Update README.md

docs: add ClawCloud Run button

README.md

@@ -1,21 +1,5 @@
 # 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
 
-<div align="center" markdown="1">
-   <sup>Special thanks to:</sup>
-   <br>
-   <br>
-   <a href="https://www.warp.dev/perplexica">
-      <img alt="Warp sponsorship" width="400" src="https://github.com/user-attachments/assets/775dd593-9b5f-40f1-bf48-479faff4c27b">
-   </a>
-
-### [Warp, the AI Devtool that lives in your terminal](https://www.warp.dev/perplexica)
-
-[Available for MacOS, Linux, & Windows](https://www.warp.dev/perplexica)
-
-</div>
-
-<hr/>
-
 [![Discord](https://dcbadge.vercel.app/api/server/26aArMy8tT?style=flat&compact=true)](https://discord.gg/26aArMy8tT)
 
 ![preview](.assets/perplexica-screenshot.png?)
@@ -159,6 +143,7 @@ Perplexica runs on Next.js and handles all API requests. It works right away on
 
 [![Deploy to Sealos](https://raw.githubusercontent.com/labring-actions/templates/main/Deploy-on-Sealos.svg)](https://usw.sealos.io/?openapp=system-template%3FtemplateName%3Dperplexica)
 [![Deploy to RepoCloud](https://d16t0pc4846x52.cloudfront.net/deploylobe.svg)](https://repocloud.io/details/?app_id=267)
+[![Run on ClawCloud](https://raw.githubusercontent.com/ClawCloud/Run-Template/refs/heads/main/Run-on-ClawCloud.svg)](https://template.run.claw.cloud/?referralCode=U11MRQ8U9RM4&openapp=system-fastdeploy%3FtemplateName%3Dperplexica)
 
 ## Upcoming Features
 

sample.config.toml

@@ -25,9 +25,8 @@ API_URL = "" # Ollama API URL - http://host.docker.internal:11434
 [MODELS.DEEPSEEK]
 API_KEY = ""
 
+[MODELS.LM_STUDIO]
+API_URL = "" # LM Studio API URL - http://host.docker.internal:1234
+
 [API_ENDPOINTS]
 SEARXNG = "" # SearxNG API URL - http://localhost:32768
-TAVILY = "" # Tavily API key
-
-[SEARCH]
-ENGINE = "searxng" # "searxng" or "tavily"

src/app/api/config/route.ts

@@ -8,8 +8,7 @@ import {
   getOllamaApiEndpoint,
   getOpenaiApiKey,
   getDeepseekApiKey,
-  getSearchEngine,
+  getLMStudioApiEndpoint,
-  getTavilyApiKey,
   updateConfig,
 } from '@/lib/config';
 import {
@@ -53,6 +52,7 @@ export const GET = async (req: Request) => {
 
     config['openaiApiKey'] = getOpenaiApiKey();
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
@@ -60,8 +60,6 @@ export const GET = async (req: Request) => {
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
     config['customOpenaiModelName'] = getCustomOpenaiModelName();
-    config['searchEngine'] = getSearchEngine();
-    config['tavilyApiKey'] = getTavilyApiKey();
 
     return Response.json({ ...config }, { status: 200 });
   } catch (err) {
@@ -97,18 +95,15 @@ export const POST = async (req: Request) => {
         DEEPSEEK: {
           API_KEY: config.deepseekApiKey,
         },
+        LM_STUDIO: {
+          API_URL: config.lmStudioApiUrl,
+        },
         CUSTOM_OPENAI: {
           API_URL: config.customOpenaiApiUrl,
           API_KEY: config.customOpenaiApiKey,
           MODEL_NAME: config.customOpenaiModelName,
         },
       },
-      SEARCH: {
-        ENGINE: config.searchEngine,
-      },
-      API_ENDPOINTS: {
-        TAVILY: config.tavilyApiKey || '',
-      },
     };
 
     updateConfig(updatedConfig);

src/app/api/discover/route.ts

@@ -1,4 +1,4 @@
-import { searchSearxng } from '../../../lib/searchEngines/searxng';
+import { searchSearxng } from '@/lib/searxng';
 
