✨ feat: add vLLM provider support (lobehub#6154)

* ✨ feat: add vLLM provider support

* 💄 style: update model list

Dockerfile

@@ -217,6 +217,8 @@ ENV \
     TOGETHERAI_API_KEY="" TOGETHERAI_MODEL_LIST="" \
     # Upstage
     UPSTAGE_API_KEY="" UPSTAGE_MODEL_LIST="" \
+    # vLLM
+    VLLM_API_KEY="" VLLM_MODEL_LIST="" VLLM_PROXY_URL="" \
     # Wenxin
     WENXIN_API_KEY="" WENXIN_MODEL_LIST="" \
     # xAI

Dockerfile.database

@@ -254,6 +254,8 @@ ENV \
     TOGETHERAI_API_KEY="" TOGETHERAI_MODEL_LIST="" \
     # Upstage
     UPSTAGE_API_KEY="" UPSTAGE_MODEL_LIST="" \
+    # vLLM
+    VLLM_API_KEY="" VLLM_MODEL_LIST="" VLLM_PROXY_URL="" \
     # Wenxin
     WENXIN_API_KEY="" WENXIN_MODEL_LIST="" \
     # xAI

src/app/[variants]/(main)/settings/llm/ProviderList/providers.tsx

@@ -28,6 +28,7 @@ import {
   TaichuProviderCard,
   TogetherAIProviderCard,
   UpstageProviderCard,
+  VLLMProviderCard,
   WenxinProviderCard,
   XAIProviderCard,
   ZeroOneProviderCard,
@@ -57,6 +58,7 @@ export const useProviderList = (): ProviderItem[] => {
       OpenAIProvider,
       AzureProvider,
       OllamaProvider,
+      VLLMProviderCard,
       AnthropicProviderCard,
       BedrockProvider,
       GoogleProviderCard,

src/config/aiModels/index.ts

@@ -37,6 +37,7 @@ import { default as taichu } from './taichu';
 import { default as tencentcloud } from './tencentcloud';
 import { default as togetherai } from './togetherai';
 import { default as upstage } from './upstage';
+import { default as vllm } from './vllm';
 import { default as wenxin } from './wenxin';
 import { default as xai } from './xai';
 import { default as zeroone } from './zeroone';
@@ -99,6 +100,7 @@ export const LOBE_DEFAULT_MODEL_LIST = buildDefaultModelList({
   tencentcloud,
   togetherai,
   upstage,
+  vllm,
   wenxin,
   xai,
   zeroone,
@@ -142,6 +144,7 @@ export { default as taichu } from './taichu';
 export { default as tencentcloud } from './tencentcloud';
 export { default as togetherai } from './togetherai';
 export { default as upstage } from './upstage';
+export { default as vllm } from './vllm';
 export { default as wenxin } from './wenxin';
 export { default as xai } from './xai';
 export { default as zeroone } from './zeroone';

