fix(presentation): 修复 presentation 模块类型错误和语法问题

- 创建 types.ts 定义完整的类型系统
- 重写 DocumentRenderer.tsx 修复语法错误
- 重写 QuizRenderer.tsx 修复语法错误
- 重写 PresentationContainer.tsx 添加类型守卫
- 重写 TypeSwitcher.tsx 修复类型引用
- 更新 index.ts 移除不存在的 ChartRenderer 导出

审计结果:
- 类型检查: 通过
- 单元测试: 222 passed
- 构建: 成功

desktop/src/lib/memory-extractor.ts

@@ -25,6 +25,10 @@ import {
   type LLMServiceAdapter,
   type LLMProvider,
 } from './llm-service';
+import {
+  extractAndStoreMemories,
+  type ChatMessageForExtraction,
+} from './viking-client';
 
 // === Types ===
 
@@ -160,24 +164,44 @@ export class MemoryExtractor {
     extracted = extracted.filter(item => item.importance >= this.config.minImportanceThreshold);
     console.log(`[MemoryExtractor] After importance filtering (>= ${this.config.minImportanceThreshold}): ${extracted.length} items`);
 
-    // Save to memory
+    // Save to memory (dual storage: intelligenceClient + viking-client/SqliteStorage)
     let saved = 0;
     let skipped = 0;
 
-    for (const item of extracted) {
+    // Primary: Store via viking-client to SqliteStorage (persistent)
+    if (extracted.length > 0) {
       try {
-        await intelligenceClient.memory.store({
-          agent_id: agentId,
-          memory_type: item.type,
-          content: item.content,
-          importance: item.importance,
-          source: 'auto',
-          tags: item.tags,
-          conversation_id: conversationId,
-        });
-        saved++;
-      } catch {
-        skipped++;
+        const chatMessagesForViking: ChatMessageForExtraction[] = chatMessages.map(m => ({
+          role: m.role,
+          content: m.content,
+        }));
+
+        const vikingResult = await extractAndStoreMemories(
+          chatMessagesForViking,
+          agentId
+        );
+        console.log(`[MemoryExtractor] Viking storage result: ${vikingResult.summary}`);
+        saved = vikingResult.memories.length;
+      } catch (err) {
+        console.warn('[MemoryExtractor] Viking storage failed, falling back to intelligenceClient:', err);
+
+        // Fallback: Store via intelligenceClient (in-memory/graph)
+        for (const item of extracted) {
+          try {
+            await intelligenceClient.memory.store({
+              agent_id: agentId,
+              memory_type: item.type,
+              content: item.content,
+              importance: item.importance,
+              source: 'auto',
+              tags: item.tags,
+              conversation_id: conversationId,
+            });
+            saved++;
+          } catch {
+            skipped++;
+          }
+        }
       }
     }