
if (uniqueResults.length === 0) break;
const checkResult = await checkQuery({
queries: searchQueries,
histories: props.histories,
searchResult: searchRes2
});
if (checkResult.length > 0) {
searchQueries = checkResult;
} else {
break;
}
}
console.log(searchResultList.length);
return {
searchRes: searchResultList,
tokens: 0,
usingSimilarityFilter: false,
usingReRank: false
};
};
packages/service/core/dataset/search/controller.ts
......@@ -23,8 +23,10 @@ import json5 from 'json5';
import { MongoDatasetCollectionTags } from '../tag/schema';
import { readFromSecondary } from '../../../common/mongo/utils';
import { MongoDatasetDataText } from '../data/dataTextSchema';
import { ChatItemType } from '@fastgpt/global/core/chat/type';
type SearchDatasetDataProps = {
histories?: ChatItemType[];
teamId: string;
model: string;
similarity?: number; // min distance
......
packages/service/core/workflow/dispatch/agent/runTool/functionCall.ts
......@@ -46,7 +46,15 @@ export const runToolWithFunctionCall = async (
externalProvider,
stream,
workflowStreamResponse,
params: { temperature, maxToken, aiChatVision }
params: {
temperature,
maxToken,
aiChatVision,
aiChatTopP,
aiChatStopSign,
aiChatResponseFormat,
aiChatJsonSchema
}
} = workflowProps;
// Interactive
......@@ -204,12 +212,18 @@ export const runToolWithFunctionCall = async (
const requestBody = llmCompletionsBodyFormat(
{
model: toolModel.model,
temperature,
max_tokens,
stream,
messages: requestMessages,
functions,
function_call: 'auto'
function_call: 'auto',
temperature,
max_tokens,
top_p: aiChatTopP,
stop: aiChatStopSign,
response_format: aiChatResponseFormat,
json_schema: aiChatJsonSchema
},
toolModel
);
......
packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts
......@@ -54,7 +54,15 @@ export const runToolWithPromptCall = async (
externalProvider,
stream,
workflowStreamResponse,
params: { temperature, maxToken, aiChatVision }
params: {
temperature,
maxToken,
aiChatVision,
aiChatTopP,
aiChatStopSign,
aiChatResponseFormat,
aiChatJsonSchema
}
} = workflowProps;
if (interactiveEntryToolParams) {
......@@ -215,10 +223,14 @@ export const runToolWithPromptCall = async (
const requestBody = llmCompletionsBodyFormat(
{
model: toolModel.model,
stream,
messages: requestMessages,
temperature,
max_tokens,
stream,
messages: requestMessages
top_p: aiChatTopP,
stop: aiChatStopSign,
response_format: aiChatResponseFormat,
json_schema: aiChatJsonSchema
},
toolModel
);
......
packages/service/core/workflow/dispatch/agent/runTool/toolChoice.ts
......@@ -93,7 +93,15 @@ export const runToolWithToolChoice = async (
stream,
externalProvider,
workflowStreamResponse,
params: { temperature, maxToken, aiChatVision }
params: {
temperature,
maxToken,
aiChatVision,
aiChatTopP,
aiChatStopSign,
aiChatResponseFormat,
aiChatJsonSchema
}
} = workflowProps;
if (maxRunToolTimes <= 0 && response) {
......@@ -263,12 +271,16 @@ export const runToolWithToolChoice = async (
const requestBody = llmCompletionsBodyFormat(
{
model: toolModel.model,
temperature,
max_tokens,
stream,
messages: requestMessages,
tools,
tool_choice: 'auto'
tool_choice: 'auto',
temperature,
max_tokens,
top_p: aiChatTopP,
stop: aiChatStopSign,
response_format: aiChatResponseFormat,
json_schema: aiChatJsonSchema
},
toolModel
);
......
packages/service/core/workflow/dispatch/agent/runTool/type.d.ts
......@@ -16,12 +16,16 @@ export type DispatchToolModuleProps = ModuleDispatchProps<{
[NodeInputKeyEnum.history]?: ChatItemType[];
[NodeInputKeyEnum.userChatInput]: string;
[NodeInputKeyEnum.fileUrlList]?: string[];
[NodeInputKeyEnum.aiModel]: string;
[NodeInputKeyEnum.aiSystemPrompt]: string;
[NodeInputKeyEnum.aiChatTemperature]: number;
[NodeInputKeyEnum.aiChatMaxToken]: number;
[NodeInputKeyEnum.aiChatVision]?: boolean;
[NodeInputKeyEnum.fileUrlList]?: string[];
[NodeInputKeyEnum.aiChatTopP]?: number;
[NodeInputKeyEnum.aiChatStopSign]?: string;
[NodeInputKeyEnum.aiChatResponseFormat]?: string;
[NodeInputKeyEnum.aiChatJsonSchema]?: string;
}> & {
messages: ChatCompletionMessageParam[];
toolNodes: ToolNodeItemType[];
......
