Merge b3aafba30c35c29b4126c2421e4ddde8f16e05d7 into 4154d5e4b113909575eeb325885346b46f4b651f

docs: add ClawCloud Run button

.github/workflows/docker-build.yaml

@@ -114,6 +114,11 @@ jobs:
           username: ${{ secrets.DOCKER_USERNAME }}
           password: ${{ secrets.DOCKER_PASSWORD }}
 
+      - name: Extract version from release tag
+        if: github.event_name == 'release'
+        id: version
+        run: echo "RELEASE_VERSION=${GITHUB_REF#refs/tags/}" >> $GITHUB_ENV
+
       - name: Create and push multi-arch manifest for main
         if: github.ref == 'refs/heads/master' && github.event_name == 'push'
         run: |

README.md

@@ -159,6 +159,7 @@ 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
 

docs/API/SEARCH.md

@@ -33,6 +33,7 @@ The API accepts a JSON object in the request body, where you define the focus mo
     ["human", "Hi, how are you?"],
     ["assistant", "I am doing well, how can I help you today?"]
   ],
+  "systemInstructions": "Focus on providing technical details about Perplexica's architecture.",
   "stream": false
 }
 ```
@@ -63,6 +64,8 @@ The API accepts a JSON object in the request body, where you define the focus mo
 
 - **`query`** (string, required): The search query or question.
 
+- **`systemInstructions`** (string, optional): Custom instructions provided by the user to guide the AI's response. These instructions are treated as user preferences and have lower priority than the system's core instructions. For example, you can specify a particular writing style, format, or focus area.
+
 - **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
 
   ```json

package.json

@@ -1,6 +1,6 @@
 {
   "name": "perplexica-frontend",
-  "version": "1.10.1",
+  "version": "1.10.2",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
@@ -20,6 +20,7 @@
     "@langchain/core": "^0.3.42",
     "@langchain/google-genai": "^0.1.12",
     "@langchain/openai": "^0.0.25",
+    "@langchain/ollama": "^0.2.0",
     "@langchain/textsplitters": "^0.1.0",
     "@tailwindcss/typography": "^0.5.12",
     "@xenova/transformers": "^2.17.2",

sample.config.toml

@@ -22,5 +22,11 @@ MODEL_NAME = ""
 [MODELS.OLLAMA]
 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
+SEARXNG = "" # SearxNG API URL - http://localhost:32768

src/app/api/chat/route.ts

@@ -20,6 +20,7 @@ import {
   getCustomOpenaiApiUrl,
   getCustomOpenaiModelName,
 } from '@/lib/config';
+import { ChatOllama } from '@langchain/ollama';
 import { searchHandlers } from '@/lib/search';
 
 export const runtime = 'nodejs';
@@ -34,6 +35,7 @@ type Message = {
 type ChatModel = {
   provider: string;
   name: string;
+  ollamaContextWindow?: number;
 };
 
 type EmbeddingModel = {
@@ -49,6 +51,7 @@ type Body = {
   files: Array<string>;
   chatModel: ChatModel;
   embeddingModel: EmbeddingModel;
+  systemInstructions: string;
 };
 
 const handleEmitterEvents = async (
@@ -231,6 +234,11 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {
@@ -278,6 +286,7 @@ export const POST = async (req: Request) => {
       embedding,
       body.optimizationMode,
       body.files,
+      body.systemInstructions,
     );
 
     const responseStream = new TransformStream();

src/app/api/config/route.ts

@@ -7,6 +7,8 @@ import {
   getGroqApiKey,
   getOllamaApiEndpoint,
   getOpenaiApiKey,
+  getDeepseekApiKey,
+  getLMStudioApiEndpoint,
   updateConfig,
 } from '@/lib/config';
 import {
@@ -50,9 +52,11 @@ export const GET = async (req: Request) => {
 
     config['openaiApiKey'] = getOpenaiApiKey();
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
+    config['deepseekApiKey'] = getDeepseekApiKey();
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
     config['customOpenaiModelName'] = getCustomOpenaiModelName();
@@ -88,6 +92,12 @@ export const POST = async (req: Request) => {
         OLLAMA: {
           API_URL: config.ollamaApiUrl,
         },
+        DEEPSEEK: {
+          API_KEY: config.deepseekApiKey,
+        },
+        LM_STUDIO: {
+          API_URL: config.lmStudioApiUrl,
+        },
         CUSTOM_OPENAI: {
           API_URL: config.customOpenaiApiUrl,
           API_KEY: config.customOpenaiApiKey,

src/app/api/images/route.ts

@@ -7,11 +7,13 @@ import {
 import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { ChatOllama } from '@langchain/ollama';
 import { ChatOpenAI } from '@langchain/openai';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface ImageSearchBody {
@@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {

