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
This commit is contained in:
233
backend/src/modules/aia/controllers/agentController.ts
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233
backend/src/modules/aia/controllers/agentController.ts
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/**
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* AIA 智能问答模块 - 智能体控制器
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* @module aia/controllers/agentController
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*
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* API 端点：
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* - GET /api/v1/aia/agents 获取智能体列表
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* - GET /api/v1/aia/agents/:id 获取智能体详情
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* - POST /api/v1/aia/intent/route 意图路由
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*/
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import type { FastifyRequest, FastifyReply } from 'fastify';
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import { logger } from '../../../common/logging/index.js';
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import * as agentService from '../services/agentService.js';
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import type { AgentStage, IntentRouteRequest } from '../types/index.js';
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/**
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* 从 JWT Token 获取用户 ID
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*/
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function getUserId(request: FastifyRequest): string {
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const userId = (request as any).user?.userId;
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if (!userId) {
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throw new Error('User not authenticated');
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}
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return userId;
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}
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// ==================== 智能体管理 ====================
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/**
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* 获取智能体列表
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* GET /api/v1/aia/agents
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*/
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export async function getAgents(
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request: FastifyRequest<{
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Querystring: { stage?: AgentStage };
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}>,
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reply: FastifyReply
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) {
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try {
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const { stage } = request.query;
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logger.info('[AIA:Controller] 获取智能体列表', { stage });
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const agents = await agentService.getAgents(stage);
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return reply.send({
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code: 0,
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data: { agents },
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});
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} catch (error) {
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logger.error('[AIA:Controller] 获取智能体列表失败', { error });
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return reply.status(500).send({
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code: -1,
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error: {
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code: 'INTERNAL_ERROR',
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message: error instanceof Error ? error.message : '服务器内部错误',
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},
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});
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}
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}
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/**
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* 获取智能体详情
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* GET /api/v1/aia/agents/:id
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*/
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export async function getAgentById(
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request: FastifyRequest<{
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Params: { id: string };
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}>,
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reply: FastifyReply
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) {
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try {
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const { id } = request.params;
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logger.info('[AIA:Controller] 获取智能体详情', { agentId: id });
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const agent = await agentService.getAgentById(id);
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if (!agent) {
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return reply.status(404).send({
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code: -1,
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error: {
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code: 'NOT_FOUND',
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message: '智能体不存在',
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},
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});
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}
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return reply.send({
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code: 0,
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data: agent,
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});
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} catch (error) {
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logger.error('[AIA:Controller] 获取智能体详情失败', { error });
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return reply.status(500).send({
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code: -1,
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error: {
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code: 'INTERNAL_ERROR',
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message: error instanceof Error ? error.message : '服务器内部错误',
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},
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});
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}
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}
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// ==================== 意图路由 ====================
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/**
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* 意图路由
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* POST /api/v1/aia/intent/route
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*
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* 根据用户输入识别意图，推荐合适的智能体
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*/
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export async function routeIntent(
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request: FastifyRequest<{
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Body: IntentRouteRequest;
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}>,
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reply: FastifyReply