 const articleWebsites = [
   'yahoo.com',

src/app/settings/page.tsx

@@ -7,6 +7,7 @@ import { Switch } from '@headlessui/react';
 import ThemeSwitcher from '@/components/theme/Switcher';
 import { ImagesIcon, VideoIcon } from 'lucide-react';
 import Link from 'next/link';
+import { PROVIDER_METADATA } from '@/lib/providers';
 
 interface SettingsType {
   chatModelProviders: {
@@ -20,12 +21,11 @@ interface SettingsType {
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
+  lmStudioApiUrl: string;
   deepseekApiKey: string;
   customOpenaiApiKey: string;
   customOpenaiApiUrl: string;
   customOpenaiModelName: string;
-  searchEngine: string;
-  tavilyApiKey?: string;
 }
 
 interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
@@ -147,7 +147,6 @@ const Page = () => {
   const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
   const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
   const [systemInstructions, setSystemInstructions] = useState<string>('');
-  const [searchEngine, setSearchEngine] = useState<string>('searxng');
   const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
 
   useEffect(() => {
@@ -210,7 +209,6 @@ const Page = () => {
       );
 
       setSystemInstructions(localStorage.getItem('systemInstructions')!);
-      setSearchEngine(localStorage.getItem('searchEngine') || 'searxng');
 
       setIsLoading(false);
     };
@@ -370,10 +368,6 @@ const Page = () => {
         localStorage.setItem('embeddingModel', value);
       } else if (key === 'systemInstructions') {
         localStorage.setItem('systemInstructions', value);
-      } else if (key === 'searchEngine') {
-        localStorage.setItem('searchEngine', value);
-      } else if (key === 'tavilyApiKey') {
-        localStorage.setItem('tavilyApiKey', value);
       }
     } catch (err) {
       console.error('Failed to save:', err);
@@ -516,32 +510,6 @@ const Page = () => {
                     />
                   </Switch>
                 </div>
-
-                <div className="flex flex-col space-y-1 mt-2">
-                  <p className="text-black/70 dark:text-white/70 text-sm">
-                    Search Engine
-                  </p>
-                  <Select
-                    value={searchEngine}
-                    onChange={(e) => {
-                      const value = e.target.value;
-                      setSearchEngine(value);
-                      saveConfig('searchEngine', value);
-                    }}
-                    options={[
-                      { value: 'searxng', label: 'SearxNG' },
-                      ...(config.tavilyApiKey ? [{ value: 'tavily', label: 'Tavily' }] : []),
-                    ]}
-                  />
-                  <p className="text-xs text-black/60 dark:text-white/60 mt-1">
-                    Select which search engine to use for web searches
-                  </p>
-                  {searchEngine === 'tavily' && !config.tavilyApiKey && (
-                    <p className="text-xs text-red-500 mt-1">
-                      Tavily API key is required to use this search engine
-                    </p>
-                  )}
-                </div>
               </div>
             </SettingsSection>
 
@@ -582,8 +550,9 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
-                            provider.slice(1),
+                              provider.slice(1),
                         }),
                       )}
                     />
@@ -724,8 +693,9 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
-                            provider.slice(1),
+                              provider.slice(1),
                         }),
                       )}
                     />
@@ -893,29 +863,22 @@ const Page = () => {
                   />
                 </div>
 
-                <div className="flex flex-col space-y-1 mt-4 pt-4 border-t border-light-200 dark:border-dark-200">
-                  <p className="text-black/90 dark:text-white/90 font-medium">Search Engine API Keys</p>
-                  <p className="text-sm text-black/60 dark:text-white/60 mt-0.5">
-                    API keys for search engines used in the application
-                  </p>
-                </div>
-
                 <div className="flex flex-col space-y-1">
                   <p className="text-black/70 dark:text-white/70 text-sm">
-                    Tavily API Key
+                    LM Studio API URL
                   </p>
                   <Input
                     type="text"
-                    placeholder="Tavily API key"
+                    placeholder="LM Studio API URL"
-                    value={config.tavilyApiKey || ''}
+                    value={config.lmStudioApiUrl}
-                    isSaving={savingStates['tavilyApiKey']}
+                    isSaving={savingStates['lmStudioApiUrl']}
                     onChange={(e) => {
                       setConfig((prev) => ({
                         ...prev!,
-                        tavilyApiKey: e.target.value,
+                        lmStudioApiUrl: e.target.value,
                       }));
                     }}
-                    onSave={(value) => saveConfig('tavilyApiKey', value)}
+                    onSave={(value) => saveConfig('lmStudioApiUrl', value)}
                   />
                 </div>
               </div>