packages/service/core/workflow/dispatch/chat/oneapi.ts
......@@ -89,6 +89,11 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
quotePrompt,
aiChatVision,
aiChatReasoning = true,
aiChatTopP,
aiChatStopSign,
aiChatResponseFormat,
aiChatJsonSchema,
fileUrlList: fileLinks, // node quote file links
stringQuoteText //abandon
}
......@@ -100,6 +105,7 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
return Promise.reject('The chat model is undefined, you need to select a chat model.');
}
aiChatVision = modelConstantsData.vision && aiChatVision;
stream = stream && isResponseAnswerText;
aiChatReasoning = !!aiChatReasoning && !!modelConstantsData.reasoning;
......@@ -160,17 +166,21 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
const requestMessages = await loadRequestMessages({
messages: filterMessages,
useVision: modelConstantsData.vision && aiChatVision,
useVision: aiChatVision,
origin: requestOrigin
});
const requestBody = llmCompletionsBodyFormat(
{
model: modelConstantsData.model,
stream,
messages: requestMessages,
temperature,
max_tokens,
stream,
messages: requestMessages
top_p: aiChatTopP,
stop: aiChatStopSign,
response_format: aiChatResponseFormat as any,
json_schema: aiChatJsonSchema
},
modelConstantsData
);
......@@ -259,11 +269,7 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
outputTokens: outputTokens,
query: `${userChatInput}`,
maxToken: max_tokens,
historyPreview: getHistoryPreview(
chatCompleteMessages,
10000,
modelConstantsData.vision && aiChatVision
),
historyPreview: getHistoryPreview(chatCompleteMessages, 10000, aiChatVision),
contextTotalLen: completeMessages.length
},
[DispatchNodeResponseKeyEnum.nodeDispatchUsages]: [
......
packages/service/worker/utils.ts
......@@ -120,7 +120,7 @@ export class WorkerPool<Props = Record<string, any>, Response = any> {
run(data: Props) {
// watch memory
addLog.debug(`${this.name} worker queueLength: ${this.workerQueue.length}`);
// addLog.debug(`${this.name} worker queueLength: ${this.workerQueue.length}`);
return new Promise<Response>((resolve, reject) => {
/*
......
packages/templates/register.ts
......@@ -7,7 +7,12 @@ import { AppTemplateSchemaType } from '@fastgpt/global/core/app/type';
const getTemplateNameList = () => {
const currentFileUrl = new URL(import.meta.url);
const templatesPath = path.join(path.dirname(currentFileUrl.pathname), 'src');
const filePath = decodeURIComponent(
process.platform === 'win32'
? currentFileUrl.pathname.substring(1) // Remove leading slash on Windows
: currentFileUrl.pathname
);
const templatesPath = path.join(path.dirname(filePath), 'src');
return fs.readdirSync(templatesPath) as string[];
};
......
packages/web/components/common/MySlider/InputSlider.tsx
......@@ -27,7 +27,7 @@ const InputSlider = ({
valLen * 0.8 + min,
valLen * 0.985 + min
];
}, []);
}, [max, min]);
return (
<HStack zIndex={10} spacing={3}>
......
packages/web/i18n/en/account.json
......@@ -55,6 +55,9 @@
"model.request_auth_tip": "When making a request to a custom request address, carry the request header: Authorization: Bearer xxx to make the request.",
"model.request_url": "Custom url",
"model.request_url_tip": "If you fill in this value, you will initiate a request directly without passing. \nYou need to follow the API format of Openai and fill in the full request address, such as\n\nLLM: {Host}}/v1/Chat/Completions\n\nEmbedding: {host}}/v1/embeddings\n\nSTT: {Host}/v1/Audio/Transcriptions\n\nTTS: {Host}}/v1/Audio/Speech\n\nRERARARARARARARANK: {Host}}/v1/RERARARARARARARARARARANK",
"model.response_format": "Response format",
"model.show_stop_sign": "Display stop sequence parameters",
"model.show_top_p": "Show Top-p parameters",
"model.test_model": "Model testing",
"model.tool_choice": "Tool choice",
"model.tool_choice_tag": "ToolCall",
......
