Merge pull request #736 from ItzCrazyKns/master

Merge master into feat/deep-research
feat(metaSearchAgent): add quality optimization mode
2025-09-16 14:21:32 +00:00 · 2025-04-08 12:28:46 +05:30 · 2025-04-08 12:27:48 +05:30 · 2025-04-07 10:21:34 +05:30 · 2025-04-07 10:21:22 +05:30 · 2025-04-07 10:18:11 +05:30
40 changed files with 2321 additions and 15524 deletions
--- a/README.md
+++ b/README.md
@@ -1,5 +1,21 @@
 # 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->

+<div align="center" markdown="1">
+   <sup>Special thanks to:</sup>
+   <br>
+   <br>
+   <a href="https://www.warp.dev/perplexica">
+      <img alt="Warp sponsorship" width="400" src="https://github.com/user-attachments/assets/775dd593-9b5f-40f1-bf48-479faff4c27b">
+   </a>
+
+### [Warp, the AI Devtool that lives in your terminal](https://www.warp.dev/perplexica)
+
+[Available for MacOS, Linux, & Windows](https://www.warp.dev/perplexica)
+
+</div>
+
+<hr/>
+
 [![Discord](https://dcbadge.vercel.app/api/server/26aArMy8tT?style=flat&compact=true)](https://discord.gg/26aArMy8tT)

 ![preview](.assets/perplexica-screenshot.png?)
@@ -41,10 +57,9 @@ Want to know more about its architecture and how it works? You can read it [here
 - **Two Main Modes:**
  - **Copilot Mode:** (In development) Boosts search by generating different queries to find more relevant internet sources. Like normal search instead of just using the context by SearxNG, it visits the top matches and tries to find relevant sources to the user's query directly from the page.
  - **Normal Mode:** Processes your query and performs a web search.
- **Focus Modes:** Special modes to better answer specific types of questions. Perplexica currently has 7 focus modes:
+- **Focus Modes:** Special modes to better answer specific types of questions. Perplexica currently has 6 focus modes:
  - **All Mode:** Searches the entire web to find the best results.
-  - **Local Research Mode:** Research and interact with local files with citations.
-  - **Chat Mode:** Have a truly creative conversation without web search.
+  - **Writing Assistant Mode:** Helpful for writing tasks that do not require searching the web.
  - **Academic Search Mode:** Finds articles and papers, ideal for academic research.
  - **YouTube Search Mode:** Finds YouTube videos based on the search query.
  - **Wolfram Alpha Search Mode:** Answers queries that need calculations or data analysis using Wolfram Alpha.
@@ -144,7 +159,6 @@ 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

--- a/docs/API/SEARCH.md
+++ b/docs/API/SEARCH.md
@@ -55,7 +55,7 @@ The API accepts a JSON object in the request body, where you define the focus mo

 - **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:

-  - `webSearch`, `academicSearch`, `localResearch`, `chat`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
+  - `webSearch`, `academicSearch`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.

 - **`optimizationMode`** (string, optional): Specifies the optimization mode to control the balance between performance and quality. Available modes:

--- a/package-lock.json
+++ b/package-lock.json
--- a/package.json
+++ b/package.json
@@ -4,7 +4,7 @@
  "license": "MIT",
  "author": "ItzCrazyKns",
  "scripts": {
-    "dev": "next dev --turbopack",
+    "dev": "next dev",
    "build": "npm run db:push && next build",
    "start": "next start",
    "lint": "next lint",
@@ -19,11 +19,9 @@
    "@langchain/community": "^0.3.36",
    "@langchain/core": "^0.3.42",
    "@langchain/google-genai": "^0.1.12",
-    "@langchain/ollama": "^0.2.0",
    "@langchain/openai": "^0.0.25",
    "@langchain/textsplitters": "^0.1.0",
    "@tailwindcss/typography": "^0.5.12",
-    "@types/react-syntax-highlighter": "^15.5.13",
    "@xenova/transformers": "^2.17.2",
    "axios": "^1.8.3",
    "better-sqlite3": "^11.9.1",
@@ -40,7 +38,6 @@
    "pdf-parse": "^1.1.1",
    "react": "^18",
    "react-dom": "^18",
-    "react-syntax-highlighter": "^15.6.1",
    "react-text-to-speech": "^0.14.5",
    "react-textarea-autosize": "^8.5.3",
    "sonner": "^1.4.41",
--- a/sample.config.toml
+++ b/sample.config.toml
@@ -25,8 +25,5 @@ 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
--- a/src/app/api/chat/route.ts
+++ b/src/app/api/chat/route.ts
@@ -20,7 +20,6 @@ import {
  getCustomOpenaiApiUrl,
  getCustomOpenaiModelName,
 } from '@/lib/config';
-import { ChatOllama } from '@langchain/ollama';
 import { searchHandlers } from '@/lib/search';

 export const runtime = 'nodejs';
@@ -35,7 +34,6 @@ type Message = {
 type ChatModel = {
  provider: string;
  name: string;
-  ollamaContextWindow?: number;
 };

 type EmbeddingModel = {
@@ -54,18 +52,12 @@ type Body = {
  systemInstructions: string;
 };

-type ModelStats = {
-  modelName: string;
-  responseTime?: number;
-};
-
 const handleEmitterEvents = async (
  stream: EventEmitter,
  writer: WritableStreamDefaultWriter,
  encoder: TextEncoder,
  aiMessageId: string,
  chatId: string,
-  startTime: number,
 ) => {
  let recievedMessage = '';
  let sources: any[] = [];
@@ -98,32 +90,12 @@ const handleEmitterEvents = async (
      sources = parsedData.data;
    }
  });
-  let modelStats: ModelStats = {
-    modelName: '',
-  };
-
-  stream.on('stats', (data) => {
-    const parsedData = JSON.parse(data);
-    if (parsedData.type === 'modelStats') {
-      modelStats = parsedData.data;
-    }
-  });
-
  stream.on('end', () => {
-    const endTime = Date.now();
-    const duration = endTime - startTime;
-
-    modelStats = {
-      ...modelStats,
-      responseTime: duration,
-    };
-
    writer.write(
      encoder.encode(
        JSON.stringify({
          type: 'messageEnd',
          messageId: aiMessageId,
-          modelStats: modelStats,
        }) + '\n',
      ),
    );
@@ -138,7 +110,6 @@ const handleEmitterEvents = async (
        metadata: JSON.stringify({
          createdAt: new Date(),
          ...(sources && sources.length > 0 && { sources }),
-          modelStats: modelStats,
        }),
      })
      .execute();
@@ -212,7 +183,6 @@ const handleHistorySave = async (

 export const POST = async (req: Request) => {
  try {
-    const startTime = Date.now();
    const body = (await req.json()) as Body;
    const { message } = body;

@@ -262,11 +232,6 @@ 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) {
@@ -321,14 +286,7 @@ export const POST = async (req: Request) => {
    const writer = responseStream.writable.getWriter();
    const encoder = new TextEncoder();

-    handleEmitterEvents(
-      stream,
-      writer,
-      encoder,
-      aiMessageId,
-      message.chatId,
-      startTime,
-    );
+    handleEmitterEvents(stream, writer, encoder, aiMessageId, message.chatId);
    handleHistorySave(message, humanMessageId, body.focusMode, body.files);

    return new Response(responseStream.readable, {
--- a/src/app/api/config/route.ts
+++ b/src/app/api/config/route.ts
@@ -8,7 +8,6 @@ import {
  getOllamaApiEndpoint,
  getOpenaiApiKey,
  getDeepseekApiKey,
-  getLMStudioApiEndpoint,
  updateConfig,
 } from '@/lib/config';
 import {
@@ -52,7 +51,6 @@ export const GET = async (req: Request) => {

    config['openaiApiKey'] = getOpenaiApiKey();
    config['ollamaApiUrl'] = getOllamaApiEndpoint();
-    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
    config['anthropicApiKey'] = getAnthropicApiKey();
    config['groqApiKey'] = getGroqApiKey();
    config['geminiApiKey'] = getGeminiApiKey();
@@ -95,9 +93,6 @@ export const POST = async (req: Request) => {
        DEEPSEEK: {
          API_KEY: config.deepseekApiKey,
        },
-        LM_STUDIO: {
-          API_URL: config.lmStudioApiUrl,
-        },
        CUSTOM_OPENAI: {
          API_URL: config.customOpenaiApiUrl,
          API_KEY: config.customOpenaiApiKey,
--- a/src/app/api/images/route.ts
+++ b/src/app/api/images/route.ts
@@ -7,13 +7,11 @@ 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 {
@@ -60,10 +58,6 @@ 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) {
--- a/src/app/api/search/route.ts
+++ b/src/app/api/search/route.ts
@@ -13,14 +13,12 @@ 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 {
@@ -99,10 +97,6 @@ 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]
--- a/src/app/api/suggestions/route.ts
+++ b/src/app/api/suggestions/route.ts
@@ -8,12 +8,10 @@ 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 {
@@ -59,10 +57,6 @@ 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) {
--- a/src/app/api/videos/route.ts
+++ b/src/app/api/videos/route.ts
@@ -7,13 +7,11 @@ 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 {
@@ -60,10 +58,6 @@ 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) {
--- a/src/app/settings/page.tsx
+++ b/src/app/settings/page.tsx
@@ -5,9 +5,8 @@ import { useEffect, useState } from 'react';
 import { cn } from '@/lib/utils';
 import { Switch } from '@headlessui/react';
 import ThemeSwitcher from '@/components/theme/Switcher';
-import { ImagesIcon, VideoIcon, Layers3 } from 'lucide-react';
+import { ImagesIcon, VideoIcon } from 'lucide-react';
 import Link from 'next/link';
-import { PROVIDER_METADATA } from '@/lib/providers';

 interface SettingsType {
  chatModelProviders: {
@@ -21,12 +20,10 @@ 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> {
@@ -147,14 +144,8 @@ const Page = () => {
  const [isLoading, setIsLoading] = useState(false);
  const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
  const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
-  const [automaticSuggestions, setAutomaticSuggestions] = useState(true);
  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 () => {
@@ -166,7 +157,6 @@ const Page = () => {
      });

      const data = (await res.json()) as SettingsType;
-
      setConfig(data);

      const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
@@ -215,16 +205,6 @@ const Page = () => {
      setAutomaticVideoSearch(
        localStorage.getItem('autoVideoSearch') === 'true',
      );
-      setAutomaticSuggestions(
-        localStorage.getItem('autoSuggestions') !== 'false', // default to true if not set
-      );
-      const storedContextWindow = parseInt(
-        localStorage.getItem('ollamaContextWindow') ?? '2048',
-      );
-      setContextWindowSize(storedContextWindow);
-      setIsCustomContextWindow(
-        !predefinedContextSizes.includes(storedContextWindow),
-      );

      setSystemInstructions(localStorage.getItem('systemInstructions')!);