src/app/api/search/route.ts

@@ -13,12 +13,14 @@ import {
   getCustomOpenaiModelName,
 } from '@/lib/config';
 import { searchHandlers } from '@/lib/search';
+import { ChatOllama } from '@langchain/ollama';
 
 interface chatModel {
   provider: string;
   name: string;
   customOpenAIKey?: string;
   customOpenAIBaseURL?: string;
+  ollamaContextWindow?: number;
 }
 
 interface embeddingModel {
@@ -34,6 +36,7 @@ interface ChatRequestBody {
   query: string;
   history: Array<[string, string]>;
   stream?: boolean;
+  systemInstructions?: string;
 }
 
 export const POST = async (req: Request) => {
@@ -96,6 +99,10 @@ export const POST = async (req: Request) => {
         .model as unknown as BaseChatModel | undefined;
     }
 
+    if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+      llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+    }
+
     if (
       embeddingModelProviders[embeddingModelProvider] &&
       embeddingModelProviders[embeddingModelProvider][embeddingModel]
@@ -125,6 +132,7 @@ export const POST = async (req: Request) => {
       embeddings,
       body.optimizationMode,
       [],
+      body.systemInstructions || '',
     );
 
     if (!body.stream) {

src/app/api/suggestions/route.ts

@@ -8,10 +8,12 @@ import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
 import { ChatOpenAI } from '@langchain/openai';
+import { ChatOllama } from '@langchain/ollama';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface SuggestionsGenerationBody {
@@ -57,6 +59,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {

src/app/api/videos/route.ts

@@ -7,11 +7,13 @@ import {
 import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { ChatOllama } from '@langchain/ollama';
 import { ChatOpenAI } from '@langchain/openai';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface VideoSearchBody {
@@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {

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: {
@@ -20,9 +21,12 @@ interface SettingsType {
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
+  lmStudioApiUrl: string;
+  deepseekApiKey: string;
   customOpenaiApiKey: string;
   customOpenaiApiUrl: string;
   customOpenaiModelName: string;
+  ollamaContextWindow: number;
 }
 
 interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
@@ -54,6 +58,38 @@ const Input = ({ className, isSaving, onSave, ...restProps }: InputProps) => {
   );
 };
 
+interface TextareaProps extends React.InputHTMLAttributes<HTMLTextAreaElement> {
+  isSaving?: boolean;
+  onSave?: (value: string) => void;
+}
+
+const Textarea = ({
+  className,
+  isSaving,
+  onSave,
+  ...restProps
+}: TextareaProps) => {
+  return (
+    <div className="relative">
+      <textarea
+        placeholder="Any special instructions for the LLM"
+        className="placeholder:text-sm text-sm w-full flex items-center justify-between p-3 bg-light-secondary dark:bg-dark-secondary rounded-lg hover:bg-light-200 dark:hover:bg-dark-200 transition-colors"
+        rows={4}
+        onBlur={(e) => onSave?.(e.target.value)}
+        {...restProps}
+      />
+      {isSaving && (
+        <div className="absolute right-3 top-3">
+          <Loader2
+            size={16}
+            className="animate-spin text-black/70 dark:text-white/70"
+          />
+        </div>
+      )}
+    </div>
+  );
+};
+
 const Select = ({
   className,
   options,
@@ -111,7 +147,13 @@ const Page = () => {
   const [isLoading, setIsLoading] = useState(false);
   const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
   const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
+  const [systemInstructions, setSystemInstructions] = useState<string>('');
   const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
+  const [contextWindowSize, setContextWindowSize] = useState(2048);
+  const [isCustomContextWindow, setIsCustomContextWindow] = useState(false);
+  const predefinedContextSizes = [
+    1024, 2048, 3072, 4096, 8192, 16384, 32768, 65536, 131072,
+  ];
 
   useEffect(() => {
     const fetchConfig = async () => {
@@ -123,6 +165,7 @@ const Page = () => {
       });
 
       const data = (await res.json()) as SettingsType;
+
       setConfig(data);
 
       const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
@@ -171,6 +214,15 @@ const Page = () => {
       setAutomaticVideoSearch(
         localStorage.getItem('autoVideoSearch') === 'true',
       );
+      const storedContextWindow = parseInt(
+        localStorage.getItem('ollamaContextWindow') ?? '2048',
+      );
+      setContextWindowSize(storedContextWindow);
+      setIsCustomContextWindow(
+        !predefinedContextSizes.includes(storedContextWindow),
+      );
+
+      setSystemInstructions(localStorage.getItem('systemInstructions')!);
 
       setIsLoading(false);
     };
@@ -328,6 +380,10 @@ const Page = () => {
         localStorage.setItem('embeddingModelProvider', value);
       } else if (key === 'embeddingModel') {
         localStorage.setItem('embeddingModel', value);
+      } else if (key === 'ollamaContextWindow') {
+        localStorage.setItem('ollamaContextWindow', value.toString());
+      } else if (key === 'systemInstructions') {
+        localStorage.setItem('systemInstructions', value);
       }
     } catch (err) {
       console.error('Failed to save:', err);
@@ -473,6 +529,19 @@ const Page = () => {
               </div>
             </SettingsSection>
 
