V4.9.1 feature (#4206)

* fix: remove DefaultTeam (#4037) * fix ：Get application bound knowledge base information logical rewrite (#4057) * fix ：Get application bound knowledge base information logical rewrite * fix ：Get application bound knowledge base information logical rewrite * fix ：Get application bound knowledge base information logical rewrite * fix ：Get application bound knowledge base information logical rewrite * update package * fix: import dataset step error;perf: ai proxy avatar (#4074) * perf: pg config params * perf: ai proxy avatar * fix: import dataset step error * feat: data input ux * perf: app dataset rewite * fix: 文本提取不支持arrayString,arrayNumber等jsonSchema (#4079) * update doc ;perf: model test (#4098) * perf: extract array * update doc * perf: model test * perf: model test * perf: think tag parse (#4102) * chat quote reader (#3912) * init chat quote full text reader * linked structure * dataset data linked * optimize code * fix ts build * test finish * delete log * fix * fix ts * fix ts * remove nextId * initial scroll * fix * fix * perf: chunk read (#4109) * package * perf: chunk read * feat: api dataset support pdf parse;fix: chunk reader auth (#4117) * feat: api dataset support pdf parse * fix: chunk reader auth * feat: invitation link (#3979) * feat: invitation link schema and apis * feat: add invitation link * feat: member status: active, leave, forbidden * fix: expires show hours and minutes * feat: invalid invitation link hint * fix: typo * chore: fix typo & i18n * fix * pref: fe * feat: add ttl index for 30-day-clean-up * perf: invite member code (#4118) * perf: invite member code * fix: ts * fix: model test channel id;fix: quote reader (#4123) * fix: model test channel id * fix: quote reader * fix chat quote reader (#4125) * perf: model test;perf: sidebar trigger (#4127) * fix: import dataset step error;perf: ai proxy avatar (#4074) * perf: pg config params * perf: ai proxy avatar * fix: import dataset step error * feat: data input ux * perf: app dataset rewite * perf: model test * perf: sidebar trigger * lock * update nanoid version * fix: select component ux * fix: ts * fix: vitest * remove test * fix: prompt toolcall ui (#4139) * load log error adapt * fix: prompt toolcall ui * perf: commercial function tip * update package * pref: copy link (#4147) * fix(i18n): namespace (#4143) * hiden dataset source (#4152) * hiden dataset source * perf: reader * chore: move all tests into a single folder (#4160) * fix modal close scroll (#4162) * fix modal close scroll * update refresh * feat: rerank modal select and weight (#4164) * fix loadInitData refresh (#4169) * fix * fix * form input number default & api dataset max token * feat: mix search weight (#4170) * feat: mix search weight * feat: svg render * fix: avatar error remove (#4173) * fix: avatar error remove * fix: index * fix: guide * fix: auth * update package;fix: input data model ui (#4181) * update package * fix: ts * update config * update jieba package * add type sign * fix: input data ui * fix: page title refresh (#4186) * fix: ts * update jieba package * fix: page title refresh * fix: remove member length check when opening invite create modal (#4193) * add env to check internal ip (#4187) * fix: ts * update jieba package * add env to check internal ip * package * fix: jieba * reset package * update config * fix: jieba package * init shell * init version * change team reload * update jieba package (#4200) * update jieba package * package * update package * remove invalid code * action * package (#4201) * package * update package * remove invalid code * package * remove i18n tip (#4202) * doc (#4205) * fix: i18n (#4208) * fix: next config (#4207) * reset package * i18n * update config * i18n * remove log --------- Co-authored-by: Finley Ge <32237950+FinleyGe@users.noreply.github.com> Co-authored-by: gggaaallleee <91131304+gggaaallleee@users.noreply.github.com> Co-authored-by: shilin <39396378+shilin66@users.noreply.github.com> Co-authored-by: heheer <heheer@sealos.io>
2025-07-22 20:37:48 +00:00 · 2025-03-18 14:40:41 +08:00
parent 56793114d8
commit e75d81d05a
316 changed files with 10626 additions and 8464 deletions
--- a/packages/service/core/ai/audio/transcriptions.ts
+++ b/packages/service/core/ai/audio/transcriptions.ts
@@ -6,10 +6,12 @@ import { getSTTModel } from '../model';

 export const aiTranscriptions = async ({
  model,
-  fileStream
+  fileStream,
+  headers
 }: {
  model: string;
  fileStream: fs.ReadStream;
+  headers?: Record<string, string>;
 }) => {
  const data = new FormData();
  data.append('model', model);
@@ -30,7 +32,8 @@ export const aiTranscriptions = async ({
      Authorization: modelData.requestAuth
        ? `Bearer ${modelData.requestAuth}`
        : aiAxiosConfig.authorization,
-      ...data.getHeaders()
+      ...data.getHeaders(),
+      ...headers
    },
    data: data
  });
--- a/packages/service/core/ai/config.ts
+++ b/packages/service/core/ai/config.ts
@@ -76,6 +76,10 @@ export const createChatCompletion = async ({
      timeout: formatTimeout
    });