@@ -376,8 +356,6 @@ const Page = () => {
        localStorage.setItem('autoImageSearch', value.toString());
      } else if (key === 'automaticVideoSearch') {
        localStorage.setItem('autoVideoSearch', value.toString());
-      } else if (key === 'automaticSuggestions') {
-        localStorage.setItem('autoSuggestions', value.toString());
      } else if (key === 'chatModelProvider') {
        localStorage.setItem('chatModelProvider', value);
      } else if (key === 'chatModel') {
@@ -386,8 +364,6 @@ 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);
      }
@@ -532,47 +508,6 @@ const Page = () => {
                    />
                  </Switch>
                </div>
-
-                <div className="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">
-                  <div className="flex items-center space-x-3">
-                    <div className="p-2 bg-light-200 dark:bg-dark-200 rounded-lg">
-                      <Layers3
-                        size={18}
-                        className="text-black/70 dark:text-white/70"
-                      />
-                    </div>
-                    <div>
-                      <p className="text-sm text-black/90 dark:text-white/90 font-medium">
-                        Automatic Suggestions
-                      </p>
-                      <p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
-                        Automatically show related suggestions after responses
-                      </p>
-                    </div>
-                  </div>
-                  <Switch
-                    checked={automaticSuggestions}
-                    onChange={(checked) => {
-                      setAutomaticSuggestions(checked);
-                      saveConfig('automaticSuggestions', checked);
-                    }}
-                    className={cn(
-                      automaticSuggestions
-                        ? 'bg-[#24A0ED]'
-                        : 'bg-light-200 dark:bg-dark-200',
-                      'relative inline-flex h-6 w-11 items-center rounded-full transition-colors focus:outline-none',
-                    )}
-                  >
-                    <span
-                      className={cn(
-                        automaticSuggestions
-                          ? 'translate-x-6'
-                          : 'translate-x-1',
-                        'inline-block h-4 w-4 transform rounded-full bg-white transition-transform',
-                      )}
-                    />
-                  </Switch>
-                </div>
              </div>
            </SettingsSection>

@@ -613,9 +548,8 @@ const Page = () => {
                        (provider) => ({
                          value: provider,
                          label:
-                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                            provider.charAt(0).toUpperCase() +
-                              provider.slice(1),
+                            provider.slice(1),
                        }),
                      )}
                    />
@@ -662,78 +596,6 @@ 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>
@@ -828,9 +690,8 @@ const Page = () => {
                        (provider) => ({
                          value: provider,
                          label:
-                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                            provider.charAt(0).toUpperCase() +
-                              provider.slice(1),
+                            provider.slice(1),
                        }),
                      )}
                    />
@@ -997,25 +858,6 @@ const Page = () => {
                    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>
--- a/src/components/Chat.tsx
+++ b/src/components/Chat.tsx
@@ -5,107 +5,31 @@ import MessageInput from './MessageInput';
 import { File, Message } from './ChatWindow';
 import MessageBox from './MessageBox';
 import MessageBoxLoading from './MessageBoxLoading';
-import { check } from 'drizzle-orm/gel-core';

 const Chat = ({
  loading,
  messages,
  sendMessage,
-  scrollTrigger,
+  messageAppeared,
  rewrite,
  fileIds,
  setFileIds,
  files,
  setFiles,
-  optimizationMode,
-  setOptimizationMode,
 }: {
  messages: Message[];
-  sendMessage: (
-    message: string,
-    options?: {
-      messageId?: string;
-      rewriteIndex?: number;
-      suggestions?: string[];
-    },
-  ) => void;
+  sendMessage: (message: string) => void;
  loading: boolean;
-  scrollTrigger: number;
+  messageAppeared: boolean;
  rewrite: (messageId: string) => void;
  fileIds: string[];
  setFileIds: (fileIds: string[]) => void;
  files: File[];
  setFiles: (files: File[]) => void;
-  optimizationMode: string;
-  setOptimizationMode: (mode: string) => void;
 }) => {
  const [dividerWidth, setDividerWidth] = useState(0);
-  const [isAtBottom, setIsAtBottom] = useState(true);
-  const [manuallyScrolledUp, setManuallyScrolledUp] = useState(false);
  const dividerRef = useRef<HTMLDivElement | null>(null);
  const messageEnd = useRef<HTMLDivElement | null>(null);
-  const SCROLL_THRESHOLD = 200; // pixels from bottom to consider "at bottom"
-
-  // Check if user is at bottom of page
-  useEffect(() => {
-    const checkIsAtBottom = () => {
-      const position = window.innerHeight + window.scrollY;
-      const height = document.body.scrollHeight;
-      const atBottom = position >= height - SCROLL_THRESHOLD;
-
-      setIsAtBottom(atBottom);
-    };
-
-    // Initial check
-    checkIsAtBottom();
-
-    // Add scroll event listener
-    window.addEventListener('scroll', checkIsAtBottom);
-
-    return () => {
-      window.removeEventListener('scroll', checkIsAtBottom);
-    };
-  }, []);
-
-  // Detect wheel and touch events to identify user's scrolling direction
-  useEffect(() => {
-    const checkIsAtBottom = () => {
-      const position = window.innerHeight + window.scrollY;
-      const height = document.body.scrollHeight;
-      const atBottom = position >= height - SCROLL_THRESHOLD;
-
-      // If user scrolls to bottom, reset the manuallyScrolledUp flag
-      if (atBottom) {
-        setManuallyScrolledUp(false);
-      }
-
-      setIsAtBottom(atBottom);
-    };
-
-    const handleWheel = (e: WheelEvent) => {
-      // Positive deltaY means scrolling down, negative means scrolling up
-      if (e.deltaY < 0) {
-        // User is scrolling up
-        setManuallyScrolledUp(true);
-      } else if (e.deltaY > 0) {
-        checkIsAtBottom();
-      }
-    };
-
-    const handleTouchStart = (e: TouchEvent) => {
-      // Immediately stop auto-scrolling on any touch interaction
-      setManuallyScrolledUp(true);
-    };
-
-    // Add event listeners
-    window.addEventListener('wheel', handleWheel, { passive: true });
-    window.addEventListener('touchstart', handleTouchStart, { passive: true });
-
-    return () => {
-      window.removeEventListener('wheel', handleWheel);
-      window.removeEventListener('touchstart', handleTouchStart);
-    };
-  }, [isAtBottom]);

  useEffect(() => {
    const updateDividerWidth = () => {
@@ -123,7 +47,6 @@ const Chat = ({
    };
  });

-  // Scroll when user sends a message
  useEffect(() => {
    const scroll = () => {
      messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
@@ -133,27 +56,11 @@ const Chat = ({
      document.title = `${messages[0].content.substring(0, 30)} - Perplexica`;
    }

-    // Always scroll when user sends a message
-    if (messages[messages.length - 1]?.role === 'user') {
+    if (messages[messages.length - 1]?.role == 'user') {
      scroll();
-      setIsAtBottom(true); // Reset to true when user sends a message
-      setManuallyScrolledUp(false); // Reset manually scrolled flag when user sends a message
    }
  }, [messages]);