+            <SettingsSection title="System Instructions">
+              <div className="flex flex-col space-y-4">
+                <Textarea
+                  value={systemInstructions}
+                  isSaving={savingStates['systemInstructions']}
+                  onChange={(e) => {
+                    setSystemInstructions(e.target.value);
+                  }}
+                  onSave={(value) => saveConfig('systemInstructions', value)}
+                />
+              </div>
+            </SettingsSection>
+
             <SettingsSection title="Model Settings">
               {config.chatModelProviders && (
                 <div className="flex flex-col space-y-4">
@@ -497,8 +566,9 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
-                            provider.slice(1),
+                              provider.slice(1),
                         }),
                       )}
                     />
@@ -545,6 +615,78 @@ const Page = () => {
                                 ];
                           })()}
                         />
+                        {selectedChatModelProvider === 'ollama' && (
+                          <div className="flex flex-col space-y-1">
+                            <p className="text-black/70 dark:text-white/70 text-sm">
+                              Chat Context Window Size
+                            </p>
+                            <Select
+                              value={
+                                isCustomContextWindow
+                                  ? 'custom'
+                                  : contextWindowSize.toString()
+                              }
+                              onChange={(e) => {
+                                const value = e.target.value;
+                                if (value === 'custom') {
+                                  setIsCustomContextWindow(true);
+                                } else {
+                                  setIsCustomContextWindow(false);
+                                  const numValue = parseInt(value);
+                                  setContextWindowSize(numValue);
+                                  setConfig((prev) => ({
+                                    ...prev!,
+                                    ollamaContextWindow: numValue,
+                                  }));
+                                  saveConfig('ollamaContextWindow', numValue);
+                                }
+                              }}
+                              options={[
+                                ...predefinedContextSizes.map((size) => ({
+                                  value: size.toString(),
+                                  label: `${size.toLocaleString()} tokens`,
+                                })),
+                                { value: 'custom', label: 'Custom...' },
+                              ]}
+                            />
+                            {isCustomContextWindow && (
+                              <div className="mt-2">
+                                <Input
+                                  type="number"
+                                  min={512}
+                                  value={contextWindowSize}
+                                  placeholder="Custom context window size (minimum 512)"
+                                  isSaving={savingStates['ollamaContextWindow']}
+                                  onChange={(e) => {
+                                    // Allow any value to be typed
+                                    const value =
+                                      parseInt(e.target.value) ||
+                                      contextWindowSize;
+                                    setContextWindowSize(value);
+                                  }}
+                                  onSave={(value) => {
+                                    // Validate only when saving
+                                    const numValue = Math.max(
+                                      512,
+                                      parseInt(value) || 2048,
+                                    );
+                                    setContextWindowSize(numValue);
+                                    setConfig((prev) => ({
+                                      ...prev!,
+                                      ollamaContextWindow: numValue,
+                                    }));
+                                    saveConfig('ollamaContextWindow', numValue);
+                                  }}
+                                />
+                              </div>
+                            )}
+                            <p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
+                              {isCustomContextWindow
+                                ? 'Adjust the context window size for Ollama models (minimum 512 tokens)'
+                                : 'Adjust the context window size for Ollama models'}
+                            </p>
+                          </div>
+                        )}
                       </div>
                     )}
                 </div>
@@ -639,8 +781,9 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
-                            provider.slice(1),
+                              provider.slice(1),
                         }),
                       )}
                     />
@@ -788,6 +931,44 @@ const Page = () => {
                     onSave={(value) => saveConfig('geminiApiKey', value)}
                   />
                 </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Deepseek API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Deepseek API Key"
+                    value={config.deepseekApiKey}
+                    isSaving={savingStates['deepseekApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        deepseekApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('deepseekApiKey', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    LM Studio API URL
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="LM Studio API URL"
+                    value={config.lmStudioApiUrl}
+                    isSaving={savingStates['lmStudioApiUrl']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        lmStudioApiUrl: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('lmStudioApiUrl', value)}
+                  />
+                </div>
               </div>
             </SettingsSection>
           </div>

src/components/Chat.tsx

@@ -16,6 +16,8 @@ const Chat = ({
   setFileIds,
   files,
   setFiles,
+  optimizationMode,
+  setOptimizationMode,
 }: {
   messages: Message[];
   sendMessage: (message: string) => void;
@@ -26,6 +28,8 @@ const Chat = ({
   setFileIds: (fileIds: string[]) => void;
   files: File[];
   setFiles: (files: File[]) => void;
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
 }) => {
   const [dividerWidth, setDividerWidth] = useState(0);
   const dividerRef = useRef<HTMLDivElement | null>(null);
@@ -99,6 +103,8 @@ const Chat = ({
             setFileIds={setFileIds}
             files={files}
             setFiles={setFiles}
+            optimizationMode={optimizationMode}
+            setOptimizationMode={setOptimizationMode}
           />
         </div>
       )}

src/components/ChatWindow.tsx

@@ -287,6 +287,16 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
   const [notFound, setNotFound] = useState(false);
 