packages/web/i18n/en/app.json
......@@ -110,12 +110,16 @@
"publish_success": "Publish Successful",
"question_guide_tip": "After the conversation, 3 guiding questions will be generated for you.",
"reasoning_response": "Output thinking",
"response_format": "Response format",
"saved_success": "Saved successfully! \nTo use this version externally, click Save and Publish",
"search_app": "Search apps",
"setting_app": "Workflow",
"setting_plugin": "Workflow",
"show_top_p_tip": "An alternative method of temperature sampling, called Nucleus sampling, the model considers the results of tokens with TOP_P probability mass quality. \nTherefore, 0.1 means that only tokens containing the highest probability quality are considered. \nThe default is 1.",
"simple_tool_tips": "This plugin contains special inputs and is not currently supported for invocation by simple applications.",
"source_updateTime": "Update time",
"stop_sign": "Stop",
"stop_sign_placeholder": "Multiple serial numbers are separated by |, for example: aaa|stop",
"stream_response": "Stream",
"stream_response_tip": "Turning this switch off forces the model to use non-streaming mode and will not output content directly. \nIn the output of the AI ​​reply, the content output by this model can be obtained for secondary processing.",
"temperature": "Temperature",
......
packages/web/i18n/en/login.json
{
"Chinese_ip_tip": "It is detected that you are a mainland Chinese IP, click to jump to visit the mainland China version.",
"Login": "Login",
"agree": "agree",
"cookies_tip": " This website uses cookies to provide a better service experience. By continuing to use the site, you agree to our Cookie Policy.",
"forget_password": "Find Password",
"login_failed": "Login failed",
"login_success": "Login successful",
"model_not_config": "It is detected that the system has not configured the model, please configure the model before using it",
"no_remind": "Don't remind again",
"password_condition": "Password maximum 60 characters",
"password_tip": "Password must be at least 6 characters long and contain at least two combinations: numbers, letters, or special characters",
"policy_tip": "By using this service, you agree to our",
"privacy": "Privacy Policy",
"privacy_policy": "Privacy Policy",
"redirect": "Jump",
"register": "Register",
"root_password_placeholder": "The root user password is the value of the environment variable DEFAULT_ROOT_PSW",
"terms": "Terms",
"use_root_login": "Log in as root user",
"agree": "agree",
"cookies_tip": " This website uses cookies to provide a better service experience. By continuing to use the site, you agree to our Cookie Policy.",
"privacy_policy": "Privacy Policy"
"use_root_login": "Log in as root user"
}
packages/web/i18n/zh-CN/account.json
......@@ -55,6 +55,9 @@
"model.request_auth_tip": "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",
"model.request_url": "自定义请求地址",
"model.request_url_tip": "如果填写该值，则会直接向该地址发起请求，不经过 OneAPI。需要遵循 OpenAI 的 API格式，并填写完整请求地址，例如：\nLLM: {{host}}/v1/chat/completions\nEmbedding: {{host}}/v1/embeddings\nSTT: {{host}}/v1/audio/transcriptions\nTTS: {{host}}/v1/audio/speech\nRerank: {{host}}/v1/rerank",
"model.response_format": "响应格式",
"model.show_stop_sign": "展示停止序列参数",
"model.show_top_p": "展示 Top-p 参数",
"model.test_model": "模型测试",
"model.tool_choice": "支持工具调用",
"model.tool_choice_tag": "工具调用",
......
packages/web/i18n/zh-CN/app.json
......@@ -110,12 +110,16 @@
"publish_success": "发布成功",
"question_guide_tip": "对话结束后，会为你生成 3 个引导性问题。",
"reasoning_response": "输出思考",
"response_format": "回复格式",
"saved_success": "保存成功！如需在外部使用该版本，请点击“保存并发布”",
"search_app": "搜索应用",
"setting_app": "应用配置",
"setting_plugin": "插件配置",
"show_top_p_tip": "用温度采样的替代方法，称为Nucleus采样，该模型考虑了具有TOP_P概率质量质量的令牌的结果。因此，0.1表示仅考虑包含最高概率质量的令牌。默认为 1。",
"simple_tool_tips": "该插件含有特殊输入，暂不支持被简易应用调用",
"source_updateTime": "更新时间",
"stop_sign": "停止序列",
"stop_sign_placeholder": "多个序列号通过 | 隔开，例如：aaa|stop",
"stream_response": "流输出",
"stream_response_tip": "关闭该开关，可以强制模型使用非流模式，并且不会直接进行内容输出。可以在 AI 回复的输出中，获取本次模型输出的内容进行二次处理。",
"temperature": "温度",
......
packages/web/i18n/zh-CN/login.json
......@@ -6,6 +6,7 @@
"forget_password": "忘记密码?",
"login_failed": "登录异常",
"login_success": "登录成功",
"model_not_config": "检测到系统未配置模型，请先配置模型后再使用",
"no_remind": "不再提醒",
"password_condition": "密码最多 60 位",
"password_tip": "密码至少 6 位，且至少包含两种组合：数字、字母或特殊字符",
......
