Merge branch 'pr/843'

Fix name of provider in embeddings models error message

package.json

@@ -15,11 +15,13 @@
     "@headlessui/react": "^2.2.0",
     "@iarna/toml": "^2.2.5",
     "@icons-pack/react-simple-icons": "^12.3.0",
-    "@langchain/anthropic": "^0.3.15",
+    "@langchain/anthropic": "^0.3.24",
-    "@langchain/community": "^0.3.36",
+    "@langchain/community": "^0.3.49",
-    "@langchain/core": "^0.3.42",
+    "@langchain/core": "^0.3.66",
-    "@langchain/google-genai": "^0.1.12",
+    "@langchain/google-genai": "^0.2.15",
-    "@langchain/openai": "^0.0.25",
+    "@langchain/groq": "^0.2.3",
+    "@langchain/ollama": "^0.2.3",
+    "@langchain/openai": "^0.6.2",
     "@langchain/textsplitters": "^0.1.0",
     "@tailwindcss/typography": "^0.5.12",
     "@xenova/transformers": "^2.17.2",
@@ -31,7 +33,7 @@
     "drizzle-orm": "^0.40.1",
     "html-to-text": "^9.0.5",
     "jspdf": "^3.0.1",
-    "langchain": "^0.1.30",
+    "langchain": "^0.3.30",
     "lucide-react": "^0.363.0",
     "mammoth": "^1.9.1",
     "markdown-to-jsx": "^7.7.2",

src/app/api/chat/route.ts

@@ -223,7 +223,7 @@ export const POST = async (req: Request) => {
 
     if (body.chatModel?.provider === 'custom_openai') {
       llm = new ChatOpenAI({
-        openAIApiKey: getCustomOpenaiApiKey(),
+        apiKey: getCustomOpenaiApiKey(),
         modelName: getCustomOpenaiModelName(),
         temperature: 0.7,
         configuration: {

src/app/api/discover/route.ts

@@ -1,55 +1,77 @@
 import { searchSearxng } from '@/lib/searxng';
 
-const articleWebsites = [
+const websitesForTopic = {
-  'yahoo.com',
+  tech: {
-  'www.exchangewire.com',
+    query: ['technology news', 'latest tech', 'AI', 'science and innovation'],
-  'businessinsider.com',
+    links: ['techcrunch.com', 'wired.com', 'theverge.com'],
-  /* 'wired.com',
+  },
-  'mashable.com',
+  finance: {
-  'theverge.com',
+    query: ['finance news', 'economy', 'stock market', 'investing'],
-  'gizmodo.com',
+    links: ['bloomberg.com', 'cnbc.com', 'marketwatch.com'],
-  'cnet.com',
+  },
-  'venturebeat.com', */
+  art: {
-];
+    query: ['art news', 'culture', 'modern art', 'cultural events'],
+    links: ['artnews.com', 'hyperallergic.com', 'theartnewspaper.com'],
+  },
+  sports: {
+    query: ['sports news', 'latest sports', 'cricket football tennis'],
+    links: ['espn.com', 'bbc.com/sport', 'skysports.com'],
+  },
+  entertainment: {
+    query: ['entertainment news', 'movies', 'TV shows', 'celebrities'],
+    links: ['hollywoodreporter.com', 'variety.com', 'deadline.com'],
+  },
+};
 
-const topics = ['AI', 'tech']; /* TODO: Add UI to customize this */
+type Topic = keyof typeof websitesForTopic;
 
 export const GET = async (req: Request) => {
   try {
     const params = new URL(req.url).searchParams;
+
     const mode: 'normal' | 'preview' =
       (params.get('mode') as 'normal' | 'preview') || 'normal';
+    const topic: Topic = (params.get('topic') as Topic) || 'tech';
+
+    const selectedTopic = websitesForTopic[topic];
 
     let data = [];
 
