🚧 wip: add lm studio

src/config/modelProviders/index.ts

@@ -13,6 +13,7 @@ import GoogleProvider from './google';
 import GroqProvider from './groq';
 import HuggingFaceProvider from './huggingface';
 import HunyuanProvider from './hunyuan';
+import LMStudioProvider from './lmstudio';
 import MinimaxProvider from './minimax';
 import MistralProvider from './mistral';
 import MoonshotProvider from './moonshot';
@@ -65,6 +66,7 @@ export const LOBE_DEFAULT_MODEL_LIST: ChatModelCard[] = [
   HunyuanProvider.chatModels,
   WenxinProvider.chatModels,
   SenseNovaProvider.chatModels,
+  LMStudioProvider.chatModels,
 ].flat();
 
 export const DEFAULT_MODEL_PROVIDER_LIST = [
@@ -100,6 +102,7 @@ export const DEFAULT_MODEL_PROVIDER_LIST = [
   Ai360Provider,
   TaichuProvider,
   SiliconCloudProvider,
+  LMStudioProvider,
 ];
 
 export const filterEnabledModels = (provider: ModelProviderCard) => {
@@ -124,6 +127,7 @@ export { default as GoogleProviderCard } from './google';
 export { default as GroqProviderCard } from './groq';
 export { default as HuggingFaceProviderCard } from './huggingface';
 export { default as HunyuanProviderCard } from './hunyuan';
+export { default as LMStudioProviderCard } from './lmstudio';
 export { default as MinimaxProviderCard } from './minimax';
 export { default as MistralProviderCard } from './mistral';
 export { default as MoonshotProviderCard } from './moonshot';

src/config/modelProviders/lmstudio.ts

@@ -0,0 +1,31 @@
+import { ModelProviderCard } from '@/types/llm';
+
+// ref: https://ollama.com/library
+const LMStudio: ModelProviderCard = {
+  chatModels: [
+    {
+      description:
+        'Llama 3.1 是 Meta 推出的领先模型，支持高达 405B 参数，可应用于复杂对话、多语言翻译和数据分析领域。',
+      displayName: 'Llama 3.1 8B',
+      enabled: true,
+      id: 'llama3.1',
+      tokens: 128_000,
+    },
+    {
+      description: 'Qwen2.5 是阿里巴巴的新一代大规模语言模型，以优异的性能支持多元化的应用需求。',
+      displayName: 'Qwen2.5 7B',
+      enabled: true,
+      id: 'qwen2.5',
+      tokens: 128_000,
+    },
+  ],
+  defaultShowBrowserRequest: true,
+  id: 'lmstudio',
+  modelList: { showModelFetcher: true },
+  modelsUrl: 'https://lmstudio.ai/models',
+  name: 'LM Studio',
+  showApiKey: false,
+  url: 'https://lmstudio.ai',
+};
+
+export default LMStudio;

src/libs/agent-runtime/AgentRuntime.ts

@@ -16,6 +16,7 @@ import { LobeGoogleAI } from './google';
 import { LobeGroq } from './groq';
 import { LobeHuggingFaceAI } from './huggingface';
 import { LobeHunyuanAI } from './hunyuan';
+import { LobeLMStudioAI } from './lmstudio';
 import { LobeMinimaxAI } from './minimax';
 import { LobeMistralAI } from './mistral';
 import { LobeMoonshotAI } from './moonshot';
@@ -138,6 +139,7 @@ class AgentRuntime {
       groq: Partial<ClientOptions>;
       huggingface: { apiKey?: string; baseURL?: string };
       hunyuan: Partial<ClientOptions>;
+      lmstudio: Partial<ClientOptions>;
       minimax: Partial<ClientOptions>;
       mistral: Partial<ClientOptions>;
       moonshot: Partial<ClientOptions>;
@@ -197,6 +199,11 @@ class AgentRuntime {
         break;
       }
 
+      case ModelProvider.LMStudio: {
+        runtimeModel = new LobeLMStudioAI(params.lmstudio);
+        break;
+      }
+
       case ModelProvider.Ollama: {
         runtimeModel = new LobeOllamaAI(params.ollama);
         break;