-  // Auto-scroll for assistant responses only if user is at bottom and hasn't manually scrolled up
-  useEffect(() => {
-    const position = window.innerHeight + window.scrollY;
-    const height = document.body.scrollHeight;
-    const atBottom = position >= height - SCROLL_THRESHOLD;
-    console.log('scrollTrigger', scrollTrigger);
-    setIsAtBottom(atBottom);
-
-    if (isAtBottom && !manuallyScrolledUp && messages.length > 0) {
-      messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
-    }
-  }, [scrollTrigger, isAtBottom, messages.length, manuallyScrolledUp]);
-
  return (
    <div className="flex flex-col space-y-6 pt-8 pb-44 lg:pb-32 sm:mx-4 md:mx-8">
      {messages.map((msg, i) => {
@@ -178,44 +85,13 @@ const Chat = ({
          </Fragment>
        );
      })}
-      {loading && <MessageBoxLoading />}
+      {loading && !messageAppeared && <MessageBoxLoading />}
      <div ref={messageEnd} className="h-0" />
-
      {dividerWidth > 0 && (
        <div
          className="bottom-24 lg:bottom-10 fixed z-40"
          style={{ width: dividerWidth }}
        >
-          {/* Scroll to bottom button - appears above the MessageInput when user has scrolled up */}
-          {manuallyScrolledUp && !isAtBottom && (
-            <div className="absolute -top-14 right-2 z-10">
-              <button
-                onClick={() => {
-                  setManuallyScrolledUp(false);
-                  setIsAtBottom(true);
-                  messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
-                }}
-                className="bg-[#24A0ED] text-white hover:bg-opacity-85 transition duration-100 rounded-full px-4 py-2 shadow-lg flex items-center justify-center"
-                aria-label="Scroll to bottom"
-              >
-                <svg
-                  xmlns="http://www.w3.org/2000/svg"
-                  className="h-5 w-5 mr-1"
-                  viewBox="0 0 20 20"
-                  fill="currentColor"
-                >
-                  <path
-                    fillRule="evenodd"
-                    d="M14.707 12.707a1 1 0 01-1.414 0L10 9.414l-3.293 3.293a1 1 0 01-1.414-1.414l4-4a1 1 0 011.414 0l4 4a1 1 0 010 1.414z"
-                    clipRule="evenodd"
-                    transform="rotate(180 10 10)"
-                  />
-                </svg>
-                <span className="text-sm">Scroll to bottom</span>
-              </button>
-            </div>
-          )}
-
          <MessageInput
            loading={loading}
            sendMessage={sendMessage}
@@ -223,8 +99,6 @@ const Chat = ({
            setFileIds={setFileIds}
            files={files}
            setFiles={setFiles}
-            optimizationMode={optimizationMode}
-            setOptimizationMode={setOptimizationMode}
          />
        </div>
      )}
--- a/src/components/ChatWindow.tsx
+++ b/src/components/ChatWindow.tsx
@@ -13,11 +13,6 @@ import { Settings } from 'lucide-react';
 import Link from 'next/link';
 import NextError from 'next/error';

-export type ModelStats = {
-  modelName: string;
-  responseTime?: number;
-};
-
 export type Message = {
  messageId: string;
  chatId: string;
@@ -26,7 +21,6 @@ export type Message = {
  role: 'user' | 'assistant';
  suggestions?: string[];
  sources?: Document[];
-  modelStats?: ModelStats;
 };

 export interface File {
@@ -278,7 +272,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
  }, []);

  const [loading, setLoading] = useState(false);
-  const [scrollTrigger, setScrollTrigger] = useState(0);
+  const [messageAppeared, setMessageAppeared] = useState(false);

  const [chatHistory, setChatHistory] = useState<[string, string][]>([]);
  const [messages, setMessages] = useState<Message[]>([]);
@@ -293,16 +287,6 @@ 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 &&
@@ -343,28 +327,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
    }
  }, [isMessagesLoaded, isConfigReady]);

-  const sendMessage = async (
-    message: string,
-    options?: {
-      messageId?: string;
-      rewriteIndex?: number;
-      suggestions?: string[];
-    },
-  ) => {
-    setScrollTrigger((x) => (x === 0 ? -1 : 0));
-    // Special case: If we're just updating an existing message with suggestions
-    if (options?.suggestions && options.messageId) {
-      setMessages((prev) =>
-        prev.map((msg) => {
-          if (msg.messageId === options.messageId) {
-            return { ...msg, suggestions: options.suggestions };
-          }
-          return msg;
-        }),
-      );
-      return;
-    }
-
+  const sendMessage = async (message: string, messageId?: string) => {
    if (loading) return;
    if (!isConfigReady) {
      toast.error('Cannot send message before the configuration is ready');
@@ -372,29 +335,13 @@ const ChatWindow = ({ id }: { id?: string }) => {
    }

    setLoading(true);
+    setMessageAppeared(false);

    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);
-
-      setScrollTrigger((prev) => prev + 1);
-    }
-
-    const messageId =
-      options?.messageId ?? crypto.randomBytes(7).toString('hex');
+    messageId = messageId ?? crypto.randomBytes(7).toString('hex');

    setMessages((prevMessages) => [
      ...prevMessages,
@@ -416,21 +363,19 @@ const ChatWindow = ({ id }: { id?: string }) => {

      if (data.type === 'sources') {
        sources = data.data;
-        if (!added) {
-          setMessages((prevMessages) => [
-            ...prevMessages,
-            {
-              content: '',
-              messageId: data.messageId,
-              chatId: chatId!,
-              role: 'assistant',
-              sources: sources,
-              createdAt: new Date(),
-            },
-          ]);
-          added = true;
-          setScrollTrigger((prev) => prev + 1);
-        }
+        setMessages((prevMessages) => [
+          ...prevMessages,
+          {
+            content: '',
+            messageId: data.messageId,
+            chatId: chatId!,
+            role: 'assistant',
+            sources: sources,
+            createdAt: new Date(),
+          },
+        ]);
+        added = true;
+        setMessageAppeared(true);
      }

      if (data.type === 'message') {
@@ -444,26 +389,23 @@ const ChatWindow = ({ id }: { id?: string }) => {
              role: 'assistant',
              sources: sources,
              createdAt: new Date(),
-              modelStats: {
-                modelName: data.modelName,
-              },
            },
          ]);
          added = true;
+          setMessageAppeared(true);
+        } else {
+          setMessages((prev) =>
+            prev.map((message) => {
+              if (message.messageId === data.messageId) {
+                return { ...message, content: message.content + data.data };
+              }
+
+              return message;
+            }),
+          );
        }

-        setMessages((prev) =>
-          prev.map((message) => {
-            if (message.messageId === data.messageId) {
-              return { ...message, content: message.content + data.data };
-            }
-
-            return message;
-          }),
-        );
-
        recievedMessage += data.data;
-        setScrollTrigger((prev) => prev + 1);
      }

      if (data.type === 'messageEnd') {
@@ -473,28 +415,12 @@ const ChatWindow = ({ id }: { id?: string }) => {
          ['assistant', recievedMessage],
        ]);

-        // Always update the message, adding modelStats if available
-        setMessages((prev) =>
-          prev.map((message) => {
-            if (message.messageId === data.messageId) {
-              return {
-                ...message,
-                // Include model stats if available, otherwise null
-                modelStats: data.modelStats || null,
-              };
-            }
-            return message;
-          }),
-        );
-
        setLoading(false);
-        setScrollTrigger((prev) => prev + 1);

        const lastMsg = messagesRef.current[messagesRef.current.length - 1];

        const autoImageSearch = localStorage.getItem('autoImageSearch');
        const autoVideoSearch = localStorage.getItem('autoVideoSearch');
-        const autoSuggestions = localStorage.getItem('autoSuggestions');

        if (autoImageSearch === 'true') {
          document
@@ -512,8 +438,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
          lastMsg.role === 'assistant' &&
          lastMsg.sources &&
          lastMsg.sources.length > 0 &&
-          !lastMsg.suggestions &&
-          autoSuggestions !== 'false' // Default to true if not set
+          !lastMsg.suggestions
        ) {
          const suggestions = await getSuggestions(messagesRef.current);
          setMessages((prev) =>
@@ -528,9 +453,6 @@ const ChatWindow = ({ id }: { id?: string }) => {
      }
    };

-    const ollamaContextWindow =
-      localStorage.getItem('ollamaContextWindow') || '2048';
-
    const res = await fetch('/api/chat', {
      method: 'POST',
      headers: {
@@ -547,13 +469,10 @@ const ChatWindow = ({ id }: { id?: string }) => {
        files: fileIds,
        focusMode: focusMode,
        optimizationMode: optimizationMode,
-        history: messageChatHistory,
+        history: chatHistory,
        chatModel: {
          name: chatModelProvider.name,
          provider: chatModelProvider.provider,
-          ...(chatModelProvider.provider === 'ollama' && {
-            ollamaContextWindow: parseInt(ollamaContextWindow),
-          }),
        },
        embeddingModel: {
          name: embeddingModelProvider.name,
@@ -591,14 +510,20 @@ const ChatWindow = ({ id }: { id?: string }) => {
  };

  const rewrite = (messageId: string) => {
-    const messageIndex = messages.findIndex(
-      (msg) => msg.messageId === messageId,
-    );
-    if (messageIndex == -1) return;
-    sendMessage(messages[messageIndex - 1].content, {
-      messageId: messageId,
-      rewriteIndex: messageIndex,
+    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)];
    });
+    setChatHistory((prev) => {
+      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
+    });
+
+    sendMessage(message.content, message.messageId);
  };