+    addLog.debug(`Start create chat completion`, {
+      model: body.model
+    });
+
    const response = await ai.chat.completions.create(body, {
      ...options,
      ...(modelConstantsData.requestUrl ? { path: modelConstantsData.requestUrl } : {}),
--- a/packages/service/core/ai/config/provider/Qwen.json
+++ b/packages/service/core/ai/config/provider/Qwen.json
@@ -76,7 +76,7 @@
    {
      "model": "qwen-max",
      "name": "Qwen-max",
-      "maxContext": 8000,
+      "maxContext": 32000,
      "maxResponse": 4000,
      "quoteMaxToken": 6000,
      "maxTemperature": 1,
--- a/packages/service/core/ai/config/utils.ts
+++ b/packages/service/core/ai/config/utils.ts
@@ -8,7 +8,7 @@ import {
  EmbeddingModelItemType,
  TTSModelType,
  STTModelType,
-  ReRankModelItemType
+  RerankModelItemType
 } from '@fastgpt/global/core/ai/model.d';
 import { debounce } from 'lodash';
 import {
@@ -94,7 +94,7 @@ export const loadSystemModels = async (init = false) => {
  global.embeddingModelMap = new Map<string, EmbeddingModelItemType>();
  global.ttsModelMap = new Map<string, TTSModelType>();
  global.sttModelMap = new Map<string, STTModelType>();
-  global.reRankModelMap = new Map<string, ReRankModelItemType>();
+  global.reRankModelMap = new Map<string, RerankModelItemType>();
  // @ts-ignore
  global.systemDefaultModel = {};

--- a/packages/service/core/ai/embedding/index.ts
+++ b/packages/service/core/ai/embedding/index.ts
@@ -8,10 +8,11 @@ type GetVectorProps = {
  model: EmbeddingModelItemType;
  input: string;
  type?: `${EmbeddingTypeEnm}`;
+  headers?: Record<string, string>;
 };

 // text to vector
-export async function getVectorsByText({ model, input, type }: GetVectorProps) {
+export async function getVectorsByText({ model, input, type, headers }: GetVectorProps) {
  if (!input) {
    return Promise.reject({
      code: 500,
@@ -35,13 +36,12 @@ export async function getVectorsByText({ model, input, type }: GetVectorProps) {
        model.requestUrl
          ? {
              path: model.requestUrl,
-              headers: model.requestAuth
-                ? {
-                    Authorization: `Bearer ${model.requestAuth}`
-                  }
-                : undefined
+              headers: {
+                ...(model.requestAuth ? { Authorization: `Bearer ${model.requestAuth}` } : {}),
+                ...headers
+              }
            }
-          : {}
+          : { headers }
      )
      .then(async (res) => {
        if (!res.data) {
--- a/packages/service/core/ai/model.ts
+++ b/packages/service/core/ai/model.ts
@@ -38,7 +38,7 @@ export function getSTTModel(model?: string) {
 }

 export const getDefaultRerankModel = () => global?.systemDefaultModel.rerank!;
-export function getReRankModel(model?: string) {
+export function getRerankModel(model?: string) {
  if (!model) return getDefaultRerankModel();
  return global.reRankModelMap.get(model) || getDefaultRerankModel();
 }
--- a/packages/service/core/ai/rerank/index.ts
+++ b/packages/service/core/ai/rerank/index.ts
@@ -2,7 +2,7 @@ import { addLog } from '../../../common/system/log';
 import { POST } from '../../../common/api/serverRequest';
 import { getDefaultRerankModel } from '../model';
 import { getAxiosConfig } from '../config';
-import { ReRankModelItemType } from '@fastgpt/global/core/ai/model.d';
+import { RerankModelItemType } from '@fastgpt/global/core/ai/model.d';

