V4.8.14 dev (#3234)

* feat: rewrite chat context (#3176)

* feat: add app auto execute (#3115)

* feat: add app auto execute

* auto exec configtion

* chatting animation

* change icon

* fix

* fix

* fix link

* feat: add chat context to all chatbox

* perf: loading ui

---------

Co-authored-by: heheer <heheer@sealos.io>

* app auto exec (#3179)

* add chat records loaded state (#3184)

* perf: chat store reset storage (#3186)

* perf: chat store reset storage

* perf: auto exec code

* chore: workflow ui (#3175)

* chore: workflow ui

* fix

* change icon color config

* change popover to mymenu

* 4.8.14 test (#3189)

* update doc

* fix: token check

* perf: icon button

* update doc

* feat: share page support configuration Whether to allow the original view (#3194)

* update doc

* perf: fix index (#3206)

* perf: i18n

* perf: Add service entry (#3226)

* 4.8.14 test (#3228)

* fix: ai log

* fix: text splitter

* fix: reference unselect & user form description & simple to advance (#3229)

* fix: reference unselect & user form description & simple to advance

* change abort position

* perf

* perf: code (#3232)

* perf: code

* update doc

* fix: create btn permission (#3233)

* update doc

* fix: refresh chatbox listener

* perf: check invalid reference

* perf: check invalid reference

* update doc

* fix: ui props

---------

Co-authored-by: heheer <heheer@sealos.io>

packages/service/core/ai/config.ts

@@ -6,6 +6,7 @@ import {
 } from '@fastgpt/global/core/ai/type';
 import { getErrText } from '@fastgpt/global/common/error/utils';
 import { addLog } from '../../common/system/log';
+import { i18nT } from '../../../web/i18n/utils';
 
 export const openaiBaseUrl = process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1';
 
@@ -62,6 +63,7 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
 }): Promise<{
   response: InferResponseType<T>;
   isStreamResponse: boolean;
+  getEmptyResponseTip: () => string;
 }> => {
   try {
     const formatTimeout = timeout ? timeout : body.stream ? 60000 : 600000;
@@ -76,9 +78,21 @@ export const createChatCompletion = async <T extends CompletionsBodyType>({
       response !== null &&
       ('iterator' in response || 'controller' in response);
 
+    const getEmptyResponseTip = () => {
+      addLog.warn(`LLM response empty`, {
+        baseUrl: userKey?.baseUrl,
+        requestBody: body
+      });
+      if (userKey?.baseUrl) {
+        return `您的 OpenAI key 没有响应: ${JSON.stringify(body)}`;
+      }
+      return i18nT('chat:LLM_model_response_empty');
+    };
+
     return {
       response: response as InferResponseType<T>,
-      isStreamResponse
+      isStreamResponse,
+      getEmptyResponseTip
     };
   } catch (error) {
     addLog.error(`LLM response error`, error);

packages/service/core/app/schema.ts

@@ -17,7 +17,8 @@ export const chatConfigType = {
   scheduledTriggerConfig: Object,
   chatInputGuide: Object,
   fileSelectConfig: Object,
-  instruction: String
+  instruction: String,
+  autoExecute: Object
 };
 
 // schema

packages/service/core/chat/chatItemSchema.ts

@@ -46,6 +46,10 @@ const ChatItemSchema = new Schema({
     type: Date,
     default: () => new Date()
   },
+  hideInUI: {
+    type: Boolean,
+    default: false
+  },
   obj: {
     // chat role
     type: String,