     if (mode === 'normal') {
+      const seenUrls = new Set();
+
       data = (
-        await Promise.all([
+        await Promise.all(
-          ...new Array(articleWebsites.length * topics.length)
+          selectedTopic.links.flatMap((link) =>
-            .fill(0)
+            selectedTopic.query.map(async (query) => {
-            .map(async (_, i) => {
               return (
-                await searchSearxng(
+                await searchSearxng(`site:${link} ${query}`, {
-                  `site:${articleWebsites[i % articleWebsites.length]} ${
-                    topics[i % topics.length]
-                  }`,
-                  {
                   engines: ['bing news'],
                   pageno: 1,
-                  },
+                  language: 'en',
-                )
+                })
               ).results;
             }),
-        ])
+          ),
+        )
       )
-        .map((result) => result)
         .flat()
+        .filter((item) => {
+          const url = item.url?.toLowerCase().trim();
+          if (seenUrls.has(url)) return false;
+          seenUrls.add(url);
+          return true;
+        })
         .sort(() => Math.random() - 0.5);
     } else {
       data = (
         await searchSearxng(
-          `site:${articleWebsites[Math.floor(Math.random() * articleWebsites.length)]} ${topics[Math.floor(Math.random() * topics.length)]}`,
+          `site:${selectedTopic.links[Math.floor(Math.random() * selectedTopic.links.length)]} ${selectedTopic.query[Math.floor(Math.random() * selectedTopic.query.length)]}`,
-          { engines: ['bing news'], pageno: 1 },
+          {
+            engines: ['bing news'],
+            pageno: 1,
+            language: 'en',
+          },
         )
       ).results;
     }

src/app/api/images/route.ts

@@ -49,7 +49,7 @@ export const POST = async (req: Request) => {
 
     if (body.chatModel?.provider === 'custom_openai') {
       llm = new ChatOpenAI({
-        openAIApiKey: getCustomOpenaiApiKey(),
+        apiKey: getCustomOpenaiApiKey(),
         modelName: getCustomOpenaiModelName(),
         temperature: 0.7,
         configuration: {

src/app/api/search/route.ts

@@ -81,8 +81,7 @@ export const POST = async (req: Request) => {
     if (body.chatModel?.provider === 'custom_openai') {
       llm = new ChatOpenAI({
         modelName: body.chatModel?.name || getCustomOpenaiModelName(),
-        openAIApiKey:
+        apiKey: body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
-          body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
         temperature: 0.7,
         configuration: {
           baseURL:

src/app/api/suggestions/route.ts

@@ -48,7 +48,7 @@ export const POST = async (req: Request) => {
 
     if (body.chatModel?.provider === 'custom_openai') {
       llm = new ChatOpenAI({
-        openAIApiKey: getCustomOpenaiApiKey(),
+        apiKey: getCustomOpenaiApiKey(),
         modelName: getCustomOpenaiModelName(),
         temperature: 0.7,
         configuration: {

src/app/api/videos/route.ts

@@ -49,7 +49,7 @@ export const POST = async (req: Request) => {
 
     if (body.chatModel?.provider === 'custom_openai') {
       llm = new ChatOpenAI({
-        openAIApiKey: getCustomOpenaiApiKey(),
+        apiKey: getCustomOpenaiApiKey(),
         modelName: getCustomOpenaiModelName(),
         temperature: 0.7,
         configuration: {

src/app/api/weather/route.ts

@@ -1,6 +1,10 @@
 export const POST = async (req: Request) => {
   try {
-    const body: { lat: number; lng: number } = await req.json();
+    const body: {
+      lat: number;
+      lng: number;
+      measureUnit: 'Imperial' | 'Metric';
+    } = await req.json();
 
     if (!body.lat || !body.lng) {
       return Response.json(
@@ -12,7 +16,9 @@ export const POST = async (req: Request) => {
     }
 
     const res = await fetch(
-      `https://api.open-meteo.com/v1/forecast?latitude=${body.lat}&longitude=${body.lng}&current=weather_code,temperature_2m,is_day,relative_humidity_2m,wind_speed_10m&timezone=auto`,
+      `https://api.open-meteo.com/v1/forecast?latitude=${body.lat}&longitude=${body.lng}&current=weather_code,temperature_2m,is_day,relative_humidity_2m,wind_speed_10m&timezone=auto${
+        body.measureUnit === 'Metric' ? '' : '&temperature_unit=fahrenheit'
+      }${body.measureUnit === 'Metric' ? '' : '&wind_speed_unit=mph'}`,
     );
 
