Files
AIclinicalresearch/docs/02-通用能力层/快速引用卡片.md
HaHafeng 3d35e9c58b 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
2026-01-14 19:09:28 +08:00

4.9 KiB
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通用能力层 - 快速引用卡片

一页纸速查表,快速找到需要的通用能力


🎯 我需要...

💬 AI 对话功能

前端:

import { AIStreamChat } from '@/shared/components/Chat';
<AIStreamChat apiEndpoint="/api/v1/xxx/chat/stream" enableDeepThinking={true} />

后端:

import { createStreamingService } from '../../../common/streaming';
const service = createStreamingService(reply);
await service.streamGenerate(messages);

📚 详细文档


🤖 调用 LLM

import { LLMFactory } from '../../../common/llm/adapters/LLMFactory';

const llm = LLMFactory.getAdapter('deepseek-v3');
const response = await llm.chat(messages);

// 流式
for await (const chunk of llm.chatStream(messages)) {
  console.log(chunk.content);
}

📚 详细文档


📁 文件存储

import { storage } from '../../../common/storage';

// 上传
const url = await storage.upload('path/file.pdf', buffer);

// 下载
const buffer = await storage.download('path/file.pdf');

📚 详细文档


异步任务

import { JobFactory } from '../../../common/jobs';

const queue = JobFactory.getQueue();

// 创建任务
await queue.createJob('job-name', { taskId: 'xxx' });

// 注册Worker
queue.registerWorker('job-name', async (job) => {
  // 处理逻辑
});

📚 详细文档


📄 文档处理

import { ExtractionClient } from '../../../common/document/ExtractionClient';

const client = new ExtractionClient();
const text = await client.extractText(buffer, 'pdf');

📚 详细文档


🔍 知识库检索RAG

import { DifyClient } from '../../../common/rag/DifyClient';

const dify = new DifyClient(apiKey, baseURL);
const results = await dify.retrievalSearch(query, options);

📚 详细文档


💾 缓存服务

import { cache } from '../../../common/cache';

await cache.set('key', value, 3600);  // TTL: 3600秒
const value = await cache.get('key');
await cache.delete('key');

📚 详细文档


📝 日志记录

import { logger } from '../../../common/logging';

logger.info('[Module] 操作描述', { userId: 'xxx', detail: 'xxx' });
logger.error('[Module] 错误', { error, stack: error.stack });

📚 详细文档


🔐 认证授权

后端:

import { authenticate, getUserId } from '../../../common/auth';

// 路由
fastify.get('/api', { preHandler: [authenticate] }, handler);

// 控制器
const userId = getUserId(request);

前端:

import { getAccessToken } from '@/framework/auth/api';
const token = getAccessToken();

// 或使用 apiClient自动携带token
import apiClient from '@/common/api/axios';
await apiClient.get('/api/xxx');

📚 详细文档


📋 Prompt 管理

import { PromptService } from '../../../common/prompt/prompt.service';

const promptService = new PromptService();
const prompt = await promptService.getActivePrompt('template_code');
const rendered = promptService.renderPrompt(template, variables);

📚 详细文档


🏗️ 架构原则

正确做法

// 1. 使用通用能力,不要重复造轮子
import { createStreamingService } from '../../../common/streaming';

// 2. 遵循云原生规范
await storage.upload();  // 不要用 fs.writeFileSync()

// 3. 使用结构化日志
logger.info('[Module] 操作', { detail });  // 不要用 console.log()

// 4. 统一认证
fastify.get('/api', { preHandler: [authenticate] });

// 5. 标准化API格式
// OpenAI Compatible, not 自定义格式

错误做法

// 1. 自己实现已有的能力
reply.raw.write('data: ...');  // ❌ 应该用 StreamingService

// 2. 直接操作本地文件
fs.writeFileSync('/tmp/file');  // ❌ 应该用 storage

// 3. 使用 console.log
console.log('debug');  // ❌ 应该用 logger

// 4. 硬编码用户ID
const userId = 'test';  // ❌ 应该用 getUserId(request)

// 5. 自定义格式
{ type: 'delta', content: 'xxx' }  // ❌ 应该用 OpenAI Compatible

📚 完整文档


更新时间: 2026-01-14