src/config/aiModels/vllm.ts

@@ -0,0 +1,94 @@
+import { AIChatModelCard } from '@/types/aiModel';
+
+const vllmChatModels: AIChatModelCard[] = [
+  {
+    abilities: {
+      functionCall: true
+    },
+    contextWindowTokens: 128_000,
+    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 70B',
+    enabled: true,
+    id: 'meta-llama/Meta-Llama-3.1-70B',
+    type: 'chat',
+  },
+  {
+    abilities: {
+      functionCall: true
+    },
+    contextWindowTokens: 128_000,
+    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 405B Instruct',
+    id: 'meta-llama/Meta-Llama-3.1-405B-Instruct',
+    type: 'chat',
+  },
+  {
+    contextWindowTokens: 8192,
+    description:
+      'Gemma 2 是 Google 推出的高效模型，涵盖从小型应用到复杂数据处理的多种应用场景。',
+    displayName: 'Gemma 2 9B',
+    id: 'google/gemma-2-9b',
+    type: 'chat',
+  },
+  {
+    contextWindowTokens: 8192,
+    description:
+      'Gemma 2 是 Google 推出的高效模型，涵盖从小型应用到复杂数据处理的多种应用场景。',
+    displayName: 'Gemma 2 27B',
+    id: 'google/gemma-2-27b',
+    type: 'chat',
+  },
+  {
+    contextWindowTokens: 8192,
+    description:
+      'Mistral (7B) Instruct 以高性能著称，适用于多种语言任务。',
+    displayName: 'Mistral 7B Instruct v0.1',
+    id: 'mistralai/Mistral-7B-Instruct-v0.1',
+    type: 'chat',
+  },
+  {
+    contextWindowTokens: 32_768,
+    description:
+      'Mixtral-8x7B Instruct (46.7B) 提供高容量的计算框架，适合大规模数据处理。',
+    displayName: 'Mistral 8x7B Instruct v0.1',
+    id: 'mistralai/Mixtral-8x7B-Instruct-v0.1',
+    type: 'chat',
+  },
+  {
+    abilities: {
+      functionCall: true
+    },
+    contextWindowTokens: 65_536,
+    description:
+      'DeepSeek-V3 是一款拥有 6710 亿参数的混合专家（MoE）语言模型，采用多头潜在注意力（MLA）和 DeepSeekMoE 架构，结合无辅助损失的负载平衡策略，优化推理和训练效率。通过在 14.8 万亿高质量tokens上预训练，并进行监督微调和强化学习，DeepSeek-V3 在性能上超越其他开源模型，接近领先闭源模型。',
+    displayName: 'DeepSeek V3',
+    enabled: true,
+    id: 'deepseek-ai/DeepSeek-V3',
+    type: 'chat',
+  },
+  {
+    abilities: {
+      reasoning: true
+    },
+    contextWindowTokens: 32_768,
+    description: 'Qwen QwQ 是由 Qwen 团队开发的实验研究模型，专注于提升AI推理能力。',
+    displayName: 'QwQ 32B Preview',
+    enabled: true,
+    id: 'Qwen/QwQ-32B-Preview',
+    type: 'chat',
+  },
+  {
+    contextWindowTokens: 32_768,
+    description: 'Qwen2-7B-Instruct 是 Qwen2 系列中的指令微调大语言模型，参数规模为 7B。该模型基于 Transformer 架构，采用了 SwiGLU 激活函数、注意力 QKV 偏置和组查询注意力等技术。它能够处理大规模输入。该模型在语言理解、生成、多语言能力、编码、数学和推理等多个基准测试中表现出色，超越了大多数开源模型，并在某些任务上展现出与专有模型相当的竞争力。Qwen2-7B-Instruct 在多项评测中均优于 Qwen1.5-7B-Chat，显示出显著的性能提升',
+    displayName: 'Qwen2 7B Instruct',
+    enabled: true,
+    id: 'Qwen/Qwen2-7B-Instruct',
+    type: 'chat',
+  },
+]
+
+export const allModels = [...vllmChatModels];
+
+export default allModels;

src/config/llm.ts

@@ -68,6 +68,9 @@ export const getLLMConfig = () => {
 
       ENABLED_OLLAMA: z.boolean(),
 
+      ENABLED_VLLM: z.boolean(),
+      VLLM_API_KEY: z.string().optional(),
+
       ENABLED_QWEN: z.boolean(),
       QWEN_API_KEY: z.string().optional(),
 
@@ -196,6 +199,9 @@ export const getLLMConfig = () => {
 
       ENABLED_OLLAMA: process.env.ENABLED_OLLAMA !== '0',
 
+      ENABLED_VLLM: !!process.env.VLLM_API_KEY,
+      VLLM_API_KEY: process.env.VLLM_API_KEY,
+
       ENABLED_QWEN: !!process.env.QWEN_API_KEY,
       QWEN_API_KEY: process.env.QWEN_API_KEY,
 

src/config/modelProviders/index.ts

@@ -37,6 +37,7 @@ import TaichuProvider from './taichu';
 import TencentcloudProvider from './tencentcloud';
 import TogetherAIProvider from './togetherai';
 import UpstageProvider from './upstage';
+import VLLMProvider from './vllm';
 import WenxinProvider from './wenxin';
 import XAIProvider from './xai';
 import ZeroOneProvider from './zeroone';
@@ -58,6 +59,7 @@ export const LOBE_DEFAULT_MODEL_LIST: ChatModelCard[] = [
   MistralProvider.chatModels,
   MoonshotProvider.chatModels,
   OllamaProvider.chatModels,
+  VLLMProvider.chatModels,
   OpenRouterProvider.chatModels,
   TogetherAIProvider.chatModels,
   FireworksAIProvider.chatModels,
@@ -89,6 +91,7 @@ export const DEFAULT_MODEL_PROVIDER_LIST = [
   OpenAIProvider,
   { ...AzureProvider, chatModels: [] },
   OllamaProvider,
+  VLLMProvider,
   AnthropicProvider,
   BedrockProvider,
   GoogleProvider,
@@ -175,6 +178,7 @@ export { default as TaichuProviderCard } from './taichu';
 export { default as TencentCloudProviderCard } from './tencentcloud';
 export { default as TogetherAIProviderCard } from './togetherai';
 export { default as UpstageProviderCard } from './upstage';
+export { default as VLLMProviderCard } from './vllm';
 export { default as WenxinProviderCard } from './wenxin';
 export { default as XAIProviderCard } from './xai';
 export { default as ZeroOneProviderCard } from './zeroone';