 type PostReRankResponse = {
  id: string;
@@ -16,11 +16,13 @@ type ReRankCallResult = { id: string; score?: number }[];
 export function reRankRecall({
  model = getDefaultRerankModel(),
  query,
-  documents
+  documents,
+  headers
 }: {
-  model?: ReRankModelItemType;
+  model?: RerankModelItemType;
  query: string;
  documents: { id: string; text: string }[];
+  headers?: Record<string, string>;
 }): Promise<ReRankCallResult> {
  if (!model) {
    return Promise.reject('no rerank model');
@@ -41,7 +43,8 @@ export function reRankRecall({
    },
    {
      headers: {
-        Authorization: model.requestAuth ? `Bearer ${model.requestAuth}` : authorization
+        Authorization: model.requestAuth ? `Bearer ${model.requestAuth}` : authorization,
+        ...headers
      },
      timeout: 30000
    }
--- a/packages/service/core/ai/type.d.ts
+++ b/packages/service/core/ai/type.d.ts
@@ -1,7 +1,7 @@
 import { ModelTypeEnum } from '@fastgpt/global/core/ai/model';
 import {
  STTModelType,
-  ReRankModelItemType,
+  RerankModelItemType,
  TTSModelType,
  EmbeddingModelItemType,
  LLMModelItemType
@@ -18,7 +18,7 @@ export type SystemModelItemType =
  | EmbeddingModelItemType
  | TTSModelType
  | STTModelType
-  | ReRankModelItemType;
+  | RerankModelItemType;

 export type SystemDefaultModelType = {
  [ModelTypeEnum.llm]?: LLMModelItemType;
@@ -28,7 +28,7 @@ export type SystemDefaultModelType = {
  [ModelTypeEnum.embedding]?: EmbeddingModelItemType;
  [ModelTypeEnum.tts]?: TTSModelType;
  [ModelTypeEnum.stt]?: STTModelType;
-  [ModelTypeEnum.rerank]?: ReRankModelItemType;
+  [ModelTypeEnum.rerank]?: RerankModelItemType;
 };

 declare global {
@@ -38,7 +38,7 @@ declare global {
  var embeddingModelMap: Map<string, EmbeddingModelItemType>;
  var ttsModelMap: Map<string, TTSModelType>;
  var sttModelMap: Map<string, STTModelType>;
-  var reRankModelMap: Map<string, ReRankModelItemType>;
+  var reRankModelMap: Map<string, RerankModelItemType>;

  var systemActiveModelList: SystemModelItemType[];
  var systemDefaultModel: SystemDefaultModelType;
--- a/packages/service/core/ai/utils.ts
+++ b/packages/service/core/ai/utils.ts
@@ -132,7 +132,7 @@ export const parseReasoningStreamContent = () => {
  let endTagBuffer = '';

  /* 
-    parseReasoning - 只控制是否主动解析 <think></think>，如果接口已经解析了，仍然会返回 think 内容。
+    parseThinkTag - 只控制是否主动解析 <think></think>，如果接口已经解析了，则不再解析。
  */
  const parsePart = (
    part: {
@@ -143,13 +143,13 @@ export const parseReasoningStreamContent = () => {
        };
      }[];
    },
-    parseReasoning = false
+    parseThinkTag = false
  ): [string, string] => {
    const content = part.choices?.[0]?.delta?.content || '';

