docs: Day 12-13 completion summary and milestone update
This commit is contained in:
AI Clinical Dev Team
150
backend/src/adapters/DeepSeekAdapter.ts
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150
backend/src/adapters/DeepSeekAdapter.ts
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@@ -0,0 +1,150 @@
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import axios from 'axios';
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import { ILLMAdapter, Message, LLMOptions, LLMResponse, StreamChunk } from './types.js';
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import { config } from '../config/env.js';
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export class DeepSeekAdapter implements ILLMAdapter {
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modelName: string;
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private apiKey: string;
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private baseURL: string;
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constructor(modelName: string = 'deepseek-chat') {
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this.modelName = modelName;
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this.apiKey = config.deepseekApiKey || '';
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this.baseURL = 'https://api.deepseek.com/v1';
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if (!this.apiKey) {
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throw new Error('DeepSeek API key is not configured');
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}
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}
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// 非流式调用
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async chat(messages: Message[], options?: LLMOptions): Promise<LLMResponse> {
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try {
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const response = await axios.post(
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`${this.baseURL}/chat/completions`,
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{
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model: this.modelName,
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messages: messages,
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temperature: options?.temperature ?? 0.7,
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max_tokens: options?.maxTokens ?? 2000,
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top_p: options?.topP ?? 0.9,
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stream: false,
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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 ${this.apiKey}`,
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},
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timeout: 60000, // 60秒超时
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}
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);
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const choice = response.data.choices[0];
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return {
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content: choice.message.content,
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model: response.data.model,
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usage: {
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promptTokens: response.data.usage.prompt_tokens,
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completionTokens: response.data.usage.completion_tokens,
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totalTokens: response.data.usage.total_tokens,
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},
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finishReason: choice.finish_reason,
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};
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} catch (error: unknown) {
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console.error('DeepSeek API Error:', error);
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if (axios.isAxiosError(error)) {
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throw new Error(
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`DeepSeek API调用失败: ${error.response?.data?.error?.message || error.message}`
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);
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}
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throw error;
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}
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}
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// 流式调用
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async *chatStream(
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messages: Message[],
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options?: LLMOptions,
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onChunk?: (chunk: StreamChunk) => void
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): AsyncGenerator<StreamChunk, void, unknown> {
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try {
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const response = await axios.post(
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`${this.baseURL}/chat/completions`,
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{
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model: this.modelName,
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messages: messages,
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temperature: options?.temperature ?? 0.7,
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max_tokens: options?.maxTokens ?? 2000,
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top_p: options?.topP ?? 0.9,
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stream: true,
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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 ${this.apiKey}`,
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},
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responseType: 'stream',
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timeout: 60000,
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}
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);
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const stream = response.data;
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let buffer = '';
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for await (const chunk of stream) {
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buffer += chunk.toString();
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const lines = buffer.split('\n');
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buffer = lines.pop() || '';
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for (const line of lines) {
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const trimmedLine = line.trim();
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if (!trimmedLine || trimmedLine === 'data: [DONE]') {
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continue;
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}
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if (trimmedLine.startsWith('data: ')) {
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try {
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const jsonStr = trimmedLine.slice(6);
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const data = JSON.parse(jsonStr);
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const choice = data.choices[0];
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const content = choice.delta?.content || '';
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const streamChunk: StreamChunk = {
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content: content,
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done: choice.finish_reason === 'stop',
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model: data.model,
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};
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if (choice.finish_reason === 'stop' && data.usage) {
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streamChunk.usage = {
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promptTokens: data.usage.prompt_tokens,
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completionTokens: data.usage.completion_tokens,
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totalTokens: data.usage.total_tokens,
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};
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}
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if (onChunk) {
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onChunk(streamChunk);
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}
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yield streamChunk;
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} catch (parseError) {
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console.error('Failed to parse SSE data:', parseError);
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}
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}
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}
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}
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} catch (error) {
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console.error('DeepSeek Stream Error:', error);
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if (axios.isAxiosError(error)) {
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throw new Error(
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`DeepSeek流式调用失败: ${error.response?.data?.error?.message || error.message}`
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);
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}