packages/web/i18n/zh-Hant/account.json
......@@ -54,6 +54,9 @@
"model.request_auth_tip": "向自訂請求地址發起請求時候，攜帶請求頭：Authorization: Bearer xxx 進行請求",
"model.request_url": "自訂請求地址",
"model.request_url_tip": "如果填寫該值，則會直接向該地址發起請求，不經過 OneAPI。\n需要遵循 OpenAI 的 API格式，並填寫完整請求地址，例如：\n\nLLM: {{host}}/v1/chat/completions\n\nEmbedding: {{host}}/v1/embeddings\n\nSTT: {{host}}/v1/audio/transcriptions\n\nTTS: {{host}}/v1/audio/speech\n\nRerank: {{host}}/v1/rerank",
"model.response_format": "響應格式",
"model.show_stop_sign": "展示停止序列參數",
"model.show_top_p": "展示 Top-p 參數",
"model.test_model": "模型測試",
"model.tool_choice": "支援工具調用",
"model.tool_choice_tag": "工具調用",
......
packages/web/i18n/zh-Hant/app.json
......@@ -110,12 +110,16 @@
"publish_success": "發布成功",
"question_guide_tip": "對話結束後，會為你產生 3 個引導性問題。",
"reasoning_response": "輸出思考",
"response_format": "回复格式",
"saved_success": "保存成功！\n如需在外部使用該版本，請點擊“儲存並發布”",
"search_app": "搜尋應用程式",
"setting_app": "應用程式設定",
"setting_plugin": "外掛設定",
"show_top_p_tip": "用溫度採樣的替代方法，稱為Nucleus採樣，該模型考慮了具有TOP_P概率質量質量的令牌的結果。\n因此，0.1表示僅考慮包含最高概率質量的令牌。\n默認為 1。",
"simple_tool_tips": "該插件含有特殊輸入，暫不支持被簡易應用調用",
"source_updateTime": "更新時間",
"stop_sign": "停止序列",
"stop_sign_placeholder": "多個序列號通過 | 隔開，例如：aaa|stop",
"stream_response": "流輸出",
"stream_response_tip": "關閉該開關​​，可以強制模型使用非流模式，並且不會直接進行內容輸出。\n可在 AI 回覆的輸出中，取得本次模型輸出的內容進行二次處理。",
"temperature": "溫度",
......
packages/web/i18n/zh-Hant/login.json
......@@ -6,6 +6,7 @@
"forget_password": "忘記密碼？",
"login_failed": "登入失敗",
"login_success": "登入成功",
"model_not_config": "檢測到系統未配置模型，請先配置模型後再使用",
"no_remind": "不再提醒",
"password_condition": "密碼最多 60 個字元",
"password_tip": "密碼至少 6 位，且至少包含兩種組合：數字、字母或特殊字符",
......
projects/app/package.json
{
"name": "app",
"version": "4.8.20",
"version": "4.8.21",
"private": false,
"scripts": {
"dev": "next dev",
......
projects/app/src/components/core/ai/AISettingModal/index.tsx
......@@ -18,7 +18,8 @@ import {
Thead,
Tr,
Table,
FlexProps
FlexProps,
Input
} from '@chakra-ui/react';
import { useSystemStore } from '@/web/common/system/useSystemStore';
import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
......@@ -31,13 +32,15 @@ import { getWebLLMModel } from '@/web/common/system/utils';
import MyIcon from '@fastgpt/web/components/common/Icon';
import dynamic from 'next/dynamic';
import InputSlider from '@fastgpt/web/components/common/MySlider/InputSlider';
import MySelect from '@fastgpt/web/components/common/MySelect';
import JsonEditor from '@fastgpt/web/components/common/Textarea/JsonEditor';
const ModelPriceModal = dynamic(() =>
import('@/components/core/ai/ModelTable').then((mod) => mod.ModelPriceModal)
);
const FlexItemStyles: FlexProps = {
mt: 5,
mt: 4,
alignItems: 'center',
h: '35px'
};
......@@ -68,7 +71,7 @@ const AIChatSettingsModal = ({
const [refresh, setRefresh] = useState(false);
const { feConfigs } = useSystemStore();
const { handleSubmit, getValues, setValue, watch } = useForm({
const { handleSubmit, getValues, setValue, watch, register } = useForm({
defaultValues: defaultData
});
const model = watch('model');
......@@ -88,6 +91,17 @@ const AIChatSettingsModal = ({
const llmSupportTemperature = typeof selectedModel?.maxTemperature === 'number';
const llmSupportReasoning = !!selectedModel?.reasoning;
const topP = watch(NodeInputKeyEnum.aiChatTopP);
const llmSupportTopP = !!selectedModel?.showTopP;
const stopSign = watch(NodeInputKeyEnum.aiChatStopSign);
const llmSupportStopSign = !!selectedModel?.showStopSign;
const responseFormat = watch(NodeInputKeyEnum.aiChatResponseFormat);
const jsonSchema = watch(NodeInputKeyEnum.aiChatJsonSchema);
const llmSupportResponseFormat =
!!selectedModel?.responseFormatList && selectedModel?.responseFormatList.length > 0;
const tokenLimit = useMemo(() => {
return selectedModel?.maxResponse || 4096;
}, [selectedModel?.maxResponse]);