    // @ts-ignore
    const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
-    if (reasoningContent || !parseReasoning) {
+    if (reasoningContent || !parseThinkTag) {
      isInThinkTag = false;
      return [reasoningContent, content];
    }
--- a/packages/service/core/app/utils.ts
+++ b/packages/service/core/app/utils.ts
@@ -0,0 +1,149 @@
+import { MongoDataset } from '../dataset/schema';
+import { getEmbeddingModel } from '../ai/model';
+import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
+import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
+import type { StoreNodeItemType } from '@fastgpt/global/core/workflow/type/node';
+
+export async function listAppDatasetDataByTeamIdAndDatasetIds({
+  teamId,
+  datasetIdList
+}: {
+  teamId?: string;
+  datasetIdList: string[];
+}) {
+  const myDatasets = await MongoDataset.find({
+    _id: { $in: datasetIdList },
+    ...(teamId && { teamId })
+  }).lean();
+
+  return myDatasets.map((item) => ({
+    datasetId: String(item._id),
+    avatar: item.avatar,
+    name: item.name,
+    vectorModel: getEmbeddingModel(item.vectorModel)
+  }));
+}
+
+export async function rewriteAppWorkflowToDetail({
+  nodes,
+  teamId,
+  isRoot
+}: {
+  nodes: StoreNodeItemType[];
+  teamId: string;
+  isRoot: boolean;
+}) {
+  const datasetIdSet = new Set<string>();
+
+  // Get all dataset ids from nodes
+  nodes.forEach((node) => {
+    if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
+
+    const input = node.inputs.find((item) => item.key === NodeInputKeyEnum.datasetSelectList);
+    if (!input) return;
+
+    const rawValue = input.value as undefined | { datasetId: string }[] | { datasetId: string };
+    if (!rawValue) return;
+
+    const datasetIds = Array.isArray(rawValue)
+      ? rawValue.map((v) => v?.datasetId).filter((id) => !!id && typeof id === 'string')
+      : rawValue?.datasetId
+        ? [String(rawValue.datasetId)]
+        : [];
+
+    datasetIds.forEach((id) => datasetIdSet.add(id));
+  });
+
+  if (datasetIdSet.size === 0) return;
+
+  // Load dataset list
+  const datasetList = await listAppDatasetDataByTeamIdAndDatasetIds({
+    teamId: isRoot ? undefined : teamId,
+    datasetIdList: Array.from(datasetIdSet)
+  });
+  const datasetMap = new Map(datasetList.map((ds) => [String(ds.datasetId), ds]));
+
+  // Rewrite dataset ids, add dataset info to nodes
+  if (datasetList.length > 0) {
+    nodes.forEach((node) => {
+      if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
+
+      node.inputs.forEach((item) => {
+        if (item.key !== NodeInputKeyEnum.datasetSelectList) return;
+
+        const val = item.value as undefined | { datasetId: string }[] | { datasetId: string };
+
+        if (Array.isArray(val)) {
+          item.value = val
+            .map((v) => {
+              const data = datasetMap.get(String(v.datasetId));
+              if (!data)
+                return {
+                  datasetId: v.datasetId,
+                  avatar: '',
+                  name: 'Dataset not found',
+                  vectorModel: ''
+                };
+              return {
+                datasetId: data.datasetId,
+                avatar: data.avatar,
+                name: data.name,
+                vectorModel: data.vectorModel
+              };
+            })
+            .filter(Boolean);
+        } else if (typeof val === 'object' && val !== null) {
+          const data = datasetMap.get(String(val.datasetId));
+          if (!data) {
+            item.value = [
+              {
+                datasetId: val.datasetId,
+                avatar: '',
+                name: 'Dataset not found',
+                vectorModel: ''
+              }
+            ];
+          } else {
+            item.value = [
+              {
+                datasetId: data.datasetId,
+                avatar: data.avatar,
+                name: data.name,
+                vectorModel: data.vectorModel
+              }
+            ];
+          }
+        }
+      });
+    });
+  }
+
+  return nodes;
+}
+
+export async function rewriteAppWorkflowToSimple(formatNodes: StoreNodeItemType[]) {
+  formatNodes.forEach((node) => {
+    if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
+
+    node.inputs.forEach((input) => {
+      if (input.key === NodeInputKeyEnum.datasetSelectList) {
+        const val = input.value as undefined | { datasetId: string }[] | { datasetId: string };
+        if (!val) {
+          input.value = [];
+        } else if (Array.isArray(val)) {
+          input.value = val
+            .map((dataset: { datasetId: string }) => ({
+              datasetId: dataset.datasetId
+            }))
+            .filter((item) => !!item.datasetId);
+        } else if (typeof val === 'object' && val !== null) {
+          input.value = [
+            {
+              datasetId: val.datasetId
+            }
+          ];
+        }
+      }
+    });
+  });
+}
--- a/packages/service/core/chat/saveChat.ts
+++ b/packages/service/core/chat/saveChat.ts
@@ -15,6 +15,7 @@ import { AppChatConfigType } from '@fastgpt/global/core/app/type';
 import { mergeChatResponseData } from '@fastgpt/global/core/chat/utils';
 import { pushChatLog } from './pushChatLog';
 import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
+import { DispatchNodeResponseKeyEnum } from '@fastgpt/global/core/workflow/runtime/constants';

 type Props = {
  chatId: string;
@@ -73,9 +74,44 @@ export async function saveChat({
      (node) => node.flowNodeType === FlowNodeTypeEnum.pluginInput
    )?.inputs;

