Merge 8241c87784 into 68e151b2bd

Adds auto scrolling.
Adds syntax highlighting to code blocks.

.github/workflows/docker-build.yaml

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

README.md

@@ -1,21 +1,5 @@
 # 🚀 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?)
@@ -57,9 +41,10 @@ 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 6 focus modes:
+- **Focus Modes:** Special modes to better answer specific types of questions. Perplexica currently has 7 focus modes:
   - **All Mode:** Searches the entire web to find the best results.
-  - **Writing Assistant Mode:** Helpful for writing tasks that do not require searching the web.
+  - **Local Research Mode:** Research and interact with local files with citations.
+  - **Chat Mode:** Have a truly creative conversation without web search.
   - **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.
@@ -153,12 +138,13 @@ For more details, check out the full documentation [here](https://github.com/Itz
 
 ## Expose Perplexica to network
 
-You can access Perplexica over your home network by following our networking guide [here](https://github.com/ItzCrazyKns/Perplexica/blob/master/docs/installation/NETWORKING.md).
+Perplexica runs on Next.js and handles all API requests. It works right away on the same network and stays accessible even with port forwarding.
 
 ## One-Click Deployment
 
 [![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
 

app.dockerfile

@@ -1,4 +1,4 @@
-FROM node:20.18.0-alpine AS builder
+FROM node:20.18.0-slim AS builder
 
 WORKDIR /home/perplexica
 
@@ -12,7 +12,7 @@ COPY public ./public
 RUN mkdir -p /home/perplexica/data
 RUN yarn build
 
-FROM node:20.18.0-alpine
+FROM node:20.18.0-slim
 
 WORKDIR /home/perplexica
 

docs/API/SEARCH.md

@@ -32,7 +32,9 @@ The API accepts a JSON object in the request body, where you define the focus mo
   "history": [
     ["human", "Hi, how are you?"],
     ["assistant", "I am doing well, how can I help you today?"]
-  ]
+  ],
+  "systemInstructions": "Focus on providing technical details about Perplexica's architecture.",
+  "stream": false
 }
 ```
 
@@ -53,7 +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`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
+  - `webSearch`, `academicSearch`, `localResearch`, `chat`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
 
 - **`optimizationMode`** (string, optional): Specifies the optimization mode to control the balance between performance and quality. Available modes:
 
@@ -62,6 +64,8 @@ The API accepts a JSON object in the request body, where you define the focus mo
 
 - **`query`** (string, required): The search query or question.
 
+- **`systemInstructions`** (string, optional): Custom instructions provided by the user to guide the AI's response. These instructions are treated as user preferences and have lower priority than the system's core instructions. For example, you can specify a particular writing style, format, or focus area.
+
 - **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
 
   ```json
@@ -71,11 +75,13 @@ The API accepts a JSON object in the request body, where you define the focus mo
   ]
   ```
 
+- **`stream`** (boolean, optional): When set to `true`, enables streaming responses. Default is `false`.
+
 ### Response
 
 The response from the API includes both the final message and the sources used to generate that message.
 
-#### Example Response
+#### Standard Response (stream: false)
 