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throw error;
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}
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}
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}
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77
backend/src/adapters/LLMFactory.ts
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77
backend/src/adapters/LLMFactory.ts
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@@ -0,0 +1,77 @@
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import { ILLMAdapter, ModelType } from './types.js';
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import { DeepSeekAdapter } from './DeepSeekAdapter.js';
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import { QwenAdapter } from './QwenAdapter.js';
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/**
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* LLM工厂类
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* 根据模型类型创建相应的适配器实例
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*/
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export class LLMFactory {
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private static adapters: Map<string, ILLMAdapter> = new Map();
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/**
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* 获取LLM适配器实例（单例模式）
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* @param modelType 模型类型
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* @returns LLM适配器实例
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*/
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static getAdapter(modelType: ModelType): ILLMAdapter {
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// 如果已经创建过该适配器，直接返回
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if (this.adapters.has(modelType)) {
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return this.adapters.get(modelType)!;
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}
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// 根据模型类型创建适配器
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let adapter: ILLMAdapter;
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switch (modelType) {
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case 'deepseek-v3':
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adapter = new DeepSeekAdapter('deepseek-chat');
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break;
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case 'qwen3-72b':
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adapter = new QwenAdapter('qwen-max'); // Qwen3-72B对应的模型名
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break;
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case 'gemini-pro':
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// TODO: 实现Gemini适配器
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throw new Error('Gemini adapter is not implemented yet');
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default:
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throw new Error(`Unsupported model type: ${modelType}`);
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}
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// 缓存适配器实例
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this.adapters.set(modelType, adapter);
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return adapter;
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}
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/**
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* 清除适配器缓存
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* @param modelType 可选，指定清除某个模型的适配器，不传则清除所有
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*/
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static clearCache(modelType?: ModelType): void {
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if (modelType) {
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this.adapters.delete(modelType);
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} else {
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this.adapters.clear();
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}
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}
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/**
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* 检查模型是否支持
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* @param modelType 模型类型
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* @returns 是否支持
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*/
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static isSupported(modelType: string): boolean {
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return ['deepseek-v3', 'qwen3-72b', 'gemini-pro'].includes(modelType);
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}
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/**
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* 获取所有支持的模型列表
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* @returns 支持的模型列表
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*/
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static getSupportedModels(): ModelType[] {
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return ['deepseek-v3', 'qwen3-72b', 'gemini-pro'];
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}
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}
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162
backend/src/adapters/QwenAdapter.ts
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162
backend/src/adapters/QwenAdapter.ts
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@@ -0,0 +1,162 @@
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import axios from 'axios';
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import { ILLMAdapter, Message, LLMOptions, LLMResponse, StreamChunk } from './types.js';
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import { config } from '../config/env.js';
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export class QwenAdapter implements ILLMAdapter {
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modelName: string;
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private apiKey: string;
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private baseURL: string;
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constructor(modelName: string = 'qwen-turbo') {
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this.modelName = modelName;
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this.apiKey = config.qwenApiKey || '';
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this.baseURL = 'https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation';
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if (!this.apiKey) {
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throw new Error('Qwen API key is not configured');
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}
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}
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// 非流式调用
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async chat(messages: Message[], options?: LLMOptions): Promise<LLMResponse> {
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try {
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const response = await axios.post(
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this.baseURL,
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{
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model: this.modelName,
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input: {
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messages: messages,
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},
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parameters: {
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temperature: options?.temperature ?? 0.7,
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max_tokens: options?.maxTokens ?? 2000,
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top_p: options?.topP ?? 0.9,
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result_format: 'message',
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},
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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 ${this.apiKey}`,
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},
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timeout: 60000,
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}
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);
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const output = response.data.output;
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const usage = response.data.usage;
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return {
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content: output.choices[0].message.content,
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model: this.modelName,
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usage: {
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promptTokens: usage.input_tokens,
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completionTokens: usage.output_tokens,
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totalTokens: usage.total_tokens || usage.input_tokens + usage.output_tokens,
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},
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finishReason: output.choices[0].finish_reason,
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};
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} catch (error: unknown) {
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console.error('Qwen API Error:', error);
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if (axios.isAxiosError(error)) {
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throw new Error(
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`Qwen API调用失败: ${error.response?.data?.message || error.message}`