packages/service/core/chat/saveChat.ts

@@ -1,15 +1,6 @@
-import type {
-  AIChatItemType,
-  ChatItemType,
-  UserChatItemType
-} from '@fastgpt/global/core/chat/type.d';
-import axios from 'axios';
+import type { AIChatItemType, UserChatItemType } from '@fastgpt/global/core/chat/type.d';
 import { MongoApp } from '../app/schema';
-import {
-  ChatItemValueTypeEnum,
-  ChatRoleEnum,
-  ChatSourceEnum
-} from '@fastgpt/global/core/chat/constants';
+import { ChatItemValueTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
 import { MongoChatItem } from './chatItemSchema';
 import { MongoChat } from './chatSchema';
 import { addLog } from '../../common/system/log';
@@ -133,21 +124,15 @@ export async function saveChat({
 export const updateInteractiveChat = async ({
   chatId,
   appId,
-  teamId,
-  tmbId,
   userInteractiveVal,
   aiResponse,
-  newVariables,
-  newTitle
+  newVariables
 }: {
   chatId: string;
   appId: string;
-  teamId: string;
-  tmbId: string;
   userInteractiveVal: string;
   aiResponse: AIChatItemType & { dataId?: string };
   newVariables?: Record<string, any>;
-  newTitle: string;
 }) => {
   if (!chatId) return;
 
@@ -232,7 +217,6 @@ export const updateInteractiveChat = async ({
       {
         $set: {
           variables: newVariables,
-          title: newTitle,
           updateTime: new Date()
         }
       },

packages/service/core/dataset/collection/controller.ts

@@ -67,7 +67,7 @@ export async function createOneCollection({
 
         fileId,
         rawLink,
-        externalFileId,
+        ...(externalFileId ? { externalFileId } : {}),
         externalFileUrl,
 
         rawTextLength,

packages/service/core/dataset/collection/schema.ts

@@ -118,7 +118,7 @@ try {
     {
       unique: true,
       partialFilterExpression: {
-        externalFileId: { $exists: true, $ne: '' }
+        externalFileId: { $exists: true }
       }
     }
   );

packages/service/core/dataset/training/controller.ts

@@ -77,7 +77,7 @@ export async function pushDataListToTrainingQueue({
 
     if (trainingMode === TrainingModeEnum.chunk) {
       return {
-        maxToken: vectorModelData.maxToken * 1.3,
+        maxToken: vectorModelData.maxToken * 1.5,
         model: vectorModelData.model,
         weight: vectorModelData.weight
       };
@@ -125,10 +125,7 @@ export async function pushDataListToTrainingQueue({
 
     const text = item.q + item.a;
 
-    // count q token
-    const token = item.q.length;
-
-    if (token > maxToken) {
+    if (text.length > maxToken) {
       filterResult.overToken.push(item);
       return;
     }

packages/service/core/workflow/dispatch/agent/runTool/functionCall.ts

@@ -27,7 +27,6 @@ import { computedMaxToken, llmCompletionsBodyFormat } from '../../../../ai/utils
 import { toolValueTypeList } from '@fastgpt/global/core/workflow/constants';
 import { WorkflowInteractiveResponseType } from '@fastgpt/global/core/workflow/template/system/interactive/type';
 import { ChatItemValueTypeEnum } from '@fastgpt/global/core/chat/constants';
-import { i18nT } from '../../../../../../web/i18n/utils';
 
 type FunctionRunResponseType = {
   toolRunResponse: DispatchFlowResponse;
@@ -216,7 +215,11 @@ export const runToolWithFunctionCall = async (
 
   // console.log(JSON.stringify(requestMessages, null, 2));
   /* Run llm */
-  const { response: aiResponse, isStreamResponse } = await createChatCompletion({
+  const {
+    response: aiResponse,
+    isStreamResponse,
+    getEmptyResponseTip
+  } = await createChatCompletion({
     body: requestBody,
     userKey: user.openaiAccount,
     options: {
@@ -256,6 +259,9 @@ export const runToolWithFunctionCall = async (
       };
     }
   })();
+  if (!answer && functionCalls.length === 0) {
+    return Promise.reject(getEmptyResponseTip());
+  }
 
   // Run the selected tool.
   const toolsRunResponse = (
@@ -549,9 +555,5 @@ async function streamResponse({
     }
   }
 
