Merge 2427caf352 into 4b2a7916fd

docs/API/SEARCH.md

@@ -33,7 +33,6 @@ 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
 }
 ```
@@ -64,8 +63,6 @@ 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": "1.10.2",
+  "version": "1.10.1",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {

sample.config.toml

@@ -22,8 +22,5 @@ MODEL_NAME = ""
 [MODELS.OLLAMA]
 API_URL = "" # Ollama API URL - http://host.docker.internal:11434
 
-[MODELS.DEEPSEEK]
-API_KEY = ""
-
 [API_ENDPOINTS]
 SEARXNG = "" # SearxNG API URL - http://localhost:32768

src/app/api/chat/route.ts

@@ -49,7 +49,6 @@ type Body = {
   files: Array<string>;
   chatModel: ChatModel;
   embeddingModel: EmbeddingModel;
-  systemInstructions: string;
 };
 
 const handleEmitterEvents = async (
@@ -279,7 +278,6 @@ export const POST = async (req: Request) => {
       embedding,
       body.optimizationMode,
       body.files,
-      body.systemInstructions,
     );
 
     const responseStream = new TransformStream();

src/app/api/config/route.ts

@@ -7,7 +7,6 @@ import {
   getGroqApiKey,
   getOllamaApiEndpoint,
   getOpenaiApiKey,
-  getDeepseekApiKey,
   updateConfig,
 } from '@/lib/config';
 import {
@@ -54,7 +53,6 @@ export const GET = async (req: Request) => {
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
-    config['deepseekApiKey'] = getDeepseekApiKey();
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
     config['customOpenaiModelName'] = getCustomOpenaiModelName();
@@ -90,9 +88,6 @@ export const POST = async (req: Request) => {
         OLLAMA: {
           API_URL: config.ollamaApiUrl,
         },
-        DEEPSEEK: {
-          API_KEY: config.deepseekApiKey,
-        },
         CUSTOM_OPENAI: {
           API_URL: config.customOpenaiApiUrl,
           API_KEY: config.customOpenaiApiKey,

src/app/api/search/route.ts

@@ -34,7 +34,6 @@ interface ChatRequestBody {
   query: string;
   history: Array<[string, string]>;
   stream?: boolean;
-  systemInstructions?: string;
 }
 
 export const POST = async (req: Request) => {
@@ -126,7 +125,6 @@ export const POST = async (req: Request) => {
       embeddings,
       body.optimizationMode,
       [],
-      body.systemInstructions || '',
     );
 
     if (!body.stream) {

src/app/settings/page.tsx

@@ -20,7 +20,6 @@ interface SettingsType {
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
-  deepseekApiKey: string;
   customOpenaiApiKey: string;
   customOpenaiApiUrl: string;
   customOpenaiModelName: string;
@@ -55,38 +54,6 @@ 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,
@@ -144,7 +111,6 @@ 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>>({});
 
   useEffect(() => {
@@ -206,8 +172,6 @@ const Page = () => {
         localStorage.getItem('autoVideoSearch') === 'true',
       );
 
-      setSystemInstructions(localStorage.getItem('systemInstructions')!);
-
       setIsLoading(false);
     };
 
@@ -364,8 +328,6 @@ const Page = () => {
         localStorage.setItem('embeddingModelProvider', value);
       } else if (key === 'embeddingModel') {
         localStorage.setItem('embeddingModel', value);
-      } else if (key === 'systemInstructions') {
-        localStorage.setItem('systemInstructions', value);
       }
     } catch (err) {
       console.error('Failed to save:', err);
@@ -511,19 +473,6 @@ 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">
@@ -839,25 +788,6 @@ 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>
             </SettingsSection>
           </div>

src/components/ChatWindow.tsx

@@ -480,7 +480,6 @@ const ChatWindow = ({ id }: { id?: string }) => {
           name: embeddingModelProvider.name,
           provider: embeddingModelProvider.provider,
         },
-        systemInstructions: localStorage.getItem('systemInstructions'),
       }),
     });
 

src/components/MessageBox.tsx

@@ -48,7 +48,6 @@ const MessageBox = ({
   const [speechMessage, setSpeechMessage] = useState(message.content);
 
   useEffect(() => {
-    const citationRegex = /\[([^\]]+)\]/g;
     const regex = /\[(\d+)\]/g;
     let processedMessage = message.content;
 
@@ -68,33 +67,11 @@ const MessageBox = ({
     ) {
       setParsedMessage(
         processedMessage.replace(
-          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;
-          },
+          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>`,
         ),
       );
       return;

src/lib/config.ts

@@ -25,9 +25,6 @@ interface Config {
     OLLAMA: {
       API_URL: string;
     };
-    DEEPSEEK: {
-      API_KEY: string;
-    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -66,8 +63,6 @@ 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;
 

src/lib/prompts/academicSearch.ts

@@ -51,10 +51,6 @@ 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

@@ -51,10 +51,6 @@ 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

@@ -92,10 +92,6 @@ 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

@@ -51,10 +51,6 @@ 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

@@ -7,10 +7,6 @@ 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

@@ -51,10 +51,6 @@ 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/deepseek.ts

@@ -1,44 +0,0 @@
-import { ChatOpenAI } from '@langchain/openai';
-import { getDeepseekApiKey } from '../config';
-import { ChatModel } from '.';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-
-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

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

src/lib/providers/groq.ts

@@ -72,14 +72,6 @@ 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

@@ -12,7 +12,6 @@ import { loadGroqChatModels } from './groq';
 import { loadAnthropicChatModels } from './anthropic';
 import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
 import { loadTransformersEmbeddingsModels } from './transformers';
-import { loadDeepseekChatModels } from './deepseek';
 
 export interface ChatModel {
   displayName: string;
@@ -33,7 +32,6 @@ export const chatModelProviders: Record<
   groq: loadGroqChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
-  deepseek: loadDeepseekChatModels,
 };
 
 export const embeddingModelProviders: Record<

src/lib/search/metaSearchAgent.ts

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