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) {
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try {
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const userId = getUserId(request);
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const { query } = request.body;
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logger.info('[AIA:Controller] 意图路由', { userId, queryLength: query?.length });
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if (!query || query.trim().length < 2) {
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return reply.status(400).send({
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code: -1,
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error: {
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code: 'VALIDATION_ERROR',
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message: '查询内容至少需要2个字符',
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},
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});
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}
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// 简单的关键词匹配意图识别
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// TODO: 后续可以使用 LLM 或专门的意图识别模型
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const intent = await matchIntent(query);
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return reply.send({
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code: 0,
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data: intent,
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});
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} catch (error) {
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logger.error('[AIA:Controller] 意图路由失败', { error });
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return reply.status(500).send({
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code: -1,
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error: {
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code: 'INTERNAL_ERROR',
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message: error instanceof Error ? error.message : '服务器内部错误',
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},
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});
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}
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}
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/**
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* 简单的关键词匹配意图识别
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*/
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async function matchIntent(query: string): Promise<{
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agentId: string;
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agentName: string;
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confidence: number;
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prefillPrompt: string;
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}> {
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const queryLower = query.toLowerCase();
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// 关键词映射
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const intentPatterns = [
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{
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patterns: ['研究设计', '方案设计', 'rct', '队列', '病例对照', '样本量'],
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agentId: 'research-design',
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agentName: '科研设计小助手',
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},
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{
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patterns: ['文献', '检索', 'pubmed', '筛选', 'meta', '系统综述'],
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agentId: 'literature-assistant',
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agentName: '文献检索助手',
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},
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{
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patterns: ['数据', '清洗', '缺失值', '异常值', '整理'],
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agentId: 'data-assistant',
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agentName: '数据管理助手',
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},
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{
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patterns: ['统计', '分析', 'spss', 't检验', '卡方', '回归', 'p值'],
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agentId: 'stat-assistant',
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agentName: '统计分析小助手',
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},
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{
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patterns: ['论文', '写作', '润色', '翻译', 'sci', '摘要', 'introduction'],
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agentId: 'writing-assistant',
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agentName: '论文撰写助手',
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},
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{
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patterns: ['投稿', '期刊', '审稿', '发表', 'if', '影响因子'],
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agentId: 'publish-assistant',
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agentName: '投稿指导助手',
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},
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];
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// 计算匹配度
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let bestMatch = {
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agentId: 'research-design',
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agentName: '科研设计小助手',
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confidence: 0.3, // 默认较低置信度
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matchCount: 0,
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};
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for (const pattern of intentPatterns) {
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let matchCount = 0;
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for (const keyword of pattern.patterns) {
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if (queryLower.includes(keyword)) {
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matchCount++;
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}
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}
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if (matchCount > bestMatch.matchCount) {
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bestMatch = {
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agentId: pattern.agentId,
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agentName: pattern.agentName,
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confidence: Math.min(0.5 + matchCount * 0.15, 0.95),
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matchCount,
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};
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}
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}
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return {
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agentId: bestMatch.agentId,
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agentName: bestMatch.agentName,
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confidence: bestMatch.confidence,
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prefillPrompt: query, // 直接使用原始查询作为预填充
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};
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}
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288
backend/src/modules/aia/controllers/conversationController.ts
Normal file
288
