UNPKG

@lobehub/chat

Version:

Lobe Chat - an open-source, high-performance chatbot framework that supports speech synthesis, multimodal, and extensible Function Call plugin system. Supports one-click free deployment of your private ChatGPT/LLM web application.

246 lines (209 loc) 7.83 kB
// @vitest-environment node import OpenAI from 'openai'; import { Mock, afterEach, beforeEach, describe, expect, it, vi } from 'vitest'; // 引入模块以便于对函数进行spy import { ChatStreamCallbacks, LobeOpenAICompatibleRuntime } from '@/libs/model-runtime'; import * as debugStreamModule from '../utils/debugStream'; import officalOpenAIModels from './fixtures/openai-models.json'; import { LobeOpenAI } from './index'; // Mock the console.error to avoid polluting test output vi.spyOn(console, 'error').mockImplementation(() => {}); describe('LobeOpenAI', () => { let instance: LobeOpenAICompatibleRuntime; beforeEach(() => { instance = new LobeOpenAI({ apiKey: 'test' }); // 使用 vi.spyOn 来模拟 chat.completions.create 方法 vi.spyOn(instance['client'].chat.completions, 'create').mockResolvedValue( new ReadableStream() as any, ); vi.spyOn(instance['client'].models, 'list').mockResolvedValue({ data: [] } as any); }); afterEach(() => { vi.clearAllMocks(); }); describe('chat', () => { it('should return a StreamingTextResponse on successful API call', async () => { // Arrange const mockStream = new ReadableStream(); const mockResponse = Promise.resolve(mockStream); (instance['client'].chat.completions.create as Mock).mockResolvedValue(mockResponse); // Act const result = await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'text-davinci-003', temperature: 0, }); // Assert expect(result).toBeInstanceOf(Response); }); describe('Error', () => { it('should return ProviderBizError with an openai error response when OpenAI.APIError is thrown', async () => { // Arrange const apiError = new OpenAI.APIError( 400, { status: 400, error: { message: 'Bad Request', }, }, 'Error message', {}, ); vi.spyOn(instance['client'].chat.completions, 'create').mockRejectedValue(apiError); // Act try { await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'text-davinci-003', temperature: 0, }); } catch (e) { expect(e).toEqual({ endpoint: 'https://api.openai.com/v1', error: { error: { message: 'Bad Request' }, status: 400, }, errorType: 'ProviderBizError', provider: 'openai', }); } }); it('should throw AgentRuntimeError with NoOpenAIAPIKey if no apiKey is provided', async () => { try { new LobeOpenAI({}); } catch (e) { expect(e).toEqual({ errorType: 'InvalidProviderAPIKey' }); } }); it('should return ProviderBizError with the cause when OpenAI.APIError is thrown with cause', async () => { // Arrange const errorInfo = { stack: 'abc', cause: { message: 'api is undefined', }, }; const apiError = new OpenAI.APIError(400, errorInfo, 'module error', {}); vi.spyOn(instance['client'].chat.completions, 'create').mockRejectedValue(apiError); // Act try { await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'text-davinci-003', temperature: 0, }); } catch (e) { expect(e).toEqual({ endpoint: 'https://api.openai.com/v1', error: { cause: { message: 'api is undefined' }, stack: 'abc', }, errorType: 'ProviderBizError', provider: 'openai', }); } }); it('should return ProviderBizError with an cause response with desensitize Url', async () => { // Arrange const errorInfo = { stack: 'abc', cause: { message: 'api is undefined' }, }; const apiError = new OpenAI.APIError(400, errorInfo, 'module error', {}); instance = new LobeOpenAI({ apiKey: 'test', baseURL: 'https://api.abc.com/v1', }); vi.spyOn(instance['client'].chat.completions, 'create').mockRejectedValue(apiError); // Act try { await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'gpt-3.5-turbo', temperature: 0, }); } catch (e) { expect(e).toEqual({ endpoint: 'https://api.***.com/v1', error: { cause: { message: 'api is undefined' }, stack: 'abc', }, errorType: 'ProviderBizError', provider: 'openai', }); } }); it('should return AgentRuntimeError for non-OpenAI errors', async () => { // Arrange const genericError = new Error('Generic Error'); vi.spyOn(instance['client'].chat.completions, 'create').mockRejectedValue(genericError); // Act try { await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'text-davinci-003', temperature: 0, }); } catch (e) { expect(e).toEqual({ endpoint: 'https://api.openai.com/v1', errorType: 'AgentRuntimeError', provider: 'openai', error: { name: genericError.name, cause: genericError.cause, message: genericError.message, stack: genericError.stack, }, }); } }); }); describe('DEBUG', () => { it('should call debugStream and return StreamingTextResponse when DEBUG_OPENAI_CHAT_COMPLETION is 1', async () => { // Arrange const mockProdStream = new ReadableStream() as any; // 模拟的 prod 流 const mockDebugStream = new ReadableStream({ start(controller) { controller.enqueue('Debug stream content'); controller.close(); }, }) as any; mockDebugStream.toReadableStream = () => mockDebugStream; // 添加 toReadableStream 方法 // 模拟 chat.completions.create 返回值,包括模拟的 tee 方法 (instance['client'].chat.completions.create as Mock).mockResolvedValue({ tee: () => [mockProdStream, { toReadableStream: () => mockDebugStream }], }); // 保存原始环境变量值 const originalDebugValue = process.env.DEBUG_OPENAI_CHAT_COMPLETION; // 模拟环境变量 process.env.DEBUG_OPENAI_CHAT_COMPLETION = '1'; vi.spyOn(debugStreamModule, 'debugStream').mockImplementation(() => Promise.resolve()); // 执行测试 // 运行你的测试函数,确保它会在条件满足时调用 debugStream // 假设的测试函数调用,你可能需要根据实际情况调整 await instance.chat({ messages: [{ content: 'Hello', role: 'user' }], model: 'text-davinci-003', temperature: 0, }); // 验证 debugStream 被调用 expect(debugStreamModule.debugStream).toHaveBeenCalled(); // 恢复原始环境变量值 process.env.DEBUG_OPENAI_CHAT_COMPLETION = originalDebugValue; }); }); }); describe('models', () => { it('should get models', async () => { // mock the models.list method (instance['client'].models.list as Mock).mockResolvedValue({ data: officalOpenAIModels }); const list = await instance.models(); expect(list).toMatchSnapshot(); }); }); });