 ```json
 {
@@ -100,6 +106,28 @@ The response from the API includes both the final message and the sources used t
 }
 ```
 
+#### Streaming Response (stream: true)
+
+When streaming is enabled, the API returns a stream of newline-delimited JSON objects. Each line contains a complete, valid JSON object. The response has Content-Type: application/json.
+
+Example of streamed response objects:
+
+```
+{"type":"init","data":"Stream connected"}
+{"type":"sources","data":[{"pageContent":"...","metadata":{"title":"...","url":"..."}},...]}
+{"type":"response","data":"Perplexica is an "}
+{"type":"response","data":"innovative, open-source "}
+{"type":"response","data":"AI-powered search engine..."}
+{"type":"done"}
+```
+
+Clients should process each line as a separate JSON object. The different message types include:
+
+- **`init`**: Initial connection message
+- **`sources`**: All sources used for the response
+- **`response`**: Chunks of the generated answer text
+- **`done`**: Indicates the stream is complete
+
 ### Fields in the Response
 
 - **`message`** (string): The search result, generated based on the query and focus mode.

package.json

@@ -1,10 +1,10 @@
 {
   "name": "perplexica-frontend",
-  "version": "1.10.0",
+  "version": "1.10.2",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
-    "dev": "next dev",
+    "dev": "next dev --turbopack",
     "build": "npm run db:push && next build",
     "start": "next start",
     "lint": "next lint",
@@ -15,11 +15,15 @@
     "@headlessui/react": "^2.2.0",
     "@iarna/toml": "^2.2.5",
     "@icons-pack/react-simple-icons": "^12.3.0",
+    "@langchain/anthropic": "^0.3.15",
     "@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",
@@ -36,6 +40,7 @@
     "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",

sample.config.toml

@@ -22,5 +22,11 @@ MODEL_NAME = ""
 [MODELS.OLLAMA]
 API_URL = "" # Ollama API URL - http://host.docker.internal:11434
 
+[MODELS.DEEPSEEK]
+API_KEY = ""
+
+[MODELS.LM_STUDIO]
+API_URL = "" # LM Studio API URL - http://host.docker.internal:1234
+
 [API_ENDPOINTS]
 SEARXNG = "" # SearxNG API URL - http://localhost:32768

src/app/api/chat/route.ts

@@ -20,6 +20,7 @@ import {
   getCustomOpenaiApiUrl,
   getCustomOpenaiModelName,
 } from '@/lib/config';
+import { ChatOllama } from '@langchain/ollama';
 import { searchHandlers } from '@/lib/search';
 
 export const runtime = 'nodejs';
@@ -34,6 +35,7 @@ type Message = {
 type ChatModel = {
   provider: string;
   name: string;
+  ollamaContextWindow?: number;
 };
 
 type EmbeddingModel = {
@@ -49,6 +51,12 @@ type Body = {
   files: Array<string>;
   chatModel: ChatModel;
   embeddingModel: EmbeddingModel;
+  systemInstructions: string;
+};
+
+type ModelStats = {
+  modelName: string;
+  responseTime?: number;
 };
 
 const handleEmitterEvents = async (
@@ -57,6 +65,7 @@ const handleEmitterEvents = async (
   encoder: TextEncoder,
   aiMessageId: string,
   chatId: string,
+  startTime: number,
 ) => {
   let recievedMessage = '';
   let sources: any[] = [];
@@ -89,12 +98,32 @@ 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',
       ),
     );
@@ -109,6 +138,7 @@ const handleEmitterEvents = async (
         metadata: JSON.stringify({
           createdAt: new Date(),
           ...(sources && sources.length > 0 && { sources }),
+          modelStats: modelStats,
         }),
       })
       .execute();
@@ -182,6 +212,7 @@ const handleHistorySave = async (
 
 export const POST = async (req: Request) => {
   try {
+    const startTime = Date.now();
     const body = (await req.json()) as Body;
     const { message } = body;
 
@@ -231,6 +262,11 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {
@@ -278,13 +314,21 @@ export const POST = async (req: Request) => {
       embedding,
       body.optimizationMode,
       body.files,
+      body.systemInstructions,
     );
 
     const responseStream = new TransformStream();
     const writer = responseStream.writable.getWriter();
     const encoder = new TextEncoder();
 
-    handleEmitterEvents(stream, writer, encoder, aiMessageId, message.chatId);
+    handleEmitterEvents(
+      stream,
+      writer,
+      encoder,
+      aiMessageId,
+      message.chatId,
+      startTime,
+    );
     handleHistorySave(message, humanMessageId, body.focusMode, body.files);
 
     return new Response(responseStream.readable, {
@@ -295,9 +339,9 @@ export const POST = async (req: Request) => {
       },
     });
   } catch (err) {
-    console.error('An error ocurred while processing chat request:', err);
+    console.error('An error occurred while processing chat request:', err);
     return Response.json(
-      { message: 'An error ocurred while processing chat request' },
+      { message: 'An error occurred while processing chat request' },
       { status: 500 },
     );
   }

src/app/api/config/route.ts

@@ -7,6 +7,8 @@ import {
   getGroqApiKey,
   getOllamaApiEndpoint,
   getOpenaiApiKey,
+  getDeepseekApiKey,
+  getLMStudioApiEndpoint,
   updateConfig,
 } from '@/lib/config';
 import {
@@ -50,18 +52,20 @@ export const GET = async (req: Request) => {
 
     config['openaiApiKey'] = getOpenaiApiKey();
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
+    config['deepseekApiKey'] = getDeepseekApiKey();
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
     config['customOpenaiModelName'] = getCustomOpenaiModelName();
 
     return Response.json({ ...config }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while getting config:', err);
+    console.error('An error occurred while getting config:', err);
     return Response.json(
-      { message: 'An error ocurred while getting config' },
+      { message: 'An error occurred while getting config' },
       { status: 500 },
     );
   }
@@ -88,6 +92,12 @@ export const POST = async (req: Request) => {
         OLLAMA: {
           API_URL: config.ollamaApiUrl,
         },
+        DEEPSEEK: {
+          API_KEY: config.deepseekApiKey,
+        },
+        LM_STUDIO: {
+          API_URL: config.lmStudioApiUrl,
+        },
         CUSTOM_OPENAI: {
           API_URL: config.customOpenaiApiUrl,
           API_KEY: config.customOpenaiApiKey,
@@ -100,9 +110,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ message: 'Config updated' }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while updating config:', err);
+    console.error('An error occurred while updating config:', err);
     return Response.json(
-      { message: 'An error ocurred while updating config' },
+      { message: 'An error occurred while updating config' },
       { status: 500 },
     );
   }

src/app/api/discover/route.ts

@@ -48,7 +48,7 @@ export const GET = async (req: Request) => {
       },
     );
   } catch (err) {
-    console.error(`An error ocurred in discover route: ${err}`);
+    console.error(`An error occurred in discover route: ${err}`);
     return Response.json(
       {
         message: 'An error has occurred',

src/app/api/images/route.ts

@@ -7,11 +7,13 @@ import {
 import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { ChatOllama } from '@langchain/ollama';
 import { ChatOpenAI } from '@langchain/openai';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface ImageSearchBody {
@@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {
@@ -74,9 +80,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ images }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching images: ${err}`);
