feat: lafClaude

src/service/plugins/searchKb.ts

@@ -3,22 +3,20 @@ import { ModelDataStatusEnum, ModelVectorSearchModeEnum, ChatModelMap } from '@/
 import { ModelSchema } from '@/types/mongoSchema';
 import { openaiCreateEmbedding } from '../utils/chat/openai';
 import { ChatRoleEnum } from '@/constants/chat';
-import { sliceTextByToken } from '@/utils/chat';
+import { modelToolMap } from '@/utils/chat';
 import { ChatItemSimpleType } from '@/types/chat';
 
 /**
  *  use openai embedding search kb
  */
 export const searchKb = async ({
-  userApiKey,
-  systemApiKey,
+  userOpenAiKey,
   prompts,
   similarity = 0.2,
   model,
   userId
 }: {
-  userApiKey?: string;
-  systemApiKey: string;
+  userOpenAiKey?: string;
   prompts: ChatItemSimpleType[];
   model: ModelSchema;
   userId: string;
@@ -33,8 +31,7 @@ export const searchKb = async ({
   async function search(textArr: string[] = []) {
     // 获取提示词的向量
     const { vectors: promptVectors } = await openaiCreateEmbedding({
-      userApiKey,
-      systemApiKey,
+      userOpenAiKey,
       userId,
       textArr
     });
@@ -81,11 +78,24 @@ export const searchKb = async ({
   ].filter((item) => item);
   const systemPrompts = await search(searchArr);
 
-  // filter system prompt
-  if (
-    systemPrompts.length === 0 &&
-    model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
-  ) {
+  // filter system prompts.
+  const filterRateMap: Record<number, number[]> = {
+    1: [1],
+    2: [0.7, 0.3]
+  };
+  const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
+
+  const filterSystemPrompt = filterRate
+    .map((rate, i) =>
+      modelToolMap[model.chat.chatModel].sliceText({
+        text: systemPrompts[i],
+        length: Math.floor(modelConstantsData.systemMaxToken * rate)
+      })
+    )
+    .join('\n');
+
+  /* 高相似度+不回复 */
+  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
     return {
       code: 201,
       searchPrompt: {
@@ -95,7 +105,7 @@ export const searchKb = async ({
     };
   }
   /* 高相似度+无上下文，不添加额外知识,仅用系统提示词 */
-  if (systemPrompts.length === 0 && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
+  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
     return {
       code: 200,
       searchPrompt: model.chat.systemPrompt
@@ -107,25 +117,7 @@ export const searchKb = async ({
     };
   }
 
-  /* 有匹配情况下，system 添加知识库内容。 */
-
-  // filter system prompts. max 70% tokens
-  const filterRateMap: Record<number, number[]> = {
-    1: [0.7],
-    2: [0.5, 0.2]
-  };
-  const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
-
-  const filterSystemPrompt = filterRate
-    .map((rate, i) =>
-      sliceTextByToken({
-        model: model.chat.chatModel,
-        text: systemPrompts[i],
-        length: Math.floor(modelConstantsData.contextMaxToken * rate)
-      })
-    )
-    .join('\n');
-
+  /* 有匹配 */
   return {
     code: 200,
     searchPrompt: {
@@ -133,9 +125,9 @@ export const searchKb = async ({
       value: `
 ${model.chat.systemPrompt}
 ${
-  model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? `不回答知识库外的内容.` : ''
+  model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? '不回答知识库外的内容.' : ''
 }
-知识库内容为: ${filterSystemPrompt}'
+知识库内容为: '${filterSystemPrompt}'
 `
     }
   };