......@@ -146,7 +160,7 @@ const AIChatSettingsModal = ({
</Flex>
<TableContainer
my={5}
my={4}
bg={'primary.50'}
borderRadius={'lg'}
borderWidth={'1px'}
......@@ -291,35 +305,120 @@ const AIChatSettingsModal = ({
</Box>
</Flex>
)}
{llmSupportReasoning && (
<Flex {...FlexItemStyles} h={'25px'}>
{llmSupportTopP && (
<Flex {...FlexItemStyles}>
<Box {...LabelStyles}>
<Flex alignItems={'center'}>{t('app:reasoning_response')}</Flex>
<Flex alignItems={'center'}>
<Box mr={0.5}>Top_p</Box>
<QuestionTip label={t('app:show_top_p_tip')} />
</Flex>
<Switch
isChecked={reasoning || false}
isChecked={topP !== undefined}
size={'sm'}
onChange={(e) => {
const value = e.target.checked;
setValue(NodeInputKeyEnum.aiChatReasoning, value);
setValue(NodeInputKeyEnum.aiChatTopP, e.target.checked ? 1 : undefined);
}}
/>
</Box>
<Box flex={'1 0 0'}>
<InputSlider
min={0}
max={1}
step={0.1}
value={topP}
isDisabled={topP === undefined}
onChange={(e) => {
setValue(NodeInputKeyEnum.aiChatTopP, e);
setRefresh(!refresh);
}}
/>
</Box>
</Flex>
)}
{showResponseAnswerText && (
<Flex {...FlexItemStyles} h={'25px'}>
{llmSupportStopSign && (
<Flex {...FlexItemStyles}>
<Box {...LabelStyles}>
<Flex alignItems={'center'}>
{t('app:stream_response')}
<QuestionTip ml={1} label={t('app:stream_response_tip')}></QuestionTip>
<Box mr={0.5}>{t('app:stop_sign')}</Box>
</Flex>
<Switch
isChecked={getValues(NodeInputKeyEnum.aiChatIsResponseText)}
isChecked={stopSign !== undefined}
size={'sm'}
onChange={(e) => {
setValue(NodeInputKeyEnum.aiChatStopSign, e.target.checked ? '' : undefined);
}}
/>
</Box>
<Box flex={'1 0 0'}>
<Input
isDisabled={stopSign === undefined}
size={'sm'}
{...register(NodeInputKeyEnum.aiChatStopSign)}
placeholder={t('app:stop_sign_placeholder')}
bg={'myGray.25'}
/>
</Box>
</Flex>
)}
{llmSupportResponseFormat && selectedModel?.responseFormatList && (
<Flex {...FlexItemStyles}>
<Box {...LabelStyles}>
<Flex alignItems={'center'}>{t('app:response_format')}</Flex>
<Switch
isChecked={responseFormat !== undefined}
size={'sm'}
onChange={(e) => {
setValue(
NodeInputKeyEnum.aiChatResponseFormat,
e.target.checked ? selectedModel?.responseFormatList?.[0] : undefined
);
}}
/>
</Box>
<Box flex={'1 0 0'}>
<MySelect<string>
isDisabled={responseFormat === undefined}
size={'sm'}
bg={'myGray.25'}
list={selectedModel.responseFormatList.map((item) => ({
value: item,
label: item
}))}
value={responseFormat}
onchange={(e) => {
setValue(NodeInputKeyEnum.aiChatResponseFormat, e);
}}
/>
</Box>
</Flex>
)}
{/* Json schema */}
{responseFormat === 'json_schema' && (
<Flex {...FlexItemStyles} h="auto">
<Box {...LabelStyles}>
<Flex alignItems={'center'}>JSON Schema</Flex>
</Box>
<Box flex={'1 0 0'}>
<JsonEditor
value={jsonSchema || ''}
onChange={(e) => {
setValue(NodeInputKeyEnum.aiChatJsonSchema, e);
}}
bg={'myGray.25'}
/>
</Box>
</Flex>
)}
{llmSupportReasoning && (
<Flex {...FlexItemStyles} h={'25px'}>
<Box {...LabelStyles}>
<Flex alignItems={'center'}>{t('app:reasoning_response')}</Flex>
<Switch
isChecked={reasoning || false}
size={'sm'}
onChange={(e) => {
const value = e.target.checked;
setValue(NodeInputKeyEnum.aiChatIsResponseText, value);
setRefresh((state) => !state);
setValue(NodeInputKeyEnum.aiChatReasoning, value);
}}
/>
</Box>
......@@ -349,6 +448,25 @@ const AIChatSettingsModal = ({
</Box>
</Flex>
)}
{showResponseAnswerText && (
<Flex {...FlexItemStyles} h={'25px'}>
<Box {...LabelStyles}>
<Flex alignItems={'center'}>
{t('app:stream_response')}
<QuestionTip ml={1} label={t('app:stream_response_tip')}></QuestionTip>
</Flex>
<Switch
isChecked={getValues(NodeInputKeyEnum.aiChatIsResponseText)}
size={'sm'}
onChange={(e) => {
const value = e.target.checked;
setValue(NodeInputKeyEnum.aiChatIsResponseText, value);
setRefresh((state) => !state);
}}
/>
</Box>
</Flex>
)}
</ModalBody>
<ModalFooter>
<Button variant={'whiteBase'} onClick={onClose}>
......