+  useEffect(() => {
+    const savedOptimizationMode = localStorage.getItem('optimizationMode');
+
+    if (savedOptimizationMode !== null) {
+      setOptimizationMode(savedOptimizationMode);
+    } else {
+      localStorage.setItem('optimizationMode', optimizationMode);
+    }
+  }, []);
+
   useEffect(() => {
     if (
       chatId &&
@@ -327,7 +337,11 @@ const ChatWindow = ({ id }: { id?: string }) => {
     }
   }, [isMessagesLoaded, isConfigReady]);
 
-  const sendMessage = async (message: string, messageId?: string) => {
+  const sendMessage = async (
+    message: string,
+    messageId?: string,
+    options?: { rewriteIndex?: number },
+  ) => {
     if (loading) return;
     if (!isConfigReady) {
       toast.error('Cannot send message before the configuration is ready');
@@ -340,6 +354,20 @@ const ChatWindow = ({ id }: { id?: string }) => {
     let sources: Document[] | undefined = undefined;
     let recievedMessage = '';
     let added = false;
+    let messageChatHistory = chatHistory;
+
+    if (options?.rewriteIndex !== undefined) {
+      const rewriteIndex = options.rewriteIndex;
+      setMessages((prev) => {
+        return [...prev.slice(0, messages.length > 2 ? rewriteIndex - 1 : 0)];
+      });
+
+      messageChatHistory = chatHistory.slice(
+        0,
+        messages.length > 2 ? rewriteIndex - 1 : 0,
+      );
+      setChatHistory(messageChatHistory);
+    }
 
     messageId = messageId ?? crypto.randomBytes(7).toString('hex');
 
@@ -455,6 +483,9 @@ const ChatWindow = ({ id }: { id?: string }) => {
       }
     };
 
+    const ollamaContextWindow =
+      localStorage.getItem('ollamaContextWindow') || '2048';
+
     const res = await fetch('/api/chat', {
       method: 'POST',
       headers: {
@@ -471,15 +502,19 @@ const ChatWindow = ({ id }: { id?: string }) => {
         files: fileIds,
         focusMode: focusMode,
         optimizationMode: optimizationMode,
-        history: chatHistory,
+        history: messageChatHistory,
         chatModel: {
           name: chatModelProvider.name,
           provider: chatModelProvider.provider,
+          ...(chatModelProvider.provider === 'ollama' && {
+            ollamaContextWindow: parseInt(ollamaContextWindow),
+          }),
         },
         embeddingModel: {
           name: embeddingModelProvider.name,
           provider: embeddingModelProvider.provider,
         },
+        systemInstructions: localStorage.getItem('systemInstructions'),
       }),
     });
 
@@ -511,20 +546,13 @@ const ChatWindow = ({ id }: { id?: string }) => {
   };
 
   const rewrite = (messageId: string) => {
-    const index = messages.findIndex((msg) => msg.messageId === messageId);
-
-    if (index === -1) return;
-
-    const message = messages[index - 1];
-
-    setMessages((prev) => {
-      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
+    const messageIndex = messages.findIndex(
+      (msg) => msg.messageId === messageId,
+    );
+    if (messageIndex == -1) return;
+    sendMessage(messages[messageIndex - 1].content, messageId, {
+      rewriteIndex: messageIndex,
     });
-    setChatHistory((prev) => {
-      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
-    });
-
-    sendMessage(message.content, message.messageId);
   };
 
   useEffect(() => {
@@ -569,6 +597,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
               setFileIds={setFileIds}
               files={files}
               setFiles={setFiles}
+              optimizationMode={optimizationMode}
+              setOptimizationMode={setOptimizationMode}
             />
           </>
         ) : (

src/components/MessageBox.tsx

@@ -48,6 +48,7 @@ const MessageBox = ({
   const [speechMessage, setSpeechMessage] = useState(message.content);
 
   useEffect(() => {
+    const citationRegex = /\[([^\]]+)\]/g;
     const regex = /\[(\d+)\]/g;
     let processedMessage = message.content;
 