     const data = await res.json();
@@ -33,12 +39,16 @@ export const POST = async (req: Request) => {
       humidity: number;
       windSpeed: number;
       icon: string;
+      temperatureUnit: 'C' | 'F';
+      windSpeedUnit: 'm/s' | 'mph';
     } = {
       temperature: data.current.temperature_2m,
       condition: '',
       humidity: data.current.relative_humidity_2m,
       windSpeed: data.current.wind_speed_10m,
       icon: '',
+      temperatureUnit: body.measureUnit === 'Metric' ? 'C' : 'F',
+      windSpeedUnit: body.measureUnit === 'Metric' ? 'm/s' : 'mph',
     };
 
     const code = data.current.weather_code;

src/app/discover/page.tsx

@@ -4,6 +4,7 @@ import { Search } from 'lucide-react';
 import { useEffect, useState } from 'react';
 import Link from 'next/link';
 import { toast } from 'sonner';
+import { cn } from '@/lib/utils';
 
 interface Discover {
   title: string;
@@ -12,14 +13,38 @@ interface Discover {
   thumbnail: string;
 }
 
+const topics: { key: string; display: string }[] = [
+  {
+    display: 'Tech & Science',
+    key: 'tech',
+  },
+  {
+    display: 'Finance',
+    key: 'finance',
+  },
+  {
+    display: 'Art & Culture',
+    key: 'art',
+  },
+  {
+    display: 'Sports',
+    key: 'sports',
+  },
+  {
+    display: 'Entertainment',
+    key: 'entertainment',
+  },
+];
+
 const Page = () => {
   const [discover, setDiscover] = useState<Discover[] | null>(null);
   const [loading, setLoading] = useState(true);
+  const [activeTopic, setActiveTopic] = useState<string>(topics[0].key);
 
-  useEffect(() => {
+  const fetchArticles = async (topic: string) => {
-    const fetchData = async () => {
+    setLoading(true);
     try {
-        const res = await fetch(`/api/discover`, {
+      const res = await fetch(`/api/discover?topic=${topic}`, {
         method: 'GET',
         headers: {
           'Content-Type': 'application/json',
@@ -43,10 +68,39 @@ const Page = () => {
     }
   };
 
-    fetchData();
+  useEffect(() => {
-  }, []);
+    fetchArticles(activeTopic);
+  }, [activeTopic]);
 
-  return loading ? (
+  return (
+    <>
+      <div>
+        <div className="flex flex-col pt-4">
+          <div className="flex items-center">
+            <Search />
+            <h1 className="text-3xl font-medium p-2">Discover</h1>
+          </div>
+          <hr className="border-t border-[#2B2C2C] my-4 w-full" />
+        </div>
+
+        <div className="flex flex-row items-center space-x-2 overflow-x-auto">
+          {topics.map((t, i) => (
+            <div
+              key={i}
+              className={cn(
+                'border-[0.1px] rounded-full text-sm px-3 py-1 text-nowrap transition duration-200 cursor-pointer',
+                activeTopic === t.key
+                  ? 'text-cyan-300 bg-cyan-300/30 border-cyan-300/60'
+                  : 'border-white/30 text-white/70 hover:text-white hover:border-white/40 hover:bg-white/5',
+              )}
+              onClick={() => setActiveTopic(t.key)}
+            >
+              <span>{t.display}</span>
+            </div>
+          ))}
+        </div>
+
+        {loading ? (
           <div className="flex flex-row items-center justify-center min-h-screen">
             <svg
               aria-hidden="true"
@@ -66,17 +120,7 @@ const Page = () => {
             </svg>
           </div>
         ) : (
-    <>
+          <div className="grid lg:grid-cols-3 sm:grid-cols-2 grid-cols-1 gap-4 pb-28 pt-5 lg:pb-8 w-full justify-items-center lg:justify-items-start">
-      <div>
-        <div className="flex flex-col pt-4">
-          <div className="flex items-center">
-            <Search />
-            <h1 className="text-3xl font-medium p-2">Discover</h1>
-          </div>
-          <hr className="border-t border-[#2B2C2C] my-4 w-full" />
-        </div>
-
-        <div className="grid lg:grid-cols-3 sm:grid-cols-2 grid-cols-1 gap-4 pb-28 lg:pb-8 w-full justify-items-center lg:justify-items-start">
             {discover &&
               discover?.map((item, i) => (
                 <Link
@@ -105,6 +149,7 @@ const Page = () => {
                 </Link>
               ))}
           </div>
+        )}
       </div>
     </>
   );

src/app/settings/page.tsx

@@ -148,6 +148,9 @@ const Page = () => {
   const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
   const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
   const [systemInstructions, setSystemInstructions] = useState<string>('');
+  const [measureUnit, setMeasureUnit] = useState<'Imperial' | 'Metric'>(
+    'Metric',
+  );
   const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
 
   useEffect(() => {
@@ -210,6 +213,10 @@ const Page = () => {
 
       setSystemInstructions(localStorage.getItem('systemInstructions')!);
 