src/libs/agent-runtime/lmstudio/index.test.ts

@@ -0,0 +1,255 @@
+// @vitest-environment node
+import OpenAI from 'openai';
+import { Mock, afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
+
+import {
+  ChatStreamCallbacks,
+  LobeOpenAICompatibleRuntime,
+  ModelProvider,
+} from '@/libs/agent-runtime';
+
+import * as debugStreamModule from '../utils/debugStream';
+import { LobeDeepSeekAI } from './index';
+
+const provider = ModelProvider.DeepSeek;
+const defaultBaseURL = 'https://api.deepseek.com/v1';
+
+const bizErrorType = 'ProviderBizError';
+const invalidErrorType = 'InvalidProviderAPIKey';
+
+// Mock the console.error to avoid polluting test output
+vi.spyOn(console, 'error').mockImplementation(() => {});
+
+let instance: LobeOpenAICompatibleRuntime;
+
+beforeEach(() => {
+  instance = new LobeDeepSeekAI({ 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,
+  );
+});
+
+afterEach(() => {
+  vi.clearAllMocks();
+});
+
+describe('LobeDeepSeekAI', () => {
+  describe('init', () => {
+    it('should correctly initialize with an API key', async () => {
+      const instance = new LobeDeepSeekAI({ apiKey: 'test_api_key' });
+      expect(instance).toBeInstanceOf(LobeDeepSeekAI);
+      expect(instance.baseURL).toEqual(defaultBaseURL);
+    });
+  });
+
+  describe('chat', () => {
+    describe('Error', () => {
+      it('should return OpenAIBizError 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: 'deepseek-chat',
+            temperature: 0,
+          });
+        } catch (e) {
+          expect(e).toEqual({
+            endpoint: defaultBaseURL,
+            error: {
+              error: { message: 'Bad Request' },
+              status: 400,
+            },
+            errorType: bizErrorType,
+            provider,
+          });
+        }
+      });
+
+      it('should throw AgentRuntimeError with NoOpenAIAPIKey if no apiKey is provided', async () => {
+        try {
+          new LobeDeepSeekAI({});
+        } catch (e) {
+          expect(e).toEqual({ errorType: invalidErrorType });
+        }
+      });
+
+      it('should return OpenAIBizError 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: 'deepseek-chat',
+            temperature: 0,
+          });
+        } catch (e) {
+          expect(e).toEqual({
+            endpoint: defaultBaseURL,
+            error: {
+              cause: { message: 'api is undefined' },
+              stack: 'abc',
+            },
+            errorType: bizErrorType,
+            provider,
+          });
+        }
+      });
+
+      it('should return OpenAIBizError 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 LobeDeepSeekAI({
+          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: 'deepseek-chat',
+            temperature: 0,
+          });
+        } catch (e) {
+          expect(e).toEqual({
+            endpoint: 'https://api.***.com/v1',
+            error: {
+              cause: { message: 'api is undefined' },
+              stack: 'abc',
+            },
+            errorType: bizErrorType,
+            provider,
+          });
+        }
+      });
+
+      it('should throw an InvalidDeepSeekAPIKey error type on 401 status code', async () => {
+        // Mock the API call to simulate a 401 error
+        const error = new Error('Unauthorized') as any;
+        error.status = 401;
+        vi.mocked(instance['client'].chat.completions.create).mockRejectedValue(error);
+
+        try {
+          await instance.chat({
+            messages: [{ content: 'Hello', role: 'user' }],
+            model: 'deepseek-chat',
+            temperature: 0,
+          });
+        } catch (e) {
+          // Expect the chat method to throw an error with InvalidDeepSeekAPIKey
+          expect(e).toEqual({
+            endpoint: defaultBaseURL,
+            error: new Error('Unauthorized'),
+            errorType: invalidErrorType,
+            provider,
+          });
+        }
+      });
+
+      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: 'deepseek-chat',
+            temperature: 0,
+          });
+        } catch (e) {
+          expect(e).toEqual({
+            endpoint: defaultBaseURL,
+            errorType: 'AgentRuntimeError',
+            provider,
+            error: {
+              name: genericError.name,
+              cause: genericError.cause,
+              message: genericError.message,
+              stack: genericError.stack,
+            },
+          });
+        }
+      });
+    });
+
+    describe('DEBUG', () => {
+      it('should call debugStream and return StreamingTextResponse when DEBUG_DEEPSEEK_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_DEEPSEEK_CHAT_COMPLETION;
+
+        // 模拟环境变量
+        process.env.DEBUG_DEEPSEEK_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: 'deepseek-chat',
+          stream: true,
+          temperature: 0,
+        });
+
+        // 验证 debugStream 被调用
+        expect(debugStreamModule.debugStream).toHaveBeenCalled();
+
+        // 恢复原始环境变量值
+        process.env.DEBUG_DEEPSEEK_CHAT_COMPLETION = originalDebugValue;
+      });
+    });
+  });
+});

src/libs/agent-runtime/lmstudio/index.ts

@@ -0,0 +1,10 @@
+import { ModelProvider } from '../types';
+import { LobeOpenAICompatibleFactory } from '../utils/openaiCompatibleFactory';
+
+export const LobeLMStudioAI = LobeOpenAICompatibleFactory({
+  baseURL: 'http://localhost:1234/v1',
+  debug: {
+    chatCompletion: () => process.env.DEBUG_LMSTUDIO_CHAT_COMPLETION === '1',
+  },
+  provider: ModelProvider.LMStudio,
+});

src/libs/agent-runtime/types/type.ts

@@ -1,5 +1,6 @@
 import OpenAI from 'openai';
 
+
 import { ILobeAgentRuntimeErrorType } from '../error';
 import { ChatStreamPayload } from './chat';
 
@@ -35,6 +36,7 @@ export enum ModelProvider {
   Groq = 'groq',
   HuggingFace = 'huggingface',
   Hunyuan = 'hunyuan',
+  LMStudio = 'lmstudio',
   Minimax = 'minimax',
   Mistral = 'mistral',
   Moonshot = 'moonshot',