Merge 7288c97326 into 09661ae11d

Feat/system instructions

README.md

@@ -89,6 +89,7 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
    - `OPENAI`: Your OpenAI API key. **You only need to fill this if you wish to use OpenAI's models**.
    - `OLLAMA`: Your Ollama API URL. You should enter it as `http://host.docker.internal:PORT_NUMBER`. If you installed Ollama on port 11434, use `http://host.docker.internal:11434`. For other ports, adjust accordingly. **You need to fill this if you wish to use Ollama's models instead of OpenAI's**.
    - `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.
+   - `OPENROUTER`: Your OpenRouter API key. **You only need to fill this if you wish to use models via OpenRouter**.
    - `ANTHROPIC`: Your Anthropic API key. **You only need to fill this if you wish to use Anthropic models**.
 
      **Note**: You can change these after starting Perplexica from the settings dialog.

sample.config.toml

@@ -11,6 +11,9 @@ API_KEY = ""
 [MODELS.ANTHROPIC]
 API_KEY = ""
 
+[MODELS.OPENROUTER]
+API_KEY = ""
+
 [MODELS.GEMINI]
 API_KEY = ""
 

src/app/api/config/route.ts

@@ -5,6 +5,7 @@ import {
   getCustomOpenaiModelName,
   getGeminiApiKey,
   getGroqApiKey,
+  getOpenrouterApiKey,
   getOllamaApiEndpoint,
   getOpenaiApiKey,
   updateConfig,
@@ -52,6 +53,7 @@ export const GET = async (req: Request) => {
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
+    config['openrouterApiKey'] = getOpenrouterApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
@@ -79,6 +81,9 @@ export const POST = async (req: Request) => {
         GROQ: {
           API_KEY: config.groqApiKey,
         },
+        OPENROUTER: {
+          API_KEY: config.openrouterApiKey,
+        },
         ANTHROPIC: {
           API_KEY: config.anthropicApiKey,
         },

src/app/api/search/route.ts

@@ -125,7 +125,7 @@ export const POST = async (req: Request) => {
       embeddings,
       body.optimizationMode,
       [],
-      "",
+      '',
     );
 
     if (!body.stream) {

src/app/settings/page.tsx

@@ -17,6 +17,7 @@ interface SettingsType {
   };
   openaiApiKey: string;
   groqApiKey: string;
+  openrouterApiKey: string;
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
@@ -801,6 +802,25 @@ const Page = () => {
                   />
                 </div>
 
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    OpenRouter API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="OpenRouter API Key"
+                    value={config.openrouterApiKey}
+                    isSaving={savingStates['openrouterApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        openrouterApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('openrouterApiKey', value)}
+                  />
+                </div>
+
                 <div className="flex flex-col space-y-1">
                   <p className="text-black/70 dark:text-white/70 text-sm">
                     Anthropic API Key

src/lib/config.ts

@@ -25,6 +25,9 @@ interface Config {
     OLLAMA: {
       API_URL: string;
     };
+    OPENROUTER: {
+      API_KEY: string;
+    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -54,6 +57,8 @@ export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
 
 export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
 
+export const getOpenrouterApiKey = () => loadConfig().MODELS.OPENROUTER.API_KEY;
+
 export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
 
 export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;

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.
 

src/lib/providers/index.ts

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

src/lib/providers/openrouter.ts

@@ -0,0 +1,61 @@
+import { ChatOpenAI } from '@langchain/openai';
+import { getOpenrouterApiKey } from '../config';
+import { ChatModel } from '.';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+
+let openrouterChatModels: Record<string, string>[] = [];
+
+async function fetchModelList(): Promise<void> {
+  try {
+    const response = await fetch('https://openrouter.ai/api/v1/models', {
+      method: 'GET',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    if (!response.ok) {
+      throw new Error(`API request failed with status: ${response.status}`);
+    }
+
+    const data = await response.json();
+
+    openrouterChatModels = data.data.map((model: any) => ({
+      displayName: model.name,
+      key: model.id,
+    }));
+  } catch (error) {
+    console.error('Error fetching models:', error);
+  }
+}
+
+export const loadOpenrouterChatModels = async () => {
+  await fetchModelList();
+
+  const openrouterApikey = getOpenrouterApiKey();
+
+  if (!openrouterApikey) return {};
+
+  try {
+    const chatModels: Record<string, ChatModel> = {};
+
+    openrouterChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatOpenAI({
+          openAIApiKey: openrouterApikey,
+          modelName: model.key,
+          temperature: 0.7,
+          configuration: {
+            baseURL: 'https://openrouter.ai/api/v1',
+          },
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading Openrouter models: ${err}`);
+    return {};
+  }
+};