+      setMeasureUnit(
+        localStorage.getItem('measureUnit')! as 'Imperial' | 'Metric',
+      );
+
       setIsLoading(false);
     };
 
@@ -368,6 +375,8 @@ const Page = () => {
         localStorage.setItem('embeddingModel', value);
       } else if (key === 'systemInstructions') {
         localStorage.setItem('systemInstructions', value);
+      } else if (key === 'measureUnit') {
+        localStorage.setItem('measureUnit', value.toString());
       }
     } catch (err) {
       console.error('Failed to save:', err);
@@ -416,13 +425,35 @@ const Page = () => {
       ) : (
         config && (
           <div className="flex flex-col space-y-6 pb-28 lg:pb-8">
-            <SettingsSection title="Appearance">
+            <SettingsSection title="Preferences">
               <div className="flex flex-col space-y-1">
                 <p className="text-black/70 dark:text-white/70 text-sm">
                   Theme
                 </p>
                 <ThemeSwitcher />
               </div>
+              <div className="flex flex-col space-y-1">
+                <p className="text-black/70 dark:text-white/70 text-sm">
+                  Measurement Units
+                </p>
+                <Select
+                  value={measureUnit ?? undefined}
+                  onChange={(e) => {
+                    setMeasureUnit(e.target.value as 'Imperial' | 'Metric');
+                    saveConfig('measureUnit', e.target.value);
+                  }}
+                  options={[
+                    {
+                      label: 'Metric',
+                      value: 'Metric',
+                    },
+                    {
+                      label: 'Imperial',
+                      value: 'Imperial',
+                    },
+                  ]}
+                />
+              </div>
             </SettingsSection>
 
             <SettingsSection title="Automatic Search">
@@ -516,7 +547,7 @@ const Page = () => {
             <SettingsSection title="System Instructions">
               <div className="flex flex-col space-y-4">
                 <Textarea
-                  value={systemInstructions}
+                  value={systemInstructions ?? undefined}
                   isSaving={savingStates['systemInstructions']}
                   onChange={(e) => {
                     setSystemInstructions(e.target.value);

src/components/ChatWindow.tsx

@@ -354,7 +354,11 @@ const ChatWindow = ({ id }: { id?: string }) => {
     }
   }, [isMessagesLoaded, isConfigReady]);
 
-  const sendMessage = async (message: string, messageId?: string) => {
+  const sendMessage = async (
+    message: string,
+    messageId?: string,
+    rewrite = false,
+  ) => {
     if (loading) return;
     if (!isConfigReady) {
       toast.error('Cannot send message before the configuration is ready');
@@ -482,6 +486,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
       }
     };
 
+    const messageIndex = messages.findIndex((m) => m.messageId === messageId);
+
     const res = await fetch('/api/chat', {
       method: 'POST',
       headers: {
@@ -498,7 +504,9 @@ const ChatWindow = ({ id }: { id?: string }) => {
         files: fileIds,
         focusMode: focusMode,
         optimizationMode: optimizationMode,
-        history: chatHistory,
+        history: rewrite
+          ? chatHistory.slice(0, messageIndex === -1 ? undefined : messageIndex)
+          : chatHistory,
         chatModel: {
           name: chatModelProvider.name,
           provider: chatModelProvider.provider,
@@ -552,7 +560,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
       return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
     });
 
-    sendMessage(message.content, message.messageId);
+    sendMessage(message.content, message.messageId, true);
   };
 
   useEffect(() => {

src/components/MessageBox.tsx

@@ -21,8 +21,16 @@ import SearchVideos from './SearchVideos';
 import { useSpeech } from 'react-text-to-speech';
 import ThinkBox from './ThinkBox';
 