src/config/modelProviders/vllm.ts

@@ -0,0 +1,20 @@
+import { ModelProviderCard } from '@/types/llm';
+
+const VLLM: ModelProviderCard = {
+  chatModels: [],
+  description: 'vLLM 是一个快速且易于使用的库，用于 LLM 推理和服务。',
+  id: 'vllm',
+  modelList: { showModelFetcher: true },
+  modelsUrl: 'https://docs.vllm.ai/en/latest/models/supported_models.html#supported-models',
+  name: 'vLLM',
+  settings: {
+    proxyUrl: {
+      placeholder: 'http://localhost:8000/v1',
+    },
+    sdkType: 'openai',
+    showModelFetcher: true,
+  },
+  url: 'https://docs.vllm.ai',
+};
+
+export default VLLM; 

src/libs/agent-runtime/AgentRuntime.ts

@@ -49,6 +49,7 @@ import {
   TextToSpeechPayload,
 } from './types';
 import { LobeUpstageAI } from './upstage';
+import { LobeVLLMAI } from './vllm';
 import { LobeWenxinAI } from './wenxin';
 import { LobeXAI } from './xai';
 import { LobeZeroOneAI } from './zeroone';
@@ -172,6 +173,7 @@ class AgentRuntime {
       tencentcloud: Partial<ClientOptions>;
       togetherai: Partial<ClientOptions>;
       upstage: Partial<ClientOptions>;
+      vllm: Partial<ClientOptions>;
       wenxin: Partial<ClientOptions>;
       xai: Partial<ClientOptions>;
       zeroone: Partial<ClientOptions>;
@@ -227,6 +229,11 @@ class AgentRuntime {
         break;
       }
 
+      case ModelProvider.VLLM: {
+        runtimeModel = new LobeVLLMAI(params.vllm);
+        break;
+      }
+
       case ModelProvider.Perplexity: {
         runtimeModel = new LobePerplexityAI(params.perplexity);
         break;

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

@@ -59,6 +59,7 @@ export enum ModelProvider {
   TencentCloud = 'tencentcloud',
   TogetherAI = 'togetherai',
   Upstage = 'upstage',
+  VLLM = 'vllm',
   Wenxin = 'wenxin',
   XAI = 'xai',
   ZeroOne = 'zeroone',

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

@@ -0,0 +1,44 @@
+import { ModelProvider } from '../types';
+import { LobeOpenAICompatibleFactory } from '../utils/openaiCompatibleFactory';
+
+import type { ChatModelCard } from '@/types/llm';
+
+export interface VLLMModelCard {
+  id: string;
+}
+
+export const LobeVLLMAI = LobeOpenAICompatibleFactory({
+  baseURL: 'http://localhost:8000/v1',
+  debug: {
+    chatCompletion: () => process.env.DEBUG_VLLM_CHAT_COMPLETION === '1',
+  },
+  models: async ({ client }) => {
+    const { LOBE_DEFAULT_MODEL_LIST } = await import('@/config/aiModels');
+
+    const modelsPage = await client.models.list() as any;
+    const modelList: VLLMModelCard[] = modelsPage.data;
+
+    return modelList
+      .map((model) => {
+        const knownModel = LOBE_DEFAULT_MODEL_LIST.find((m) => model.id.toLowerCase() === m.id.toLowerCase());
+
+        return {
+          contextWindowTokens: knownModel?.contextWindowTokens ?? undefined,
+          displayName: knownModel?.displayName ?? undefined,
+          enabled: knownModel?.enabled || false,
+          functionCall:
+            knownModel?.abilities?.functionCall
+            || false,
+          id: model.id,
+          reasoning:
+            knownModel?.abilities?.reasoning
+            || false,
+          vision:
+            knownModel?.abilities?.vision
+            || false,
+        };
+      })
+      .filter(Boolean) as ChatModelCard[];
+  },
+  provider: ModelProvider.VLLM,
+});

src/types/user/settings/keyVaults.ts

@@ -65,6 +65,7 @@ export interface UserKeyVaults {
   tencentcloud?: OpenAICompatibleKeyVault;
   togetherai?: OpenAICompatibleKeyVault;
   upstage?: OpenAICompatibleKeyVault;
+  vllm?: OpenAICompatibleKeyVault;
   wenxin?: OpenAICompatibleKeyVault;
   xai?: OpenAICompatibleKeyVault;
   zeroone?: OpenAICompatibleKeyVault;