Change embedding (#1428)

* fix: text spliter

* perf: embedding model

files/helm/fastgpt/templates/configmap-config.yaml

@@ -99,13 +99,41 @@ data:
         }
       ],
       "vectorModels": [
+        {
+          "model": "text-embedding-3-large",
+          "name": "Embedding-2",
+          "avatar": "/imgs/model/openai.svg",
+          "charsPointsPrice": 0,
+          "defaultToken": 512,
+          "maxToken": 3000,
+          "weight": 100,
+          "dbConfig": {},
+          "queryConfig": {},
+          "defaultConfig": {
+            "dimensions": 1024
+          }
+        },
+        {
+          "model": "text-embedding-3-small",
+          "name": "Embedding-2",
+          "avatar": "/imgs/model/openai.svg",
+          "charsPointsPrice": 0,
+          "defaultToken": 512,
+          "maxToken": 3000,
+          "weight": 100,
+          "dbConfig": {},
+          "queryConfig": {}
+        },
         {
           "model": "text-embedding-ada-002",
           "name": "Embedding-2",
+          "avatar": "/imgs/model/openai.svg",
           "charsPointsPrice": 0,
-          "defaultToken": 700,
+          "defaultToken": 512,
           "maxToken": 3000,
-          "weight": 100
+          "weight": 100,
+          "dbConfig": {},
+          "queryConfig": {}
         }
       ],
       "reRankModels": [],

packages/global/common/string/textSplitter.ts

@@ -17,17 +17,47 @@ type SplitResponse = {
 
 // 判断字符串是否为markdown的表格形式
 const strIsMdTable = (str: string) => {
-  const regex = /^(\|.*\|[\r]*)$/m;
+  // 检查是否包含表格分隔符 |
+  if (!str.includes('|')) {
+    return false;
+  }
 
-  return regex.test(str);
+  const lines = str.split('\n');
+
+  // 检查表格是否至少有两行
+  if (lines.length < 2) {
+    return false;
+  }
+
+  // 检查表头行是否包含 |
+  const headerLine = lines[0].trim();
+  if (!headerLine.startsWith('|') || !headerLine.endsWith('|')) {
+    return false;
+  }
+
+  // 检查分隔行是否由 | 和 - 组成
+  const separatorLine = lines[1].trim();
+  const separatorRegex = /^(\|[\s:]*-+[\s:]*)+\|$/;
+  if (!separatorRegex.test(separatorLine)) {
+    return false;
+  }
+
+  // 检查数据行是否包含 |
+  for (let i = 2; i < lines.length; i++) {
+    const dataLine = lines[i].trim();
+    if (dataLine && (!dataLine.startsWith('|') || !dataLine.endsWith('|'))) {
+      return false;
+    }
+  }
+  return true;
 };
 const markdownTableSplit = (props: SplitProps): SplitResponse => {
   let { text = '', chunkLen } = props;
   const splitText2Lines = text.split('\n');
   const header = splitText2Lines[0];
-
   const headerSize = header.split('|').length - 2;
-  const mdSplitString = `| ${new Array(headerSize)
+
+  const mdSplitString = `| ${new Array(headerSize > 0 ? headerSize : 1)
     .fill(0)
     .map(() => '---')
     .join(' | ')} |`;
@@ -304,7 +334,7 @@ export const splitText2Chunks = (props: SplitProps): SplitResponse => {
   const splitWithCustomSign = text.split(CUSTOM_SPLIT_SIGN);
 
   const splitResult = splitWithCustomSign.map((item) => {
-    if (strIsMdTable(text)) {
+    if (strIsMdTable(item)) {
       return markdownTableSplit(props);
     }
 

packages/global/core/ai/model.ts

@@ -23,7 +23,7 @@ export const defaultQAModels: LLMModelItemType[] = [
 
 export const defaultVectorModels: VectorModelItemType[] = [
   {
-    model: 'text-embedding-ada-002',
+    model: 'text-embedding-3-small',
     name: 'Embedding-2',
     charsPointsPrice: 0,
     defaultToken: 500,

packages/service/core/dataset/schema.ts

@@ -62,7 +62,7 @@ const DatasetSchema = new Schema({
   vectorModel: {
     type: String,
     required: true,
-    default: 'text-embedding-ada-002'
+    default: 'text-embedding-3-small'
   },
   agentModel: {
     type: String,

projects/app/data/config.json

@@ -80,6 +80,31 @@
     }
   ],
   "vectorModels": [
+    {
+      "model": "text-embedding-3-large",
+      "name": "Embedding-2",
+      "avatar": "/imgs/model/openai.svg",
+      "charsPointsPrice": 0,
+      "defaultToken": 512,
+      "maxToken": 3000,
+      "weight": 100,
+      "dbConfig": {},
+      "queryConfig": {},
+      "defaultConfig": {
+        "dimensions": 1024
+      }
+    },
+    {
+      "model": "text-embedding-3-small",
+      "name": "Embedding-2",
+      "avatar": "/imgs/model/openai.svg",
+      "charsPointsPrice": 0,
+      "defaultToken": 512,
+      "maxToken": 3000,
+      "weight": 100,
+      "dbConfig": {},
+      "queryConfig": {}
+    },
     {
       "model": "text-embedding-ada-002",
       "name": "Embedding-2",

projects/app/src/pages/api/core/dataset/file/getPreviewChunks.ts

@@ -35,9 +35,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
           csvFormat: true
         });
         // split chunks (5 chunk)
-        const sliceRawText = 10 * chunkSize;
         const { chunks } = splitText2Chunks({
-          text: rawText.slice(0, sliceRawText),
+          text: rawText,
           chunkLen: chunkSize,
           overlapRatio,
           customReg: customSplitChar ? [customSplitChar] : []