-const ThinkTagProcessor = ({ children }: { children: React.ReactNode }) => {
+const ThinkTagProcessor = ({
-  return <ThinkBox content={children as string} />;
+  children,
+  thinkingEnded,
+}: {
+  children: React.ReactNode;
+  thinkingEnded: boolean;
+}) => {
+  return (
+    <ThinkBox content={children as string} thinkingEnded={thinkingEnded} />
+  );
 };
 
 const MessageBox = ({
@@ -46,6 +54,7 @@ const MessageBox = ({
 }) => {
   const [parsedMessage, setParsedMessage] = useState(message.content);
   const [speechMessage, setSpeechMessage] = useState(message.content);
+  const [thinkingEnded, setThinkingEnded] = useState(false);
 
   useEffect(() => {
     const citationRegex = /\[([^\]]+)\]/g;
@@ -61,6 +70,10 @@ const MessageBox = ({
       }
     }
 
+    if (message.role === 'assistant' && message.content.includes('</think>')) {
+      setThinkingEnded(true);
+    }
+
     if (
       message.role === 'assistant' &&
       message?.sources &&
@@ -88,7 +101,7 @@ const MessageBox = ({
                 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}]`;
+                  return ``;
                 }
               })
               .join('');
@@ -99,6 +112,14 @@ const MessageBox = ({
       );
       setSpeechMessage(message.content.replace(regex, ''));
       return;
+    } else if (
+      message.role === 'assistant' &&
+      message?.sources &&
+      message.sources.length === 0
+    ) {
+      setParsedMessage(processedMessage.replace(regex, ''));
+      setSpeechMessage(message.content.replace(regex, ''));
+      return;
     }
 
     setSpeechMessage(message.content.replace(regex, ''));
@@ -111,6 +132,9 @@ const MessageBox = ({
     overrides: {
       think: {
         component: ThinkTagProcessor,
+        props: {
+          thinkingEnded: thinkingEnded,
+        },
       },
     },
   };

src/components/ThinkBox.tsx

@@ -1,15 +1,23 @@
 'use client';
 
-import { useState } from 'react';
+import { useEffect, useState } from 'react';
-import { cn } from '@/lib/utils';
 import { ChevronDown, ChevronUp, BrainCircuit } from 'lucide-react';
 
 interface ThinkBoxProps {
   content: string;
+  thinkingEnded: boolean;
 }
 
-const ThinkBox = ({ content }: ThinkBoxProps) => {
+const ThinkBox = ({ content, thinkingEnded }: ThinkBoxProps) => {
-  const [isExpanded, setIsExpanded] = useState(false);
+  const [isExpanded, setIsExpanded] = useState(true);
+
+  useEffect(() => {
+    if (thinkingEnded) {
+      setIsExpanded(false);
+    } else {
+      setIsExpanded(true);
+    }
+  }, [thinkingEnded]);
 
   return (
     <div className="my-4 bg-light-secondary/50 dark:bg-dark-secondary/50 rounded-xl border border-light-200 dark:border-dark-200 overflow-hidden">

src/components/WeatherWidget.tsx

@@ -9,7 +9,10 @@ const WeatherWidget = () => {
     humidity: 0,
     windSpeed: 0,
     icon: '',
+    temperatureUnit: 'C',
+    windSpeedUnit: 'm/s',
   });
+
   const [loading, setLoading] = useState(true);
 
   useEffect(() => {
@@ -73,6 +76,7 @@ const WeatherWidget = () => {
         body: JSON.stringify({
           lat: location.latitude,
           lng: location.longitude,
+          measureUnit: localStorage.getItem('measureUnit') ?? 'Metric',
         }),
       });
 
@@ -91,6 +95,8 @@ const WeatherWidget = () => {
         humidity: data.humidity,
         windSpeed: data.windSpeed,
         icon: data.icon,
+        temperatureUnit: data.temperatureUnit,
+        windSpeedUnit: data.windSpeedUnit,
       });
       setLoading(false);
     });
@@ -125,7 +131,7 @@ const WeatherWidget = () => {
               className="h-10 w-auto"
             />
             <span className="text-base font-semibold text-black dark:text-white">
-              {data.temperature}°C
+              {data.temperature}°{data.temperatureUnit}
             </span>
           </div>
           <div className="flex flex-col justify-between flex-1 h-full py-1">
@@ -135,7 +141,7 @@ const WeatherWidget = () => {
               </span>
               <span className="flex items-center text-xs text-black/60 dark:text-white/60">
                 <Wind className="w-3 h-3 mr-1" />
-                {data.windSpeed} km/h
+                {data.windSpeed} {data.windSpeedUnit}
               </span>
             </div>
             <span className="text-xs text-black/60 dark:text-white/60 mt-1">