@@ -67,13 +68,36 @@ const MessageBox = ({
     ) {
       setParsedMessage(
         processedMessage.replace(
-          regex,
-          (_, number) =>
-            `<a href="${
-              message.sources?.[number - 1]?.metadata?.url
-            }" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
+          citationRegex,
+          (_, capturedContent: string) => {
+            const numbers = capturedContent
+              .split(',')
+              .map((numStr) => numStr.trim());
+
+            const linksHtml = numbers
+              .map((numStr) => {
+                const number = parseInt(numStr);
+
+                if (isNaN(number) || number <= 0) {
+                  return `[${numStr}]`;
+                }
+
+                const source = message.sources?.[number - 1];
+                const url = source?.metadata?.url;
+
+                if (url) {
+                  return `<a href="${url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${numStr}</a>`;
+                } else {
+                  return `[${numStr}]`;
+                }
+              })
+              .join('');
+
+            return linksHtml;
+          },
         ),
       );
+      setSpeechMessage(message.content.replace(regex, ''));
       return;
     }
 

src/components/MessageInput.tsx

@@ -4,6 +4,7 @@ import { useEffect, useRef, useState } from 'react';
 import TextareaAutosize from 'react-textarea-autosize';
 import Attach from './MessageInputActions/Attach';
 import CopilotToggle from './MessageInputActions/Copilot';
+import Optimization from './MessageInputActions/Optimization';
 import { File } from './ChatWindow';
 import AttachSmall from './MessageInputActions/AttachSmall';
 
@@ -14,6 +15,8 @@ const MessageInput = ({
   setFileIds,
   files,
   setFiles,
+  optimizationMode,
+  setOptimizationMode,
 }: {
   sendMessage: (message: string) => void;
   loading: boolean;
@@ -21,6 +24,8 @@ const MessageInput = ({
   setFileIds: (fileIds: string[]) => void;
   files: File[];
   setFiles: (files: File[]) => void;
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
 }) => {
   const [copilotEnabled, setCopilotEnabled] = useState(false);
   const [message, setMessage] = useState('');
@@ -40,20 +45,16 @@ const MessageInput = ({
   useEffect(() => {
     const handleKeyDown = (e: KeyboardEvent) => {
       const activeElement = document.activeElement;
-
       const isInputFocused =
         activeElement?.tagName === 'INPUT' ||
         activeElement?.tagName === 'TEXTAREA' ||
         activeElement?.hasAttribute('contenteditable');
-
       if (e.key === '/' && !isInputFocused) {
         e.preventDefault();
         inputRef.current?.focus();
       }
     };
-
     document.addEventListener('keydown', handleKeyDown);
-
     return () => {
       document.removeEventListener('keydown', handleKeyDown);
     };
@@ -75,58 +76,95 @@ const MessageInput = ({
         }
       }}
       className={cn(
-        'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200',
-        mode === 'multi' ? 'flex-col rounded-lg' : 'flex-row rounded-full',
+        'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center border border-light-200 dark:border-dark-200',
+        mode === 'multi'
+          ? 'flex-col rounded-lg'
+          : 'flex-col md:flex-row rounded-lg md:rounded-full',
       )}
     >
       {mode === 'single' && (
-        <AttachSmall
-          fileIds={fileIds}
-          setFileIds={setFileIds}
-          files={files}
-          setFiles={setFiles}
-        />
-      )}
-      <TextareaAutosize
-        ref={inputRef}
-        value={message}
-        onChange={(e) => setMessage(e.target.value)}
-        onHeightChange={(height, props) => {
-          setTextareaRows(Math.ceil(height / props.rowHeight));
-        }}
-        className="transition bg-transparent dark:placeholder:text-white/50 placeholder:text-sm text-sm dark:text-white resize-none focus:outline-none w-full px-2 max-h-24 lg:max-h-36 xl:max-h-48 flex-grow flex-shrink"
-        placeholder="Ask a follow-up"
-      />
-      {mode === 'single' && (
-        <div className="flex flex-row items-center space-x-4">
-          <CopilotToggle
-            copilotEnabled={copilotEnabled}
-            setCopilotEnabled={setCopilotEnabled}
-          />
-          <button
-            disabled={message.trim().length === 0 || loading}
-            className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
-          >
-            <ArrowUp className="bg-background" size={17} />
-          </button>
-        </div>
-      )}
-      {mode === 'multi' && (
-        <div className="flex flex-row items-center justify-between w-full pt-2">
-          <AttachSmall
-            fileIds={fileIds}
-            setFileIds={setFileIds}
-            files={files}
-            setFiles={setFiles}
-          />
-          <div className="flex flex-row items-center space-x-4">
+        <div className="flex flex-row items-center justify-between w-full mb-2 md:mb-0 md:w-auto">
+          <div className="flex flex-row items-center space-x-2">
+            <AttachSmall
+              fileIds={fileIds}
+              setFileIds={setFileIds}
+              files={files}
+              setFiles={setFiles}
+            />
+            <Optimization
+              optimizationMode={optimizationMode}
+              setOptimizationMode={setOptimizationMode}
+            />
+          </div>
+          <div className="md:hidden">
             <CopilotToggle
               copilotEnabled={copilotEnabled}
               setCopilotEnabled={setCopilotEnabled}
             />
+          </div>
+        </div>
+      )}
+      <div className="flex flex-row items-center w-full">
+        <TextareaAutosize
+          ref={inputRef}
+          value={message}
+          onChange={(e) => setMessage(e.target.value)}
+          onHeightChange={(height, props) => {
+            setTextareaRows(Math.ceil(height / props.rowHeight));
+          }}
+          className="transition bg-transparent dark:placeholder:text-white/50 placeholder:text-sm text-sm dark:text-white resize-none focus:outline-none w-full px-2 max-h-24 lg:max-h-36 xl:max-h-48 flex-grow flex-shrink"
+          placeholder="Ask a follow-up"
+        />
+        {mode === 'single' && (
+          <div className="flex flex-row items-center space-x-4">
+            <div className="hidden md:block">
+              <CopilotToggle
+                copilotEnabled={copilotEnabled}
+                setCopilotEnabled={setCopilotEnabled}
+              />
+            </div>
             <button
               disabled={message.trim().length === 0 || loading}
-              className="bg-[#24A0ED] text-white text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
+              className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
+            >
+              <ArrowUp className="bg-background" size={17} />
+            </button>
+          </div>
+        )}
+      </div>
+
+      {mode === 'multi' && (
+        <div className="flex flex-col md:flex-row items-start md:items-center justify-between w-full pt-2">
+          <div className="flex flex-row items-center justify-between w-full md:w-auto mb-2 md:mb-0">
+            <div className="flex flex-row items-center space-x-2">
+              <AttachSmall
+                fileIds={fileIds}
+                setFileIds={setFileIds}
+                files={files}
+                setFiles={setFiles}
+              />
+              <Optimization
+                optimizationMode={optimizationMode}
+                setOptimizationMode={setOptimizationMode}
+              />
+            </div>
+            <div className="md:hidden">
+              <CopilotToggle
+                copilotEnabled={copilotEnabled}
+                setCopilotEnabled={setCopilotEnabled}
+              />
+            </div>
+          </div>
+          <div className="flex flex-row items-center space-x-4 self-end">
+            <div className="hidden md:block">
+              <CopilotToggle
+                copilotEnabled={copilotEnabled}
+                setCopilotEnabled={setCopilotEnabled}
+              />
+            </div>
+            <button
+              disabled={message.trim().length === 0 || loading}
+              className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
             >
               <ArrowUp className="bg-background" size={17} />
             </button>