backend/src/modules/aia/controllers/conversationController.ts
Normal file
@@ -0,0 +1,288 @@
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/**
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* AIA 智能问答模块 - 对话控制器
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* @module aia/controllers/conversationController
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*
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* API 端点：
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* - GET /api/v1/aia/conversations 获取对话列表
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* - POST /api/v1/aia/conversations 创建对话
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* - GET /api/v1/aia/conversations/:id 获取对话详情
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* - DELETE /api/v1/aia/conversations/:id 删除对话
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* - POST /api/v1/aia/conversations/:id/messages/stream 发送消息（流式）
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*/
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import type { FastifyRequest, FastifyReply } from 'fastify';
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import { logger } from '../../../common/logging/index.js';
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import * as conversationService from '../services/conversationService.js';
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import type { CreateConversationRequest, SendMessageRequest } from '../types/index.js';
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/**
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* 从 JWT Token 获取用户 ID
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*/
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function getUserId(request: FastifyRequest): string {
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const userId = (request as any).user?.userId;
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if (!userId) {
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throw new Error('User not authenticated');
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}
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return userId;
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}
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// ==================== 对话管理 ====================
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/**
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* 获取对话列表
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* GET /api/v1/aia/conversations
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*/
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export async function getConversations(
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request: FastifyRequest<{
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Querystring: {
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agentId?: string;
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projectId?: string;
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page?: string;
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pageSize?: string;
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};
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}>,
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reply: FastifyReply
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) {
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try {
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const userId = getUserId(request);
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const { agentId, projectId, page, pageSize } = request.query;
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logger.info('[AIA:Controller] 获取对话列表', { userId, agentId, projectId });
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const result = await conversationService.getConversations(userId, {
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agentId,
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projectId: projectId === 'null' ? null : projectId,
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page: page ? parseInt(page) : 1,
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pageSize: pageSize ? parseInt(pageSize) : 20,
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});
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return reply.send({
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code: 0,
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data: {
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conversations: result.conversations,
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pagination: {
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total: result.total,
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page: page ? parseInt(page) : 1,
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pageSize: pageSize ? parseInt(pageSize) : 20,
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totalPages: Math.ceil(result.total / (pageSize ? parseInt(pageSize) : 20)),
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},
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},
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});
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} catch (error) {
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logger.error('[AIA:Controller] 获取对话列表失败', { error });
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return reply.status(500).send({
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code: -1,
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error: {
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code: 'INTERNAL_ERROR',
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message: error instanceof Error ? error.message : '服务器内部错误',
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},
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});
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}
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}
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/**
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* 创建对话
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* POST /api/v1/aia/conversations
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*/
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export async function createConversation(
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request: FastifyRequest<{
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Body: CreateConversationRequest;
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}>,
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reply: FastifyReply
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) {
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try {
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const userId = getUserId(request);
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const { agentId, projectId, title } = request.body;
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logger.info('[AIA:Controller] 创建对话', { userId, agentId, projectId });
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if (!agentId) {
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return reply.status(400).send({
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code: -1,
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error: {
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code: 'VALIDATION_ERROR',
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message: 'agentId 是必填项',
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},
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});
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}
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const conversation = await conversationService.createConversation(userId, {
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agentId,
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projectId,