src/components/MessageBox.tsx

@@ -97,6 +97,7 @@ const MessageBox = ({
           },
         ),
       );
+      setSpeechMessage(message.content.replace(regex, ''));
       return;
     }
 

src/lib/chains/imageSearchAgent.ts

@@ -7,7 +7,7 @@ import { PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
-import { searchSearxng } from '../searchEngines/searxng';
+import { searchSearxng } from '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const imageSearchChainPrompt = `

src/lib/chains/videoSearchAgent.ts

@@ -7,7 +7,7 @@ import { PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
-import { searchSearxng } from '../searchEngines/searxng';
+import { searchSearxng } from '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const VideoSearchChainPrompt = `

src/lib/config.ts

@@ -1,7 +1,14 @@
-import fs from 'fs';
-import path from 'path';
 import toml from '@iarna/toml';
 
+// Use dynamic imports for Node.js modules to prevent client-side errors
+let fs: any;
+let path: any;
+if (typeof window === 'undefined') {
+  // We're on the server
+  fs = require('fs');
+  path = require('path');
+}
+
 const configFileName = 'config.toml';
 
 interface Config {
@@ -28,6 +35,9 @@ interface Config {
     DEEPSEEK: {
       API_KEY: string;
     };
+    LM_STUDIO: {
+      API_URL: string;
+    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -36,10 +46,6 @@ interface Config {
   };
   API_ENDPOINTS: {
     SEARXNG: string;
-    TAVILY: string;
-  };
-  SEARCH: {
-    ENGINE: string;
   };
 }
 
@@ -47,10 +53,17 @@ type RecursivePartial<T> = {
   [P in keyof T]?: RecursivePartial<T[P]>;
 };
 
-const loadConfig = () =>
+const loadConfig = () => {
-  toml.parse(
+  // Server-side only
-    fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
+  if (typeof window === 'undefined') {
-  ) as any as Config;
+    return toml.parse(
+      fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
+    ) as any as Config;
+  }
+
+  // Client-side fallback - settings will be loaded via API
+  return {} as Config;
+};
 
 export const getSimilarityMeasure = () =>
   loadConfig().GENERAL.SIMILARITY_MEASURE;
@@ -68,12 +81,6 @@ export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
 export const getSearxngApiEndpoint = () =>
   process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
 
-export const getTavilyApiKey = () =>
-  process.env.TAVILY_API_KEY || loadConfig().API_ENDPOINTS.TAVILY;
-
-export const getSearchEngine = () =>
-  process.env.SEARCH_ENGINE || loadConfig().SEARCH?.ENGINE || 'searxng';
-
 export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
 
 export const getDeepseekApiKey = () => loadConfig().MODELS.DEEPSEEK.API_KEY;
@@ -87,6 +94,9 @@ export const getCustomOpenaiApiUrl = () =>
 export const getCustomOpenaiModelName = () =>
   loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
 
+export const getLMStudioApiEndpoint = () =>
+  loadConfig().MODELS.LM_STUDIO.API_URL;
+
 const mergeConfigs = (current: any, update: any): any => {
   if (update === null || update === undefined) {
     return current;
@@ -119,10 +129,13 @@ const mergeConfigs = (current: any, update: any): any => {
 };
 
 export const updateConfig = (config: RecursivePartial<Config>) => {
-  const currentConfig = loadConfig();
+  // Server-side only
-  const mergedConfig = mergeConfigs(currentConfig, config);
+  if (typeof window === 'undefined') {
-  fs.writeFileSync(
+    const currentConfig = loadConfig();
-    path.join(path.join(process.cwd(), `${configFileName}`)),
+    const mergedConfig = mergeConfigs(currentConfig, config);
-    toml.stringify(mergedConfig),
+    fs.writeFileSync(
-  );
+      path.join(path.join(process.cwd(), `${configFileName}`)),
+      toml.stringify(mergedConfig),
+    );
+  }
 };

src/lib/providers/anthropic.ts

@@ -1,6 +1,11 @@
 import { ChatAnthropic } from '@langchain/anthropic';
 import { ChatModel } from '.';
 import { getAnthropicApiKey } from '../config';
+
+export const PROVIDER_INFO = {
+  key: 'anthropic',
+  displayName: 'Anthropic',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const anthropicChatModels: Record<string, string>[] = [