  useEffect(() => {
@@ -637,14 +562,12 @@ const ChatWindow = ({ id }: { id?: string }) => {
              loading={loading}
              messages={messages}
              sendMessage={sendMessage}
-              scrollTrigger={scrollTrigger}
+              messageAppeared={messageAppeared}
              rewrite={rewrite}
              fileIds={fileIds}
              setFileIds={setFileIds}
              files={files}
              setFiles={setFiles}
-              optimizationMode={optimizationMode}
-              setOptimizationMode={setOptimizationMode}
            />
          </>
        ) : (
--- a/src/components/MessageActions/ModelInfo.tsx
+++ b/src/components/MessageActions/ModelInfo.tsx
@@ -1,82 +0,0 @@
-'use client';
-
-import React, { useState, useEffect, useRef } from 'react';
-import { Info } from 'lucide-react';
-import { ModelStats } from '../ChatWindow';
-import { cn } from '@/lib/utils';
-
-interface ModelInfoButtonProps {
-  modelStats: ModelStats | null;
-}
-
-const ModelInfoButton: React.FC<ModelInfoButtonProps> = ({ modelStats }) => {
-  const [showPopover, setShowPopover] = useState(false);
-  const popoverRef = useRef<HTMLDivElement>(null);
-  const buttonRef = useRef<HTMLButtonElement>(null);
-
-  // Always render, using "Unknown" as fallback if model info isn't available
-  const modelName = modelStats?.modelName || 'Unknown';
-
-  useEffect(() => {
-    const handleClickOutside = (event: MouseEvent) => {
-      if (
-        popoverRef.current &&
-        !popoverRef.current.contains(event.target as Node) &&
-        buttonRef.current &&
-        !buttonRef.current.contains(event.target as Node)
-      ) {
-        setShowPopover(false);
-      }
-    };
-
-    document.addEventListener('mousedown', handleClickOutside);
-    return () => {
-      document.removeEventListener('mousedown', handleClickOutside);
-    };
-  }, []);
-
-  return (
-    <div className="relative">
-      <button
-        ref={buttonRef}
-        className="p-1 ml-1 text-black/50 dark:text-white/50 rounded-full hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
-        onClick={() => setShowPopover(!showPopover)}
-        aria-label="Show model information"
-      >
-        <Info size={14} />
-      </button>
-      {showPopover && (
-        <div
-          ref={popoverRef}
-          className="absolute z-10 left-6 top-0 w-64 rounded-md shadow-lg bg-white dark:bg-dark-secondary border border-light-200 dark:border-dark-200"
-        >
-          <div className="py-2 px-3">
-            <h4 className="text-sm font-medium mb-2 text-black dark:text-white">
-              Model Information
-            </h4>
-            <div className="space-y-1 text-xs">
-              <div className="flex justify-between">
-                <span className="text-black/70 dark:text-white/70">Model:</span>
-                <span className="text-black dark:text-white font-medium">
-                  {modelName}
-                </span>
-              </div>
-              {modelStats?.responseTime && (
-                <div className="flex justify-between">
-                  <span className="text-black/70 dark:text-white/70">
-                    Response time:
-                  </span>
-                  <span className="text-black dark:text-white font-medium">
-                    {(modelStats.responseTime / 1000).toFixed(2)}s
-                  </span>
-                </div>
-              )}
-            </div>
-          </div>
-        </div>
-      )}
-    </div>
-  );
-};
-
-export default ModelInfoButton;
--- a/src/components/MessageBox.tsx
+++ b/src/components/MessageBox.tsx
@@ -4,7 +4,6 @@
 import React, { MutableRefObject, useEffect, useState } from 'react';
 import { Message } from './ChatWindow';
 import { cn } from '@/lib/utils';
-import { getSuggestions } from '@/lib/actions';
 import {
  BookCopy,
  Disc3,
@@ -12,92 +11,20 @@ import {
  StopCircle,
  Layers3,
  Plus,
-  Sparkles,
-  Copy as CopyIcon,
-  CheckCheck,
 } from 'lucide-react';
 import Markdown, { MarkdownToJSX } from 'markdown-to-jsx';
 import Copy from './MessageActions/Copy';
 import Rewrite from './MessageActions/Rewrite';
-import ModelInfoButton from './MessageActions/ModelInfo';
 import MessageSources from './MessageSources';
 import SearchImages from './SearchImages';
 import SearchVideos from './SearchVideos';
 import { useSpeech } from 'react-text-to-speech';
 import ThinkBox from './ThinkBox';
-import { Prism as SyntaxHighlighter } from 'react-syntax-highlighter';
-import { oneDark } from 'react-syntax-highlighter/dist/cjs/styles/prism';

 const ThinkTagProcessor = ({ children }: { children: React.ReactNode }) => {
  return <ThinkBox content={children as string} />;
 };

-const CodeBlock = ({
-  className,
-  children,
-}: {
-  className?: string;
-  children: React.ReactNode;
-}) => {
-  // Extract language from className (format could be "language-javascript" or "lang-javascript")
-  let language = '';
-  if (className) {
-    if (className.startsWith('language-')) {
-      language = className.replace('language-', '');
-    } else if (className.startsWith('lang-')) {
-      language = className.replace('lang-', '');
-    }
-  }
-
-  const content = children as string;
-
-  const [isCopied, setIsCopied] = useState(false);
-
-  const handleCopyCode = () => {
-    navigator.clipboard.writeText(content);
-    setIsCopied(true);
-    setTimeout(() => setIsCopied(false), 2000);
-  };
-
-  console.log('Code block language:', language, 'Class name:', className); // For debugging
-
-  return (
-    <div className="rounded-md overflow-hidden my-4 relative group border border-dark-secondary">
-      <div className="flex justify-between items-center px-4 py-2 bg-dark-200 border-b border-dark-secondary text-xs text-white/70 font-mono">
-        <span>{language}</span>
-        <button
-          onClick={handleCopyCode}
-          className="p-1 rounded-md hover:bg-dark-secondary transition duration-200"
-          aria-label="Copy code to clipboard"
-        >
-          {isCopied ? (
-            <CheckCheck size={14} className="text-green-500" />
-          ) : (
-            <CopyIcon size={14} className="text-white/70" />
-          )}
-        </button>
-      </div>
-      <SyntaxHighlighter
-        language={language || 'text'}
-        style={oneDark}
-        customStyle={{
-          margin: 0,
-          padding: '1rem',
-          borderRadius: 0,
-          backgroundColor: '#1c1c1c',
-        }}
-        wrapLines={true}
-        wrapLongLines={true}
-        showLineNumbers={language !== '' && content.split('\n').length > 1}
-        useInlineStyles={true}
-        PreTag="div"
-      >
-        {content}
-      </SyntaxHighlighter>
-    </div>
-  );
-};
-
 const MessageBox = ({
  message,
  messageIndex,
@@ -115,40 +42,10 @@ const MessageBox = ({
  dividerRef?: MutableRefObject<HTMLDivElement | null>;
  isLast: boolean;
  rewrite: (messageId: string) => void;
-  sendMessage: (
-    message: string,
-    options?: {
-      messageId?: string;
-      rewriteIndex?: number;
-      suggestions?: string[];
-    },
-  ) => void;
+  sendMessage: (message: string) => void;
 }) => {
  const [parsedMessage, setParsedMessage] = useState(message.content);
  const [speechMessage, setSpeechMessage] = useState(message.content);
-  const [loadingSuggestions, setLoadingSuggestions] = useState(false);
-  const [autoSuggestions, setAutoSuggestions] = useState(
-    localStorage.getItem('autoSuggestions'),
-  );
-
-  const handleLoadSuggestions = async () => {
-    if (
-      loadingSuggestions ||
-      (message?.suggestions && message.suggestions.length > 0)
-    )
-      return;
-
-    setLoadingSuggestions(true);
-    try {
-      const suggestions = await getSuggestions([...history]);
-      // We need to update the message.suggestions property through parent component
-      sendMessage('', { messageId: message.messageId, suggestions });
-    } catch (error) {
-      console.error('Error loading suggestions:', error);
-    } finally {
-      setLoadingSuggestions(false);
-    }
-  };

  useEffect(() => {
    const citationRegex = /\[([^\]]+)\]/g;
@@ -200,7 +97,6 @@ const MessageBox = ({
          },
        ),
      );
-      setSpeechMessage(message.content.replace(regex, ''));
      return;
    }

@@ -208,18 +104,6 @@ const MessageBox = ({
    setParsedMessage(processedMessage);
  }, [message.content, message.sources, message.role]);

-  useEffect(() => {
-    const handleStorageChange = () => {
-      setAutoSuggestions(localStorage.getItem('autoSuggestions'));
-    };
-
-    window.addEventListener('storage', handleStorageChange);
-
-    return () => {
-      window.removeEventListener('storage', handleStorageChange);
-    };
-  }, []);
-
  const { speechStatus, start, stop } = useSpeech({ text: speechMessage });

  const markdownOverrides: MarkdownToJSX.Options = {
@@ -227,24 +111,6 @@ const MessageBox = ({
      think: {
        component: ThinkTagProcessor,
      },
-      code: {
-        component: ({ className, children }) => {
-          // Check if it's an inline code block or a fenced code block
-          if (className) {
-            // This is a fenced code block (```code```)
-            return <CodeBlock className={className}>{children}</CodeBlock>;
-          }
-          // This is an inline code block (`code`)
-          return (
-            <code className="px-1.5 py-0.5 rounded bg-dark-secondary text-white font-mono text-sm">
-              {children}
-            </code>
-          );
-        },
-      },
-      pre: {
-        component: ({ children }) => children,
-      },
    },
  };

