feat(dc): Complete Tool C Day 5 - AI Chat + Ant Design X Integration

Summary:
- Upgrade to Ant Design 6.0.1 + install Ant Design X (2.1.0) + X SDK (2.1.0)
- Develop frontend common capability layer: Chat component library (~968 lines)
  * ChatContainer.tsx - Core container component
  * MessageRenderer.tsx - Message renderer
  * CodeBlockRenderer.tsx - Code block renderer with syntax highlighting
  * Complete TypeScript types and documentation
- Integrate ChatContainer into Tool C
- Fix 7 critical UI issues:
  * AG Grid module registration error
  * UI refinement (borders, shadows, gradients)
  * Add AI welcome message
  * Auto-clear input field after sending
  * Remove page scrollbars
  * Manual code execution (not auto-run)
  * Support simple Q&A (new /ai/chat API)
- Complete end-to-end testing
- Update all documentation (4 status docs + 6 dev logs)

Technical Stack:
- Frontend: React 19 + Ant Design 6.0 + Ant Design X 2.1
- Components: Bubble, Sender from @ant-design/x
- Total code: ~5418 lines

Status: Tool C MVP completed, production ready

backend/src/modules/dc/tool-c/controllers/AIController.ts

@@ -13,6 +13,9 @@
 import { FastifyRequest, FastifyReply } from 'fastify';
 import { logger } from '../../../../common/logging/index.js';
 import { aiCodeService } from '../services/AICodeService.js';
+import { sessionService } from '../services/SessionService.js';
+import { LLMFactory } from '../../../../common/llm/adapters/LLMFactory.js';
+import { ModelType } from '../../../../common/llm/adapters/types.js';
 
 // ==================== 请求参数类型定义 ====================
 
@@ -198,6 +201,64 @@ export class AIController {
     }
   }
   
+  /**
+   * POST /api/v1/dc/tool-c/ai/chat
+   * 简单问答（不生成代码，直接回答）
+   */
+  async chat(request: FastifyRequest, reply: FastifyReply) {
+    try {
+      const { sessionId, message } = request.body as GenerateCodeBody;
+      
+      logger.info(`[AIController] 收到简单问答请求: sessionId=${sessionId}`);
+      
+      // 参数验证
+      if (!sessionId || !message) {
+        return reply.code(400).send({
+          success: false,
+          error: '缺少必要参数：sessionId 或 message'
+        });
+      }
+      
+      // 获取 Session 信息
+      const session = await sessionService.getSession(sessionId);
+      
+      // 调用 LLM 进行简单问答
+      const llm = LLMFactory.getAdapter('deepseek-v3' as ModelType);
+      const response = await llm.chat([
+        { 
+          role: 'system', 
+          content: `你是一个数据分析助手。当前数据集信息：
+- 文件名：${session.fileName}
+- 总行数：${session.totalRows}
+- 总列数：${session.totalCols}
+- 列名：${session.columns.join(', ')}
+
+请直接回答用户的问题，不要生成代码。` 
+        },
+        { role: 'user', content: message }
+      ], {
+        temperature: 0.7,
+        maxTokens: 500,
+      });
+      
+      return reply.code(200).send({
+        success: true,
+        message: '回答成功',
+        data: {
+          messageId: Date.now().toString(),
+          content: response.content,
+          explanation: response.content,
+        }
+      });
+    } catch (error: any) {
+      logger.error(`[AIController] chat失败: ${error.message}`);
+      return reply.code(500).send({
+        success: false,
+        error: error.message || '问答失败，请重试'
+      });
+    }
+  }
+
   /**
    * GET /api/v1/dc/tool-c/ai/history/:sessionId
    * 获取对话历史

backend/src/modules/dc/tool-c/routes/index.ts

@@ -76,6 +76,11 @@ export async function toolCRoutes(fastify: FastifyInstance) {
     handler: aiController.process.bind(aiController),
   });
 
+  // 简单问答（不生成代码）
+  fastify.post('/ai/chat', {
+    handler: aiController.chat.bind(aiController),
+  });
+
   // 获取对话历史
   fastify.get('/ai/history/:sessionId', {
     handler: aiController.getHistory.bind(aiController),