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title,
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});
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return reply.send({
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code: 0,
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data: conversation,
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||||
});
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} catch (error) {
|
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logger.error('[AIA:Controller] 创建对话失败', { error });
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return reply.status(500).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'INTERNAL_ERROR',
|
||||
message: error instanceof Error ? error.message : '服务器内部错误',
|
||||
},
|
||||
});
|
||||
}
|
||||
}
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||||
|
||||
/**
|
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* 获取对话详情
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* GET /api/v1/aia/conversations/:id
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*/
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export async function getConversationById(
|
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request: FastifyRequest<{
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||||
Params: { id: string };
|
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Querystring: { limit?: string };
|
||||
}>,
|
||||
reply: FastifyReply
|
||||
) {
|
||||
try {
|
||||
const userId = getUserId(request);
|
||||
const { id } = request.params;
|
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const { limit } = request.query;
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|
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logger.info('[AIA:Controller] 获取对话详情', { userId, conversationId: id });
|
||||
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||||
const conversation = await conversationService.getConversationById(
|
||||
userId,
|
||||
id,
|
||||
limit ? parseInt(limit) : 50
|
||||
);
|
||||
|
||||
if (!conversation) {
|
||||
return reply.status(404).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'NOT_FOUND',
|
||||
message: '对话不存在',
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
return reply.send({
|
||||
code: 0,
|
||||
data: conversation,
|
||||
});
|
||||
} catch (error) {
|
||||
logger.error('[AIA:Controller] 获取对话详情失败', { error });
|
||||
return reply.status(500).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'INTERNAL_ERROR',
|
||||
message: error instanceof Error ? error.message : '服务器内部错误',
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除对话
|
||||
* DELETE /api/v1/aia/conversations/:id
|
||||
*/
|
||||
export async function deleteConversation(
|
||||
request: FastifyRequest<{
|
||||
Params: { id: string };
|
||||
}>,
|
||||
reply: FastifyReply
|
||||
) {
|
||||
try {
|
||||
const userId = getUserId(request);
|
||||
const { id } = request.params;
|
||||
|
||||
logger.info('[AIA:Controller] 删除对话', { userId, conversationId: id });
|
||||
|
||||
const deleted = await conversationService.deleteConversation(userId, id);
|
||||
|
||||
if (!deleted) {
|
||||
return reply.status(404).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'NOT_FOUND',
|
||||
message: '对话不存在',
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
return reply.send({
|
||||
code: 0,
|
||||
data: { deleted: true },
|
||||
});
|
||||
} catch (error) {
|
||||
logger.error('[AIA:Controller] 删除对话失败', { error });
|
||||
return reply.status(500).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'INTERNAL_ERROR',
|
||||
message: error instanceof Error ? error.message : '服务器内部错误',
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 消息发送 ====================
|
||||
|
||||
/**
|
||||
* 发送消息（流式输出）
|
||||
* POST /api/v1/aia/conversations/:id/messages/stream
|
||||
*/
|
||||
export async function sendMessageStream(
|
||||
request: FastifyRequest<{
|
||||
Params: { id: string };
|
||||
Body: SendMessageRequest;
|
||||
}>,
|
||||
reply: FastifyReply
|
||||
) {
|
||||
try {
|
||||
const userId = getUserId(request);
|
||||
const { id } = request.params;
|
||||
const { content, attachmentIds, enableDeepThinking } = request.body;
|
||||
|
||||
logger.info('[AIA:Controller] 发送消息', {
|
||||
userId,
|
||||
conversationId: id,
|
||||
contentLength: content?.length,
|
||||
attachmentCount: attachmentIds?.length || 0,
|
||||
});
|
||||
|
||||
if (!content || content.trim().length === 0) {
|
||||
return reply.status(400).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'VALIDATION_ERROR',
|
||||
message: '消息内容不能为空',
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
// 流式输出
|
||||
await conversationService.sendMessageStream(
|
||||
userId,
|
||||
id,
|
||||
{ content, attachmentIds, enableDeepThinking },
|
||||
reply
|
||||
);
|
||||
|
||||
} catch (error) {
|
||||
const errorMessage = error instanceof Error ? error.message : String(error);
|
||||
logger.error('[AIA:Controller] 发送消息失败', {
|
||||
error: errorMessage,
|
||||
stack: error instanceof Error ? error.stack : undefined,
|
||||
conversationId: request.params.id,
|
||||
});
|
||||
|
||||
// 如果还没有发送响应头，返回错误
|
||||
if (!reply.sent) {
|
||||
return reply.status(500).send({
|
||||
code: -1,
|
||||
error: {
|
||||
code: 'INTERNAL_ERROR',
|
||||
message: errorMessage,
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
16
backend/src/modules/aia/index.ts
Normal file
16
backend/src/modules/aia/index.ts
Normal file
@@ -0,0 +1,16 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 入口文件
|
||||
* @module aia
|
||||
*
|
||||
* 功能：
|
||||
* - 智能体大厅（Dashboard）
|
||||
* - 多轮对话
|
||||
* - 深度思考模式
|
||||
* - 附件上传
|
||||
* - 意图路由
|
||||
*/
|
||||
|
||||
import aiaRoutes from './routes/index.js';
|
||||
|
||||
export { aiaRoutes };
|
||||
|
||||
69
backend/src/modules/aia/routes/index.ts
Normal file
69
backend/src/modules/aia/routes/index.ts
Normal file
@@ -0,0 +1,69 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 路由定义
|
||||
* @module aia/routes
|
||||
*
|
||||
* API前缀: /api/v1/aia
|
||||
*/
|
||||
|
||||
import type { FastifyInstance, FastifyRequest, FastifyReply } from 'fastify';
|
||||
import * as conversationController from '../controllers/conversationController.js';
|
||||
import * as agentController from '../controllers/agentController.js';
|
||||
import { authenticate } from '../../../common/auth/auth.middleware.js';
|
||||
|
||||
export default async function aiaRoutes(fastify: FastifyInstance) {
|
||||
// ==================== 智能体管理 ====================
|
||||
|
||||
// 获取智能体列表（公开接口，用于首页展示）
|
||||
// GET /api/v1/aia/agents
|
||||
fastify.get('/agents', async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return agentController.getAgents(request as any, reply);
|
||||
});
|
||||
|
||||
// 获取智能体详情
|
||||
// GET /api/v1/aia/agents/:id
|
||||
fastify.get('/agents/:id', async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return agentController.getAgentById(request as any, reply);
|
||||
});
|
||||
|
||||
// ==================== 意图路由 ====================
|
||||
|
||||
// 意图路由（需要认证）
|
||||
// POST /api/v1/aia/intent/route
|
||||
fastify.post('/intent/route', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return agentController.routeIntent(request as any, reply);
|
||||
});
|
||||
|
||||
// ==================== 对话管理 ====================
|
||||
|
||||
// 获取对话列表
|
||||
// GET /api/v1/aia/conversations
|
||||
fastify.get('/conversations', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return conversationController.getConversations(request as any, reply);
|
||||
});
|
||||
|
||||
// 创建对话
|
||||
// POST /api/v1/aia/conversations
|
||||
fastify.post('/conversations', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return conversationController.createConversation(request as any, reply);
|
||||
});
|
||||
|
||||
// 获取对话详情