@@ -282,7 +148,6 @@ const MessageBox = ({
              </div>
            )}
            <div className="flex flex-col space-y-2">
-              {' '}
              <div className="flex flex-row items-center space-x-2">
                <Disc3
                  className={cn(
@@ -294,16 +159,12 @@ const MessageBox = ({
                <h3 className="text-black dark:text-white font-medium text-xl">
                  Answer
                </h3>
-                {message.modelStats && (
-                  <ModelInfoButton modelStats={message.modelStats} />
-                )}
              </div>
+
              <Markdown
                className={cn(
-                  'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
-                  'prose-code:bg-transparent prose-code:p-0 prose-code:text-inherit prose-code:font-normal prose-code:before:content-none prose-code:after:content-none',
-                  'prose-pre:bg-transparent prose-pre:border-0 prose-pre:m-0 prose-pre:p-0',
-                  'max-w-none break-words text-white',
+                  'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
+                  'max-w-none break-words text-black dark:text-white',
                )}
                options={markdownOverrides}
              >
@@ -338,37 +199,18 @@ const MessageBox = ({
                  </div>
                </div>
              )}
-              {isLast && message.role === 'assistant' && !loading && (
-                <>
-                  <div className="h-px w-full bg-light-secondary dark:bg-dark-secondary" />
-                  <div className="flex flex-col space-y-3 text-black dark:text-white">
-                    <div className="flex flex-row items-center space-x-2 mt-4">
-                      <Layers3 />
-                      <h3 className="text-xl font-medium">Related</h3>{' '}
-                      {(!autoSuggestions || autoSuggestions === 'false') &&
-                      (!message.suggestions ||
-                        message.suggestions.length === 0) ? (
-                        <div className="bg-light-secondary dark:bg-dark-secondary">
-                          <button
-                            onClick={handleLoadSuggestions}
-                            disabled={loadingSuggestions}
-                            className="px-4 py-2 flex flex-row items-center justify-center space-x-2 rounded-lg bg-light-secondary dark:bg-dark-secondary hover:bg-light-200 dark:hover:bg-dark-200 transition duration-200 text-black/70 dark:text-white/70 hover:text-black dark:hover:text-white"
-                          >
-                            {loadingSuggestions ? (
-                              <div className="w-4 h-4 border-2 border-t-transparent border-gray-400 dark:border-gray-500 rounded-full animate-spin" />
-                            ) : (
-                              <Sparkles size={16} />
-                            )}
-                            <span>
-                              {loadingSuggestions
-                                ? 'Loading suggestions...'
-                                : 'Load suggestions'}
-                            </span>
-                          </button>
-                        </div>
-                      ) : null}
-                    </div>
-                    {message.suggestions && message.suggestions.length > 0 ? (
+              {isLast &&
+                message.suggestions &&
+                message.suggestions.length > 0 &&
+                message.role === 'assistant' &&
+                !loading && (
+                  <>
+                    <div className="h-px w-full bg-light-secondary dark:bg-dark-secondary" />
+                    <div className="flex flex-col space-y-3 text-black dark:text-white">
+                      <div className="flex flex-row items-center space-x-2 mt-4">
+                        <Layers3 />
+                        <h3 className="text-xl font-medium">Related</h3>
+                      </div>
                      <div className="flex flex-col space-y-3">
                        {message.suggestions.map((suggestion, i) => (
                          <div
@@ -393,10 +235,9 @@ const MessageBox = ({
                          </div>
                        ))}
                      </div>
-                    ) : null}
-                  </div>
-                </>
-              )}
+                    </div>
+                  </>
+                )}
            </div>
          </div>
          <div className="lg:sticky lg:top-20 flex flex-col items-center space-y-3 w-full lg:w-3/12 z-30 h-full pb-4">
--- a/src/components/MessageInput.tsx
+++ b/src/components/MessageInput.tsx
@@ -4,7 +4,6 @@ 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';

@@ -15,8 +14,6 @@ const MessageInput = ({
  setFileIds,
  files,
  setFiles,
-  optimizationMode,
-  setOptimizationMode,
 }: {
  sendMessage: (message: string) => void;
  loading: boolean;
@@ -24,8 +21,6 @@ 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('');
@@ -45,16 +40,20 @@ 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);
    };
@@ -76,95 +75,58 @@ const MessageInput = ({
        }
      }}
      className={cn(
-        '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',
+        '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',
      )}
    >
      {mode === 'single' && (
-        <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">
+        <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">
            <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 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"
+              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"
            >
              <ArrowUp className="bg-background" size={17} />
            </button>
--- a/src/components/MessageInputActions/Focus.tsx
+++ b/src/components/MessageInputActions/Focus.tsx
@@ -2,7 +2,6 @@ import {
  BadgePercent,
  ChevronDown,
  Globe,
-  MessageCircle,
  Pencil,
  ScanEye,
  SwatchBook,
@@ -31,23 +30,11 @@ const focusModes = [
    icon: <SwatchBook size={20} />,
  },
  {
-    key: 'chat',
-    title: 'Chat',
-    description: 'Have a creative conversation',
-    icon: <MessageCircle size={16} />,
-  },
-  {
-    key: 'localResearch',
-    title: 'Local Research',
-    description: 'Research and interact with local files with citations',
+    key: 'writingAssistant',
+    title: 'Writing',
+    description: 'Chat without searching the web',
    icon: <Pencil size={16} />,
  },
-  {
-    key: 'redditSearch',
-    title: 'Reddit',
-    description: 'Search for discussions and opinions',
-    icon: <SiReddit className="h-5 w-auto mr-0.5" />,
-  },
  {
    key: 'wolframAlphaSearch',
    title: 'Wolfram Alpha',
@@ -60,6 +47,12 @@ const focusModes = [
    description: 'Search and watch videos',
    icon: <SiYoutube className="h-5 w-auto mr-0.5" />,
  },
+  {
+    key: 'redditSearch',
+    title: 'Reddit',
+    description: 'Search for discussions and opinions',
+    icon: <SiReddit className="h-5 w-auto mr-0.5" />,
+  },
 ];

 const Focus = ({
--- a/src/components/MessageInputActions/Optimization.tsx
+++ b/src/components/MessageInputActions/Optimization.tsx
@@ -1,4 +1,4 @@
-import { ChevronDown, Minimize2, Sliders, Star, Zap } from 'lucide-react';
+import { ChevronDown, Sliders, Star, Zap } from 'lucide-react';
 import { cn } from '@/lib/utils';
 import {
  Popover,
@@ -7,6 +7,7 @@ import {
  Transition,
 } from '@headlessui/react';
 import { Fragment } from 'react';
+
 const OptimizationModes = [
  {
    key: 'speed',
@@ -40,13 +41,8 @@ const Optimization = ({
  optimizationMode: string;
  setOptimizationMode: (mode: string) => void;
 }) => {
-  const handleOptimizationChange = (mode: string) => {
-    setOptimizationMode(mode);
-    localStorage.setItem('optimizationMode', mode);
-  };
-
  return (
-    <Popover className="relative">
+    <Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
      <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"
@@ -74,19 +70,17 @@ const Optimization = ({
        leaveFrom="opacity-100 translate-y-0"
        leaveTo="opacity-0 translate-y-1"
      >
-        <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">
+        <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">
            {OptimizationModes.map((mode, i) => (
              <PopoverButton
-                onClick={() => handleOptimizationChange(mode.key)}
+                onClick={() => setOptimizationMode(mode.key)}
                key={i}
-                disabled={mode.key === 'quality'}
                className={cn(
                  'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition',
                  optimizationMode === mode.key
                    ? 'bg-light-secondary dark:bg-dark-secondary'
                    : 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
-                  mode.key === 'quality' && 'opacity-50 cursor-not-allowed',
                )}
              >
                <div className="flex flex-row items-center space-x-1 text-black dark:text-white">
--- a/src/components/SearchImages.tsx
+++ b/src/components/SearchImages.tsx
@@ -35,10 +35,9 @@ 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',
@@ -55,9 +54,6 @@ const SearchImages = ({
                    customOpenAIBaseURL: customOpenAIBaseURL,
                    customOpenAIKey: customOpenAIKey,
                  }),
-                  ...(chatModelProvider === 'ollama' && {
-                    ollamaContextWindow: parseInt(ollamaContextWindow),
-                  }),
                },
              }),
            });
--- a/src/components/SearchVideos.tsx
+++ b/src/components/SearchVideos.tsx
@@ -50,10 +50,9 @@ 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',
@@ -70,9 +69,6 @@ const Searchvideos = ({
                    customOpenAIBaseURL: customOpenAIBaseURL,
                    customOpenAIKey: customOpenAIKey,
                  }),
-                  ...(chatModelProvider === 'ollama' && {
-                    ollamaContextWindow: parseInt(ollamaContextWindow),
-                  }),
                },
              }),
            });
--- a/src/lib/actions.ts
+++ b/src/lib/actions.ts
@@ -6,8 +6,6 @@ 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',
@@ -23,9 +21,6 @@ export const getSuggestions = async (chatHisory: Message[]) => {
          customOpenAIKey,
          customOpenAIBaseURL,
        }),
-        ...(chatModelProvider === 'ollama' && {
-          ollamaContextWindow: parseInt(ollamaContextWindow),
-        }),
      },
    }),
  });
--- a/src/lib/config.ts
+++ b/src/lib/config.ts
@@ -1,14 +1,7 @@
+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 {
@@ -35,9 +28,6 @@ interface Config {
    DEEPSEEK: {
      API_KEY: string;
    };
-    LM_STUDIO: {
-      API_URL: string;
-    };
    CUSTOM_OPENAI: {
      API_URL: string;
      API_KEY: string;
@@ -53,17 +43,10 @@ type RecursivePartial<T> = {
  [P in keyof T]?: RecursivePartial<T[P]>;
 };