src/lib/providers/deepseek.ts

@@ -3,6 +3,11 @@ import { getDeepseekApiKey } from '../config';
 import { ChatModel } from '.';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
+export const PROVIDER_INFO = {
+  key: 'deepseek',
+  displayName: 'Deepseek AI',
+};
+
 const deepseekChatModels: Record<string, string>[] = [
   {
     displayName: 'Deepseek Chat (Deepseek V3)',

src/lib/providers/gemini.ts

@@ -4,6 +4,11 @@ import {
 } from '@langchain/google-genai';
 import { getGeminiApiKey } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'gemini',
+  displayName: 'Google Gemini',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { Embeddings } from '@langchain/core/embeddings';
 

src/lib/providers/groq.ts

@@ -1,6 +1,11 @@
 import { ChatOpenAI } from '@langchain/openai';
 import { getGroqApiKey } from '../config';
 import { ChatModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'groq',
+  displayName: 'Groq',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const groqChatModels: Record<string, string>[] = [

src/lib/providers/index.ts

@@ -1,18 +1,60 @@
 import { Embeddings } from '@langchain/core/embeddings';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai';
+import {
+  loadOpenAIChatModels,
+  loadOpenAIEmbeddingModels,
+  PROVIDER_INFO as OpenAIInfo,
+  PROVIDER_INFO,
+} from './openai';
 import {
   getCustomOpenaiApiKey,
   getCustomOpenaiApiUrl,
   getCustomOpenaiModelName,
 } from '../config';
 import { ChatOpenAI } from '@langchain/openai';
-import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
+import {
-import { loadGroqChatModels } from './groq';
+  loadOllamaChatModels,
-import { loadAnthropicChatModels } from './anthropic';
+  loadOllamaEmbeddingModels,
-import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
+  PROVIDER_INFO as OllamaInfo,
-import { loadTransformersEmbeddingsModels } from './transformers';
+} from './ollama';
-import { loadDeepseekChatModels } from './deepseek';
+import { loadGroqChatModels, PROVIDER_INFO as GroqInfo } from './groq';
+import {
+  loadAnthropicChatModels,
+  PROVIDER_INFO as AnthropicInfo,
+} from './anthropic';
+import {
+  loadGeminiChatModels,
+  loadGeminiEmbeddingModels,
+  PROVIDER_INFO as GeminiInfo,
+} from './gemini';
+import {
+  loadTransformersEmbeddingsModels,
+  PROVIDER_INFO as TransformersInfo,
+} from './transformers';
+import {
+  loadDeepseekChatModels,
+  PROVIDER_INFO as DeepseekInfo,
+} from './deepseek';
+import {
+  loadLMStudioChatModels,
+  loadLMStudioEmbeddingsModels,
+  PROVIDER_INFO as LMStudioInfo,
+} from './lmstudio';
+
+export const PROVIDER_METADATA = {
+  openai: OpenAIInfo,
+  ollama: OllamaInfo,
+  groq: GroqInfo,
+  anthropic: AnthropicInfo,
+  gemini: GeminiInfo,
+  transformers: TransformersInfo,
+  deepseek: DeepseekInfo,
+  lmstudio: LMStudioInfo,
+  custom_openai: {
+    key: 'custom_openai',
+    displayName: 'Custom OpenAI',
+  },
+};
 
 export interface ChatModel {
   displayName: string;
@@ -34,6 +76,7 @@ export const chatModelProviders: Record<
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
   deepseek: loadDeepseekChatModels,
+  lmstudio: loadLMStudioChatModels,
 };
 
 export const embeddingModelProviders: Record<
@@ -44,6 +87,7 @@ export const embeddingModelProviders: Record<
   ollama: loadOllamaEmbeddingModels,
   gemini: loadGeminiEmbeddingModels,
   transformers: loadTransformersEmbeddingsModels,
+  lmstudio: loadLMStudioEmbeddingsModels,
 };
 