-  if (!textAnswer && functionCalls.length === 0) {
-    return Promise.reject(i18nT('chat:LLM_model_response_empty'));
-  }
-
   return { answer: textAnswer, functionCalls };
 }

packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts

@@ -29,7 +29,6 @@ import { WorkflowResponseType } from '../../type';
 import { toolValueTypeList } from '@fastgpt/global/core/workflow/constants';
 import { WorkflowInteractiveResponseType } from '@fastgpt/global/core/workflow/template/system/interactive/type';
 import { ChatItemValueTypeEnum } from '@fastgpt/global/core/chat/constants';
-import { i18nT } from '../../../../../../web/i18n/utils';
 
 type FunctionCallCompletion = {
   id: string;
@@ -225,7 +224,11 @@ export const runToolWithPromptCall = async (
 
   // console.log(JSON.stringify(requestMessages, null, 2));
   /* Run llm */
-  const { response: aiResponse, isStreamResponse } = await createChatCompletion({
+  const {
+    response: aiResponse,
+    isStreamResponse,
+    getEmptyResponseTip
+  } = await createChatCompletion({
     body: requestBody,
     userKey: user.openaiAccount,
     options: {
@@ -251,8 +254,11 @@ export const runToolWithPromptCall = async (
       return result.choices?.[0]?.message?.content || '';
     }
   })();
-
   const { answer: replaceAnswer, toolJson } = parseAnswer(answer);
+  if (!answer && !toolJson) {
+    return Promise.reject(getEmptyResponseTip());
+  }
+
   // No tools
   if (!toolJson) {
     if (replaceAnswer === ERROR_TEXT) {
@@ -534,9 +540,6 @@ async function streamResponse({
     }
   }
 
-  if (!textAnswer) {
-    return Promise.reject(i18nT('chat:LLM_model_response_empty'));
-  }
   return { answer: textAnswer.trim() };
 }
 

packages/service/core/workflow/dispatch/agent/runTool/toolChoice.ts

@@ -272,7 +272,11 @@ export const runToolWithToolChoice = async (
   );
   // console.log(JSON.stringify(requestBody, null, 2), '==requestBody');
   /* Run llm */
-  const { response: aiResponse, isStreamResponse } = await createChatCompletion({
+  const {
+    response: aiResponse,
+    isStreamResponse,
+    getEmptyResponseTip
+  } = await createChatCompletion({
     body: requestBody,
     userKey: user.openaiAccount,
     options: {
@@ -336,6 +340,9 @@ export const runToolWithToolChoice = async (
       };
     }
   })();
+  if (!answer && toolCalls.length === 0) {
+    return Promise.reject(getEmptyResponseTip());
+  }
 
   // Run the selected tool by LLM.
   const toolsRunResponse = (
@@ -645,9 +652,5 @@ async function streamResponse({
     }
   }
 
-  if (!textAnswer && toolCalls.length === 0) {
-    return Promise.reject(i18nT('chat:LLM_model_response_empty'));
-  }
-
   return { answer: textAnswer, toolCalls };
 }

packages/service/core/workflow/dispatch/chat/oneapi.ts

@@ -33,15 +33,13 @@ import { getLLMModel, ModelTypeEnum } from '../../../ai/model';
 import type { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
 import { NodeInputKeyEnum, NodeOutputKeyEnum } from '@fastgpt/global/core/workflow/constants';
 import { DispatchNodeResponseKeyEnum } from '@fastgpt/global/core/workflow/runtime/constants';
-import { getHistories } from '../utils';
+import { checkQuoteQAValue, getHistories } from '../utils';
 import { filterSearchResultsByMaxChars } from '../../utils';
 import { getHistoryPreview } from '@fastgpt/global/core/chat/utils';
-import { addLog } from '../../../../common/system/log';
 import { computedMaxToken, llmCompletionsBodyFormat } from '../../../ai/utils';
 import { WorkflowResponseType } from '../type';
 import { formatTime2YMDHM } from '@fastgpt/global/common/string/time';
 import { AiChatQuoteRoleType } from '@fastgpt/global/core/workflow/template/system/aiChat/type';
-import { getErrText } from '@fastgpt/global/common/error/utils';
 import { getFileContentFromLinks, getHistoryFileLinks } from '../tools/readFiles';
 import { parseUrlToFileType } from '@fastgpt/global/common/file/tools';
 import { i18nT } from '../../../../../web/i18n/utils';
@@ -93,6 +91,7 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
   stream = stream && isResponseAnswerText;
 
