279 lines
7.8 KiB
JavaScript
279 lines
7.8 KiB
JavaScript
// src/services/llmService.js
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// LLM服务层 - 集成AI模型进行对话和工具调用
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import axios from 'axios';
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import { mcpService } from './mcpService';
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import { logger } from '../utils/logger';
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/**
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* LLM服务配置
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*/
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const LLM_CONFIG = {
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// 可以使用 OpenAI、Claude、通义千问等
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provider: 'openai', // 或 'claude', 'qwen'
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apiKey: process.env.REACT_APP_OPENAI_API_KEY || '',
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apiUrl: 'https://api.openai.com/v1/chat/completions',
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model: 'gpt-4o-mini', // 更便宜的模型
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};
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/**
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* LLM服务类
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*/
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class LLMService {
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constructor() {
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this.conversationHistory = [];
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}
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/**
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* 构建系统提示词
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*/
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getSystemPrompt(availableTools) {
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return `你是一个专业的金融投资助手。你可以使用以下工具来帮助用户查询信息：
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${availableTools.map(tool => `
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**${tool.name}**
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描述：${tool.description}
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参数：${JSON.stringify(tool.parameters, null, 2)}
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`).join('\n')}
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用户提问时，请按照以下步骤：
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1. 理解用户的意图
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2. 选择合适的工具（可以多个）
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3. 提取工具需要的参数
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4. 调用工具后，用自然语言总结结果
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回复格式：
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- 如果需要调用工具，返回JSON格式：{"tool": "工具名", "arguments": {...}}
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- 如果不需要工具，直接回复自然语言
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注意：
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- 贵州茅台的股票代码是 600519
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- 涨停是指股票当日涨幅达到10%
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- 概念板块是指相同题材的股票分类`;
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}
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/**
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* 智能对话 - 使用LLM理解意图并调用工具
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*/
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async chat(userMessage, conversationHistory = []) {
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try {
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// 1. 获取可用工具列表
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const toolsResult = await mcpService.listTools();
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if (!toolsResult.success) {
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throw new Error('获取工具列表失败');
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}
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const availableTools = toolsResult.data;
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// 2. 构建对话历史
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const messages = [
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{
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role: 'system',
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content: this.getSystemPrompt(availableTools),
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},
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...conversationHistory.map(msg => ({
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role: msg.isUser ? 'user' : 'assistant',
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content: msg.content,
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})),
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{
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role: 'user',
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content: userMessage,
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},
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];
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// 3. 调用LLM
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logger.info('LLMService', '调用LLM', { messageCount: messages.length });
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// 注意：这里需要配置API密钥
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if (!LLM_CONFIG.apiKey) {
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// 如果没有配置LLM，使用简单的关键词匹配
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logger.warn('LLMService', '未配置LLM API密钥，使用简单匹配');
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return await this.fallbackChat(userMessage);
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}
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const response = await axios.post(
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LLM_CONFIG.apiUrl,
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{
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model: LLM_CONFIG.model,
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messages: messages,
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temperature: 0.7,
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max_tokens: 1000,
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},
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{
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${LLM_CONFIG.apiKey}`,
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},
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timeout: 30000,
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}
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);
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const aiResponse = response.data.choices[0].message.content;
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logger.info('LLMService', 'LLM响应', { response: aiResponse });
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// 4. 解析LLM响应
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// 如果LLM返回工具调用指令
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try {
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const toolCall = JSON.parse(aiResponse);
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if (toolCall.tool && toolCall.arguments) {
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// 调用MCP工具
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const toolResult = await mcpService.callTool(toolCall.tool, toolCall.arguments);
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if (!toolResult.success) {
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return {
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success: false,
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error: toolResult.error,
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};
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}
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// 5. 让LLM总结工具结果
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const summaryMessages = [
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...messages,
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{
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role: 'assistant',
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content: aiResponse,
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},
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{
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role: 'system',
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content: `工具 ${toolCall.tool} 返回的数据：\n${JSON.stringify(toolResult.data, null, 2)}\n\n请用自然语言总结这些数据，给用户一个简洁清晰的回复。`,
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},
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];
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const summaryResponse = await axios.post(
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LLM_CONFIG.apiUrl,
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{
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model: LLM_CONFIG.model,
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messages: summaryMessages,
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temperature: 0.7,
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max_tokens: 500,
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},
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{
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${LLM_CONFIG.apiKey}`,
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},
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timeout: 30000,
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}
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);
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const summary = summaryResponse.data.choices[0].message.content;
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return {
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success: true,
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data: {
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message: summary,
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rawData: toolResult.data,
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toolUsed: toolCall.tool,
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},
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};
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}
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} catch (parseError) {
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// 不是JSON格式，说明是直接回复
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return {
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success: true,
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data: {
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message: aiResponse,
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},
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};
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}
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// 默认返回LLM的直接回复
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return {
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success: true,
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data: {
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message: aiResponse,
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},
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};
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} catch (error) {
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logger.error('LLMService', 'chat error', error);
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return {
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success: false,
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error: error.message || '对话处理失败',
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};
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}
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}
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/**
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* 降级方案：简单的关键词匹配（当没有配置LLM时）
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*/
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async fallbackChat(userMessage) {
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logger.info('LLMService', '使用降级方案', { message: userMessage });
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// 使用原有的简单匹配逻辑
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if (userMessage.includes('新闻') || userMessage.includes('资讯')) {
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const result = await mcpService.callTool('search_china_news', {
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query: userMessage.replace(/新闻|资讯/g, '').trim(),
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top_k: 5,
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});
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return this.formatFallbackResponse(result, '新闻搜索');
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} else if (userMessage.includes('概念') || userMessage.includes('板块')) {
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const query = userMessage.replace(/概念|板块/g, '').trim();
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const result = await mcpService.callTool('search_concepts', {
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query,
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size: 5,
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sort_by: 'change_pct',
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});
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return this.formatFallbackResponse(result, '概念搜索');
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} else if (userMessage.includes('涨停')) {
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const query = userMessage.replace(/涨停/g, '').trim();
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const result = await mcpService.callTool('search_limit_up_stocks', {
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query,
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mode: 'hybrid',
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page_size: 5,
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});
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return this.formatFallbackResponse(result, '涨停分析');
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} else if (/^[0-9]{6}$/.test(userMessage.trim())) {
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// 6位数字 = 股票代码
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const result = await mcpService.callTool('get_stock_basic_info', {
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seccode: userMessage.trim(),
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});
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return this.formatFallbackResponse(result, '股票信息');
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} else if (userMessage.includes('茅台') || userMessage.includes('贵州茅台')) {
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// 特殊处理茅台
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const result = await mcpService.callTool('get_stock_basic_info', {
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seccode: '600519',
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});
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return this.formatFallbackResponse(result, '贵州茅台股票信息');
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} else {
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// 默认：搜索新闻
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const result = await mcpService.callTool('search_china_news', {
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query: userMessage,
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top_k: 5,
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});
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return this.formatFallbackResponse(result, '新闻搜索');
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}
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}
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/**
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* 格式化降级响应
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*/
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formatFallbackResponse(result, action) {
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if (!result.success) {
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return {
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success: false,
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error: result.error,
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};
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}
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return {
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success: true,
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data: {
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message: `已为您完成${action}，找到以下结果：`,
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rawData: result.data,
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},
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};
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}
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/**
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* 清除对话历史
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*/
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clearHistory() {
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this.conversationHistory = [];
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}
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}
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// 导出单例
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export const llmService = new LLMService();
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export default LLMService;
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