projects/app/src/global/support/api/userRes.d.ts
import type { UserTypee } from '@fastgpt/global/support/user/type.d';
import type { UserType } from '@fastgpt/global/support/user/type.d';
import type { PromotionRecordSchema } from '@fastgpt/global/support/activity/type.d';
export interface ResLogin {
user: UserType;
......
projects/app/src/pageComponents/account/model/ModelConfigTable.tsx
......@@ -767,6 +767,51 @@ const ModelEditModal = ({
</Flex>
</Td>
</Tr>
<Tr>
<Td>
<HStack spacing={1}>
<Box>{t('account:model.show_top_p')}</Box>
</HStack>
</Td>
<Td textAlign={'right'}>
<Flex justifyContent={'flex-end'}>
<Switch {...register('showTopP')} />
</Flex>
</Td>
</Tr>
<Tr>
<Td>
<HStack spacing={1}>
<Box>{t('account:model.show_stop_sign')}</Box>
</HStack>
</Td>
<Td textAlign={'right'}>
<Flex justifyContent={'flex-end'}>
<Switch {...register('showStopSign')} />
</Flex>
</Td>
</Tr>
<Tr>
<Td>{t('account:model.response_format')}</Td>
<Td textAlign={'right'}>
<JsonEditor
value={JSON.stringify(getValues('responseFormatList'), null, 2)}
resize
onChange={(e) => {
if (!e) {
setValue('responseFormatList', []);
return;
}
try {
setValue('responseFormatList', JSON.parse(e));
} catch (error) {
console.error(error);
}
}}
{...InputStyles}
/>
</Td>
</Tr>
</>
)}
{isEmbeddingModel && (
......
projects/app/src/pageComponents/app/detail/SimpleApp/EditForm.tsx
import React, { useMemo, useTransition } from 'react';
import React, { useEffect, useMemo, useTransition } from 'react';
import {
Box,
Flex,
......@@ -116,6 +116,25 @@ const EditForm = ({
const tokenLimit = useMemo(() => {
return selectedModel?.quoteMaxToken || 3000;
}, [selectedModel?.quoteMaxToken]);
// Force close image select when model not support vision
useEffect(() => {
if (!selectedModel.vision) {
setAppForm((state) => ({
...state,
chatConfig: {
...state.chatConfig,
...(state.chatConfig.fileSelectConfig
? {
fileSelectConfig: {
...state.chatConfig.fileSelectConfig,
canSelectImg: false
}
}
: {})
}
}));
}
}, [selectedModel]);
return (
<>
......@@ -139,24 +158,18 @@ const EditForm = ({
temperature: appForm.aiSettings.temperature,
maxToken: appForm.aiSettings.maxToken,
maxHistories: appForm.aiSettings.maxHistories,
aiChatReasoning: appForm.aiSettings.aiChatReasoning ?? true
aiChatReasoning: appForm.aiSettings.aiChatReasoning ?? true,
aiChatTopP: appForm.aiSettings.aiChatTopP,
aiChatStopSign: appForm.aiSettings.aiChatStopSign,
aiChatResponseFormat: appForm.aiSettings.aiChatResponseFormat,
aiChatJsonSchema: appForm.aiSettings.aiChatJsonSchema
}}
onChange={({
model,
temperature,
maxToken,
maxHistories,
aiChatReasoning = false
}) => {
onChange={({ maxHistories = 6, aiChatReasoning = true, ...data }) => {
setAppForm((state) => ({
...state,
aiSettings: {
...state.aiSettings,
model,
temperature,
maxToken,
maxHistories: maxHistories ?? 6,
aiChatReasoning
...data
}
}));
}}
......