 export const getAvailableChatModelProviders = async () => {

src/lib/providers/lmstudio.ts

@@ -0,0 +1,100 @@
+import { getKeepAlive, getLMStudioApiEndpoint } from '../config';
+import axios from 'axios';
+import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'lmstudio',
+  displayName: 'LM Studio',
+};
+import { ChatOpenAI } from '@langchain/openai';
+import { OpenAIEmbeddings } from '@langchain/openai';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { Embeddings } from '@langchain/core/embeddings';
+
+interface LMStudioModel {
+  id: string;
+  name?: string;
+}
+
+const ensureV1Endpoint = (endpoint: string): string =>
+  endpoint.endsWith('/v1') ? endpoint : `${endpoint}/v1`;
+
+const checkServerAvailability = async (endpoint: string): Promise<boolean> => {
+  try {
+    await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+    return true;
+  } catch {
+    return false;
+  }
+};
+
+export const loadLMStudioChatModels = async () => {
+  const endpoint = getLMStudioApiEndpoint();
+
+  if (!endpoint) return {};
+  if (!(await checkServerAvailability(endpoint))) return {};
+
+  try {
+    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+
+    const chatModels: Record<string, ChatModel> = {};
+
+    response.data.data.forEach((model: LMStudioModel) => {
+      chatModels[model.id] = {
+        displayName: model.name || model.id,
+        model: new ChatOpenAI({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: ensureV1Endpoint(endpoint),
+          },
+          modelName: model.id,
+          temperature: 0.7,
+          streaming: true,
+          maxRetries: 3,
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading LM Studio models: ${err}`);
+    return {};
+  }
+};
+
+export const loadLMStudioEmbeddingsModels = async () => {
+  const endpoint = getLMStudioApiEndpoint();
+
+  if (!endpoint) return {};
+  if (!(await checkServerAvailability(endpoint))) return {};
+
+  try {
+    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+
+    const embeddingsModels: Record<string, EmbeddingModel> = {};
+
+    response.data.data.forEach((model: LMStudioModel) => {
+      embeddingsModels[model.id] = {
+        displayName: model.name || model.id,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: ensureV1Endpoint(endpoint),
+          },
+          modelName: model.id,
+        }) as unknown as Embeddings,
+      };
+    });
+
+    return embeddingsModels;
+  } catch (err) {
+    console.error(`Error loading LM Studio embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/ollama.ts

@@ -1,6 +1,11 @@
 import axios from 'axios';
 import { getKeepAlive, getOllamaApiEndpoint } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'ollama',
+  displayName: 'Ollama',
+};
 import { ChatOllama } from '@langchain/community/chat_models/ollama';
 import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
 

src/lib/providers/openai.ts

@@ -1,6 +1,11 @@
 import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
 import { getOpenaiApiKey } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'openai',
+  displayName: 'OpenAI',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { Embeddings } from '@langchain/core/embeddings';
 
@@ -25,6 +30,18 @@ const openaiChatModels: Record<string, string>[] = [
     displayName: 'GPT-4 omni mini',
     key: 'gpt-4o-mini',
   },
+  {
+    displayName: 'GPT 4.1 nano',
+    key: 'gpt-4.1-nano',
+  },
+  {
+    displayName: 'GPT 4.1 mini',
+    key: 'gpt-4.1-mini',
+  },
+  {
+    displayName: 'GPT 4.1',
+    key: 'gpt-4.1',
+  },
 ];
 
 const openaiEmbeddingModels: Record<string, string>[] = [

src/lib/providers/transformers.ts

@@ -1,5 +1,10 @@
 import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
 
+export const PROVIDER_INFO = {
+  key: 'transformers',
+  displayName: 'Hugging Face',
+};
+
 export const loadTransformersEmbeddingsModels = async () => {
   try {
     const embeddingModels = {

src/lib/search/metaSearchAgent.ts

@@ -17,9 +17,7 @@ import LineListOutputParser from '../outputParsers/listLineOutputParser';
 import LineOutputParser from '../outputParsers/lineOutputParser';
 import { getDocumentsFromLinks } from '../utils/documents';
 import { Document } from 'langchain/document';
-import { searchTavily } from '../searchEngines/tavily';
+import { searchSearxng } from '../searxng';
-import { searchSearxng } from '../searchEngines/searxng';
-import { getSearchEngine } from '../config';
 import path from 'node:path';
 import fs from 'node:fs';
 import computeSimilarity from '../utils/computeSimilarity';
@@ -207,42 +205,25 @@ class MetaSearchAgent implements MetaSearchAgentType {
         } else {
           question = question.replace(/<think>.*?<\/think>/g, '');
 