src/lib/chains/imageSearchAgent.ts

@@ -3,32 +3,18 @@ import {
   RunnableMap,
   RunnableLambda,
 } from '@langchain/core/runnables';
-import { PromptTemplate } from '@langchain/core/prompts';
+import { ChatPromptTemplate } 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 '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import LineOutputParser from '../outputParsers/lineOutputParser';
 
 const imageSearchChainPrompt = `
 You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search the web for images.
 You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
-
+Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
-Example:
-1. Follow up question: What is a cat?
-Rephrased: A cat
-
-2. Follow up question: What is a car? How does it works?
-Rephrased: Car working
-
-3. Follow up question: How does an AC work?
-Rephrased: AC working
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
 `;
 
 type ImageSearchChainInput = {
@@ -54,12 +40,39 @@ const createImageSearchChain = (llm: BaseChatModel) => {
         return input.query;
       },
     }),
-    PromptTemplate.fromTemplate(imageSearchChainPrompt),
+    ChatPromptTemplate.fromMessages([
+      ['system', imageSearchChainPrompt],
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nWhat is a cat?\n</follow_up>',
+      ],
+      ['assistant', '<query>A cat</query>'],
+
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nWhat is a car? How does it work?\n</follow_up>',
+      ],
+      ['assistant', '<query>Car working</query>'],
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
+      ],
+      ['assistant', '<query>AC working</query>'],
+      [
+        'user',
+        '<conversation>{chat_history}</conversation>\n<follow_up>\n{query}\n</follow_up>',
+      ],
+    ]),
     llm,
     strParser,
     RunnableLambda.from(async (input: string) => {
-      input = input.replace(/<think>.*?<\/think>/g, '');
+      const queryParser = new LineOutputParser({
+        key: 'query',
+      });
 
+      return await queryParser.parse(input);
+    }),
+    RunnableLambda.from(async (input: string) => {
       const res = await searchSearxng(input, {
         engines: ['bing images', 'google images'],
       });

src/lib/chains/videoSearchAgent.ts

@@ -3,33 +3,19 @@ import {
   RunnableMap,
   RunnableLambda,
 } from '@langchain/core/runnables';
-import { PromptTemplate } from '@langchain/core/prompts';
+import { ChatPromptTemplate } 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 '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import LineOutputParser from '../outputParsers/lineOutputParser';
 
-const VideoSearchChainPrompt = `
+const videoSearchChainPrompt = `
-  You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search Youtube for videos.
+You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search Youtube for videos.
-  You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
+You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
-  
+Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
-  Example:
+`;
-  1. Follow up question: How does a car work?
-  Rephrased: How does a car work?
-  
-  2. Follow up question: What is the theory of relativity?
-  Rephrased: What is theory of relativity
-  
-  3. Follow up question: How does an AC work?
-  Rephrased: How does an AC work
-  
-  Conversation:
-  {chat_history}
-  
-  Follow up question: {query}
-  Rephrased question:
-  `;
 
 type VideoSearchChainInput = {
   chat_history: BaseMessage[];
@@ -55,12 +41,37 @@ const createVideoSearchChain = (llm: BaseChatModel) => {
         return input.query;
       },
     }),
-    PromptTemplate.fromTemplate(VideoSearchChainPrompt),
+    ChatPromptTemplate.fromMessages([
+      ['system', videoSearchChainPrompt],
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nHow does a car work?\n</follow_up>',
+      ],
+      ['assistant', '<query>How does a car work?</query>'],
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nWhat is the theory of relativity?\n</follow_up>',
+      ],
+      ['assistant', '<query>Theory of relativity</query>'],
+      [
+        'user',
+        '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
+      ],
+      ['assistant', '<query>AC working</query>'],
+      [
+        'user',
+        '<conversation>{chat_history}</conversation>\n<follow_up>\n{query}\n</follow_up>',
+      ],
+    ]),
     llm,
     strParser,
     RunnableLambda.from(async (input: string) => {
-      input = input.replace(/<think>.*?<\/think>/g, '');
+      const queryParser = new LineOutputParser({
-
+        key: 'query',
+      });
+      return await queryParser.parse(input);
+    }),
+    RunnableLambda.from(async (input: string) => {
       const res = await searchSearxng(input, {
         engines: ['youtube'],
       });
@@ -92,8 +103,8 @@ const handleVideoSearch = (
   input: VideoSearchChainInput,
   llm: BaseChatModel,
 ) => {
-  const VideoSearchChain = createVideoSearchChain(llm);
+  const videoSearchChain = createVideoSearchChain(llm);
-  return VideoSearchChain.invoke(input);
+  return videoSearchChain.invoke(input);
 };
 