src/components/MessageInputActions/Optimization.tsx

@@ -1,4 +1,4 @@
-import { ChevronDown, Sliders, Star, Zap } from 'lucide-react';
+import { ChevronDown, Minimize2, Sliders, Star, Zap } from 'lucide-react';
 import { cn } from '@/lib/utils';
 import {
   Popover,
@@ -7,7 +7,6 @@ import {
   Transition,
 } from '@headlessui/react';
 import { Fragment } from 'react';
-
 const OptimizationModes = [
   {
     key: 'speed',
@@ -41,8 +40,13 @@ const Optimization = ({
   optimizationMode: string;
   setOptimizationMode: (mode: string) => void;
 }) => {
+  const handleOptimizationChange = (mode: string) => {
+    setOptimizationMode(mode);
+    localStorage.setItem('optimizationMode', mode);
+  };
+
   return (
-    <Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
+    <Popover className="relative">
       <PopoverButton
         type="button"
         className="p-2 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
@@ -70,11 +74,11 @@ const Optimization = ({
         leaveFrom="opacity-100 translate-y-0"
         leaveTo="opacity-0 translate-y-1"
       >
-        <PopoverPanel className="absolute z-10 w-64 md:w-[250px] right-0">
-          <div className="flex flex-col gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-full p-4 max-h-[200px] md:max-h-none overflow-y-auto">
+        <PopoverPanel className="absolute z-10 bottom-[100%] mb-2 left-1/2 transform -translate-x-1/2">
+          <div className="flex flex-col gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-max max-w-[300px] p-4 max-h-[200px] md:max-h-none overflow-y-auto">
             {OptimizationModes.map((mode, i) => (
               <PopoverButton
-                onClick={() => setOptimizationMode(mode.key)}
+                onClick={() => handleOptimizationChange(mode.key)}
                 key={i}
                 disabled={mode.key === 'quality'}
                 className={cn(

src/components/SearchImages.tsx

@@ -35,9 +35,10 @@ const SearchImages = ({
 
             const chatModelProvider = localStorage.getItem('chatModelProvider');
             const chatModel = localStorage.getItem('chatModel');
-
             const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
             const customOpenAIKey = localStorage.getItem('openAIApiKey');
+            const ollamaContextWindow =
+              localStorage.getItem('ollamaContextWindow') || '2048';
 