|
||||
// GET /api/v1/aia/conversations/:id
|
||||
fastify.get('/conversations/:id', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return conversationController.getConversationById(request as any, reply);
|
||||
});
|
||||
|
||||
// 删除对话
|
||||
// DELETE /api/v1/aia/conversations/:id
|
||||
fastify.delete('/conversations/:id', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return conversationController.deleteConversation(request as any, reply);
|
||||
});
|
||||
|
||||
// ==================== 消息发送 ====================
|
||||
|
||||
// 发送消息（流式输出）
|
||||
// POST /api/v1/aia/conversations/:id/messages/stream
|
||||
fastify.post('/conversations/:id/messages/stream', { preHandler: [authenticate] }, async (request: FastifyRequest, reply: FastifyReply) => {
|
||||
return conversationController.sendMessageStream(request as any, reply);
|
||||
});
|
||||
}
|
||||
382
backend/src/modules/aia/services/agentService.ts
Normal file
382
backend/src/modules/aia/services/agentService.ts
Normal file
@@ -0,0 +1,382 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 智能体服务
|
||||
* @module aia/services/agentService
|
||||
*
|
||||
* 负责智能体配置管理、Prompt 获取
|
||||
* 12个智能体配置（对应前端 AgentHub）
|
||||
*/
|
||||
|
||||
import { logger } from '../../../common/logging/index.js';
|
||||
import { cache } from '../../../common/cache/index.js';
|
||||
import type { Agent, AgentStage } from '../types/index.js';
|
||||
|
||||
// ==================== 智能体配置 ====================
|
||||
|
||||
/**
|
||||
* 12个智能体配置（与前端保持一致）
|
||||
*/
|
||||
const AGENTS: Agent[] = [
|
||||
// Phase 1: 选题优化智能体
|
||||
{
|
||||
id: 'TOPIC_01',
|
||||
name: '科学问题梳理',
|
||||
description: '从科学问题的清晰度、系统性、可验证性等角度使用科学理论对您的科学问题进行全面的评价。',
|
||||
icon: '🔬',
|
||||
stage: 'topic',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是一个专业的临床研究方法学专家，擅长科学问题的梳理与评价。
|
||||
|
||||
你的任务是：
|
||||
1. 从科学问题的清晰度、系统性、可验证性等角度进行全面评价
|
||||
2. 使用科学理论和方法学原则指导用户完善问题
|
||||
3. 提供具体、可操作的建议
|
||||
|
||||
请用专业但易懂的语言回答，结构清晰，逻辑严密。`,
|
||||
welcomeMessage: '你好！我是**科学问题梳理助手**。请告诉我你感兴趣的研究方向，我将从科学性、创新性等维度帮你梳理。',
|
||||
},
|
||||
{
|
||||
id: 'TOPIC_02',
|
||||
name: 'PICO 梳理',
|
||||
description: '基于科学问题梳理研究对象、干预（暴露）、对照和结局指标，并评价并给出合理化的建议。',
|
||||
icon: '🎯',
|
||||
stage: 'topic',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是一个 PICO 框架专家，擅长将临床问题拆解为结构化的研究要素。
|
||||
|
||||
PICO 框架：
|
||||
- P (Population): 研究人群
|
||||
- I (Intervention): 干预措施/暴露因素
|
||||
- C (Comparison): 对照
|
||||
- O (Outcome): 结局指标
|
||||
|
||||
请帮助用户清晰地定义每个要素，并评价其科学性和可行性。`,
|
||||
welcomeMessage: '你好！我是**PICO梳理助手**。请描述你的研究想法，我来帮你拆解为 P (人群)、I (干预)、C (对照)、O (结局)。',
|
||||
},
|
||||
{
|
||||
id: 'TOPIC_03',
|
||||
name: '选题评价',
|
||||
description: '从创新性、临床价值、科学性和可行性等方面使用科学理论对您的临床问题进行全面的评价。',
|
||||
icon: '✅',
|
||||
stage: 'topic',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是一个临床研究选题评审专家，擅长从多维度评价研究选题。
|
||||
|
||||
评价维度：
|
||||
1. 创新性：是否填补知识空白，有新颖性
|
||||
2. 临床价值：对临床实践的指导意义
|
||||
3. 科学性：研究设计的严谨性和可行性
|
||||
4. 可行性：资源、时间、技术条件
|
||||
|
||||
请客观评价，指出优势和改进空间。`,
|
||||
welcomeMessage: '你好！我是**选题评价助手**。请提供你的初步选题，我将从创新性、临床价值等方面进行评估。',
|
||||
},
|
||||
|
||||
// Phase 2: 方案设计智能体
|
||||
{
|
||||
id: 'DESIGN_04',
|
||||
name: '观察指标设计',
|
||||
description: '基于研究设计和因果关系提供可能的观察指标集。',
|
||||
icon: '👁️',
|
||||
stage: 'design',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是观察指标设计专家，擅长根据研究目的推荐合适的观察指标。
|
||||
|
||||
指标类型：
|
||||
- 主要结局指标（Primary Outcome）
|
||||
- 次要结局指标（Secondary Outcome）
|
||||
- 安全性指标
|
||||
- 中间指标
|
||||
|
||||
请考虑指标的可测量性、临床意义、客观性。`,
|
||||
welcomeMessage: '你好！我是**观察指标设计助手**。请告诉我你的研究目的，我来帮你推荐主要和次要观察指标。',
|
||||
},
|
||||
{
|
||||
id: 'DESIGN_05',
|
||||
name: '病例报告表设计',
|
||||
description: '基于研究方案设计梳理观察指标集并给出建议的病例报告表框架。',
|
||||
icon: '📋',
|
||||
stage: 'design',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是 CRF (Case Report Form) 设计专家。
|
||||
|
||||
CRF 设计要点：
|
||||
1. 基线资料采集
|
||||
2. 观察指标记录
|
||||
3. 随访时间点设计
|
||||
4. 数据质控要求
|
||||
|
||||
请提供结构清晰、逻辑合理的 CRF 框架。`,
|
||||
welcomeMessage: '你好！我是**CRF设计助手**。我可以帮你构建病例报告表的框架。',
|
||||
},
|
||||
{
|
||||
id: 'DESIGN_06',
|
||||
name: '样本量计算',
|
||||
description: '基于研究阶段和研究设计为研究提供科学合理的样本量估算结果。',
|
||||
icon: '🔢',
|
||||
stage: 'design',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是样本量计算专家，擅长各种研究设计的样本量估算。
|
||||
|
||||
常见研究类型：
|
||||
- RCT (随机对照试验)
|
||||
- 队列研究
|
||||
- 病例对照研究
|
||||
- 诊断性试验
|
||||
|
||||
请根据用户提供的参数（α、β、效应量、脱失率等）进行科学的样本量计算。`,
|
||||
welcomeMessage: '你好！需要计算样本量吗？请告诉我研究类型（如RCT、队列研究）和主要指标的预期值。',
|
||||
},
|
||||
{
|
||||
id: 'DESIGN_07',
|
||||
name: '临床研究方案撰写',
|
||||
description: '基于科学问题、PICOS等信息，给出一个初步的临床研究设计方案，请尽量多给一些信息和需求。',
|
||||
icon: '📝',
|
||||
stage: 'design',
|
||||
color: '#4F6EF2',
|
||||
systemPrompt: `你是临床研究方案撰写专家，可以帮助用户撰写完整的研究方案。
|
||||
|
||||
方案结构：
|
||||
1. 研究背景与目的
|
||||
2. 研究设计（类型、盲法、随机等）
|
||||
3. 研究对象（纳入/排除标准）
|
||||
4. 干预措施
|
||||
5. 观察指标
|
||||
6. 统计分析计划
|
||||
7. 质量控制
|
||||
8. 伦理考虑
|
||||
|
||||
请基于用户提供的信息，给出结构完整、逻辑严密的方案。`,
|
||||
welcomeMessage: '你好！欢迎来到**方案设计工作台**。我们将基于科学问题和PICOS信息，共同撰写一份完整的临床研究方案。',
|
||||
},
|
||||
|
||||
// Phase 3: 方案预评审
|
||||
{
|
||||
id: 'REVIEW_08',
|
||||
name: '方法学评审智能体',
|
||||
description: '从研究问题、研究方案和临床意义方面，对研究进行临床研究方法学的全面评价。',
|
||||
icon: '🛡️',
|
||||
stage: 'review',
|
||||
color: '#CA8A04',
|
||||
systemPrompt: `你是一个资深的临床研究方法学评审专家，模拟审稿人视角进行评审。
|
||||
|
||||
评审要点：
|
||||
1. 研究问题是否明确、有价值
|
||||
2. 研究设计是否科学、严谨
|
||||
3. 纳入/排除标准是否合理
|
||||
4. 样本量是否充足
|
||||
5. 统计方法是否适当
|
||||
6. 是否存在偏倚风险
|
||||
|
||||
请指出优势和需要改进的地方。`,
|
||||
welcomeMessage: '你好！我是**方法学评审助手**。请上传你的方案草稿，我将模拟审稿人视角进行方法学审查。',
|
||||
},
|
||||
|
||||
// Phase 4: 工具类智能体（仅配置，不提供对话）
|
||||
{
|
||||
id: 'TOOL_09',
|
||||
name: '数据评价与预处理',
|
||||
description: '对现有数据的质量进行自动评价，并给出数据质量报告。',
|
||||
icon: '💾',
|
||||
stage: 'data',
|
||||
color: '#0D9488',
|
||||
isTool: true,
|
||||
targetModule: '/dc',
|
||||
},
|
||||
{
|
||||
id: 'TOOL_10',
|
||||
name: '智能统计分析',
|
||||
description: '内置3条智能研究路径，以及近百种统计分析工具。',
|
||||
icon: '📊',
|
||||
stage: 'data',
|
||||
color: '#0D9488',
|
||||
isTool: true,
|
||||
targetModule: '/dc/analysis',
|
||||
},
|
||||
|
||||
// Phase 5: 写作助手
|
||||
{
|
||||
id: 'WRITING_11',
|
||||
name: '论文润色',
|
||||
description: '结合目标杂志，提供专业化的润色服务。',
|
||||
icon: '✍️',
|
||||
stage: 'writing',
|
||||
color: '#9333EA',
|
||||
systemPrompt: `You are a professional academic editor specializing in medical research papers.
|
||||
|
||||
Your expertise includes:
|
||||
- Grammar and syntax correction
|
||||
- Academic tone refinement
|
||||
- Clarity and flow improvement
|
||||
- Journal-specific style guidance
|
||||
|
||||
Please provide precise, actionable suggestions.`,
|
||||
welcomeMessage: 'Please paste the text you want to polish. I will check grammar, flow, and academic tone.',
|
||||
},
|
||||
{
|
||||
id: 'WRITING_12',
|
||||
name: '论文翻译',
|
||||
description: '结合目标杂志，提供专业化的翻译并进行润色。',
|
||||
icon: '🌐',
|
||||
stage: 'writing',
|
||||
color: '#9333EA',
|
||||
systemPrompt: `你是一个专业的医学论文翻译专家，精通中英互译。
|
||||
|
||||
翻译要求：
|
||||
1. 准确传达原意
|
||||
2. 符合医学术语规范
|
||||
3. 保持学术风格
|
||||
4. 流畅自然
|
||||
|
||||
请提供地道的学术英语翻译。`,
|
||||
welcomeMessage: '你好！请贴入需要翻译的段落，我将为你提供地道的学术英语翻译。',
|
||||
},
|
||||
];
|
||||
|
||||
// 缓存键前缀
|
||||
const CACHE_KEY_PREFIX = 'aia:agent:';
|
||||
const CACHE_TTL = 3600; // 1小时
|
||||
|
||||
// ==================== 智能体查询 ====================
|
||||
|
||||
/**
|
||||
* 获取所有智能体列表
|
||||
*/
|
||||
export async function getAllAgents(): Promise<Agent[]> {
|
||||
const cacheKey = `${CACHE_KEY_PREFIX}all`;
|
||||
|
||||
// 尝试从缓存获取
|
||||
const cached = await cache.get(cacheKey);
|
||||
if (cached) {
|
||||
logger.debug('[AIA:AgentService] 从缓存获取智能体列表');
|
||||
return cached as Agent[];
|
||||
}
|
||||
|
||||
// 返回预设配置
|
||||
await cache.set(cacheKey, AGENTS, CACHE_TTL);
|
||||
|
||||
logger.info('[AIA:AgentService] 获取智能体列表', { count: AGENTS.length });
|
||||
return AGENTS;
|
||||
}
|
||||
|
||||
/**
|
||||
* 根据 ID 获取智能体
|