+    console.error(`An error occurred while searching images: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching images' },
+      { message: 'An error occurred while searching images' },
       { status: 500 },
     );
   }

src/app/api/models/route.ts

@@ -34,7 +34,7 @@ export const GET = async (req: Request) => {
       },
     );
   } catch (err) {
-    console.error('An error ocurred while fetching models', err);
+    console.error('An error occurred while fetching models', err);
     return Response.json(
       {
         message: 'An error has occurred.',

src/app/api/search/route.ts

@@ -13,12 +13,14 @@ import {
   getCustomOpenaiModelName,
 } from '@/lib/config';
 import { searchHandlers } from '@/lib/search';
+import { ChatOllama } from '@langchain/ollama';
 
 interface chatModel {
   provider: string;
   name: string;
   customOpenAIKey?: string;
   customOpenAIBaseURL?: string;
+  ollamaContextWindow?: number;
 }
 
 interface embeddingModel {
@@ -33,6 +35,8 @@ interface ChatRequestBody {
   embeddingModel?: embeddingModel;
   query: string;
   history: Array<[string, string]>;
+  stream?: boolean;
+  systemInstructions?: string;
 }
 
 export const POST = async (req: Request) => {
@@ -48,6 +52,7 @@ export const POST = async (req: Request) => {
 
     body.history = body.history || [];
     body.optimizationMode = body.optimizationMode || 'balanced';
+    body.stream = body.stream || false;
 
     const history: BaseMessage[] = body.history.map((msg) => {
       return msg[0] === 'human'
@@ -94,6 +99,10 @@ export const POST = async (req: Request) => {
         .model as unknown as BaseChatModel | undefined;
     }
 
+    if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+      llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+    }
+
     if (
       embeddingModelProviders[embeddingModelProvider] &&
       embeddingModelProviders[embeddingModelProvider][embeddingModel]
@@ -123,8 +132,10 @@ export const POST = async (req: Request) => {
       embeddings,
       body.optimizationMode,
       [],
+      body.systemInstructions || '',
     );
 
+    if (!body.stream) {
       return new Promise(
         (
           resolve: (value: Response) => void,
@@ -133,7 +144,7 @@ export const POST = async (req: Request) => {
           let message = '';
           let sources: any[] = [];
 
-        emitter.on('data', (data) => {
+          emitter.on('data', (data: string) => {
             try {
               const parsedData = JSON.parse(data);
               if (parsedData.type === 'response') {
@@ -143,7 +154,10 @@ export const POST = async (req: Request) => {
               }
             } catch (error) {
               reject(
-              Response.json({ message: 'Error parsing data' }, { status: 500 }),
+                Response.json(
+                  { message: 'Error parsing data' },
+                  { status: 500 },
+                ),
               );
             }
           });
@@ -152,13 +166,106 @@ export const POST = async (req: Request) => {
             resolve(Response.json({ message, sources }, { status: 200 }));
           });
 
-        emitter.on('error', (error) => {
+          emitter.on('error', (error: any) => {
             reject(
-            Response.json({ message: 'Search error', error }, { status: 500 }),
+              Response.json(
+                { message: 'Search error', error },
+                { status: 500 },
+              ),
             );
           });
         },
       );
+    }
+
+    const encoder = new TextEncoder();
+
+    const abortController = new AbortController();
+    const { signal } = abortController;
+
+    const stream = new ReadableStream({
+      start(controller) {
+        let sources: any[] = [];
+
+        controller.enqueue(
+          encoder.encode(
+            JSON.stringify({
+              type: 'init',
+              data: 'Stream connected',
+            }) + '\n',
+          ),
+        );
+
+        signal.addEventListener('abort', () => {
+          emitter.removeAllListeners();
+
+          try {
+            controller.close();
+          } catch (error) {}
+        });
+
+        emitter.on('data', (data: string) => {
+          if (signal.aborted) return;
+
+          try {
+            const parsedData = JSON.parse(data);
+
+            if (parsedData.type === 'response') {
+              controller.enqueue(
+                encoder.encode(
+                  JSON.stringify({
+                    type: 'response',
+                    data: parsedData.data,
+                  }) + '\n',
+                ),
+              );
+            } else if (parsedData.type === 'sources') {
+              sources = parsedData.data;
+              controller.enqueue(
+                encoder.encode(
+                  JSON.stringify({
+                    type: 'sources',
+                    data: sources,
+                  }) + '\n',
+                ),
+              );
+            }
+          } catch (error) {
+            controller.error(error);
+          }
+        });
+
+        emitter.on('end', () => {
+          if (signal.aborted) return;
+
+          controller.enqueue(
+            encoder.encode(
+              JSON.stringify({
+                type: 'done',
+              }) + '\n',
+            ),
+          );
+          controller.close();
+        });
+
+        emitter.on('error', (error: any) => {
+          if (signal.aborted) return;
+
+          controller.error(error);
+        });
+      },
+      cancel() {
+        abortController.abort();
+      },
+    });
+
+    return new Response(stream, {
+      headers: {
+        'Content-Type': 'text/event-stream',
+        'Cache-Control': 'no-cache, no-transform',
+        Connection: 'keep-alive',
+      },
+    });
   } catch (err: any) {
     console.error(`Error in getting search results: ${err.message}`);
     return Response.json(

src/app/api/suggestions/route.ts

@@ -8,10 +8,12 @@ import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
 import { ChatOpenAI } from '@langchain/openai';
+import { ChatOllama } from '@langchain/ollama';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface SuggestionsGenerationBody {
@@ -57,6 +59,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {
@@ -72,9 +78,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ suggestions }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while generating suggestions: ${err}`);
+    console.error(`An error occurred while generating suggestions: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while generating suggestions' },
+      { message: 'An error occurred while generating suggestions' },
       { status: 500 },
     );
   }

src/app/api/videos/route.ts

@@ -7,11 +7,13 @@ import {
 import { getAvailableChatModelProviders } from '@/lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { ChatOllama } from '@langchain/ollama';
 import { ChatOpenAI } from '@langchain/openai';
 
 interface ChatModel {
   provider: string;
   model: string;
+  ollamaContextWindow?: number;
 }
 
 interface VideoSearchBody {
@@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
       }) as unknown as BaseChatModel;
     } else if (chatModelProvider && chatModel) {
       llm = chatModel.model;
+      // Set context window size for Ollama models