-          const searchEngine = getSearchEngine();
+          const res = await searchSearxng(question, {
+            language: 'en',
+            engines: this.config.activeEngines,
+          });
 
-          let res;
+          const documents = res.results.map(
-          
+            (result) =>
-          if (searchEngine === 'tavily') {
+              new Document({
-            res = await searchTavily(question, {
+                pageContent:
-              search_depth: 'basic',
+                  result.content ||
-              max_results: 15,
+                  (this.config.activeEngines.includes('youtube')
-              include_images: true,
+                    ? result.title
-            });
+                    : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
-          } else {
+                metadata: {
-            // Default to SearxNG
+                  title: result.title,
-            res = await searchSearxng(question, {
+                  url: result.url,
-              language: 'en',
+                  ...(result.img_src && { img_src: result.img_src }),
-              engines: this.config.activeEngines,
+                },
-            });
+              }),
-          }
-
-          let documents: Document[] = [];
-          
-          documents = documents.concat(
-            res.results.map(
-              (result) =>
-                new Document({
-                  pageContent:
-                    result.content ||
-                    (this.config.activeEngines.includes('youtube')
-                      ? result.title
-                      : ''),
-                  metadata: {
-                    title: result.title,
-                    url: result.url,
-                    ...(result.img_src ? { img_src: result.img_src } : {}),
-                  },
-                }),
-            )
           );
 
           return { query: question, docs: documents };

src/lib/searchEngines/tavily.ts

@@ -1,79 +0,0 @@
-import axios from 'axios';
-import { getTavilyApiKey } from '../config';
-
-interface TavilySearchOptions {
-  topic?: 'general' | 'news';
-  search_depth?: 'basic' | 'advanced';
-  chunks_per_source?: number;
-  max_results?: number;
-  time_range?: 'day' | 'week' | 'month' | 'year' | 'd' | 'w' | 'm' | 'y';
-  days?: number;
-  include_answer?: boolean | 'basic' | 'advanced';
-  include_raw_content?: boolean;
-  include_images?: boolean;
-  include_image_descriptions?: boolean;
-  include_domains?: string[];
-  exclude_domains?: string[];
-}
-
-interface TavilySearchResult {
-  title: string;
-  url: string;
-  content: string;
-  score: number;
-  raw_content?: string;
-}
-
-interface TavilySearchResponse {
-  query: string;
-  answer?: string;
-  images?: Array<{
-    url: string;
-    description?: string;
-  }>;
-  results: TavilySearchResult[];
-  response_time: string;
-}
-
-export const searchTavily = async (
-  query: string,
-  opts?: TavilySearchOptions,
-) => {
-  const tavilyApiKey = getTavilyApiKey();
-  
-  if (!tavilyApiKey) {
-    throw new Error('Tavily API key is not configured');
-  }
-
-  const url = 'https://api.tavily.com/search';
-  
-  const response = await axios.post<TavilySearchResponse>(
-    url,
-    {
-      query,
-      ...opts,
-    },
-    {
-      headers: {
-        'Content-Type': 'application/json',
-        'Authorization': `Bearer ${tavilyApiKey}`,
-      },
-    }
-  );
-
-  const results = response.data.results;
-  
-  // Convert Tavily results to match the format expected by the rest of the application
-  const formattedResults = results.map(result => ({
-    title: result.title,
-    url: result.url,
-    content: result.content,
-    img_src: undefined, // Tavily doesn't provide image URLs in the standard response
-  }));
-
-  return { 
-    results: formattedResults, 
-    suggestions: [], // Tavily doesn't provide suggestions, so return empty array
-    answer: response.data.answer, // Include the AI-generated answer if available
-  };
-}; 

src/lib/searxng.ts

@@ -1,5 +1,5 @@
 import axios from 'axios';
-import { getSearxngApiEndpoint } from '../config';
+import { getSearxngApiEndpoint } from './config';
 
 interface SearxngSearchOptions {
   categories?: string[];

src/lib/utils/documents.ts

@@ -64,7 +64,7 @@ export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
         const splittedText = await splitter.splitText(parsedText);
         const title = res.data
           .toString('utf8')
-          .match(/<title>(.*?)<\/title>/)?.[1];
+          .match(/<title.*>(.*?)<\/title>/)?.[1];
 
         const linkDocs = splittedText.map((text) => {
           return new Document({