||||
*/
|
||||
export async function getAgentById(agentId: string): Promise<Agent | null> {
|
||||
const cacheKey = `${CACHE_KEY_PREFIX}${agentId}`;
|
||||
|
||||
// 尝试从缓存获取
|
||||
const cached = await cache.get(cacheKey);
|
||||
if (cached) {
|
||||
logger.debug('[AIA:AgentService] 从缓存获取智能体', { agentId });
|
||||
return cached as Agent;
|
||||
}
|
||||
|
||||
// 从预设配置中查找
|
||||
const agent = AGENTS.find(a => a.id === agentId);
|
||||
|
||||
if (agent) {
|
||||
await cache.set(cacheKey, agent, CACHE_TTL);
|
||||
logger.info('[AIA:AgentService] 获取智能体', { agentId, name: agent.name });
|
||||
} else {
|
||||
logger.warn('[AIA:AgentService] 智能体不存在', { agentId });
|
||||
}
|
||||
|
||||
return agent || null;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取智能体列表（支持阶段过滤）
|
||||
*/
|
||||
export async function getAgents(stage?: AgentStage): Promise<Agent[]> {
|
||||
const allAgents = await getAllAgents();
|
||||
if (stage) {
|
||||
return allAgents.filter(a => a.stage === stage);
|
||||
}
|
||||
return allAgents;
|
||||
}
|
||||
|
||||
/**
|
||||
* 根据阶段获取智能体列表
|
||||
*/
|
||||
export async function getAgentsByStage(stage: AgentStage): Promise<Agent[]> {
|
||||
return getAgents(stage);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取智能体的系统提示词
|
||||
*/
|
||||
export async function getAgentSystemPrompt(agentId: string): Promise<string> {
|
||||
const agent = await getAgentById(agentId);
|
||||
|
||||
if (!agent) {
|
||||
throw new Error(`智能体不存在: ${agentId}`);
|
||||
}
|
||||
|
||||
if (agent.isTool) {
|
||||
throw new Error(`智能体 ${agentId} 是工具类，不支持对话`);
|
||||
}
|
||||
|
||||
if (!agent.systemPrompt) {
|
||||
throw new Error(`智能体 ${agentId} 未配置系统提示词`);
|
||||
}
|
||||
|
||||
return agent.systemPrompt;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取智能体的欢迎语
|
||||
*/
|
||||
export async function getAgentWelcomeMessage(agentId: string): Promise<string> {
|
||||
const agent = await getAgentById(agentId);
|
||||
|
||||
if (!agent) {
|
||||
return '你好！有什么可以帮您的？';
|
||||
}
|
||||
|
||||
return agent.welcomeMessage || '你好！有什么可以帮您的？';
|
||||
}
|
||||
|
||||
/**
|
||||
* 意图路由：根据用户输入推荐智能体
|
||||
* TODO: 后续可接入向量检索或意图分类模型
|
||||
*/
|
||||
export async function routeIntent(query: string): Promise<{
|
||||
agentId: string;
|
||||
confidence: number;
|
||||
reason: string;
|
||||
}> {
|
||||
const lowerQuery = query.toLowerCase();
|
||||
|
||||
// 简单关键词匹配（后续优化为向量检索）
|
||||
if (lowerQuery.includes('pico') || lowerQuery.includes('人群') || lowerQuery.includes('干预')) {
|
||||
return { agentId: 'TOPIC_02', confidence: 0.8, reason: '检测到PICO相关关键词' };
|
||||
}
|
||||
|
||||
if (lowerQuery.includes('样本量') || lowerQuery.includes('sample size')) {
|
||||
return { agentId: 'DESIGN_06', confidence: 0.9, reason: '检测到样本量计算需求' };
|
||||
}
|
||||
|
||||
if (lowerQuery.includes('翻译') || lowerQuery.includes('translate')) {
|
||||
return { agentId: 'WRITING_12', confidence: 0.85, reason: '检测到翻译需求' };
|
||||
}
|
||||
|
||||
if (lowerQuery.includes('润色') || lowerQuery.includes('polish') || lowerQuery.includes('修改')) {
|
||||
return { agentId: 'WRITING_11', confidence: 0.85, reason: '检测到润色需求' };
|
||||
}
|
||||
|
||||
// 默认推荐科学问题梳理
|
||||
return { agentId: 'TOPIC_01', confidence: 0.6, reason: '默认推荐' };
|
||||
}
|
||||
|
||||
/**
|
||||
* 清除智能体缓存
|
||||
*/
|
||||
export async function clearAgentCache(agentId?: string): Promise<void> {
|
||||
if (agentId) {
|
||||
await cache.delete(`${CACHE_KEY_PREFIX}${agentId}`);
|
||||
logger.info('[AIA:AgentService] 清除智能体缓存', { agentId });
|
||||
} else {
|
||||
await cache.delete(`${CACHE_KEY_PREFIX}all`);
|
||||
logger.info('[AIA:AgentService] 清除所有智能体缓存');
|
||||
}
|
||||
}
|
||||
113
backend/src/modules/aia/services/attachmentService.ts
Normal file
113
backend/src/modules/aia/services/attachmentService.ts
Normal file
@@ -0,0 +1,113 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 附件处理服务
|
||||
* @module aia/services/attachmentService
|
||||
*
|
||||
* 负责：
|
||||
* - 附件上传（对接存储服务）
|
||||
* - 文档内容提取（对接文档处理引擎）
|
||||
* - Token 截断控制（30k Token 上限）
|
||||
*/
|
||||
|
||||
import { logger } from '../../../common/logging/index.js';
|
||||
import { storage } from '../../../common/storage/index.js';
|
||||
import { ExtractionClient } from '../../../common/document/ExtractionClient.js';
|
||||
import type { Attachment } from '../types/index.js';
|
||||
|
||||
// ==================== 常量配置 ====================
|
||||
|
||||
const MAX_ATTACHMENTS = 5;
|
||||
const MAX_TOKENS_PER_ATTACHMENT = 30000; // 单个附件最大 30k Token
|
||||
const ALLOWED_FILE_TYPES = ['pdf', 'docx', 'txt', 'xlsx', 'doc'];
|
||||
|
||||
// ==================== 附件上传 ====================
|
||||
|
||||
/**
|
||||
* 上传附件并提取文本
|
||||
*/
|
||||
export async function uploadAttachment(
|
||||
userId: string,
|
||||
conversationId: string,
|
||||
file: {
|
||||
filename: string;
|
||||
mimetype: string;
|
||||
buffer: Buffer;
|
||||
}
|
||||
): Promise<Attachment> {
|
||||
// 1. 验证文件类型
|
||||
const ext = file.filename.split('.').pop()?.toLowerCase();
|
||||
if (!ext || !ALLOWED_FILE_TYPES.includes(ext)) {
|
||||
throw new Error(`不支持的文件类型: ${ext}。支持: ${ALLOWED_FILE_TYPES.join(', ')}`);
|
||||
}
|
||||
|
||||
// 2. 上传到存储服务
|
||||
const storageKey = `aia/${userId}/${conversationId}/${Date.now()}_${file.filename}`;
|
||||
const url = await storage.upload(storageKey, file.buffer, {
|
||||
contentType: file.mimetype,
|
||||
});
|
||||
|
||||
logger.info('[AIA:AttachmentService] 附件上传成功', {
|
||||
filename: file.filename,
|
||||
url,
|
||||
});
|
||||
|
||||
// 3. 提取文本内容（异步处理）
|
||||
let extractedText = '';
|
||||
try {
|
||||
const extractionClient = new ExtractionClient();
|
||||
extractedText = await extractionClient.extractText(file.buffer, ext);
|
||||
|
||||
// 4. Token 截断控制
|
||||
const tokens = estimateTokens(extractedText);
|
||||
if (tokens > MAX_TOKENS_PER_ATTACHMENT) {
|
||||
const ratio = MAX_TOKENS_PER_ATTACHMENT / tokens;
|
||||
const truncatedLength = Math.floor(extractedText.length * ratio);
|
||||
extractedText = extractedText.slice(0, truncatedLength) + '\n\n[内容已截断，超过30k Token限制]';
|
||||
|
||||
logger.info('[AIA:AttachmentService] 附件内容截断', {
|
||||
originalTokens: tokens,
|
||||
truncatedTokens: MAX_TOKENS_PER_ATTACHMENT,
|
||||
filename: file.filename,
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error('[AIA:AttachmentService] 文本提取失败', {
|
||||
error,
|
||||
filename: file.filename,
|
||||
});
|
||||
extractedText = '[文档内容提取失败]';
|
||||
}
|
||||
|
||||
// 5. 构建附件对象
|
||||
const attachment: Attachment = {
|
||||
id: `att-${Date.now()}`,
|
||||
name: file.filename,
|
||||
url,
|
||||
size: file.buffer.length,
|
||||
mimeType: file.mimetype,
|
||||
extractedText,
|
||||
tokens: estimateTokens(extractedText),
|
||||
};
|
||||
|
||||
return attachment;
|
||||
}
|
||||
|
||||
/**
|
||||
* 批量获取附件文本内容
|
||||
*/
|
||||
export async function getAttachmentsText(attachmentIds: string[]): Promise<string> {
|
||||
// TODO: 从存储中获取附件并提取文本
|
||||
// 当前版本：简化实现，假设附件文本已在消息的 attachments 字段中
|
||||
|
||||
logger.debug('[AIA:AttachmentService] 获取附件文本', { attachmentIds });
|
||||
return '';
|
||||
}
|
||||
|
||||
/**
|
||||
* 估算 Token 数量
|
||||
*/
|
||||
function estimateTokens(text: string): number {
|
||||
const chineseChars = (text.match(/[\u4e00-\u9fa5]/g) || []).length;
|
||||
const otherChars = text.length - chineseChars;
|
||||
return Math.ceil(chineseChars / 1.5 + otherChars / 4);
|
||||
}
|
||||
|
||||
398
backend/src/modules/aia/services/conversationService.ts
Normal file
398
backend/src/modules/aia/services/conversationService.ts
Normal file
@@ -0,0 +1,398 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 对话服务（重构版）
|
||||
* @module aia/services/conversationService
|
||||
*
|
||||
* 使用通用能力层：
|
||||
* - StreamingService: OpenAI Compatible 流式响应
|
||||
* - 深度思考处理（<think> 标签）
|
||||
* - 智能体配置管理
|
||||
*
|
||||
* @version 2.0
|
||||
*/
|
||||
|
||||
import { FastifyReply } from 'fastify';