   const chatHistories = getHistories(history, histories);
+  quoteQA = checkQuoteQAValue(quoteQA);
 
   const modelConstantsData = getLLMModel(model);
   if (!modelConstantsData) {
@@ -169,99 +168,91 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
     modelConstantsData
   );
   // console.log(JSON.stringify(requestBody, null, 2), '===');
-  try {
-    const { response, isStreamResponse } = await createChatCompletion({
-      body: requestBody,
-      userKey: user.openaiAccount,
-      options: {
-        headers: {
-          Accept: 'application/json, text/plain, */*'
-        }
+  const { response, isStreamResponse, getEmptyResponseTip } = await createChatCompletion({
+    body: requestBody,
+    userKey: user.openaiAccount,
+    options: {
+      headers: {
+        Accept: 'application/json, text/plain, */*'
       }
-    });
+    }
+  });
 
-    const { answerText } = await (async () => {
-      if (res && isStreamResponse) {
-        // sse response
-        const { answer } = await streamResponse({
-          res,
-          stream: response,
-          workflowStreamResponse
+  const { answerText } = await (async () => {
+    if (res && isStreamResponse) {
+      // sse response
+      const { answer } = await streamResponse({
+        res,
+        stream: response,
+        workflowStreamResponse
+      });
+
+      return {
+        answerText: answer
+      };
+    } else {
+      const unStreamResponse = response as ChatCompletion;
+      const answer = unStreamResponse.choices?.[0]?.message?.content || '';
+
+      if (stream) {
+        // Some models do not support streaming
+        workflowStreamResponse?.({
+          event: SseResponseEventEnum.fastAnswer,
+          data: textAdaptGptResponse({
+            text: answer
+          })
         });
-
-        if (!answer) {
-          return Promise.reject(i18nT('chat:LLM_model_response_empty'));
-        }
-
-        return {
-          answerText: answer
-        };
-      } else {
-        const unStreamResponse = response as ChatCompletion;
-        const answer = unStreamResponse.choices?.[0]?.message?.content || '';
-
-        if (stream) {
-          // Some models do not support streaming
-          workflowStreamResponse?.({
-            event: SseResponseEventEnum.fastAnswer,
-            data: textAdaptGptResponse({
-              text: answer
-            })
-          });
-        }
-
-        return {
-          answerText: answer
-        };
       }
-    })();
 
-    const completeMessages = requestMessages.concat({
-      role: ChatCompletionRequestMessageRoleEnum.Assistant,
-      content: answerText
-    });
-    const chatCompleteMessages = GPTMessages2Chats(completeMessages);
+      return {
+        answerText: answer
+      };
+    }
+  })();
 
-    const tokens = await countMessagesTokens(chatCompleteMessages);
-    const { totalPoints, modelName } = formatModelChars2Points({
-      model,
+  if (!answerText) {
+    return Promise.reject(getEmptyResponseTip());
+  }
+
+  const completeMessages = requestMessages.concat({
+    role: ChatCompletionRequestMessageRoleEnum.Assistant,
+    content: answerText
+  });
+  const chatCompleteMessages = GPTMessages2Chats(completeMessages);
+
+  const tokens = await countMessagesTokens(chatCompleteMessages);
+  const { totalPoints, modelName } = formatModelChars2Points({
+    model,
+    tokens,
+    modelType: ModelTypeEnum.llm
+  });
+
+  return {
+    answerText,
+    [DispatchNodeResponseKeyEnum.nodeResponse]: {
+      totalPoints: user.openaiAccount?.key ? 0 : totalPoints,
+      model: modelName,
       tokens,
-      modelType: ModelTypeEnum.llm
-    });
-
-    return {
-      answerText,
-      [DispatchNodeResponseKeyEnum.nodeResponse]: {
+      query: `${userChatInput}`,
+      maxToken: max_tokens,
+      historyPreview: getHistoryPreview(
+        chatCompleteMessages,
+        10000,
+        modelConstantsData.vision && aiChatVision
+      ),
+      contextTotalLen: completeMessages.length
+    },
+    [DispatchNodeResponseKeyEnum.nodeDispatchUsages]: [
+      {
+        moduleName: name,
         totalPoints: user.openaiAccount?.key ? 0 : totalPoints,
         model: modelName,
-        tokens,
-        query: `${userChatInput}`,
-        maxToken: max_tokens,
-        historyPreview: getHistoryPreview(
-          chatCompleteMessages,
-          10000,
-          modelConstantsData.vision && aiChatVision
-        ),
-        contextTotalLen: completeMessages.length
-      },
-      [DispatchNodeResponseKeyEnum.nodeDispatchUsages]: [
-        {
-          moduleName: name,
-          totalPoints: user.openaiAccount?.key ? 0 : totalPoints,
-          model: modelName,
-          tokens
-        }
-      ],
-      [DispatchNodeResponseKeyEnum.toolResponses]: answerText,
-      history: chatCompleteMessages
-    };
-  } catch (error) {
-    if (user.openaiAccount?.baseUrl) {
-      return Promise.reject(`您的 OpenAI key 出错了: ${getErrText(error)}`);
-    }
-
-    return Promise.reject(error);
-  }
+        tokens
+      }
+    ],
+    [DispatchNodeResponseKeyEnum.toolResponses]: answerText,
+    history: chatCompleteMessages
+  };
 };
 
