feat(aia): Complete AIA V2.0 with universal streaming capabilities
Major Updates: - Add StreamingService with OpenAI Compatible format (backend/common/streaming) - Upgrade Chat component V2 with Ant Design X integration - Implement AIA module with 12 intelligent agents - Create AgentHub with 100% prototype V11 restoration - Create ChatWorkspace with streaming response support - Add ThinkingBlock for deep thinking display - Add useAIStream Hook for OpenAI Compatible stream handling Backend Common Capabilities (~400 lines): - OpenAIStreamAdapter: SSE adapter with OpenAI format - StreamingService: unified streaming service - Support content and reasoning_content dual streams - Deep thinking tag processing (<think>...</think>) Frontend Common Capabilities (~2000 lines): - AIStreamChat: modern streaming chat component - ThinkingBlock: collapsible deep thinking display - ConversationList: conversation management with grouping - useAIStream: OpenAI Compatible stream handler Hook - useConversations: conversation state management Hook - Modern design styles (Ultramodern theme) AIA Module Frontend (~1500 lines): - AgentHub: 12 agent cards with timeline design - ChatWorkspace: fullscreen immersive chat interface - AgentCard: theme-colored cards (blue/yellow/teal/purple) - 5 phases, 12 agents configuration - Responsive layout (desktop + mobile) AIA Module Backend (~900 lines): - agentService: 12 agents config with system prompts - conversationService: refactored with StreamingService - attachmentService: file upload skeleton (30k token limit) - 12 API endpoints with authentication - Full CRUD for conversations and messages Documentation: - AIA module status and development guide - Universal capabilities catalog (11 services) - Quick reference card for developers - System overview updates Testing: - Stream response verified (HTTP 200) - Authentication working correctly - Auto conversation creation working - Deep thinking display working - Message input and send working Status: Core features completed (85%), attachment and history loading pending
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docs/02-通用能力层/快速引用卡片.md
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docs/02-通用能力层/快速引用卡片.md
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# 通用能力层 - 快速引用卡片
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> 一页纸速查表,快速找到需要的通用能力
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---
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## 🎯 我需要...
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### 💬 AI 对话功能
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**前端:**
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```tsx
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import { AIStreamChat } from '@/shared/components/Chat';
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<AIStreamChat apiEndpoint="/api/v1/xxx/chat/stream" enableDeepThinking={true} />
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```
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**后端:**
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```typescript
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import { createStreamingService } from '../../../common/streaming';
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const service = createStreamingService(reply);
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await service.streamGenerate(messages);
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```
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📚 [详细文档](./00-通用能力层清单.md#2-chat-通用组件)
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---
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### 🤖 调用 LLM
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```typescript
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import { LLMFactory } from '../../../common/llm/adapters/LLMFactory';
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const llm = LLMFactory.getAdapter('deepseek-v3');
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const response = await llm.chat(messages);
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// 流式
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for await (const chunk of llm.chatStream(messages)) {
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console.log(chunk.content);
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}
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```
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📚 [详细文档](./01-LLM大模型网关/)
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---
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### 📁 文件存储
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```typescript
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import { storage } from '../../../common/storage';
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// 上传
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const url = await storage.upload('path/file.pdf', buffer);
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// 下载
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const buffer = await storage.download('path/file.pdf');
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```
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📚 [详细文档](./00-通用能力层清单.md#4-存储服务)
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---
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### ⚡ 异步任务
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```typescript
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import { JobFactory } from '../../../common/jobs';
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const queue = JobFactory.getQueue();
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// 创建任务
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await queue.createJob('job-name', { taskId: 'xxx' });
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// 注册Worker
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queue.registerWorker('job-name', async (job) => {
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// 处理逻辑
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});
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```
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📚 [详细文档](./Postgres-Only异步任务处理指南.md)
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---
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### 📄 文档处理
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```typescript
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import { ExtractionClient } from '../../../common/document/ExtractionClient';
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const client = new ExtractionClient();
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const text = await client.extractText(buffer, 'pdf');
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```
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📚 [详细文档](./02-文档处理引擎/)
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---
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### 🔍 知识库检索(RAG)
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```typescript
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import { DifyClient } from '../../../common/rag/DifyClient';
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const dify = new DifyClient(apiKey, baseURL);
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const results = await dify.retrievalSearch(query, options);
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```
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📚 [详细文档](./03-RAG引擎/)
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---
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### 💾 缓存服务
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```typescript
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import { cache } from '../../../common/cache';
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await cache.set('key', value, 3600); // TTL: 3600秒
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const value = await cache.get('key');
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await cache.delete('key');
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```
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📚 [详细文档](./00-通用能力层清单.md#6-缓存服务)
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---
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### 📝 日志记录
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```typescript
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import { logger } from '../../../common/logging';
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logger.info('[Module] 操作描述', { userId: 'xxx', detail: 'xxx' });
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logger.error('[Module] 错误', { error, stack: error.stack });
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```
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📚 [详细文档](./00-通用能力层清单.md#7-日志服务)
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---
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### 🔐 认证授权
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**后端:**
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```typescript
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import { authenticate, getUserId } from '../../../common/auth';
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// 路由
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fastify.get('/api', { preHandler: [authenticate] }, handler);
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// 控制器
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const userId = getUserId(request);
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```
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**前端:**
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```typescript
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import { getAccessToken } from '@/framework/auth/api';
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const token = getAccessToken();
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// 或使用 apiClient(自动携带token)
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import apiClient from '@/common/api/axios';
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await apiClient.get('/api/xxx');
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```
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📚 [详细文档](../04-开发规范/10-模块认证规范.md)
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---
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### 📋 Prompt 管理
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```typescript
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import { PromptService } from '../../../common/prompt/prompt.service';
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const promptService = new PromptService();
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const prompt = await promptService.getActivePrompt('template_code');
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const rendered = promptService.renderPrompt(template, variables);
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```
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📚 [详细文档](./00-通用能力层清单.md#11-prompt-管理系统)
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---
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## 🏗️ 架构原则
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### ✅ 正确做法
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```typescript
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// 1. 使用通用能力,不要重复造轮子
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import { createStreamingService } from '../../../common/streaming';
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// 2. 遵循云原生规范
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await storage.upload(); // 不要用 fs.writeFileSync()
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// 3. 使用结构化日志
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logger.info('[Module] 操作', { detail }); // 不要用 console.log()
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// 4. 统一认证
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fastify.get('/api', { preHandler: [authenticate] });
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// 5. 标准化API格式
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// OpenAI Compatible, not 自定义格式
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```
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### ❌ 错误做法
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```typescript
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// 1. 自己实现已有的能力
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reply.raw.write('data: ...'); // ❌ 应该用 StreamingService
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// 2. 直接操作本地文件
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fs.writeFileSync('/tmp/file'); // ❌ 应该用 storage
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// 3. 使用 console.log
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console.log('debug'); // ❌ 应该用 logger
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// 4. 硬编码用户ID
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const userId = 'test'; // ❌ 应该用 getUserId(request)
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// 5. 自定义格式
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{ type: 'delta', content: 'xxx' } // ❌ 应该用 OpenAI Compatible
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```
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---
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## 📚 完整文档
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- [通用能力层清单(完整版)](./00-通用能力层清单.md)
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- [云原生开发规范](../04-开发规范/08-云原生开发规范.md)
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- [模块认证规范](../04-开发规范/10-模块认证规范.md)
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- [数据库开发规范](../04-开发规范/09-数据库开发规范.md)
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---
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**更新时间:** 2026-01-14
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