-const loadConfig = () => {
-  // Server-side only
-  if (typeof window === 'undefined') {
-    return toml.parse(
-      fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
-    ) as any as Config;
-  }
-
-  // Client-side fallback - settings will be loaded via API
-  return {} as Config;
-};
+const loadConfig = () =>
+  toml.parse(
+    fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
+  ) as any as Config;

 export const getSimilarityMeasure = () =>
  loadConfig().GENERAL.SIMILARITY_MEASURE;
@@ -94,9 +77,6 @@ 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;
@@ -129,13 +109,10 @@ const mergeConfigs = (current: any, update: any): any => {
 };

 export const updateConfig = (config: RecursivePartial<Config>) => {
-  // Server-side only
-  if (typeof window === 'undefined') {
-    const currentConfig = loadConfig();
-    const mergedConfig = mergeConfigs(currentConfig, config);
-    fs.writeFileSync(
-      path.join(path.join(process.cwd(), `${configFileName}`)),
-      toml.stringify(mergedConfig),
-    );
-  }
+  const currentConfig = loadConfig();
+  const mergedConfig = mergeConfigs(currentConfig, config);
+  fs.writeFileSync(
+    path.join(path.join(process.cwd(), `${configFileName}`)),
+    toml.stringify(mergedConfig),
+  );
 };
--- a/src/lib/prompts/chat.ts
+++ b/src/lib/prompts/chat.ts
@@ -1,19 +0,0 @@
-export const chatPrompt = `
-You are Perplexica, an AI model who is expert at having creative conversations with users. You are currently set on focus mode 'Chat', which means you will engage in a truly creative conversation without searching the web or citing sources.
-
-In Chat mode, you should be:
- Creative and engaging in your responses
- Helpful and informative based on your internal knowledge
- Conversational and natural in your tone
- Willing to explore ideas, hypothetical scenarios, and creative topics
-
-Since you are in Chat mode, you would not perform web searches or cite sources. If the user asks a question that would benefit from web search or specific data, you can suggest they switch to a different focus mode like 'All Mode' for general web search or another specialized mode.
-
-### 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>
-`;
--- a/src/lib/prompts/index.ts
+++ b/src/lib/prompts/index.ts
@@ -11,8 +11,7 @@ import {
  wolframAlphaSearchResponsePrompt,
  wolframAlphaSearchRetrieverPrompt,
 } from './wolframAlpha';
-import { localResearchPrompt } from './localResearch';
-import { chatPrompt } from './chat';
+import { writingAssistantPrompt } from './writingAssistant';
 import {
  youtubeSearchResponsePrompt,
  youtubeSearchRetrieverPrompt,
@@ -27,8 +26,7 @@ export default {
  redditSearchRetrieverPrompt,
  wolframAlphaSearchResponsePrompt,
  wolframAlphaSearchRetrieverPrompt,
-  localResearchPrompt,
-  chatPrompt,
+  writingAssistantPrompt,
  youtubeSearchResponsePrompt,
  youtubeSearchRetrieverPrompt,
 };
--- a/src/lib/prompts/writingAssistant.ts
+++ b/src/lib/prompts/writingAssistant.ts
@@ -1,6 +1,6 @@
-export const localResearchPrompt = `
-You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Local Research', this means you will be helping the user research and interact with local files with citations. 
-Since you are in local research mode, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode.
+export const writingAssistantPrompt = `
+You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query. 
+Since you are a writing assistant, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode.
 You will be shared a context that can contain information from files user has uploaded to get answers from. You will have to generate answers upon that.

 You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
--- a/src/lib/providers/anthropic.ts
+++ b/src/lib/providers/anthropic.ts
@@ -1,11 +1,6 @@
 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>[] = [
--- a/src/lib/providers/deepseek.ts
+++ b/src/lib/providers/deepseek.ts
@@ -3,11 +3,6 @@ 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)',
--- a/src/lib/providers/gemini.ts
+++ b/src/lib/providers/gemini.ts
@@ -4,11 +4,6 @@ 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';

--- a/src/lib/providers/groq.ts
+++ b/src/lib/providers/groq.ts
@@ -1,11 +1,6 @@
 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>[] = [
--- a/src/lib/providers/index.ts
+++ b/src/lib/providers/index.ts
@@ -1,60 +1,18 @@
 import { Embeddings } from '@langchain/core/embeddings';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import {
-  loadOpenAIChatModels,
-  loadOpenAIEmbeddingModels,
-  PROVIDER_INFO as OpenAIInfo,
-  PROVIDER_INFO,
-} from './openai';
+import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai';
 import {
  getCustomOpenaiApiKey,
  getCustomOpenaiApiUrl,
  getCustomOpenaiModelName,
 } from '../config';
 import { ChatOpenAI } from '@langchain/openai';
-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',
-  },
-};
+import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
+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;
@@ -76,7 +34,6 @@ export const chatModelProviders: Record<
  anthropic: loadAnthropicChatModels,
  gemini: loadGeminiChatModels,
  deepseek: loadDeepseekChatModels,
-  lmstudio: loadLMStudioChatModels,
 };

 export const embeddingModelProviders: Record<
@@ -87,7 +44,6 @@ export const embeddingModelProviders: Record<
  ollama: loadOllamaEmbeddingModels,
  gemini: loadGeminiEmbeddingModels,
  transformers: loadTransformersEmbeddingsModels,
-  lmstudio: loadLMStudioEmbeddingsModels,
 };

 export const getAvailableChatModelProviders = async () => {
--- a/src/lib/providers/lmstudio.ts
+++ b/src/lib/providers/lmstudio.ts
@@ -1,100 +0,0 @@
-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 {};
-  }
-};
--- a/src/lib/providers/ollama.ts
+++ b/src/lib/providers/ollama.ts
@@ -1,13 +1,8 @@
 import axios from 'axios';
 import { getKeepAlive, getOllamaApiEndpoint } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
-
-export const PROVIDER_INFO = {
-  key: 'ollama',
-  displayName: 'Ollama',
-};
-import { ChatOllama } from '@langchain/ollama';
-import { OllamaEmbeddings } from '@langchain/ollama';
+import { ChatOllama } from '@langchain/community/chat_models/ollama';
+import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';

 export const loadOllamaChatModels = async () => {
  const ollamaApiEndpoint = getOllamaApiEndpoint();
--- a/src/lib/providers/openai.ts
+++ b/src/lib/providers/openai.ts
@@ -1,11 +1,6 @@
 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';

@@ -30,18 +25,6 @@ const openaiChatModels: Record<string, string>[] = [
    displayName: 'GPT-4 omni mini',
    key: 'gpt-4o-mini',
  },
-  {
-    displayName: 'GPT 4.1 nano',
-    key: 'gpt-4.1-nano',
-  },
-  {
-    displayName: 'GPT 4.1 mini',
-    key: 'gpt-4.1-mini',
-  },
-  {
-    displayName: 'GPT 4.1',
-    key: 'gpt-4.1',
-  },
 ];

 const openaiEmbeddingModels: Record<string, string>[] = [
--- a/src/lib/providers/transformers.ts
+++ b/src/lib/providers/transformers.ts
@@ -1,10 +1,5 @@
 import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';

-export const PROVIDER_INFO = {
-  key: 'transformers',
-  displayName: 'Hugging Face',
-};
-
 export const loadTransformersEmbeddingsModels = async () => {
  try {
    const embeddingModels = {
--- a/src/lib/search/index.ts
+++ b/src/lib/search/index.ts
@@ -20,24 +20,15 @@ export const searchHandlers: Record<string, MetaSearchAgent> = {
    searchWeb: true,
    summarizer: false,
  }),
-  localResearch: new MetaSearchAgent({
+  writingAssistant: new MetaSearchAgent({
    activeEngines: [],
    queryGeneratorPrompt: '',
-    responsePrompt: prompts.localResearchPrompt,
+    responsePrompt: prompts.writingAssistantPrompt,
    rerank: true,
    rerankThreshold: 0,
    searchWeb: false,
    summarizer: false,
  }),
-  chat: new MetaSearchAgent({
-    activeEngines: [],
-    queryGeneratorPrompt: '',
-    responsePrompt: prompts.chatPrompt,
-    rerank: false,
-    rerankThreshold: 0,
-    searchWeb: false,
-    summarizer: false,
-  }),
  wolframAlphaSearch: new MetaSearchAgent({
    activeEngines: ['wolframalpha'],
    queryGeneratorPrompt: prompts.wolframAlphaSearchRetrieverPrompt,
--- a/src/lib/search/metaSearchAgent.ts
+++ b/src/lib/search/metaSearchAgent.ts
@@ -6,24 +6,20 @@ import {
  MessagesPlaceholder,
  PromptTemplate,
 } from '@langchain/core/prompts';
-import {
-  RunnableLambda,
-  RunnableMap,
-  RunnableSequence,
-} from '@langchain/core/runnables';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
 import LineListOutputParser from '../outputParsers/listLineOutputParser';
 import LineOutputParser from '../outputParsers/lineOutputParser';
 import { getDocumentsFromLinks } from '../utils/documents';
 import { Document } from 'langchain/document';
-import { searchSearxng } from '../searxng';
+import { searchSearxng, SearxngSearchResult } from '../searxng';
 import path from 'node:path';
 import fs from 'node:fs';
 import computeSimilarity from '../utils/computeSimilarity';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import { StreamEvent } from '@langchain/core/tracers/log_stream';
+import { EventEmitter } from 'node:stream';

 export interface MetaSearchAgentType {
  searchAndAnswer: (
@@ -47,7 +43,7 @@ interface Config {
  activeEngines: string[];
 }

-type BasicChainInput = {
+type SearchInput = {
  chat_history: BaseMessage[];
  query: string;
 };
@@ -60,237 +56,385 @@ class MetaSearchAgent implements MetaSearchAgentType {
    this.config = config;
  }

-  private async createSearchRetrieverChain(llm: BaseChatModel) {
+  private async searchSources(
+    llm: BaseChatModel,
+    input: SearchInput,
+    emitter: EventEmitter,
+  ) {
    (llm as unknown as ChatOpenAI).temperature = 0;

-    return RunnableSequence.from([
-      PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
-      llm,
-      this.strParser,
-      RunnableLambda.from(async (input: string) => {
-        const linksOutputParser = new LineListOutputParser({
-          key: 'links',
-        });
+    const chatPrompt = PromptTemplate.fromTemplate(
+      this.config.queryGeneratorPrompt,
+    );

-        const questionOutputParser = new LineOutputParser({
-          key: 'question',
-        });
+    const processedChatPrompt = await chatPrompt.invoke({
+      chat_history: formatChatHistoryAsString(input.chat_history),
+      query: input.query,
+    });