+    // Format save chat content: Remove quote q/a
+    const processedContent = content.map((item) => {
+      if (item.obj === ChatRoleEnum.AI) {
+        const nodeResponse = item[DispatchNodeResponseKeyEnum.nodeResponse];
+
+        if (nodeResponse) {
+          return {
+            ...item,
+            [DispatchNodeResponseKeyEnum.nodeResponse]: nodeResponse.map((responseItem) => {
+              if (
+                responseItem.moduleType === FlowNodeTypeEnum.datasetSearchNode &&
+                responseItem.quoteList
+              ) {
+                return {
+                  ...responseItem,
+                  quoteList: responseItem.quoteList.map((quote: any) => ({
+                    id: quote.id,
+                    chunkIndex: quote.chunkIndex,
+                    datasetId: quote.datasetId,
+                    collectionId: quote.collectionId,
+                    sourceId: quote.sourceId,
+                    sourceName: quote.sourceName,
+                    score: quote.score,
+                    tokens: quote.tokens
+                  }))
+                };
+              }
+              return responseItem;
+            })
+          };
+        }
+      }
+      return item;
+    });
+
    await mongoSessionRun(async (session) => {
      const [{ _id: chatItemIdHuman }, { _id: chatItemIdAi }] = await MongoChatItem.insertMany(
-        content.map((item) => ({
+        processedContent.map((item) => ({
          chatId,
          teamId,
          tmbId,
--- a/packages/service/core/dataset/apiDataset/api.ts
+++ b/packages/service/core/dataset/apiDataset/api.ts
@@ -111,11 +111,13 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
  const getFileContent = async ({
    teamId,
    tmbId,
-    apiFileId
+    apiFileId,
+    customPdfParse
  }: {
    teamId: string;
    tmbId: string;
    apiFileId: string;
+    customPdfParse?: boolean;
  }) => {
    const data = await request<APIFileContentResponse>(
      `/v1/file/content`,
@@ -133,7 +135,8 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
        teamId,
        tmbId,
        url: previewUrl,
-        relatedId: apiFileId
+        relatedId: apiFileId,
+        customPdfParse
      });
      return rawText;
    }
--- a/packages/service/core/dataset/data/dataTextSchema.ts
+++ b/packages/service/core/dataset/data/dataTextSchema.ts
@@ -41,7 +41,7 @@ try {
    }
  );
  DatasetDataTextSchema.index({ teamId: 1, datasetId: 1, collectionId: 1 });
-  DatasetDataTextSchema.index({ dataId: 1 }, { unique: true });
+  DatasetDataTextSchema.index({ dataId: 'hashed' });
 } catch (error) {
  console.log(error);
 }
--- a/packages/service/core/dataset/data/schema.ts
+++ b/packages/service/core/dataset/data/schema.ts
@@ -40,6 +40,15 @@ const DatasetDataSchema = new Schema({
    type: String,
    default: ''
  },
+  history: {
+    type: [
+      {
+        q: String,
+        a: String,
+        updateTime: Date
+      }
+    ]
+  },
  indexes: {
    type: [
      {
@@ -77,7 +86,8 @@ const DatasetDataSchema = new Schema({

  // Abandon
  fullTextToken: String,
-  initFullText: Boolean
+  initFullText: Boolean,
+  initJieba: Boolean
 });

 try {
@@ -89,15 +99,14 @@ try {
    chunkIndex: 1,
    updateTime: -1
  });
-  // FullText tmp full text index
-  // DatasetDataSchema.index({ teamId: 1, datasetId: 1, fullTextToken: 'text' });
  // Recall vectors after data matching
  DatasetDataSchema.index({ teamId: 1, datasetId: 1, collectionId: 1, 'indexes.dataId': 1 });
  DatasetDataSchema.index({ updateTime: 1 });
  // rebuild data
  DatasetDataSchema.index({ rebuilding: 1, teamId: 1, datasetId: 1 });