|
||||
import { logger } from '../../../common/logging/index.js';
|
||||
import { prisma } from '../../../config/database.js';
|
||||
import { streamChat, createStreamingService } from '../../../common/streaming/index.js';
|
||||
import type { OpenAIMessage, StreamOptions } from '../../../common/streaming/index.js';
|
||||
import * as agentService from './agentService.js';
|
||||
import type {
|
||||
Conversation,
|
||||
Message,
|
||||
CreateConversationRequest,
|
||||
SendMessageRequest,
|
||||
Attachment,
|
||||
} from '../types/index.js';
|
||||
|
||||
// ==================== 常量配置 ====================
|
||||
|
||||
const DEFAULT_MODEL = 'deepseek-v3';
|
||||
const MAX_CONTEXT_MESSAGES = 20;
|
||||
const MAX_CONTEXT_TOKENS = 8000;
|
||||
|
||||
// ==================== 对话管理 ====================
|
||||
|
||||
/**
|
||||
* 创建新对话
|
||||
*/
|
||||
export async function createConversation(
|
||||
userId: string,
|
||||
request: CreateConversationRequest
|
||||
): Promise<Conversation> {
|
||||
const { agentId, projectId, title } = request;
|
||||
|
||||
// 验证智能体是否存在
|
||||
const agent = await agentService.getAgentById(agentId);
|
||||
if (!agent) {
|
||||
throw new Error(`智能体不存在: ${agentId}`);
|
||||
}
|
||||
|
||||
if (agent.isTool) {
|
||||
throw new Error(`智能体 ${agentId} 是工具类，不支持创建对话`);
|
||||
}
|
||||
|
||||
// 生成默认标题
|
||||
const conversationTitle = title || `与${agent.name}的对话`;
|
||||
|
||||
const conversation = await prisma.conversation.create({
|
||||
data: {
|
||||
userId,
|
||||
agentId,
|
||||
projectId: projectId || null,
|
||||
title: conversationTitle,
|
||||
},
|
||||
});
|
||||
|
||||
logger.info('[AIA:ConversationService] 创建对话', {
|
||||
conversationId: conversation.id,
|
||||
userId,
|
||||
agentId,
|
||||
});
|
||||
|
||||
return {
|
||||
id: conversation.id,
|
||||
userId: conversation.userId,
|
||||
projectId: conversation.projectId || undefined,
|
||||
agentId: conversation.agentId,
|
||||
title: conversation.title,
|
||||
createdAt: conversation.createdAt.toISOString(),
|
||||
updatedAt: conversation.updatedAt.toISOString(),
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取用户的对话列表
|
||||
*/
|
||||
export async function getConversations(
|
||||
userId: string,
|
||||
options: {
|
||||
agentId?: string;
|
||||
projectId?: string | null;
|
||||
page?: number;
|
||||
pageSize?: number;
|
||||
} = {}
|
||||
): Promise<{ conversations: Conversation[]; total: number }> {
|
||||
const { agentId, projectId, page = 1, pageSize = 20 } = options;
|
||||
|
||||
const where: any = { userId };
|
||||
if (agentId) where.agentId = agentId;
|
||||
if (projectId !== undefined) where.projectId = projectId;
|
||||
|
||||
const [conversations, total] = await Promise.all([
|
||||
prisma.conversation.findMany({
|
||||
where,
|
||||
orderBy: { updatedAt: 'desc' },
|
||||
skip: (page - 1) * pageSize,
|
||||
take: pageSize,
|
||||
}),
|
||||
prisma.conversation.count({ where }),
|
||||
]);
|
||||
|
||||
return {
|
||||
conversations: conversations.map(c => ({
|
||||
id: c.id,
|
||||
userId: c.userId,
|
||||
projectId: c.projectId || undefined,
|
||||
agentId: c.agentId,
|
||||
title: c.title,
|
||||
createdAt: c.createdAt.toISOString(),
|
||||
updatedAt: c.updatedAt.toISOString(),
|
||||
})),
|
||||
total,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取单个对话详情
|
||||
*/
|
||||
export async function getConversationById(
|
||||
userId: string,
|
||||
conversationId: string
|
||||
): Promise<Conversation | null> {
|
||||
const conversation = await prisma.conversation.findFirst({
|
||||
where: { id: conversationId, userId },
|
||||
});
|
||||
|
||||
if (!conversation) return null;
|
||||
|
||||
return {
|
||||
id: conversation.id,
|
||||
userId: conversation.userId,
|
||||
projectId: conversation.projectId || undefined,
|
||||
agentId: conversation.agentId,
|
||||
title: conversation.title,
|
||||
createdAt: conversation.createdAt.toISOString(),
|
||||
updatedAt: conversation.updatedAt.toISOString(),
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 更新对话
|
||||
*/
|
||||
export async function updateConversation(
|
||||
userId: string,
|
||||
conversationId: string,
|
||||
updates: { title?: string }
|
||||
): Promise<Conversation> {
|
||||
const conversation = await prisma.conversation.updateMany({
|
||||
where: { id: conversationId, userId },
|
||||
data: updates,
|
||||
});
|
||||
|
||||
if (conversation.count === 0) {
|
||||
throw new Error('对话不存在');
|
||||
}
|
||||
|
||||
const updated = await getConversationById(userId, conversationId);
|
||||
if (!updated) {
|
||||
throw new Error('更新失败');
|
||||
}
|
||||
|
||||
logger.info('[AIA:ConversationService] 更新对话', { conversationId, updates });
|
||||
return updated;
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除对话
|
||||
*/
|
||||
export async function deleteConversation(
|
||||
userId: string,
|
||||
conversationId: string
|
||||
): Promise<void> {
|
||||
const result = await prisma.conversation.deleteMany({
|
||||
where: { id: conversationId, userId },
|
||||
});
|
||||
|
||||
if (result.count === 0) {
|
||||
throw new Error('对话不存在');
|
||||
}
|
||||
|
||||
logger.info('[AIA:ConversationService] 删除对话', { conversationId });
|
||||
}
|
||||
|
||||
// ==================== 消息管理 ====================
|
||||
|
||||
/**
|
||||
* 获取对话的消息列表
|
||||
*/
|
||||
export async function getMessages(
|
||||
userId: string,
|
||||
conversationId: string,
|
||||
options: { page?: number; pageSize?: number } = {}
|
||||
): Promise<{ messages: Message[]; total: number }> {
|
||||
const { page = 1, pageSize = 50 } = options;
|
||||
|
||||
// 验证对话存在
|
||||
const conversation = await prisma.conversation.findFirst({
|
||||
where: { id: conversationId, userId },
|
||||
});
|
||||
|
||||
if (!conversation) {
|
||||
throw new Error('对话不存在');
|
||||
}
|
||||
|
||||
const [messages, total] = await Promise.all([
|
||||
prisma.message.findMany({
|
||||
where: { conversationId },
|
||||
orderBy: { createdAt: 'asc' },
|
||||
skip: (page - 1) * pageSize,
|
||||
take: pageSize,
|
||||
}),
|
||||
prisma.message.count({ where: { conversationId } }),
|
||||
]);
|
||||
|
||||
return {
|
||||
messages: messages.map(m => ({
|
||||
id: m.id,
|
||||
conversationId: m.conversationId,
|
||||
role: m.role as 'user' | 'assistant',
|
||||
content: m.content,
|
||||
thinkingContent: m.thinkingContent || undefined,
|
||||
attachments: (m.attachments as any)?.ids as string[] | undefined,
|
||||
model: m.model || undefined,
|
||||
tokens: m.tokens || undefined,
|
||||
createdAt: m.createdAt.toISOString(),
|
||||
})),
|
||||
total,
|
||||
};
|
||||
}
|
||||
|
||||
// ==================== 流式消息发送（重构版） ====================
|
||||
|
||||
/**
|
||||
* 发送消息（流式输出）- 使用通用 StreamingService
|
||||
*/
|
||||
export async function sendMessageStream(
|
||||
userId: string,
|
||||
conversationId: string,
|
||||
request: SendMessageRequest,
|
||||
reply: FastifyReply
|
||||
): Promise<void> {
|
||||
const { content, attachmentIds, enableDeepThinking } = request;
|
||||
|
||||
// 1. 验证对话存在
|
||||
const conversation = await prisma.conversation.findFirst({
|
||||
where: { id: conversationId, userId },
|
||||
});
|
||||
|
||||
if (!conversation) {
|
||||
throw new Error('对话不存在');
|
||||
}
|
||||
|
||||
// 2. 获取智能体系统提示词
|
||||
const systemPrompt = await agentService.getAgentSystemPrompt(conversation.agentId);
|
||||
|
||||
// 3. 保存用户消息
|
||||
await prisma.message.create({
|
||||
data: {
|
||||
conversationId,
|
||||
role: 'user',
|
||||
content,
|
||||
attachments: attachmentIds ? { ids: attachmentIds } : undefined,
|
||||
},
|
||||
});
|
||||
|
||||
// 4. 组装上下文
|
||||
const contextMessages = await buildContextMessages(conversationId, systemPrompt);
|
||||
|
||||
// 5. 处理附件文本（如果有）
|
||||
let userContent = content;
|
||||
if (attachmentIds && attachmentIds.length > 0) {
|
||||
const attachmentText = await getAttachmentText(attachmentIds);
|
||||
