feat: complete Day 21-24 knowledge base features

- Day 21-22: fix CORS and file upload issues
- Day 23-24: implement @knowledge base search and conversation integration
- Backend: integrate Dify RAG into conversation system
- Frontend: load knowledge base list and @ reference feature

backend/src/index.ts

@@ -8,12 +8,6 @@ import { agentRoutes } from './routes/agents.js';
 import { conversationRoutes } from './routes/conversations.js';
 import knowledgeBaseRoutes from './routes/knowledgeBases.js';
 
-console.log('\n' + '='.repeat(60));
-console.log('🔧 正在加载修复后的服务器配置...');
-console.log('📅 修复版本: 2025-10-11 - CORS完整配置');
-console.log('='.repeat(60) + '\n');
-
-console.log('🚨🚨🚨 测试日志: 文件已加载 🚨🚨🚨');
 
 // 全局处理BigInt序列化
 (BigInt.prototype as any).toJSON = function() {
@@ -54,10 +48,6 @@ await fastify.register(multipart, {
 });
 console.log('✅ 文件上传插件已配置: 最大文件大小 10MB');
 
-// 添加请求日志钩子（用于调试）
-fastify.addHook('onRequest', async (request, _reply) => {
-  console.log(`📥 ${request.method} ${request.url} - Origin: ${request.headers.origin || 'none'}`);
-});
 
 // 健康检查路由
 fastify.get('/health', async () => {

backend/src/services/conversationService.ts

@@ -2,6 +2,7 @@ import { prisma } from '../config/database.js';
 import { LLMFactory } from '../adapters/LLMFactory.js';
 import { Message, ModelType, StreamChunk } from '../adapters/types.js';
 import { agentService } from './agentService.js';
+import * as knowledgeBaseService from './knowledgeBaseService.js';
 
 interface CreateConversationData {
   userId: string;
@@ -217,8 +218,44 @@ export class ConversationService {
     // 获取知识库上下文（如果有@知识库）
     let knowledgeBaseContext = '';
     if (knowledgeBaseIds && knowledgeBaseIds.length > 0) {
-      // TODO: 调用Dify RAG获取知识库上下文
-      knowledgeBaseContext = '相关文献内容...';
+      const knowledgeResults: string[] = [];
+      
+      // 对每个知识库进行检索
+      for (const kbId of knowledgeBaseIds) {
+        try {
+          const searchResult = await knowledgeBaseService.searchKnowledgeBase(
+            userId,
+            kbId,
+            content,
+            3 // 每个知识库返回3个最相关的段落
+          );
+
+          // 格式化检索结果
+          if (searchResult.records && searchResult.records.length > 0) {
+            const kbInfo = await prisma.knowledgeBase.findUnique({
+              where: { id: kbId },
+              select: { name: true },
+            });
+
+            knowledgeResults.push(
+              `【知识库：${kbInfo?.name || '未命名'}】\n` +
+              searchResult.records
+                .map((record: any, index: number) => {
+                  const score = (record.score * 100).toFixed(1);
+                  return `${index + 1}. [相关度${score}%] ${record.segment.content}`;
+                })
+                .join('\n\n')
+            );
+          }
+        } catch (error) {
+          console.error(`Failed to search knowledge base ${kbId}:`, error);
+          // 检索失败不阻止对话，继续处理
+        }
+      }
+
+      if (knowledgeResults.length > 0) {
+        knowledgeBaseContext = knowledgeResults.join('\n\n---\n\n');
+      }
     }
 
     // 组装上下文
@@ -299,8 +336,44 @@ export class ConversationService {
     // 获取知识库上下文（如果有@知识库）
     let knowledgeBaseContext = '';
     if (knowledgeBaseIds && knowledgeBaseIds.length > 0) {
-      // TODO: 调用Dify RAG获取知识库上下文
-      knowledgeBaseContext = '相关文献内容...';
+      const knowledgeResults: string[] = [];
+      
+      // 对每个知识库进行检索
+      for (const kbId of knowledgeBaseIds) {
+        try {
+          const searchResult = await knowledgeBaseService.searchKnowledgeBase(
+            userId,
+            kbId,
+            content,
+            3 // 每个知识库返回3个最相关的段落
+          );
+
+          // 格式化检索结果
+          if (searchResult.records && searchResult.records.length > 0) {
+            const kbInfo = await prisma.knowledgeBase.findUnique({
+              where: { id: kbId },
+              select: { name: true },
+            });
+
+            knowledgeResults.push(
+              `【知识库：${kbInfo?.name || '未命名'}】\n` +
+              searchResult.records
+                .map((record: any, index: number) => {
+                  const score = (record.score * 100).toFixed(1);
+                  return `${index + 1}. [相关度${score}%] ${record.segment.content}`;
+                })
+                .join('\n\n')
+            );
+          }
+        } catch (error) {
+          console.error(`Failed to search knowledge base ${kbId}:`, error);
+          // 检索失败不阻止对话，继续处理
+        }
+      }
+
+      if (knowledgeResults.length > 0) {
+        knowledgeBaseContext = knowledgeResults.join('\n\n---\n\n');
+      }
     }
 
     // 组装上下文