 export default handleVideoSearch;

src/lib/providers/aimlapi.ts

@@ -38,7 +38,7 @@ export const loadAimlApiChatModels = async () => {
         chatModels[model.id] = {
           displayName: model.name || model.id,
           model: new ChatOpenAI({
-            openAIApiKey: apiKey,
+            apiKey: apiKey,
             modelName: model.id,
             temperature: 0.7,
             configuration: {
@@ -76,7 +76,7 @@ export const loadAimlApiEmbeddingModels = async () => {
         embeddingModels[model.id] = {
           displayName: model.name || model.id,
           model: new OpenAIEmbeddings({
-            openAIApiKey: apiKey,
+            apiKey: apiKey,
             modelName: model.id,
             configuration: {
               baseURL: API_URL,

src/lib/providers/anthropic.ts

@@ -9,6 +9,18 @@ export const PROVIDER_INFO = {
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const anthropicChatModels: Record<string, string>[] = [
+  {
+    displayName: 'Claude 4.1 Opus',
+    key: 'claude-opus-4-1-20250805',
+  },
+  {
+    displayName: 'Claude 4 Opus',
+    key: 'claude-opus-4-20250514',
+  },
+  {
+    displayName: 'Claude 4 Sonnet',
+    key: 'claude-sonnet-4-20250514',
+  },
   {
     displayName: 'Claude 3.7 Sonnet',
     key: 'claude-3-7-sonnet-20250219',

src/lib/providers/deepseek.ts

@@ -31,7 +31,7 @@ export const loadDeepseekChatModels = async () => {
       chatModels[model.key] = {
         displayName: model.displayName,
         model: new ChatOpenAI({
-          openAIApiKey: deepseekApiKey,
+          apiKey: deepseekApiKey,
           modelName: model.key,
           temperature: 0.7,
           configuration: {

src/lib/providers/gemini.ts

@@ -14,16 +14,16 @@ import { Embeddings } from '@langchain/core/embeddings';
 
 const geminiChatModels: Record<string, string>[] = [
   {
-    displayName: 'Gemini 2.5 Flash Preview 05-20',
+    displayName: 'Gemini 2.5 Flash',
-    key: 'gemini-2.5-flash-preview-05-20',
+    key: 'gemini-2.5-flash',
   },
   {
-    displayName: 'Gemini 2.5 Pro Preview',
+    displayName: 'Gemini 2.5 Flash-Lite',
-    key: 'gemini-2.5-pro-preview-05-06',
+    key: 'gemini-2.5-flash-lite',
   },
   {
-    displayName: 'Gemini 2.5 Pro Experimental',
+    displayName: 'Gemini 2.5 Pro',
-    key: 'gemini-2.5-pro-preview-05-06',
+    key: 'gemini-2.5-pro',
   },
   {
     displayName: 'Gemini 2.0 Flash',
@@ -75,7 +75,7 @@ export const loadGeminiChatModels = async () => {
         displayName: model.displayName,
         model: new ChatGoogleGenerativeAI({
           apiKey: geminiApiKey,
-          modelName: model.key,
+          model: model.key,
           temperature: 0.7,
         }) as unknown as BaseChatModel,
       };
@@ -108,7 +108,7 @@ export const loadGeminiEmbeddingModels = async () => {
 
     return embeddingModels;
   } catch (err) {
-    console.error(`Error loading OpenAI embeddings models: ${err}`);
+    console.error(`Error loading Gemini embeddings models: ${err}`);
     return {};
   }
 };

src/lib/providers/groq.ts

@@ -1,4 +1,4 @@
-import { ChatOpenAI } from '@langchain/openai';
+import { ChatGroq } from '@langchain/groq';
 import { getGroqApiKey } from '../config';
 import { ChatModel } from '.';
 