             const res = await fetch(`/api/images`, {
               method: 'POST',
@@ -54,6 +55,9 @@ const SearchImages = ({
                     customOpenAIBaseURL: customOpenAIBaseURL,
                     customOpenAIKey: customOpenAIKey,
                   }),
+                  ...(chatModelProvider === 'ollama' && {
+                    ollamaContextWindow: parseInt(ollamaContextWindow),
+                  }),
                 },
               }),
             });

src/components/SearchVideos.tsx

@@ -50,9 +50,10 @@ const Searchvideos = ({
 
             const chatModelProvider = localStorage.getItem('chatModelProvider');
             const chatModel = localStorage.getItem('chatModel');
-
             const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
             const customOpenAIKey = localStorage.getItem('openAIApiKey');
+            const ollamaContextWindow =
+              localStorage.getItem('ollamaContextWindow') || '2048';
 
             const res = await fetch(`/api/videos`, {
               method: 'POST',
@@ -69,6 +70,9 @@ const Searchvideos = ({
                     customOpenAIBaseURL: customOpenAIBaseURL,
                     customOpenAIKey: customOpenAIKey,
                   }),
+                  ...(chatModelProvider === 'ollama' && {
+                    ollamaContextWindow: parseInt(ollamaContextWindow),
+                  }),
                 },
               }),
             });

src/lib/actions.ts

@@ -6,6 +6,8 @@ export const getSuggestions = async (chatHisory: Message[]) => {
 
   const customOpenAIKey = localStorage.getItem('openAIApiKey');
   const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
+  const ollamaContextWindow =
+    localStorage.getItem('ollamaContextWindow') || '2048';
 
   const res = await fetch(`/api/suggestions`, {
     method: 'POST',
@@ -21,6 +23,9 @@ export const getSuggestions = async (chatHisory: Message[]) => {
           customOpenAIKey,
           customOpenAIBaseURL,
         }),
+        ...(chatModelProvider === 'ollama' && {
+          ollamaContextWindow: parseInt(ollamaContextWindow),
+        }),
       },
     }),
   });

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 {
@@ -25,6 +32,12 @@ interface Config {
     OLLAMA: {
       API_URL: string;
     };
+    DEEPSEEK: {
+      API_KEY: string;
+    };
+    LM_STUDIO: {
+      API_URL: string;
+    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -40,10 +53,17 @@ type RecursivePartial<T> = {
   [P in keyof T]?: RecursivePartial<T[P]>;
 };
 
-const loadConfig = () =>
-  toml.parse(
-    fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
-  ) as any as Config;
+const loadConfig = () => {
+  // Server-side only
+  if (typeof window === 'undefined') {
+    return toml.parse(
+      fs.readFileSync(path.join(process.cwd(), `${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;
@@ -63,6 +83,8 @@ export const getSearxngApiEndpoint = () =>
 
 export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
 
+export const getDeepseekApiKey = () => loadConfig().MODELS.DEEPSEEK.API_KEY;
+
 export const getCustomOpenaiApiKey = () =>
   loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
 
@@ -72,6 +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;
@@ -104,10 +129,13 @@ const mergeConfigs = (current: any, update: any): any => {
 };
 
 export const updateConfig = (config: RecursivePartial<Config>) => {
-  const currentConfig = loadConfig();
-  const mergedConfig = mergeConfigs(currentConfig, config);
-  fs.writeFileSync(
-    path.join(path.join(process.cwd(), `${configFileName}`)),
-    toml.stringify(mergedConfig),
-  );
+  // Server-side only
+  if (typeof window === 'undefined') {
+    const currentConfig = loadConfig();
+    const mergedConfig = mergeConfigs(currentConfig, config);
+    fs.writeFileSync(
+      path.join(path.join(process.cwd(), `${configFileName}`)),
+      toml.stringify(mergedConfig),
+    );
+  }
 };

src/lib/prompts/academicSearch.ts

@@ -51,6 +51,10 @@ export const academicSearchResponsePrompt = `
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
     - You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
     
+    ### User instructions
+    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+    {systemInstructions}
+
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.

src/lib/prompts/redditSearch.ts

@@ -51,6 +51,10 @@ export const redditSearchResponsePrompt = `
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
     - You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
     
+    ### User instructions
+    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+    {systemInstructions}
+
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.

src/lib/prompts/webSearch.ts

@@ -1,6 +1,6 @@
 export const webSearchRetrieverPrompt = `
 You are an AI question rephraser. You will be given a conversation and a follow-up question,  you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
-If it is a smple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
+If it is a simple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
 If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
 You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.
 
@@ -92,6 +92,10 @@ export const webSearchResponsePrompt = `
     - If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
 
+    ### User instructions
+    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+    {systemInstructions}
+
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.

src/lib/prompts/wolframAlpha.ts

@@ -51,6 +51,10 @@ export const wolframAlphaSearchResponsePrompt = `
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
     - You are set on focus mode 'Wolfram Alpha', this means you will be searching for information on the web using Wolfram Alpha. It is a computational knowledge engine that can answer factual queries and perform computations.
     