+      if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
+        llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
+      }
     }
 
     if (!llm) {
@@ -74,9 +80,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ videos }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching videos: ${err}`);
+    console.error(`An error occurred while searching videos: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching videos' },
+      { message: 'An error occurred while searching videos' },
       { status: 500 },
     );
   }

src/app/settings/page.tsx

@@ -5,8 +5,9 @@ import { useEffect, useState } from 'react';
 import { cn } from '@/lib/utils';
 import { Switch } from '@headlessui/react';
 import ThemeSwitcher from '@/components/theme/Switcher';
-import { ImagesIcon, VideoIcon } from 'lucide-react';
+import { ImagesIcon, VideoIcon, Layers3 } from 'lucide-react';
 import Link from 'next/link';
+import { PROVIDER_METADATA } from '@/lib/providers';
 
 interface SettingsType {
   chatModelProviders: {
@@ -20,9 +21,12 @@ interface SettingsType {
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
+  lmStudioApiUrl: string;
+  deepseekApiKey: string;
   customOpenaiApiKey: string;
   customOpenaiApiUrl: string;
   customOpenaiModelName: string;
+  ollamaContextWindow: number;
 }
 
 interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
@@ -54,6 +58,38 @@ const Input = ({ className, isSaving, onSave, ...restProps }: InputProps) => {
   );
 };
 
+interface TextareaProps extends React.InputHTMLAttributes<HTMLTextAreaElement> {
+  isSaving?: boolean;
+  onSave?: (value: string) => void;
+}
+
+const Textarea = ({
+  className,
+  isSaving,
+  onSave,
+  ...restProps
+}: TextareaProps) => {
+  return (
+    <div className="relative">
+      <textarea
+        placeholder="Any special instructions for the LLM"
+        className="placeholder:text-sm text-sm w-full flex items-center justify-between p-3 bg-light-secondary dark:bg-dark-secondary rounded-lg hover:bg-light-200 dark:hover:bg-dark-200 transition-colors"
+        rows={4}
+        onBlur={(e) => onSave?.(e.target.value)}
+        {...restProps}
+      />
+      {isSaving && (
+        <div className="absolute right-3 top-3">
+          <Loader2
+            size={16}
+            className="animate-spin text-black/70 dark:text-white/70"
+          />
+        </div>
+      )}
+    </div>
+  );
+};
+
 const Select = ({
   className,
   options,
@@ -111,7 +147,14 @@ 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 () => {
@@ -123,6 +166,7 @@ const Page = () => {
       });
 
       const data = (await res.json()) as SettingsType;
+
       setConfig(data);
 
       const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
@@ -171,6 +215,18 @@ 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')!);
 
       setIsLoading(false);
     };
@@ -320,6 +376,8 @@ 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') {
@@ -328,6 +386,10 @@ const Page = () => {
         localStorage.setItem('embeddingModelProvider', value);
       } else if (key === 'embeddingModel') {
         localStorage.setItem('embeddingModel', value);
+      } else if (key === 'ollamaContextWindow') {
+        localStorage.setItem('ollamaContextWindow', value.toString());
+      } else if (key === 'systemInstructions') {
+        localStorage.setItem('systemInstructions', value);
       }
     } catch (err) {
       console.error('Failed to save:', err);
@@ -470,6 +532,60 @@ 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>
+
+            <SettingsSection title="System Instructions">
+              <div className="flex flex-col space-y-4">
+                <Textarea
+                  value={systemInstructions}
+                  isSaving={savingStates['systemInstructions']}
+                  onChange={(e) => {
+                    setSystemInstructions(e.target.value);
+                  }}
+                  onSave={(value) => saveConfig('systemInstructions', value)}
+                />
               </div>
             </SettingsSection>
 
@@ -497,6 +613,7 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
                               provider.slice(1),
                         }),
@@ -545,6 +662,78 @@ const Page = () => {
                                 ];
                           })()}
                         />
+                        {selectedChatModelProvider === 'ollama' && (
+                          <div className="flex flex-col space-y-1">
+                            <p className="text-black/70 dark:text-white/70 text-sm">
+                              Chat Context Window Size
+                            </p>
+                            <Select
+                              value={
+                                isCustomContextWindow
+                                  ? 'custom'
+                                  : contextWindowSize.toString()
+                              }
+                              onChange={(e) => {
+                                const value = e.target.value;
+                                if (value === 'custom') {
+                                  setIsCustomContextWindow(true);
+                                } else {
+                                  setIsCustomContextWindow(false);
+                                  const numValue = parseInt(value);
+                                  setContextWindowSize(numValue);
+                                  setConfig((prev) => ({
+                                    ...prev!,
+                                    ollamaContextWindow: numValue,
+                                  }));
+                                  saveConfig('ollamaContextWindow', numValue);
+                                }
+                              }}
+                              options={[
+                                ...predefinedContextSizes.map((size) => ({
+                                  value: size.toString(),
+                                  label: `${size.toLocaleString()} tokens`,
+                                })),
+                                { value: 'custom', label: 'Custom...' },
+                              ]}
+                            />
+                            {isCustomContextWindow && (
+                              <div className="mt-2">
+                                <Input
+                                  type="number"
+                                  min={512}
+                                  value={contextWindowSize}
+                                  placeholder="Custom context window size (minimum 512)"
+                                  isSaving={savingStates['ollamaContextWindow']}
+                                  onChange={(e) => {
+                                    // Allow any value to be typed
+                                    const value =
+                                      parseInt(e.target.value) ||
+                                      contextWindowSize;
+                                    setContextWindowSize(value);
+                                  }}
+                                  onSave={(value) => {
+                                    // Validate only when saving
+                                    const numValue = Math.max(
+                                      512,
+                                      parseInt(value) || 2048,