if (attachmentText) {
|
||||
userContent = `${content}\n\n---\n附件内容：\n${attachmentText}`;
|
||||
}
|
||||
}
|
||||
|
||||
// 添加当前用户消息到上下文
|
||||
contextMessages.push({ role: 'user', content: userContent });
|
||||
|
||||
// 6. 使用通用 StreamingService 执行流式生成
|
||||
try {
|
||||
const streamingService = createStreamingService(reply, {
|
||||
model: DEFAULT_MODEL,
|
||||
temperature: 0.7,
|
||||
maxTokens: 4096,
|
||||
enableDeepThinking: enableDeepThinking ?? false,
|
||||
userId,
|
||||
conversationId,
|
||||
});
|
||||
|
||||
const result = await streamingService.streamGenerate(contextMessages, {
|
||||
onContent: (delta) => {
|
||||
// 可选：实时回调
|
||||
},
|
||||
onThinking: (delta) => {
|
||||
// 可选：思考内容回调
|
||||
},
|
||||
onComplete: async (fullContent, thinkingContent) => {
|
||||
// 7. 保存 AI 回复到数据库
|
||||
const aiMessage = await prisma.message.create({
|
||||
data: {
|
||||
conversationId,
|
||||
role: 'assistant',
|
||||
content: fullContent,
|
||||
thinkingContent: thinkingContent || null,
|
||||
model: DEFAULT_MODEL,
|
||||
tokens: estimateTokens(fullContent),
|
||||
},
|
||||
});
|
||||
|
||||
// 8. 更新对话时间
|
||||
await prisma.conversation.update({
|
||||
where: { id: conversationId },
|
||||
data: { updatedAt: new Date() },
|
||||
});
|
||||
|
||||
logger.info('[AIA:ConversationService] 消息发送完成', {
|
||||
conversationId,
|
||||
messageId: aiMessage.id,
|
||||
tokens: aiMessage.tokens,
|
||||
hasThinking: !!thinkingContent,
|
||||
});
|
||||
},
|
||||
onError: (error) => {
|
||||
logger.error('[AIA:ConversationService] 流式生成失败', {
|
||||
error,
|
||||
conversationId,
|
||||
});
|
||||
},
|
||||
});
|
||||
|
||||
} catch (error) {
|
||||
logger.error('[AIA:ConversationService] 流式响应异常', { error, conversationId });
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
// ==================== 辅助函数 ====================
|
||||
|
||||
/**
|
||||
* 构建上下文消息
|
||||
*/
|
||||
async function buildContextMessages(
|
||||
conversationId: string,
|
||||
systemPrompt: string
|
||||
): Promise<OpenAIMessage[]> {
|
||||
// 获取历史消息
|
||||
const messages = await prisma.message.findMany({
|
||||
where: { conversationId },
|
||||
orderBy: { createdAt: 'asc' },
|
||||
take: MAX_CONTEXT_MESSAGES,
|
||||
});
|
||||
|
||||
// 构建消息列表
|
||||
const contextMessages: OpenAIMessage[] = [
|
||||
{ role: 'system', content: systemPrompt },
|
||||
];
|
||||
|
||||
for (const msg of messages) {
|
||||
contextMessages.push({
|
||||
role: msg.role as 'user' | 'assistant',
|
||||
content: msg.content,
|
||||
});
|
||||
}
|
||||
|
||||
// TODO: Token 截断逻辑（如果超过 MAX_CONTEXT_TOKENS）
|
||||
|
||||
return contextMessages;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取附件文本内容
|
||||
* TODO: 对接文档处理服务
|
||||
*/
|
||||
async function getAttachmentText(attachmentIds: string[]): Promise<string> {
|
||||
// 预留：从文档处理引擎获取附件文本
|
||||
logger.debug('[AIA:ConversationService] 获取附件文本', { attachmentIds });
|
||||
return '';
|
||||
}
|
||||
|
||||
/**
|
||||
* 估算 Token 数量
|
||||
*/
|
||||
function estimateTokens(text: string): number {
|
||||
const chineseChars = (text.match(/[\u4e00-\u9fa5]/g) || []).length;
|
||||
const otherChars = text.length - chineseChars;
|
||||
return Math.ceil(chineseChars / 1.5 + otherChars / 4);
|
||||
}
|
||||
201
backend/src/modules/aia/types/index.ts
Normal file
201
backend/src/modules/aia/types/index.ts
Normal file
@@ -0,0 +1,201 @@
|
||||
/**
|
||||
* AIA 智能问答模块 - 类型定义
|
||||
* @module aia/types
|
||||
*/
|
||||
|
||||
// ==================== 智能体相关 ====================
|
||||
|
||||
/**
|
||||
* 智能体阶段
|
||||
*/
|
||||
export type AgentStage = 'design' | 'data' | 'analysis' | 'write' | 'publish';
|
||||
|
||||
/**
|
||||
* 智能体配置
|
||||
*/
|
||||
export interface Agent {
|
||||
id: string;
|
||||
name: string;
|
||||
description: string;
|
||||
icon: string;
|
||||
stage: AgentStage;
|
||||
color: string;
|
||||
knowledgeBaseId?: string;
|
||||
systemPrompt?: string;
|
||||
welcomeMessage?: string;
|
||||
suggestedQuestions?: string[];
|
||||
isTool?: boolean;
|
||||
targetModule?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 智能体列表响应
|
||||
*/
|
||||
export interface AgentListResponse {
|
||||
agents: Agent[];
|
||||
}
|
||||
|
||||
// ==================== 对话相关 ====================
|
||||
|
||||
/**
|
||||
* 消息角色
|
||||
*/
|
||||
export type MessageRole = 'user' | 'assistant' | 'system';
|
||||
|
||||
/**
|
||||
* 附件信息
|
||||
*/
|
||||
export interface Attachment {
|
||||
id: string;
|
||||
filename: string;
|
||||
mimeType: string;
|
||||
size: number;
|
||||
ossUrl: string;
|
||||
textContent?: string;
|
||||
tokenCount: number;
|
||||
truncated: boolean;
|
||||
createdAt: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 消息
|
||||
*/
|
||||
export interface Message {
|
||||
id: string;
|
||||
conversationId: string;
|
||||
role: MessageRole;
|
||||
content: string;
|
||||
thinkingContent?: string;
|
||||
attachments?: Attachment[];
|
||||
model?: string;
|
||||
tokens?: number;
|
||||
isPinned: boolean;
|
||||
createdAt: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 对话
|
||||
*/
|
||||
export interface Conversation {
|
||||
id: string;
|
||||
userId: string;
|
||||
projectId?: string;
|
||||
agentId: string;
|
||||
title: string;
|
||||
messageCount?: number;
|
||||
lastMessage?: string;
|
||||
createdAt: string;
|
||||
updatedAt: string;
|
||||
messages?: Message[];
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建对话请求
|
||||
*/
|
||||
export interface CreateConversationRequest {
|
||||
agentId: string;
|
||||
projectId?: string;
|
||||
title?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 发送消息请求
|
||||
*/
|
||||
export interface SendMessageRequest {
|
||||
content: string;
|
||||
attachmentIds?: string[];
|
||||
enableDeepThinking?: boolean;
|
||||
}
|
||||
|
||||
// ==================== 意图路由相关 ====================
|
||||
|
||||
/**
|
||||
* 意图路由请求
|
||||
*/
|
||||
export interface IntentRouteRequest {
|
||||
query: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 意图路由响应
|
||||
*/
|
||||
export interface IntentRouteResponse {
|
||||
agentId: string;
|
||||
agentName: string;
|
||||
confidence: number;
|
||||
prefillPrompt: string;
|
||||
}
|
||||
|
||||
// ==================== 流式输出相关 ====================
|
||||
|
||||
/**
|
||||
* SSE 事件类型
|
||||
*/
|
||||
export type SSEEventType =
|
||||
| 'thinking_start'
|
||||
| 'thinking_delta'
|
||||
| 'thinking_end'
|
||||
| 'message_start'
|
||||
| 'delta'
|
||||
| 'message_end'
|
||||
| 'error'
|
||||
| 'done';
|
||||
|
||||
/**
|
||||
* SSE 事件数据
|
||||
*/
|
||||
export interface SSEEvent {
|
||||
type: SSEEventType;
|
||||
data: Record<string, unknown>;
|
||||
}
|
||||
|
||||
// ==================== 附件处理配置 ====================
|
||||
|
||||
/**
|
||||
* 附件处理配置
|
||||
*/
|
||||
export const ATTACHMENT_CONFIG = {
|
||||
maxCount: 5, // 每条消息最多5个附件
|
||||
maxSizePerFile: 20 * 1024 * 1024, // 单个文件20MB
|
||||
maxTokens: 30000, // 提取文本最多30K tokens
|
||||
supportedTypes: [
|
||||
'application/pdf',
|
||||
'application/vnd.openxmlformats-officedocument.wordprocessingml.document',
|
||||
'text/plain',
|
||||
'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',
|
||||
],
|
||||
supportedExtensions: ['pdf', 'docx', 'txt', 'xlsx'],
|
||||
};
|
||||
|
||||
// ==================== API 响应格式 ====================
|
||||
|
||||
/**
|
||||
* 通用 API 响应
|
||||
*/
|
||||
export interface ApiResponse<T> {
|
||||
code: number;
|
||||
data?: T;
|
||||
error?: {
|
||||
code: string;
|
||||
message: string;
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 分页信息
|
||||
*/
|
||||
export interface Pagination {
|
||||
total: number;
|
||||
page: number;
|
||||
pageSize: number;
|
||||
totalPages: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 带分页的列表响应
|
||||
*/
|
||||
export interface PaginatedResponse<T> {
|
||||
items: T[];
|
||||
pagination: Pagination;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user