+    ### User instructions
+    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+    {systemInstructions}
+
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.

src/lib/prompts/writingAssistant.ts

@@ -7,6 +7,10 @@ You have to cite the answer using [number] notation. You must cite the sentences
 Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
 However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
+### User instructions
+These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+{systemInstructions}
+
 <context>
 {context}
 </context>

src/lib/prompts/youtubeSearch.ts

@@ -51,6 +51,10 @@ export const youtubeSearchResponsePrompt = `
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
     - You are set on focus mode 'Youtube', this means you will be searching for videos on the web using Youtube and providing information based on the video's transcrip
     
+    ### User instructions
+    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+    {systemInstructions}
+
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.

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

@@ -0,0 +1,49 @@
+import { ChatOpenAI } from '@langchain/openai';
+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)',
+    key: 'deepseek-chat',
+  },
+  {
+    displayName: 'Deepseek Reasoner (Deepseek R1)',
+    key: 'deepseek-reasoner',
+  },
+];
+
+export const loadDeepseekChatModels = async () => {
+  const deepseekApiKey = getDeepseekApiKey();
+
+  if (!deepseekApiKey) return {};
+
+  try {
+    const chatModels: Record<string, ChatModel> = {};
+
+    deepseekChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatOpenAI({
+          openAIApiKey: deepseekApiKey,
+          modelName: model.key,
+          temperature: 0.7,
+          configuration: {
+            baseURL: 'https://api.deepseek.com',
+          },
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading Deepseek models: ${err}`);
+    return {};
+  }
+};

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';
 
@@ -40,8 +45,12 @@ const geminiChatModels: Record<string, string>[] = [
 
 const geminiEmbeddingModels: Record<string, string>[] = [
   {
-    displayName: 'Gemini Embedding',
-    key: 'gemini-embedding-exp',
+    displayName: 'Text Embedding 004',
+    key: 'models/text-embedding-004',
+  },
+  {
+    displayName: 'Embedding 001',
+    key: 'models/embedding-001',
   },
 ];
 

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>[] = [
@@ -72,6 +77,14 @@ const groqChatModels: Record<string, string>[] = [
     displayName: 'Llama 3.2 90B Vision Preview (Preview)',
     key: 'llama-3.2-90b-vision-preview',
   },
+  /* {
+    displayName: 'Llama 4 Maverick 17B 128E Instruct (Preview)',
+    key: 'meta-llama/llama-4-maverick-17b-128e-instruct',
+  }, */
+  {
+    displayName: 'Llama 4 Scout 17B 16E Instruct (Preview)',
+    key: 'meta-llama/llama-4-scout-17b-16e-instruct',
+  },
 ];
 
 export const loadGroqChatModels = async () => {

src/lib/providers/index.ts

@@ -1,17 +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 { loadGroqChatModels } from './groq';
-import { loadAnthropicChatModels } from './anthropic';
-import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
-import { loadTransformersEmbeddingsModels } from './transformers';
+import {
+  loadOllamaChatModels,
+  loadOllamaEmbeddingModels,
+  PROVIDER_INFO as OllamaInfo,
+} from './ollama';
+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;
@@ -32,6 +75,8 @@ export const chatModelProviders: Record<
   groq: loadGroqChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
+  deepseek: loadDeepseekChatModels,
+  lmstudio: loadLMStudioChatModels,
 };
 
 export const embeddingModelProviders: Record<
@@ -42,6 +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

@@ -1,8 +1,13 @@
 import axios from 'axios';
 import { getKeepAlive, getOllamaApiEndpoint } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
-import { ChatOllama } from '@langchain/community/chat_models/ollama';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+
+export const PROVIDER_INFO = {
+  key: 'ollama',
+  displayName: 'Ollama',
+};
+import { ChatOllama } from '@langchain/ollama';
+import { OllamaEmbeddings } from '@langchain/ollama';
 
 export const loadOllamaChatModels = async () => {
   const ollamaApiEndpoint = getOllamaApiEndpoint();

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';
 

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

@@ -33,6 +33,7 @@ export interface MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) => Promise<eventEmitter>;
 }
 
@@ -236,9 +237,11 @@ class MetaSearchAgent implements MetaSearchAgentType {
     fileIds: string[],
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
+    systemInstructions: string,
   ) {
     return RunnableSequence.from([
       RunnableMap.from({
+        systemInstructions: () => systemInstructions,
         query: (input: BasicChainInput) => input.query,
         chat_history: (input: BasicChainInput) => input.chat_history,
         date: () => new Date().toISOString(),
@@ -468,6 +471,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) {
     const emitter = new eventEmitter();
 
@@ -476,6 +480,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
       fileIds,
       embeddings,
       optimizationMode,
+      systemInstructions,
     );
 
     const stream = answeringChain.streamEvents(

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({