-  DatasetDataSchema.index({ initFullText: 1 });
+  // 为查询 initJieba 字段不存在的数据添加索引
+  DatasetDataSchema.index({ initJieba: 1, updateTime: 1 });
 } catch (error) {
  console.log(error);
 }
--- a/packages/service/core/dataset/read.ts
+++ b/packages/service/core/dataset/read.ts
@@ -127,7 +127,8 @@ export const readApiServerFileContent = async ({
  yuqueServer,
  apiFileId,
  teamId,
-  tmbId
+  tmbId,
+  customPdfParse
 }: {
  apiServer?: APIFileServer;
  feishuServer?: FeishuServer;
@@ -135,9 +136,15 @@ export const readApiServerFileContent = async ({
  apiFileId: string;
  teamId: string;
  tmbId: string;
+  customPdfParse?: boolean;
 }) => {
  if (apiServer) {
-    return useApiDatasetRequest({ apiServer }).getFileContent({ teamId, tmbId, apiFileId });
+    return useApiDatasetRequest({ apiServer }).getFileContent({
+      teamId,
+      tmbId,
+      apiFileId,
+      customPdfParse
+    });
  }

  if (feishuServer || yuqueServer) {
--- a/packages/service/core/dataset/search/controller.ts
+++ b/packages/service/core/dataset/search/controller.ts
@@ -16,7 +16,7 @@ import { reRankRecall } from '../../../core/ai/rerank';
 import { countPromptTokens } from '../../../common/string/tiktoken/index';
 import { datasetSearchResultConcat } from '@fastgpt/global/core/dataset/search/utils';
 import { hashStr } from '@fastgpt/global/common/string/tools';
-import { jiebaSplit } from '../../../common/string/jieba';
+import { jiebaSplit } from '../../../common/string/jieba/index';
 import { getCollectionSourceData } from '@fastgpt/global/core/dataset/collection/utils';
 import { Types } from '../../../common/mongo';
 import json5 from 'json5';
@@ -27,6 +27,7 @@ import { ChatItemType } from '@fastgpt/global/core/chat/type';
 import { POST } from '../../../common/api/plusRequest';
 import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
 import { datasetSearchQueryExtension } from './utils';
+import type { RerankModelItemType } from '@fastgpt/global/core/ai/model.d';

 export type SearchDatasetDataProps = {
  histories: ChatItemType[];
@@ -39,7 +40,11 @@ export type SearchDatasetDataProps = {
  [NodeInputKeyEnum.datasetSimilarity]?: number; // min distance
  [NodeInputKeyEnum.datasetMaxTokens]: number; // max Token limit
  [NodeInputKeyEnum.datasetSearchMode]?: `${DatasetSearchModeEnum}`;
+  [NodeInputKeyEnum.datasetSearchEmbeddingWeight]?: number;
+
  [NodeInputKeyEnum.datasetSearchUsingReRank]?: boolean;
+  [NodeInputKeyEnum.datasetSearchRerankModel]?: RerankModelItemType;
+  [NodeInputKeyEnum.datasetSearchRerankWeight]?: number;

  /* 
    {
@@ -75,13 +80,16 @@ export type SearchDatasetDataResponse = {
 };

 export const datasetDataReRank = async ({
+  rerankModel,
  data,
  query
 }: {
+  rerankModel?: RerankModelItemType;
  data: SearchDataResponseItemType[];
  query: string;
 }): Promise<SearchDataResponseItemType[]> => {
  const results = await reRankRecall({
+    model: rerankModel,
    query,
    documents: data.map((item) => ({
      id: item.id,
@@ -154,7 +162,10 @@ export async function searchDatasetData(
    similarity = 0,
    limit: maxTokens,
    searchMode = DatasetSearchModeEnum.embedding,
+    embeddingWeight = 0.5,
    usingReRank = false,
+    rerankModel,
+    rerankWeight = 0.5,
    datasetIds = [],
    collectionFilterMatch
  } = props;
@@ -526,7 +537,7 @@ export async function searchDatasetData(
                $match: {
                  teamId: new Types.ObjectId(teamId),
                  datasetId: new Types.ObjectId(id),
-                  $text: { $search: jiebaSplit({ text: query }) },
+                  $text: { $search: await jiebaSplit({ text: query }) },
                  ...(filterCollectionIdList
                    ? {
                        collectionId: {
@@ -711,6 +722,7 @@ export async function searchDatasetData(
    });
    try {
      return await datasetDataReRank({
+        rerankModel,
        query: reRankQuery,
        data: filterSameDataResults
      });
@@ -721,11 +733,26 @@ export async function searchDatasetData(
  })();