 async function filterDatasetQuote({

packages/service/core/workflow/dispatch/tools/http468.ts

@@ -209,7 +209,6 @@ export const dispatchHttp468Request = async (props: HttpRequestProps): Promise<H
   try {
     const { formatResponse, rawResponse } = await (async () => {
       const systemPluginCb = global.systemPluginCb;
-      console.log(systemPluginCb, '-=', httpReqUrl);
       if (systemPluginCb[httpReqUrl]) {
         const pluginResult = await replaceSystemPluginResponse({
           response: await systemPluginCb[httpReqUrl](requestBody),
@@ -395,7 +394,7 @@ async function replaceSystemPluginResponse({
         response[key] = `${ReadFileBaseUrl}/${filename}?token=${await createFileToken({
           bucketName: 'chat',
           teamId,
-          tmbId,
+          uid: tmbId,
           fileId
         })}`;
       } catch (error) {}

packages/service/core/workflow/dispatch/utils.ts

@@ -13,6 +13,7 @@ import { responseWrite } from '../../../common/response';
 import { NextApiResponse } from 'next';
 import { SseResponseEventEnum } from '@fastgpt/global/core/workflow/runtime/constants';
 import { getNanoid } from '@fastgpt/global/common/string/tools';
+import { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
 
 export const getWorkflowResponseWrite = ({
   res,
@@ -87,27 +88,6 @@ export const filterToolNodeIdByEdges = ({
     .map((edge) => edge.target);
 };
 
-// export const checkTheModuleConnectedByTool = (
-//   modules: StoreNodeItemType[],
-//   node: StoreNodeItemType
-// ) => {
-//   let sign = false;
-//   const toolModules = modules.filter((item) => item.flowNodeType === FlowNodeTypeEnum.tools);
-
-//   toolModules.forEach((item) => {
-//     const toolOutput = item.outputs.find(
-//       (output) => output.key === NodeOutputKeyEnum.selectedTools
-//     );
-//     toolOutput?.targets.forEach((target) => {
-//       if (target.moduleId === node.moduleId) {
-//         sign = true;
-//       }
-//     });
-//   });
-
-//   return sign;
-// };
-
 export const getHistories = (history?: ChatItemType[] | number, histories: ChatItemType[] = []) => {
   if (!history) return [];
 
@@ -149,6 +129,13 @@ export const valueTypeFormat = (value: any, type?: WorkflowIOValueTypeEnum) => {
   return value;
 };
 
+export const checkQuoteQAValue = (quoteQA: SearchDataResponseItemType[] = []) => {
+  if (quoteQA.some((item) => !item.q || !item.datasetId)) {
+    return undefined;
+  }
+  return quoteQA;
+};
+
 /* remove system variable */
 export const removeSystemVariable = (variables: Record<string, any>) => {
   const copyVariables = { ...variables };