-        const links = await linksOutputParser.parse(input);
-        let question = this.config.summarizer
-          ? await questionOutputParser.parse(input)
-          : input;
+    const llmRes = await llm.invoke(processedChatPrompt);
+    const messageStr = await this.strParser.invoke(llmRes);

-        if (question === 'not_needed') {
-          return { query: '', docs: [] };
+    const linksOutputParser = new LineListOutputParser({
+      key: 'links',
+    });
+
+    const questionOutputParser = new LineOutputParser({
+      key: 'question',
+    });
+
+    const links = await linksOutputParser.parse(messageStr);
+    let question = this.config.summarizer
+      ? await questionOutputParser.parse(messageStr)
+      : messageStr;
+
+    if (question === 'not_needed') {
+      return { query: '', docs: [] };
+    }
+
+    if (links.length > 0) {
+      if (question.length === 0) {
+        question = 'summarize';
+      }
+
+      let docs: Document[] = [];
+
+      const linkDocs = await getDocumentsFromLinks({ links });
+
+      const docGroups: Document[] = [];
+
+      linkDocs.map((doc) => {
+        const URLDocExists = docGroups.find(
+          (d) =>
+            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
+        );
+
+        if (!URLDocExists) {
+          docGroups.push({
+            ...doc,
+            metadata: {
+              ...doc.metadata,
+              totalDocs: 1,
+            },
+          });
        }

-        if (links.length > 0) {
-          if (question.length === 0) {
-            question = 'summarize';
-          }
+        const docIndex = docGroups.findIndex(
+          (d) =>
+            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
+        );

-          let docs: Document[] = [];
-
-          const linkDocs = await getDocumentsFromLinks({ links });
-
-          const docGroups: Document[] = [];
-
-          linkDocs.map((doc) => {
-            const URLDocExists = docGroups.find(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (!URLDocExists) {
-              docGroups.push({
-                ...doc,
-                metadata: {
-                  ...doc.metadata,
-                  totalDocs: 1,
-                },
-              });
-            }
-
-            const docIndex = docGroups.findIndex(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (docIndex !== -1) {
-              docGroups[docIndex].pageContent =
-                docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
-              docGroups[docIndex].metadata.totalDocs += 1;
-            }
-          });
-
-          await Promise.all(
-            docGroups.map(async (doc) => {
-              const res = await llm.invoke(`
-            You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the 
-            text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
-            If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
-            
-            - **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
-            - **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
-            - **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
-
-            The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
-
-            <example>
-            1. \`<text>
-            Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. 
-            It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications 
-            by using containers.
-            </text>
-
-            <query>
-            What is Docker and how does it work?
-            </query>
-
-            Response:
-            Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application 
-            deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in 
-            any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
-            \`
-            2. \`<text>
-            The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
-            relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
-            on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
-            Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
-            General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
-            realm, including astronomy.
-            </text>
-
-            <query>
-            summarize
-            </query>
-
-            Response:
-            The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
-            relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
-            relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
-            1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
-            \`
-            </example>
-
-            Everything below is the actual data you will be working with. Good luck!
-
-            <query>
-            ${question}
-            </query>
-
-            <text>
-            ${doc.pageContent}
-            </text>
-
-            Make sure to answer the query in the summary.
-          `);
-
-              const document = new Document({
-                pageContent: res.content as string,
-                metadata: {
-                  title: doc.metadata.title,
-                  url: doc.metadata.url,
-                },
-              });
-
-              docs.push(document);
-            }),
-          );
-
-          return { query: question, docs: docs };
-        } else {
-          question = question.replace(/<think>.*?<\/think>/g, '');
-
-          const res = await searchSearxng(question, {
-            language: 'en',
-            engines: this.config.activeEngines,
-          });
-
-          const documents = res.results.map(
-            (result) =>
-              new Document({
-                pageContent:
-                  result.content ||
-                  (this.config.activeEngines.includes('youtube')
-                    ? result.title
-                    : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
-                metadata: {
-                  title: result.title,
-                  url: result.url,
-                  ...(result.img_src && { img_src: result.img_src }),
-                },
-              }),
-          );
-
-          return { query: question, docs: documents };
+        if (docIndex !== -1) {
+          docGroups[docIndex].pageContent =
+            docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
+          docGroups[docIndex].metadata.totalDocs += 1;
        }
-      }),
-    ]);
+      });
+
+      await Promise.all(
+        docGroups.map(async (doc) => {
+          const res = await llm.invoke(`
+        You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the 
+        text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
+        If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
+        
+        - **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
+        - **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
+        - **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
+
+        The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
+
+        <example>
+        1. \`<text>
+        Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. 
+        It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications 
+        by using containers.
+        </text>
+
+        <query>
+        What is Docker and how does it work?
+        </query>
+
+        Response:
+        Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application 
+        deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in 
+        any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
+        \`
+        2. \`<text>
+        The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
+        relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
+        on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
+        Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
+        General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
+        realm, including astronomy.
+        </text>
+
+        <query>
+        summarize
+        </query>
+
+        Response:
+        The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
+        relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
+        relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
+        1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
+        \`
+        </example>
+
+        Everything below is the actual data you will be working with. Good luck!
+
+        <query>
+        ${question}
+        </query>
+
+        <text>
+        ${doc.pageContent}
+        </text>
+
+        Make sure to answer the query in the summary.
+      `);
+
+          const document = new Document({
+            pageContent: res.content as string,
+            metadata: {
+              title: doc.metadata.title,
+              url: doc.metadata.url,
+            },
+          });
+
+          docs.push(document);
+        }),
+      );
+
+      return { query: question, docs: docs };
+    } else {
+      question = question.replace(/<think>.*?<\/think>/g, '');
+
+      const res = await searchSearxng(question, {
+        language: 'en',
+        engines: this.config.activeEngines,
+      });
+
+      const documents = res.results.map(
+        (result) =>
+          new Document({
+            pageContent:
+              result.content ||
+              (this.config.activeEngines.includes('youtube')
+                ? result.title
+                : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
+            metadata: {
+              title: result.title,
+              url: result.url,
+              ...(result.img_src && { img_src: result.img_src }),
+            },
+          }),
+      );
+
+      return { query: question, docs: documents };
+    }
  }

-  private async createAnsweringChain(
+  private async performDeepResearch(
+    llm: BaseChatModel,
+    input: SearchInput,
+    emitter: EventEmitter,
+  ) {
+    (llm as unknown as ChatOpenAI).temperature = 0;
+
+    const queryGenPrompt = PromptTemplate.fromTemplate(
+      this.config.queryGeneratorPrompt,
+    );
+
+    const formattedChatPrompt = await queryGenPrompt.invoke({
+      chat_history: formatChatHistoryAsString(input.chat_history),
+      query: input.query,
+    });
+
+    let i = 0;
+    let currentQuery = await this.strParser.invoke(
+      await llm.invoke(formattedChatPrompt),
+    );
+    const originalQuery = currentQuery;
+    const pastQueries: string[] = [];
+    const results: SearxngSearchResult[] = [];
+
+    while (i < 10) {
+      const res = await searchSearxng(currentQuery, {
+        language: 'en',
+        engines: this.config.activeEngines,
+      });
+
+      results.push(...res.results);
+
+      const reflectorPrompt = PromptTemplate.fromTemplate(`
+          You are an LLM that is tasked with reflecting on the results of a search query.
+
+          ## Goal
+          You will be given question of the user, a list of search results collected from the web to answer that question along with past queries made to collect those results. You have to analyze the results based on user's question and do the following:
+          
+          1. Identify unexplored areas or areas with less detailed information in the results and generate a new query that focuses on those areas. The new queries should be more specific and a similar query shall not exist in past queries which will be provided to you. Make sure to include keywords that you're looking for because the new query will be used to search the web for information on that topic. Make sure the query contains only 1 question and is not too long to ensure it is Search Engine friendly.
+          2. You'll have to generate a description explaining what you are doing for example "I am looking for more information about X" or "Understanding how X works" etc. The description should be short and concise.
+          
+          ## Output format
+
+          You need to output in XML format and do not generate any other text. ake sure to not include any other text in the output or start a conversation in the output. The output should be in the following format:
+
+          <query>(query)</query>
+          <description>(description)</description>
+
+          ## Example
+          Say the user asked "What is Llama 4 by Meta?" and let search results contain information about Llama 4 being an LLM and very little information about its features. You can output:
+
+          <query>Llama 4 features</query> // Generate queries that capture keywords for SEO and not making words like "How", "What", "Why" etc.
+          <description>Looking for new features in Llama 4</description>
+
+          or something like
+
+          <query>How is Llama 4 better than its previous generation models</query>
+          <description>Understanding the difference between Llama 4 and previous generation models.</description>
+          
+          ## BELOW IS THE ACTUAL DATA YOU WILL BE WORKING WITH. IT IS NOT A PART OF EXAMPLES. YOU'LL HAVE TO GENERATE YOUR ANSWER BASED ON THIS DATA.
+          <user_question>\n{question}\n</user_question>
+          <search_results>\n{search_results}\n</search_results>
+          <past_queries>\n{past_queries}\n</past_queries>
+
+          Response:
+      `);
+
+      const formattedReflectorPrompt = await reflectorPrompt.invoke({
+        question: originalQuery,
+        search_results: results
+          .map(
+            (result) => `<result>${result.title} - ${result.content}</result>`,
+          )
+          .join('\n'),
+        past_queries: pastQueries.map((q) => `<query>${q}</query>`).join('\n'),
+      });
+
+      const feedback = await this.strParser.invoke(
+        await llm.invoke(formattedReflectorPrompt),
+      );
+
+      console.log(`Feedback: ${feedback}`);
+
+      const queryOutputParser = new LineOutputParser({
+        key: 'query',
+      });
+
+      const descriptionOutputParser = new LineOutputParser({
+        key: 'description',
+      });
+
+      currentQuery = await queryOutputParser.parse(feedback);
+      const description = await descriptionOutputParser.parse(feedback);
+      console.log(`Query: ${currentQuery}`);
+      console.log(`Description: ${description}`);
+
+      pastQueries.push(currentQuery);
+      ++i;
+    }
+
+    const uniqueResults: SearxngSearchResult[] = [];
+
+    results.forEach((res) => {
+      const exists = uniqueResults.find((r) => r.url === res.url);
+
+      if (!exists) {
+        uniqueResults.push(res);
+      } else {
+        exists.content += `\n\n` + res.content;
+      }
+    });
+
+    const documents = uniqueResults /* .slice(0, 50) */
+      .map(
+        (r) =>
+          new Document({
+            pageContent: r.content || '',
+            metadata: {
+              title: r.title,
+              url: r.url,
+              ...(r.img_src && { img_src: r.img_src }),
+            },
+          }),
+      );
+
+    return documents;
+  }
+
+  private async streamAnswer(
    llm: BaseChatModel,
    fileIds: string[],
    embeddings: Embeddings,
    optimizationMode: 'speed' | 'balanced' | 'quality',
    systemInstructions: string,
+    input: SearchInput,
+    emitter: EventEmitter,
  ) {
-    return RunnableSequence.from([
-      RunnableMap.from({
-        systemInstructions: () => systemInstructions,
-        query: (input: BasicChainInput) => input.query,
-        chat_history: (input: BasicChainInput) => input.chat_history,
-        date: () => new Date().toISOString(),
-        context: RunnableLambda.from(async (input: BasicChainInput) => {
-          const processedHistory = formatChatHistoryAsString(
-            input.chat_history,
-          );
+    const chatPrompt = ChatPromptTemplate.fromMessages([
+      ['system', this.config.responsePrompt],
+      new MessagesPlaceholder('chat_history'),
+      ['user', '{query}'],
+    ]);