projects/app/src/pageComponents/app/detail/WorkflowComponents/Flow/nodes/render/RenderInput/templates/SettingLLMModel.tsx
......@@ -40,7 +40,14 @@ const SelectAiModelRender = ({ item, inputs = [], nodeId }: RenderInputProps) =>
aiChatVision:
inputs.find((input) => input.key === NodeInputKeyEnum.aiChatVision)?.value ?? true,
aiChatReasoning:
inputs.find((input) => input.key === NodeInputKeyEnum.aiChatReasoning)?.value ?? true
inputs.find((input) => input.key === NodeInputKeyEnum.aiChatReasoning)?.value ?? true,
aiChatTopP: inputs.find((input) => input.key === NodeInputKeyEnum.aiChatTopP)?.value,
aiChatStopSign: inputs.find((input) => input.key === NodeInputKeyEnum.aiChatStopSign)?.value,
aiChatResponseFormat: inputs.find(
(input) => input.key === NodeInputKeyEnum.aiChatResponseFormat
)?.value,
aiChatJsonSchema: inputs.find((input) => input.key === NodeInputKeyEnum.aiChatJsonSchema)
?.value
}),
[inputs]
);
......
projects/app/src/pages/_error.tsx
......@@ -28,12 +28,12 @@ function Error() {
return (
<Box whiteSpace={'pre-wrap'}>
{`出现未捕获的异常。
1. 私有部署用户，90%由于配置文件不正确导致。
1. 私有部署用户，90%由于配置文件不正确/模型未启用导致。
2. 部分系统不兼容相关API。大部分是苹果的safari 浏览器导致，可以尝试更换 chrome。
3. 请关闭浏览器翻译功能，部分翻译导致页面崩溃。
排除3后，打开控制台的 console 查看具体报错信息。
如果提示 xxx undefined 的话，就是配置文件有错误。
如果提示 xxx undefined 的话，就是配置文件有错误，或者是缺少可用模型，请确保系统内每个系列模型至少有一个可用。
`}
</Box>
);
......
projects/app/src/pages/api/core/ai/model/test.ts
......@@ -16,6 +16,7 @@ import { reRankRecall } from '@fastgpt/service/core/ai/rerank';
import { aiTranscriptions } from '@fastgpt/service/core/ai/audio/transcriptions';
import { isProduction } from '@fastgpt/global/common/system/constants';
import * as fs from 'fs';
import { llmCompletionsBodyFormat } from '@fastgpt/service/core/ai/utils';
export type testQuery = { model: string };
......@@ -57,22 +58,23 @@ export default NextAPI(handler);
const testLLMModel = async (model: LLMModelItemType) => {
const ai = getAIApi({});
const response = await ai.chat.completions.create(
const requestBody = llmCompletionsBodyFormat(
{
model: model.model,
messages: [{ role: 'user', content: 'hi' }],
stream: false,
max_tokens: 10
},
{
...(model.requestUrl ? { path: model.requestUrl } : {}),
headers: model.requestAuth
? {
Authorization: `Bearer ${model.requestAuth}`
}
: undefined
}
model
);
const response = await ai.chat.completions.create(requestBody, {
...(model.requestUrl ? { path: model.requestUrl } : {}),
headers: model.requestAuth
? {
Authorization: `Bearer ${model.requestAuth}`
}
: undefined
});
const responseText = response.choices?.[0]?.message?.content;
......
projects/app/src/pages/api/core/dataset/searchTest.ts
......@@ -15,6 +15,7 @@ import { NextAPI } from '@/service/middleware/entry';
import { ReadPermissionVal } from '@fastgpt/global/support/permission/constant';
import { CommonErrEnum } from '@fastgpt/global/common/error/code/common';
import { useIPFrequencyLimit } from '@fastgpt/service/common/middle/reqFrequencyLimit';
import { agentSearchDatasetData } from '@fastgpt/service/core/dataset/search/agent';
async function handler(req: NextApiRequest) {
const {
......@@ -59,6 +60,7 @@ async function handler(req: NextApiRequest) {
});
const { searchRes, tokens, ...result } = await searchDatasetData({
histories: [],
teamId,
reRankQuery: rewriteQuery,
queries: concatQueries,
......