+                                    );
+                                    setContextWindowSize(numValue);
+                                    setConfig((prev) => ({
+                                      ...prev!,
+                                      ollamaContextWindow: numValue,
+                                    }));
+                                    saveConfig('ollamaContextWindow', numValue);
+                                  }}
+                                />
+                              </div>
+                            )}
+                            <p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
+                              {isCustomContextWindow
+                                ? 'Adjust the context window size for Ollama models (minimum 512 tokens)'
+                                : 'Adjust the context window size for Ollama models'}
+                            </p>
+                          </div>
+                        )}
                       </div>
                     )}
                 </div>
@@ -639,6 +828,7 @@ const Page = () => {
                         (provider) => ({
                           value: provider,
                           label:
+                            (PROVIDER_METADATA as any)[provider]?.displayName ||
                             provider.charAt(0).toUpperCase() +
                               provider.slice(1),
                         }),
@@ -788,6 +978,44 @@ const Page = () => {
                     onSave={(value) => saveConfig('geminiApiKey', value)}
                   />
                 </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Deepseek API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Deepseek API Key"
+                    value={config.deepseekApiKey}
+                    isSaving={savingStates['deepseekApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        deepseekApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('deepseekApiKey', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    LM Studio API URL
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="LM Studio API URL"
+                    value={config.lmStudioApiUrl}
+                    isSaving={savingStates['lmStudioApiUrl']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        lmStudioApiUrl: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('lmStudioApiUrl', value)}
+                  />
+                </div>
               </div>
             </SettingsSection>
           </div>

src/components/Chat.tsx

@@ -5,31 +5,107 @@ 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,
-  messageAppeared,
+  scrollTrigger,
   rewrite,
   fileIds,
   setFileIds,
   files,
   setFiles,
+  optimizationMode,
+  setOptimizationMode,
 }: {
   messages: Message[];
-  sendMessage: (message: string) => void;
+  sendMessage: (
+    message: string,
+    options?: {
+      messageId?: string;
+      rewriteIndex?: number;
+      suggestions?: string[];
+    },
+  ) => void;
   loading: boolean;
-  messageAppeared: boolean;
+  scrollTrigger: number;
   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 = () => {
@@ -47,6 +123,7 @@ const Chat = ({
     };
   });
 
+  // Scroll when user sends a message
   useEffect(() => {
     const scroll = () => {
       messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
@@ -56,11 +133,27 @@ const Chat = ({
       document.title = `${messages[0].content.substring(0, 30)} - Perplexica`;
     }
 
-    if (messages[messages.length - 1]?.role == 'user') {
+    // Always scroll when user sends a message
+    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) => {
@@ -85,13 +178,44 @@ const Chat = ({
           </Fragment>
         );
       })}
-      {loading && !messageAppeared && <MessageBoxLoading />}
+      {loading && <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}
@@ -99,6 +223,8 @@ const Chat = ({
             setFileIds={setFileIds}
             files={files}
             setFiles={setFiles}
+            optimizationMode={optimizationMode}
+            setOptimizationMode={setOptimizationMode}
           />
         </div>
       )}

src/components/ChatWindow.tsx

@@ -13,6 +13,11 @@ 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;
@@ -21,6 +26,7 @@ export type Message = {
   role: 'user' | 'assistant';
   suggestions?: string[];
   sources?: Document[];
+  modelStats?: ModelStats;
 };
 
 export interface File {
@@ -272,7 +278,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
   }, []);
 
   const [loading, setLoading] = useState(false);
-  const [messageAppeared, setMessageAppeared] = useState(false);
+  const [scrollTrigger, setScrollTrigger] = useState(0);
 
   const [chatHistory, setChatHistory] = useState<[string, string][]>([]);
   const [messages, setMessages] = useState<Message[]>([]);
@@ -287,6 +293,16 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
   const [notFound, setNotFound] = useState(false);
 
+  useEffect(() => {
+    const savedOptimizationMode = localStorage.getItem('optimizationMode');
+
+    if (savedOptimizationMode !== null) {
+      setOptimizationMode(savedOptimizationMode);
+    } else {
+      localStorage.setItem('optimizationMode', optimizationMode);
+    }
+  }, []);
+
   useEffect(() => {
     if (
       chatId &&
@@ -327,7 +343,28 @@ const ChatWindow = ({ id }: { id?: string }) => {
     }
   }, [isMessagesLoaded, isConfigReady]);
 
-  const sendMessage = async (message: string, messageId?: string) => {
+  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;
+    }
+
     if (loading) return;
     if (!isConfigReady) {
       toast.error('Cannot send message before the configuration is ready');
@@ -335,13 +372,29 @@ const ChatWindow = ({ id }: { id?: string }) => {
     }
 
     setLoading(true);
-    setMessageAppeared(false);
 
     let sources: Document[] | undefined = undefined;
     let recievedMessage = '';
     let added = false;
+    let messageChatHistory = chatHistory;
 
-    messageId = messageId ?? crypto.randomBytes(7).toString('hex');
+    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');
 
     setMessages((prevMessages) => [
       ...prevMessages,
@@ -376,8 +429,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
             },
           ]);
           added = true;
+          setScrollTrigger((prev) => prev + 1);
         }
-        setMessageAppeared(true);
       }
 
       if (data.type === 'message') {
@@ -391,6 +444,9 @@ const ChatWindow = ({ id }: { id?: string }) => {
               role: 'assistant',
               sources: sources,
               createdAt: new Date(),
+              modelStats: {
+                modelName: data.modelName,
+              },
             },
           ]);
           added = true;
@@ -407,7 +463,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
         );
 
         recievedMessage += data.data;
-        setMessageAppeared(true);
+        setScrollTrigger((prev) => prev + 1);
       }
 
       if (data.type === 'messageEnd') {
@@ -417,12 +473,28 @@ 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
@@ -440,7 +512,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
           lastMsg.role === 'assistant' &&
           lastMsg.sources &&
           lastMsg.sources.length > 0 &&
-          !lastMsg.suggestions
+          !lastMsg.suggestions &&
+          autoSuggestions !== 'false' // Default to true if not set