-          let docs: Document[] | null = null;
-          let query = input.query;
+    let context = '';

-          if (this.config.searchWeb) {
-            const searchRetrieverChain =
-              await this.createSearchRetrieverChain(llm);
+    if (optimizationMode === 'speed' || optimizationMode === 'balanced') {
+      let docs: Document[] | null = null;
+      let query = input.query;

-            const searchRetrieverResult = await searchRetrieverChain.invoke({
-              chat_history: processedHistory,
-              query,
-            });
+      if (this.config.searchWeb) {
+        const searchResults = await this.searchSources(llm, input, emitter);

-            query = searchRetrieverResult.query;
-            docs = searchRetrieverResult.docs;
-          }
+        query = searchResults.query;
+        docs = searchResults.docs;
+      }

-          const sortedDocs = await this.rerankDocs(
-            query,
-            docs ?? [],
-            fileIds,
-            embeddings,
-            optimizationMode,
-          );
+      const sortedDocs = await this.rerankDocs(
+        query,
+        docs ?? [],
+        fileIds,
+        embeddings,
+        optimizationMode,
+      );

-          return sortedDocs;
-        })
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(this.processDocs),
-      }),
-      ChatPromptTemplate.fromMessages([
-        ['system', this.config.responsePrompt],
-        new MessagesPlaceholder('chat_history'),
-        ['user', '{query}'],
-      ]),
-      llm,
-      this.strParser,
-    ]).withConfig({
-      runName: 'FinalResponseGenerator',
+      emitter.emit(
+        'data',
+        JSON.stringify({ type: 'sources', data: sortedDocs }),
+      );
+
+      context = this.processDocs(sortedDocs);
+    } else if (optimizationMode === 'quality') {
+      let docs: Document[] = [];
+
+      docs = await this.performDeepResearch(llm, input, emitter);
+
+      emitter.emit('data', JSON.stringify({ type: 'sources', data: docs }));
+
+      context = this.processDocs(docs);
+    }
+
+    const formattedChatPrompt = await chatPrompt.invoke({
+      query: input.query,
+      chat_history: input.chat_history,
+      date: new Date().toISOString(),
+      context: context,
+      systemInstructions: systemInstructions,
    });
+
+    const llmRes = await llm.stream(formattedChatPrompt);
+
+    for await (const data of llmRes) {
+      const messageStr = await this.strParser.invoke(data);
+
+      emitter.emit(
+        'data',
+        JSON.stringify({ type: 'response', data: messageStr }),
+      );
+    }
+
+    emitter.emit('end');
  }

  private async rerankDocs(
@@ -426,88 +570,13 @@ class MetaSearchAgent implements MetaSearchAgentType {
    return docs
      .map(
        (_, index) =>
-          `${index + 1}. ${docs[index].metadata.title} ${docs[index].pageContent}`,
+          `${index + 1}. ${docs[index].metadata.title} ${
+            docs[index].pageContent
+          }`,
      )
      .join('\n');
  }

-  private async handleStream(
-    stream: AsyncGenerator<StreamEvent, any, any>,
-    emitter: eventEmitter,
-    llm: BaseChatModel,
-  ) {
-    for await (const event of stream) {
-      if (
-        event.event === 'on_chain_end' &&
-        event.name === 'FinalSourceRetriever'
-      ) {
-        emitter.emit(
-          'data',
-          JSON.stringify({ type: 'sources', data: event.data.output }),
-        );
-      }
-      if (
-        event.event === 'on_chain_stream' &&
-        event.name === 'FinalResponseGenerator'
-      ) {
-        emitter.emit(
-          'data',
-          JSON.stringify({ type: 'response', data: event.data.chunk }),
-        );
-      }
-      if (
-        event.event === 'on_chain_end' &&
-        event.name === 'FinalResponseGenerator'
-      ) {
-        // Get model name safely with better detection
-        let modelName = 'Unknown';
-        try {
-          // @ts-ignore - Different LLM implementations have different properties
-          if (llm.modelName) {
-            // @ts-ignore
-            modelName = llm.modelName;
-            // @ts-ignore
-          } else if (llm._llm && llm._llm.modelName) {
-            // @ts-ignore
-            modelName = llm._llm.modelName;
-            // @ts-ignore
-          } else if (llm.model && llm.model.modelName) {
-            // @ts-ignore
-            modelName = llm.model.modelName;
-          } else if ('model' in llm) {
-            // @ts-ignore
-            const model = llm.model;
-            if (typeof model === 'string') {
-              modelName = model;
-              // @ts-ignore
-            } else if (model && model.modelName) {
-              // @ts-ignore
-              modelName = model.modelName;
-            }
-          } else if (llm.constructor && llm.constructor.name) {
-            // Last resort: use the class name
-            modelName = llm.constructor.name;
-          }
-        } catch (e) {
-          console.error('Failed to get model name:', e);
-        }
-
-        // Send model info before ending
-        emitter.emit(
-          'stats',
-          JSON.stringify({
-            type: 'modelStats',
-            data: {
-              modelName,
-            },
-          }),
-        );
-
-        emitter.emit('end');
-      }
-    }
-  }
-
  async searchAndAnswer(
    message: string,
    history: BaseMessage[],
@@ -519,26 +588,19 @@ class MetaSearchAgent implements MetaSearchAgentType {
  ) {
    const emitter = new eventEmitter();

-    const answeringChain = await this.createAnsweringChain(
+    this.streamAnswer(
      llm,
      fileIds,
      embeddings,
      optimizationMode,
      systemInstructions,
-    );
-
-    const stream = answeringChain.streamEvents(
      {
        chat_history: history,
        query: message,
      },
-      {
-        version: 'v1',
-      },
+      emitter,
    );

-    this.handleStream(stream, emitter, llm);
-
    return emitter;
  }
 }
--- a/src/lib/searxng.ts
+++ b/src/lib/searxng.ts
@@ -8,7 +8,7 @@ interface SearxngSearchOptions {
  pageno?: number;
 }

-interface SearxngSearchResult {
+export interface SearxngSearchResult {
  title: string;
  url: string;
  img_src?: string;
--- a/src/lib/utils/documents.ts
+++ b/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({
--- a/yarn.lock
+++ b/yarn.lock
Author	SHA1	Message	Date
ItzCrazyKns	83f1c6ce12	Merge pull request #736 from ItzCrazyKns/master Merge master into feat/deep-research	2025-04-08 12:28:46 +05:30
ItzCrazyKns	fd6c58734d	feat(metaSearchAgent): add quality optimization mode	2025-04-08 12:27:48 +05:30
ItzCrazyKns	114a7aa09d	Merge pull request #728 from ItzCrazyKns/master-deep-research Merge master into feat/deep-research	2025-04-07 10:21:34 +05:30
ItzCrazyKns	d0ba8c9038	Merge branch 'feat/deep-research' into master-deep-research	2025-04-07 10:21:22 +05:30
ItzCrazyKns	934fb0a23b	Update metaSearchAgent.ts	2025-04-07 10:18:11 +05:30
ItzCrazyKns	8ecf3b4e99	feat(chat-window): update message handling	2025-04-02 13:02:45 +05:30
ItzCrazyKns	b5ee8386e7	Merge pull request #714 from ItzCrazyKns/master Merge master into feat/deep-research	2025-04-01 14:16:45 +05:30
ItzCrazyKns	0fcd598ff7	feat(metaSearchAgent): eliminate runnables	2025-03-24 17:27:54 +05:30