projects/app/src/pages/login/index.tsx
......@@ -29,6 +29,7 @@ import { GET } from '@/web/common/api/request';
import { getDocPath } from '@/web/common/system/doc';
import { getWebReqUrl } from '@fastgpt/web/common/system/utils';
import LoginForm from '@/pageComponents/login/LoginForm/LoginForm';
import { useToast } from '@fastgpt/web/hooks/useToast';
const RegisterForm = dynamic(() => import('@/pageComponents/login/RegisterForm'));
const ForgetPasswordForm = dynamic(() => import('@/pageComponents/login/ForgetPasswordForm'));
......@@ -41,12 +42,13 @@ const Login = ({ ChineseRedirectUrl }: { ChineseRedirectUrl: string }) => {
const router = useRouter();
const { t } = useTranslation();
const { lastRoute = '' } = router.query as { lastRoute: string };
const { feConfigs } = useSystemStore();
const { feConfigs, llmModelList } = useSystemStore();
const [pageType, setPageType] = useState<`${LoginPageTypeEnum}`>(LoginPageTypeEnum.passwordLogin);
const { setUserInfo } = useUserStore();
const { setLastChatAppId } = useChatStore();
const { isOpen, onOpen, onClose } = useDisclosure();
const { isPc } = useSystem();
const { toast } = useToast();
const {
isOpen: isOpenCookiesDrawer,
......@@ -61,6 +63,16 @@ const Login = ({ ChineseRedirectUrl }: { ChineseRedirectUrl: string }) => {
(res: ResLogin) => {
setUserInfo(res.user);
// Check that the model is available
if (res.user.username === 'root' && llmModelList?.length === 0) {
toast({
status: 'warning',
title: t('login:model_not_config')
});
router.push('/account/model');
return;
}
const decodeLastRoute = decodeURIComponent(lastRoute);
// 检查是否是当前的 route
const navigateTo =
......
projects/app/src/web/core/app/utils.ts
......@@ -106,14 +106,14 @@ export function form2AppWorkflow(
version: AiChatModule.version,
inputs: [
{
key: 'model',
key: NodeInputKeyEnum.aiModel,
renderTypeList: [FlowNodeInputTypeEnum.settingLLMModel, FlowNodeInputTypeEnum.reference],
label: '',
valueType: WorkflowIOValueTypeEnum.string,
value: formData.aiSettings.model
},
{
key: 'temperature',
key: NodeInputKeyEnum.aiChatTemperature,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
value: formData.aiSettings.temperature,
......@@ -123,7 +123,7 @@ export function form2AppWorkflow(
step: 1
},
{
key: 'maxToken',
key: NodeInputKeyEnum.aiChatMaxToken,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
value: formData.aiSettings.maxToken,
......@@ -133,7 +133,7 @@ export function form2AppWorkflow(
step: 50
},
{
key: 'isResponseAnswerText',
key: NodeInputKeyEnum.aiChatIsResponseText,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
value: true,
......@@ -143,7 +143,7 @@ export function form2AppWorkflow(
AiChatQuoteTemplate,
AiChatQuotePrompt,
{
key: 'systemPrompt',
key: NodeInputKeyEnum.aiSystemPrompt,
renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
max: 3000,
valueType: WorkflowIOValueTypeEnum.string,
......@@ -153,7 +153,7 @@ export function form2AppWorkflow(
value: formData.aiSettings.systemPrompt
},
{
key: 'history',
key: NodeInputKeyEnum.history,
renderTypeList: [FlowNodeInputTypeEnum.numberInput, FlowNodeInputTypeEnum.reference],
valueType: WorkflowIOValueTypeEnum.chatHistory,
label: 'core.module.input.label.chat history',
......@@ -163,16 +163,16 @@ export function form2AppWorkflow(
value: formData.aiSettings.maxHistories
},
{
key: 'userChatInput',
key: NodeInputKeyEnum.userChatInput,
renderTypeList: [FlowNodeInputTypeEnum.reference, FlowNodeInputTypeEnum.textarea],
valueType: WorkflowIOValueTypeEnum.string,
label: i18nT('common:core.module.input.label.user question'),
required: true,
toolDescription: i18nT('common:core.module.input.label.user question'),
value: [workflowStartNodeId, 'userChatInput']
value: [workflowStartNodeId, NodeInputKeyEnum.userChatInput]
},
{
key: 'quoteQA',
key: NodeInputKeyEnum.aiChatDatasetQuote,
renderTypeList: [FlowNodeInputTypeEnum.settingDatasetQuotePrompt],
label: '',
debugLabel: i18nT('common:core.module.Dataset quote.label'),
......@@ -197,6 +197,34 @@ export function form2AppWorkflow(
label: '',
valueType: WorkflowIOValueTypeEnum.boolean,
value: formData.aiSettings.aiChatReasoning
},
{
key: NodeInputKeyEnum.aiChatTopP,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.number,
value: formData.aiSettings.aiChatTopP
},
{
key: NodeInputKeyEnum.aiChatStopSign,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string,
value: formData.aiSettings.aiChatStopSign
},
{
key: NodeInputKeyEnum.aiChatResponseFormat,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string,
value: formData.aiSettings.aiChatResponseFormat
},
{
key: NodeInputKeyEnum.aiChatJsonSchema,
renderTypeList: [FlowNodeInputTypeEnum.hidden],
label: '',
valueType: WorkflowIOValueTypeEnum.string,
value: formData.aiSettings.aiChatJsonSchema
}
],
outputs: AiChatModule.outputs
......
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