v4.6.2 (#523)

projects/app/src/pages/api/admin/initv46-2.ts

@@ -152,6 +152,7 @@ async function init(limit: number): Promise<any> {
         collectionId: data.collection_id,
         q: data.q,
         a: data.a,
+        fullTextToken: '',
         indexes: [
           {
             defaultIndex: !data.a,

projects/app/src/pages/api/admin/initv462-2.ts

@@ -0,0 +1,80 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@fastgpt/service/common/response';
+import { connectToDatabase } from '@/service/mongo';
+import { delay } from '@/utils/tools';
+import { authCert } from '@fastgpt/service/support/permission/auth/common';
+import { MongoApp } from '@fastgpt/service/core/app/schema';
+import { FlowNodeInputTypeEnum, FlowNodeTypeEnum } from '@fastgpt/global/core/module/node/constant';
+import { DatasetSearchModeEnum } from '@fastgpt/global/core/dataset/constant';
+import { ModuleDataTypeEnum, ModuleInputKeyEnum } from '@fastgpt/global/core/module/constants';
+import { ModuleItemType } from '@fastgpt/global/core/module/type';
+
+let success = 0;
+/* pg 中的数据搬到 mongo dataset.datas 中，并做映射 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  try {
+    const { limit = 50 } = req.body as { limit: number };
+    await authCert({ req, authRoot: true });
+    await connectToDatabase();
+    success = 0;
+
+    console.log('total', await MongoApp.countDocuments());
+
+    await initApp(limit);
+
+    jsonRes(res, {
+      message: 'success'
+    });
+  } catch (error) {
+    console.log(error);
+
+    jsonRes(res, {
+      code: 500,
+      error
+    });
+  }
+}
+export async function initApp(limit = 50): Promise<any> {
+  try {
+    const apps = await MongoApp.find({ inited: false }).limit(limit);
+    if (apps.length === 0) return;
+
+    const result = await Promise.allSettled(
+      apps.map(async (app) => {
+        // 遍历app的modules，找到 datasetSearch, 如果 rerank=true， searchMode = embFullTextReRank, 否则等于embedding
+        const modules = JSON.parse(JSON.stringify(app.modules)) as ModuleItemType[];
+        modules.forEach((module) => {
+          if (module.flowType === FlowNodeTypeEnum.datasetSearchNode) {
+            module.inputs.forEach((input, i) => {
+              if (input.key === 'rerank') {
+                const val = !!input.value as boolean;
+                module.inputs.splice(i, 1, {
+                  key: ModuleInputKeyEnum.datasetSearchMode,
+                  type: FlowNodeInputTypeEnum.hidden,
+                  label: 'core.dataset.search.Mode',
+                  valueType: ModuleDataTypeEnum.string,
+                  showTargetInApp: false,
+                  showTargetInPlugin: false,
+                  value: val
+                    ? DatasetSearchModeEnum.embFullTextReRank
+                    : DatasetSearchModeEnum.embedding
+                });
+              }
+            });
+          }
+        });
+        app.modules = modules;
+        app.inited = true;
+        await app.save();
+      })
+    );
+
+    success += result.filter((item) => item.status === 'fulfilled').length;
+    console.log(`success: ${success}`);
+    return initApp(limit);
+  } catch (error) {
+    console.log(error);
+    await delay(1000);
+    return initApp(limit);
+  }
+}