         ) {
           const suggestions = await getSuggestions(messagesRef.current);
           setMessages((prev) =>
@@ -455,6 +528,9 @@ const ChatWindow = ({ id }: { id?: string }) => {
       }
     };
 
+    const ollamaContextWindow =
+      localStorage.getItem('ollamaContextWindow') || '2048';
+
     const res = await fetch('/api/chat', {
       method: 'POST',
       headers: {
@@ -471,15 +547,19 @@ const ChatWindow = ({ id }: { id?: string }) => {
         files: fileIds,
         focusMode: focusMode,
         optimizationMode: optimizationMode,
-        history: chatHistory,
+        history: messageChatHistory,
         chatModel: {
           name: chatModelProvider.name,
           provider: chatModelProvider.provider,
+          ...(chatModelProvider.provider === 'ollama' && {
+            ollamaContextWindow: parseInt(ollamaContextWindow),
+          }),
         },
         embeddingModel: {
           name: embeddingModelProvider.name,
           provider: embeddingModelProvider.provider,
         },
+        systemInstructions: localStorage.getItem('systemInstructions'),
       }),
     });
 
@@ -511,20 +591,14 @@ const ChatWindow = ({ id }: { id?: string }) => {
   };
 
   const rewrite = (messageId: string) => {
-    const index = messages.findIndex((msg) => msg.messageId === messageId);
-
-    if (index === -1) return;
-
-    const message = messages[index - 1];
-
-    setMessages((prev) => {
-      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
+    const messageIndex = messages.findIndex(
+      (msg) => msg.messageId === messageId,
+    );
+    if (messageIndex == -1) return;
+    sendMessage(messages[messageIndex - 1].content, {
+      messageId: messageId,
+      rewriteIndex: messageIndex,
     });
-    setChatHistory((prev) => {
-      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
-    });
-
-    sendMessage(message.content, message.messageId);
   };
 
   useEffect(() => {
@@ -563,12 +637,14 @@ const ChatWindow = ({ id }: { id?: string }) => {
               loading={loading}
               messages={messages}
               sendMessage={sendMessage}
-              messageAppeared={messageAppeared}
+              scrollTrigger={scrollTrigger}
               rewrite={rewrite}
               fileIds={fileIds}
               setFileIds={setFileIds}
               files={files}
               setFiles={setFiles}
+              optimizationMode={optimizationMode}
+              setOptimizationMode={setOptimizationMode}
             />
           </>
         ) : (

src/components/MessageActions/ModelInfo.tsx

@@ -0,0 +1,82 @@
+'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;

src/components/MessageBox.tsx

@@ -4,6 +4,7 @@
 import React, { MutableRefObject, useEffect, useState } from 'react';
 import { Message } from './ChatWindow';
 import { cn } from '@/lib/utils';
+import { getSuggestions } from '@/lib/actions';
 import {
   BookCopy,
   Disc3,
@@ -11,20 +12,92 @@ 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,
@@ -42,12 +115,43 @@ const MessageBox = ({
   dividerRef?: MutableRefObject<HTMLDivElement | null>;
   isLast: boolean;
   rewrite: (messageId: string) => void;
-  sendMessage: (message: string) => void;
+  sendMessage: (
+    message: string,
+    options?: {
+      messageId?: string;
+      rewriteIndex?: number;
+      suggestions?: 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;
     const regex = /\[(\d+)\]/g;
     let processedMessage = message.content;
 
@@ -67,13 +171,36 @@ const MessageBox = ({
     ) {
       setParsedMessage(
         processedMessage.replace(
-          regex,
-          (_, number) =>
-            `<a href="${
-              message.sources?.[number - 1]?.metadata?.url
-            }" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
+          citationRegex,
+          (_, capturedContent: string) => {
+            const numbers = capturedContent
+              .split(',')
+              .map((numStr) => numStr.trim());
+
+            const linksHtml = numbers
+              .map((numStr) => {
+                const number = parseInt(numStr);
+
+                if (isNaN(number) || number <= 0) {
+                  return `[${numStr}]`;
+                }
+
+                const source = message.sources?.[number - 1];
+                const url = source?.metadata?.url;
+
+                if (url) {
+                  return `<a href="${url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${numStr}</a>`;
+                } else {
+                  return `[${numStr}]`;
+                }
+              })
+              .join('');
+
+            return linksHtml;
+          },
         ),
       );
+      setSpeechMessage(message.content.replace(regex, ''));
       return;
     }
 
@@ -81,6 +208,18 @@ 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 = {
@@ -88,6 +227,24 @@ 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,
+      },
     },
   };
 
@@ -125,6 +282,7 @@ const MessageBox = ({
               </div>
             )}
             <div className="flex flex-col space-y-2">
+              {' '}
               <div className="flex flex-row items-center space-x-2">
                 <Disc3
                   className={cn(
@@ -136,12 +294,16 @@ 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] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
-                  'max-w-none break-words text-black dark: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] 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',
                 )}
                 options={markdownOverrides}
               >
@@ -176,18 +338,37 @@ const MessageBox = ({
                   </div>
                 </div>
               )}
-              {isLast &&
-                message.suggestions &&
-                message.suggestions.length > 0 &&
-                message.role === 'assistant' &&
-                !loading && (
+              {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>
+                      <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 ? (
                       <div className="flex flex-col space-y-3">
                         {message.suggestions.map((suggestion, i) => (
                           <div
@@ -212,6 +393,7 @@ const MessageBox = ({
                           </div>
                         ))}
                       </div>
+                    ) : null}
                   </div>
                 </>
               )}

src/components/MessageInput.tsx

@@ -4,6 +4,7 @@ import { useEffect, useRef, useState } from 'react';
 import TextareaAutosize from 'react-textarea-autosize';
 import Attach from './MessageInputActions/Attach';
 import CopilotToggle from './MessageInputActions/Copilot';
+import Optimization from './MessageInputActions/Optimization';
 import { File } from './ChatWindow';
 import AttachSmall from './MessageInputActions/AttachSmall';
 
@@ -14,6 +15,8 @@ const MessageInput = ({
   setFileIds,
   files,
   setFiles,
+  optimizationMode,
+  setOptimizationMode,
 }: {
   sendMessage: (message: string) => void;
   loading: boolean;
@@ -21,6 +24,8 @@ const MessageInput = ({
   setFileIds: (fileIds: string[]) => void;
   files: File[];
   setFiles: (files: File[]) => void;
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
 }) => {
   const [copilotEnabled, setCopilotEnabled] = useState(false);