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);
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}
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throw error;
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}
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}
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// 流式调用
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async *chatStream(
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messages: Message[],
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options?: LLMOptions,
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onChunk?: (chunk: StreamChunk) => void
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): AsyncGenerator<StreamChunk, void, unknown> {
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try {
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const response = await axios.post(
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this.baseURL,
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{
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model: this.modelName,
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input: {
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messages: messages,
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},
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parameters: {
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temperature: options?.temperature ?? 0.7,
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max_tokens: options?.maxTokens ?? 2000,
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top_p: options?.topP ?? 0.9,
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result_format: 'message',
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incremental_output: true,
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},
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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 ${this.apiKey}`,
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'X-DashScope-SSE': 'enable',
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},
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responseType: 'stream',
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timeout: 60000,
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}
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);
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const stream = response.data;
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let buffer = '';
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for await (const chunk of stream) {
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buffer += chunk.toString();
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const lines = buffer.split('\n');
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buffer = lines.pop() || '';
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for (const line of lines) {
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const trimmedLine = line.trim();
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if (!trimmedLine || trimmedLine.startsWith(':')) {
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continue;
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}
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if (trimmedLine.startsWith('data:')) {
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try {
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const jsonStr = trimmedLine.slice(5).trim();
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const data = JSON.parse(jsonStr);
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const output = data.output;
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const choice = output.choices[0];
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const content = choice.message?.content || '';
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const streamChunk: StreamChunk = {
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content: content,
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done: choice.finish_reason === 'stop',
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model: this.modelName,
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};
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if (choice.finish_reason === 'stop' && data.usage) {
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streamChunk.usage = {
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promptTokens: data.usage.input_tokens,
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completionTokens: data.usage.output_tokens,
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totalTokens: data.usage.total_tokens || data.usage.input_tokens + data.usage.output_tokens,
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};
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}
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if (onChunk) {
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onChunk(streamChunk);
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}
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yield streamChunk;
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} catch (parseError) {
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console.error('Failed to parse Qwen SSE data:', parseError);
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}
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}
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}
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}
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} catch (error) {
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console.error('Qwen Stream Error:', error);
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if (axios.isAxiosError(error)) {
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throw new Error(
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`Qwen流式调用失败: ${error.response?.data?.message || error.message}`
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);
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}
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throw error;
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}
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}
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}
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55
backend/src/adapters/types.ts
Normal file
55
backend/src/adapters/types.ts
Normal file
@@ -0,0 +1,55 @@
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// LLM适配器类型定义
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export interface Message {
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role: 'system' | 'user' | 'assistant';
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content: string;
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}
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export interface LLMOptions {
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temperature?: number;
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maxTokens?: number;
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topP?: number;
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stream?: boolean;
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}
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export interface LLMResponse {
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content: string;
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model: string;
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usage?: {
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promptTokens: number;
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completionTokens: number;
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totalTokens: number;
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};
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finishReason?: string;
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}
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export interface StreamChunk {
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content: string;
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done: boolean;
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model?: string;
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usage?: {
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promptTokens: number;
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completionTokens: number;
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totalTokens: number;
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};
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}
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// LLM适配器接口
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export interface ILLMAdapter {
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// 模型名称
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modelName: string;
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// 非流式调用
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chat(messages: Message[], options?: LLMOptions): Promise<LLMResponse>;
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// 流式调用
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chatStream(
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messages: Message[],
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options?: LLMOptions,
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onChunk?: (chunk: StreamChunk) => void
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): AsyncGenerator<StreamChunk, void, unknown>;
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}
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// 支持的模型类型
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export type ModelType = 'deepseek-v3' | 'qwen3-72b' | 'gemini-pro';
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Block a user