  // embedding recall and fullText recall rrf concat
-  const rrfConcatResults = datasetSearchResultConcat([
-    { k: 60, list: embeddingRecallResults },
-    { k: 60, list: fullTextRecallResults },
-    { k: 58, list: reRankResults }
+  const baseK = 120;
+  const embK = Math.round(baseK * (1 - embeddingWeight)); // 搜索结果的 k 值
+  const fullTextK = Math.round(baseK * embeddingWeight); // rerank 结果的 k 值
+
+  const rrfSearchResult = datasetSearchResultConcat([
+    { k: embK, list: embeddingRecallResults },
+    { k: fullTextK, list: fullTextRecallResults }
  ]);
+  const rrfConcatResults = (() => {
+    if (reRankResults.length === 0) return rrfSearchResult;
+    if (rerankWeight === 1) return reRankResults;
+
+    const searchK = Math.round(baseK * rerankWeight); // 搜索结果的 k 值
+    const rerankK = Math.round(baseK * (1 - rerankWeight)); // rerank 结果的 k 值
+
+    return datasetSearchResultConcat([
+      { k: searchK, list: rrfSearchResult },
+      { k: rerankK, list: reRankResults }
+    ]);
+  })();

  // remove same q and a data
  set = new Set<string>();
--- a/packages/service/core/workflow/dispatch/agent/extract.ts
+++ b/packages/service/core/workflow/dispatch/agent/extract.ts
@@ -9,7 +9,11 @@ import {
 import { ChatItemValueTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
 import { createChatCompletion } from '../../../ai/config';
 import type { ContextExtractAgentItemType } from '@fastgpt/global/core/workflow/template/system/contextExtract/type';
-import { NodeInputKeyEnum, NodeOutputKeyEnum } from '@fastgpt/global/core/workflow/constants';
+import {
+  NodeInputKeyEnum,
+  NodeOutputKeyEnum,
+  toolValueTypeList
+} from '@fastgpt/global/core/workflow/constants';
 import { DispatchNodeResponseKeyEnum } from '@fastgpt/global/core/workflow/runtime/constants';
 import type { ModuleDispatchProps } from '@fastgpt/global/core/workflow/runtime/type';
 import { Prompt_ExtractJson } from '@fastgpt/global/core/ai/prompt/agent';
@@ -192,10 +196,13 @@ ${description ? `- ${description}` : ''}
    }
  > = {};
  extractKeys.forEach((item) => {
+    const jsonSchema = (
+      toolValueTypeList.find((type) => type.value === item.valueType) || toolValueTypeList[0]
+    )?.jsonSchema;
    properties[item.key] = {
-      type: item.valueType || 'string',
+      ...jsonSchema,
      description: item.desc,
-      ...(item.enum ? { enum: item.enum.split('\n') } : {})
+      ...(item.enum ? { enum: item.enum.split('\n').filter(Boolean) } : {})
    };
  });
  // function body
--- a/packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts
+++ b/packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts
@@ -1,11 +1,6 @@
 import { createChatCompletion } from '../../../../ai/config';
 import { filterGPTMessageByMaxContext, loadRequestMessages } from '../../../../chat/utils';
-import {
-  ChatCompletion,
-  StreamChatType,
-  ChatCompletionMessageParam,
-  ChatCompletionAssistantMessageParam
-} from '@fastgpt/global/core/ai/type';
+import { StreamChatType, ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
 import { NextApiResponse } from 'next';
 import { responseWriteController } from '../../../../../common/response';
 import { SseResponseEventEnum } from '@fastgpt/global/core/workflow/runtime/constants';
--- a/packages/service/core/workflow/dispatch/chat/oneapi.ts
+++ b/packages/service/core/workflow/dispatch/chat/oneapi.ts
@@ -208,6 +208,7 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
        res,
        stream: response,
        aiChatReasoning,
+        parseThinkTag: modelConstantsData.reasoning,
        isResponseAnswerText,
        workflowStreamResponse
      });
@@ -513,12 +514,14 @@ async function streamResponse({
  stream,
  workflowStreamResponse,
  aiChatReasoning,
+  parseThinkTag,
  isResponseAnswerText
 }: {
  res: NextApiResponse;
  stream: StreamChatType;
  workflowStreamResponse?: WorkflowResponseType;
  aiChatReasoning?: boolean;
+  parseThinkTag?: boolean;
  isResponseAnswerText?: boolean;
 }) {
  const write = responseWriteController({
@@ -535,7 +538,7 @@ async function streamResponse({
      break;
    }

-    const [reasoningContent, content] = parsePart(part, aiChatReasoning);
+    const [reasoningContent, content] = parsePart(part, parseThinkTag);
    answer += content;
    reasoning += reasoningContent;