   const [message, setMessage] = useState('');
@@ -40,20 +45,16 @@ const MessageInput = ({
   useEffect(() => {
     const handleKeyDown = (e: KeyboardEvent) => {
       const activeElement = document.activeElement;
-
       const isInputFocused =
         activeElement?.tagName === 'INPUT' ||
         activeElement?.tagName === 'TEXTAREA' ||
         activeElement?.hasAttribute('contenteditable');
-
       if (e.key === '/' && !isInputFocused) {
         e.preventDefault();
         inputRef.current?.focus();
       }
     };
-
     document.addEventListener('keydown', handleKeyDown);
-
     return () => {
       document.removeEventListener('keydown', handleKeyDown);
     };
@@ -75,18 +76,35 @@ const MessageInput = ({
         }
       }}
       className={cn(
-        'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200',
-        mode === 'multi' ? 'flex-col rounded-lg' : 'flex-row rounded-full',
+        'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center border border-light-200 dark:border-dark-200',
+        mode === 'multi'
+          ? 'flex-col rounded-lg'
+          : 'flex-col md:flex-row rounded-lg md:rounded-full',
       )}
     >
       {mode === 'single' && (
+        <div className="flex flex-row items-center justify-between w-full mb-2 md:mb-0 md:w-auto">
+          <div className="flex flex-row items-center space-x-2">
             <AttachSmall
               fileIds={fileIds}
               setFileIds={setFileIds}
               files={files}
               setFiles={setFiles}
             />
+            <Optimization
+              optimizationMode={optimizationMode}
+              setOptimizationMode={setOptimizationMode}
+            />
+          </div>
+          <div className="md:hidden">
+            <CopilotToggle
+              copilotEnabled={copilotEnabled}
+              setCopilotEnabled={setCopilotEnabled}
+            />
+          </div>
+        </div>
       )}
+      <div className="flex flex-row items-center w-full">
         <TextareaAutosize
           ref={inputRef}
           value={message}
@@ -99,10 +117,12 @@ const MessageInput = ({
         />
         {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"
@@ -111,22 +131,40 @@ const MessageInput = ({
             </button>
           </div>
         )}
+      </div>
+
       {mode === 'multi' && (
-        <div className="flex flex-row items-center justify-between w-full pt-2">
+        <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}
               />
-          <div className="flex flex-row items-center space-x-4">
+              <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 text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
+              className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
             >
               <ArrowUp className="bg-background" size={17} />
             </button>

src/components/MessageInputActions/Focus.tsx

@@ -2,6 +2,7 @@ import {
   BadgePercent,
   ChevronDown,
   Globe,
+  MessageCircle,
   Pencil,
   ScanEye,
   SwatchBook,
@@ -30,11 +31,23 @@ const focusModes = [
     icon: <SwatchBook size={20} />,
   },
   {
-    key: 'writingAssistant',
-    title: 'Writing',
-    description: 'Chat without searching the web',
+    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',
     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',
@@ -47,12 +60,6 @@ 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 = ({

src/components/MessageInputActions/Optimization.tsx

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

src/components/SearchImages.tsx

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

src/components/SearchVideos.tsx

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

src/lib/actions.ts

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

src/lib/config.ts

@@ -1,7 +1,14 @@
-import fs from 'fs';
-import path from 'path';
 import toml from '@iarna/toml';
 
+// Use dynamic imports for Node.js modules to prevent client-side errors
+let fs: any;
+let path: any;
+if (typeof window === 'undefined') {
+  // We're on the server
+  fs = require('fs');
+  path = require('path');
+}
+
 const configFileName = 'config.toml';
 
 interface Config {
@@ -25,6 +32,12 @@ interface Config {
     OLLAMA: {
       API_URL: string;
     };
+    DEEPSEEK: {
+      API_KEY: string;
+    };
+    LM_STUDIO: {
+      API_URL: string;
+    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -40,10 +53,17 @@ type RecursivePartial<T> = {
   [P in keyof T]?: RecursivePartial<T[P]>;
 };
 
-const loadConfig = () =>
-  toml.parse(
+const loadConfig = () => {
+  // Server-side only
+  if (typeof window === 'undefined') {
+    return toml.parse(
       fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
     ) as any as Config;
+  }
+
+  // Client-side fallback - settings will be loaded via API
+  return {} as Config;
+};
 
 export const getSimilarityMeasure = () =>
   loadConfig().GENERAL.SIMILARITY_MEASURE;
@@ -63,6 +83,8 @@ export const getSearxngApiEndpoint = () =>
 
 export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
 
+export const getDeepseekApiKey = () => loadConfig().MODELS.DEEPSEEK.API_KEY;
+
 export const getCustomOpenaiApiKey = () =>
   loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
 
@@ -72,6 +94,9 @@ export const getCustomOpenaiApiUrl = () =>
 export const getCustomOpenaiModelName = () =>
   loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
 
+export const getLMStudioApiEndpoint = () =>
+  loadConfig().MODELS.LM_STUDIO.API_URL;
+
 const mergeConfigs = (current: any, update: any): any => {
   if (update === null || update === undefined) {
     return current;
@@ -104,10 +129,13 @@ const mergeConfigs = (current: any, update: any): any => {
 };
 
 export const updateConfig = (config: RecursivePartial<Config>) => {
+  // Server-side only
+  if (typeof window === 'undefined') {
     const currentConfig = loadConfig();
     const mergedConfig = mergeConfigs(currentConfig, config);
     fs.writeFileSync(
       path.join(path.join(process.cwd(), `${configFileName}`)),
       toml.stringify(mergedConfig),
     );
+  }
 };

src/lib/prompts/academicSearch.ts

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

src/lib/prompts/chat.ts

@@ -0,0 +1,19 @@
+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>
+`;

src/lib/prompts/index.ts

@@ -11,7 +11,8 @@ import {
   wolframAlphaSearchResponsePrompt,
   wolframAlphaSearchRetrieverPrompt,
 } from './wolframAlpha';
-import { writingAssistantPrompt } from './writingAssistant';
+import { localResearchPrompt } from './localResearch';
+import { chatPrompt } from './chat';
 import {
   youtubeSearchResponsePrompt,
   youtubeSearchRetrieverPrompt,
@@ -26,7 +27,8 @@ export default {
   redditSearchRetrieverPrompt,
   wolframAlphaSearchResponsePrompt,
   wolframAlphaSearchRetrieverPrompt,
-  writingAssistantPrompt,
+  localResearchPrompt,
+  chatPrompt,
   youtubeSearchResponsePrompt,
   youtubeSearchRetrieverPrompt,
 };

src/lib/prompts/localResearch.ts

@@ -1,12 +1,16 @@
-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.
+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.
 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.
 Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
 However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
+### User instructions