@@ -28,13 +28,10 @@ export const loadGroqChatModels = async () => {
     groqChatModels.forEach((model: any) => {
       chatModels[model.id] = {
         displayName: model.id,
-        model: new ChatOpenAI({
+        model: new ChatGroq({
-          openAIApiKey: groqApiKey,
+          apiKey: groqApiKey,
-          modelName: model.id,
+          model: model.id,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
         }) as unknown as BaseChatModel,
       };
     });

src/lib/providers/index.ts

@@ -118,7 +118,7 @@ export const getAvailableChatModelProviders = async () => {
           [customOpenAiModelName]: {
             displayName: customOpenAiModelName,
             model: new ChatOpenAI({
-              openAIApiKey: customOpenAiApiKey,
+              apiKey: customOpenAiApiKey,
               modelName: customOpenAiModelName,
               temperature: 0.7,
               configuration: {

src/lib/providers/lmstudio.ts

@@ -47,7 +47,7 @@ export const loadLMStudioChatModels = async () => {
       chatModels[model.id] = {
         displayName: model.name || model.id,
         model: new ChatOpenAI({
-          openAIApiKey: 'lm-studio',
+          apiKey: 'lm-studio',
           configuration: {
             baseURL: ensureV1Endpoint(endpoint),
           },
@@ -83,7 +83,7 @@ export const loadLMStudioEmbeddingsModels = async () => {
       embeddingsModels[model.id] = {
         displayName: model.name || model.id,
         model: new OpenAIEmbeddings({
-          openAIApiKey: 'lm-studio',
+          apiKey: 'lm-studio',
           configuration: {
             baseURL: ensureV1Endpoint(endpoint),
           },

src/lib/providers/ollama.ts

@@ -6,8 +6,8 @@ export const PROVIDER_INFO = {
   key: 'ollama',
   displayName: 'Ollama',
 };
-import { ChatOllama } from '@langchain/community/chat_models/ollama';
+import { ChatOllama } from '@langchain/ollama';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+import { OllamaEmbeddings } from '@langchain/ollama';
 
 export const loadOllamaChatModels = async () => {
   const ollamaApiEndpoint = getOllamaApiEndpoint();

src/lib/providers/openai.ts

@@ -42,6 +42,18 @@ const openaiChatModels: Record<string, string>[] = [
     displayName: 'GPT 4.1',
     key: 'gpt-4.1',
   },
+  {
+    displayName: 'GPT 5 nano',
+    key: 'gpt-5-nano',
+  },
+  {
+    displayName: 'GPT 5 mini',
+    key: 'gpt-5-mini',
+  },
+  {
+    displayName: 'GPT 5',
+    key: 'gpt-5',
+  },
 ];
 
 const openaiEmbeddingModels: Record<string, string>[] = [
@@ -67,9 +79,9 @@ export const loadOpenAIChatModels = async () => {
       chatModels[model.key] = {
         displayName: model.displayName,
         model: new ChatOpenAI({
-          openAIApiKey: openaiApiKey,
+          apiKey: openaiApiKey,
           modelName: model.key,
-          temperature: 0.7,
+          temperature: model.key.includes('gpt-5') ? 1 : 0.7,
         }) as unknown as BaseChatModel,
       };
     });
@@ -93,7 +105,7 @@ export const loadOpenAIEmbeddingModels = async () => {
       embeddingModels[model.key] = {
         displayName: model.displayName,
         model: new OpenAIEmbeddings({
-          openAIApiKey: openaiApiKey,
+          apiKey: openaiApiKey,
           modelName: model.key,
         }) as unknown as Embeddings,
       };

src/lib/utils/formatHistory.ts

@@ -1,8 +1,11 @@
-import { BaseMessage } from '@langchain/core/messages';
+import { BaseMessage, isAIMessage } from '@langchain/core/messages';
 
 const formatChatHistoryAsString = (history: BaseMessage[]) => {
   return history
-    .map((message) => `${message._getType()}: ${message.content}`)
+    .map(
+      (message) =>
+        `${isAIMessage(message) ? 'AI' : 'User'}: ${message.content}`,
+    )
     .join('\n');
 };