--- a/packages/service/core/workflow/dispatch/dataset/search.ts
+++ b/packages/service/core/workflow/dispatch/dataset/search.ts
@@ -6,7 +6,7 @@ import { formatModelChars2Points } from '../../../../support/wallet/usage/utils'
 import type { SelectedDatasetType } from '@fastgpt/global/core/workflow/api.d';
 import type { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
 import type { ModuleDispatchProps } from '@fastgpt/global/core/workflow/runtime/type';
-import { getEmbeddingModel } from '../../../ai/model';
+import { getEmbeddingModel, getRerankModel } from '../../../ai/model';
 import { deepRagSearch, defaultSearchDatasetData } from '../../../dataset/search/controller';
 import { NodeInputKeyEnum, NodeOutputKeyEnum } from '@fastgpt/global/core/workflow/constants';
 import { DispatchNodeResponseKeyEnum } from '@fastgpt/global/core/workflow/runtime/constants';
@@ -22,9 +22,14 @@ type DatasetSearchProps = ModuleDispatchProps<{
  [NodeInputKeyEnum.datasetSelectList]: SelectedDatasetType;
  [NodeInputKeyEnum.datasetSimilarity]: number;
  [NodeInputKeyEnum.datasetMaxTokens]: number;
-  [NodeInputKeyEnum.datasetSearchMode]: `${DatasetSearchModeEnum}`;
  [NodeInputKeyEnum.userChatInput]?: string;
+  [NodeInputKeyEnum.datasetSearchMode]: `${DatasetSearchModeEnum}`;
+  [NodeInputKeyEnum.datasetSearchEmbeddingWeight]?: number;
+
  [NodeInputKeyEnum.datasetSearchUsingReRank]: boolean;
+  [NodeInputKeyEnum.datasetSearchRerankModel]?: string;
+  [NodeInputKeyEnum.datasetSearchRerankWeight]?: number;
+
  [NodeInputKeyEnum.collectionFilterMatch]: string;
  [NodeInputKeyEnum.authTmbId]?: boolean;

@@ -53,11 +58,14 @@ export async function dispatchDatasetSearch(
      datasets = [],
      similarity,
      limit = 1500,
-      usingReRank,
-      searchMode,
      userChatInput = '',
      authTmbId = false,
      collectionFilterMatch,
+      searchMode,
+      embeddingWeight,
+      usingReRank,
+      rerankModel,
+      rerankWeight,

      datasetSearchUsingExtensionQuery,
      datasetSearchExtensionModel,
@@ -122,7 +130,10 @@ export async function dispatchDatasetSearch(
    limit,
    datasetIds,
    searchMode,
+    embeddingWeight,
    usingReRank: usingReRank && (await checkTeamReRankPermission(teamId)),
+    rerankModel: getRerankModel(rerankModel),
+    rerankWeight,
    collectionFilterMatch
  };
  const {
@@ -219,6 +230,9 @@ export async function dispatchDatasetSearch(
    similarity: usingSimilarityFilter ? similarity : undefined,
    limit,
    searchMode,
+    embeddingWeight: searchMode === DatasetSearchModeEnum.mixedRecall ? embeddingWeight : undefined,
+    rerankModel: usingReRank ? getRerankModel(rerankModel)?.name : undefined,
+    rerankWeight: usingReRank ? rerankWeight : undefined,
    searchUsingReRank: searchUsingReRank,
    quoteList: searchRes,
    queryExtensionResult,
--- a/packages/service/core/workflow/dispatch/index.ts
+++ b/packages/service/core/workflow/dispatch/index.ts
@@ -21,7 +21,7 @@ import {
  FlowNodeInputTypeEnum,
  FlowNodeTypeEnum
 } from '@fastgpt/global/core/workflow/node/constant';
-import { getNanoid, replaceVariable } from '@fastgpt/global/common/string/tools';
+import { getNanoid } from '@fastgpt/global/common/string/tools';
 import { getSystemTime } from '@fastgpt/global/common/time/timezone';

 import { dispatchWorkflowStart } from './init/workflowStart';
@@ -426,6 +426,14 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
    })();

    if (!nodeRunResult) return [];
+    if (res?.closed) {
+      addLog.warn('Request is closed', {
+        appId: props.runningAppInfo.id,
+        nodeId: node.nodeId,
+        nodeName: node.name
+      });
+      return [];
+    }

    /* 
      特殊情况：