+These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
+{systemInstructions}
+
 <context>
 {context}
 </context>

src/lib/prompts/redditSearch.ts

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

src/lib/prompts/webSearch.ts

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

src/lib/prompts/wolframAlpha.ts

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

src/lib/prompts/youtubeSearch.ts

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

src/lib/providers/anthropic.ts

@@ -1,6 +1,11 @@
-import { ChatOpenAI } from '@langchain/openai';
+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>[] = [
@@ -45,13 +50,10 @@ export const loadAnthropicChatModels = async () => {
     anthropicChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: anthropicApiKey,
+        model: new ChatAnthropic({
+          apiKey: anthropicApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://api.anthropic.com/v1/',
-          },
         }) as unknown as BaseChatModel,
       };
     });

src/lib/providers/deepseek.ts

@@ -0,0 +1,49 @@
+import { ChatOpenAI } from '@langchain/openai';
+import { getDeepseekApiKey } from '../config';
+import { ChatModel } from '.';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+
+export const PROVIDER_INFO = {
+  key: 'deepseek',
+  displayName: 'Deepseek AI',
+};
+
+const deepseekChatModels: Record<string, string>[] = [
+  {
+    displayName: 'Deepseek Chat (Deepseek V3)',
+    key: 'deepseek-chat',
+  },
+  {
+    displayName: 'Deepseek Reasoner (Deepseek R1)',
+    key: 'deepseek-reasoner',
+  },
+];
+
+export const loadDeepseekChatModels = async () => {
+  const deepseekApiKey = getDeepseekApiKey();
+
+  if (!deepseekApiKey) return {};
+
+  try {
+    const chatModels: Record<string, ChatModel> = {};
+
+    deepseekChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatOpenAI({
+          openAIApiKey: deepseekApiKey,
+          modelName: model.key,
+          temperature: 0.7,
+          configuration: {
+            baseURL: 'https://api.deepseek.com',
+          },
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading Deepseek models: ${err}`);
+    return {};
+  }
+};

src/lib/providers/gemini.ts

@@ -1,10 +1,22 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+import {
+  ChatGoogleGenerativeAI,
+  GoogleGenerativeAIEmbeddings,
+} 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';
 
 const geminiChatModels: Record<string, string>[] = [
+  {
+    displayName: 'Gemini 2.5 Pro Experimental',
+    key: 'gemini-2.5-pro-exp-03-25',
+  },
   {
     displayName: 'Gemini 2.0 Flash',
     key: 'gemini-2.0-flash',
@@ -14,8 +26,8 @@ const geminiChatModels: Record<string, string>[] = [
     key: 'gemini-2.0-flash-lite',
   },
   {
-    displayName: 'Gemini 2.0 Pro Experimental',
-    key: 'gemini-2.0-pro-exp-02-05',
+    displayName: 'Gemini 2.0 Flash Thinking Experimental',
+    key: 'gemini-2.0-flash-thinking-exp-01-21',
   },
   {
     displayName: 'Gemini 1.5 Flash',
@@ -33,8 +45,12 @@ const geminiChatModels: Record<string, string>[] = [
 
 const geminiEmbeddingModels: Record<string, string>[] = [
   {
-    displayName: 'Gemini Embedding',
-    key: 'gemini-embedding-exp',
+    displayName: 'Text Embedding 004',
+    key: 'models/text-embedding-004',
+  },
+  {
+    displayName: 'Embedding 001',
+    key: 'models/embedding-001',
   },
 ];
 
@@ -49,13 +65,10 @@ export const loadGeminiChatModels = async () => {
     geminiChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: geminiApiKey,
+        model: new ChatGoogleGenerativeAI({
+          apiKey: geminiApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as BaseChatModel,
       };
     });
@@ -78,12 +91,9 @@ export const loadGeminiEmbeddingModels = async () => {
     geminiEmbeddingModels.forEach((model) => {
       embeddingModels[model.key] = {
         displayName: model.displayName,
-        model: new OpenAIEmbeddings({
-          openAIApiKey: geminiApiKey,
+        model: new GoogleGenerativeAIEmbeddings({
+          apiKey: geminiApiKey,
           modelName: model.key,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as Embeddings,
       };
     });

src/lib/providers/groq.ts

@@ -1,6 +1,11 @@
 import { ChatOpenAI } from '@langchain/openai';
 import { getGroqApiKey } from '../config';
 import { ChatModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'groq',
+  displayName: 'Groq',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const groqChatModels: Record<string, string>[] = [
@@ -72,6 +77,14 @@ const groqChatModels: Record<string, string>[] = [
     displayName: 'Llama 3.2 90B Vision Preview (Preview)',
     key: 'llama-3.2-90b-vision-preview',
   },
+  /* {
+    displayName: 'Llama 4 Maverick 17B 128E Instruct (Preview)',
+    key: 'meta-llama/llama-4-maverick-17b-128e-instruct',
+  }, */
+  {
+    displayName: 'Llama 4 Scout 17B 16E Instruct (Preview)',
+    key: 'meta-llama/llama-4-scout-17b-16e-instruct',
+  },
 ];
 
 export const loadGroqChatModels = async () => {

src/lib/providers/index.ts

@@ -1,17 +1,60 @@
 import { Embeddings } from '@langchain/core/embeddings';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai';
+import {
+  loadOpenAIChatModels,
+  loadOpenAIEmbeddingModels,
+  PROVIDER_INFO as OpenAIInfo,
+  PROVIDER_INFO,
+} from './openai';
 import {
   getCustomOpenaiApiKey,
   getCustomOpenaiApiUrl,
   getCustomOpenaiModelName,
 } from '../config';
 import { ChatOpenAI } from '@langchain/openai';
-import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
-import { loadGroqChatModels } from './groq';
-import { loadAnthropicChatModels } from './anthropic';
-import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
-import { loadTransformersEmbeddingsModels } from './transformers';
+import {
+  loadOllamaChatModels,
+  loadOllamaEmbeddingModels,
+  PROVIDER_INFO as OllamaInfo,
+} from './ollama';
+import { loadGroqChatModels, PROVIDER_INFO as GroqInfo } from './groq';
+import {
+  loadAnthropicChatModels,
+  PROVIDER_INFO as AnthropicInfo,
+} from './anthropic';
+import {
+  loadGeminiChatModels,
+  loadGeminiEmbeddingModels,
+  PROVIDER_INFO as GeminiInfo,
+} from './gemini';
+import {
+  loadTransformersEmbeddingsModels,
+  PROVIDER_INFO as TransformersInfo,
+} from './transformers';
+import {
+  loadDeepseekChatModels,
+  PROVIDER_INFO as DeepseekInfo,
+} from './deepseek';
+import {
+  loadLMStudioChatModels,
+  loadLMStudioEmbeddingsModels,
+  PROVIDER_INFO as LMStudioInfo,
+} from './lmstudio';
+
+export const PROVIDER_METADATA = {
+  openai: OpenAIInfo,
+  ollama: OllamaInfo,
+  groq: GroqInfo,
+  anthropic: AnthropicInfo,
+  gemini: GeminiInfo,
+  transformers: TransformersInfo,
+  deepseek: DeepseekInfo,
+  lmstudio: LMStudioInfo,
+  custom_openai: {
+    key: 'custom_openai',
+    displayName: 'Custom OpenAI',
+  },
+};
 
 export interface ChatModel {
   displayName: string;
@@ -32,6 +75,8 @@ export const chatModelProviders: Record<
   groq: loadGroqChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
+  deepseek: loadDeepseekChatModels,
+  lmstudio: loadLMStudioChatModels,
 };
 
 export const embeddingModelProviders: Record<
@@ -42,6 +87,7 @@ export const embeddingModelProviders: Record<
   ollama: loadOllamaEmbeddingModels,
   gemini: loadGeminiEmbeddingModels,
   transformers: loadTransformersEmbeddingsModels,
+  lmstudio: loadLMStudioEmbeddingsModels,
 };
 
 export const getAvailableChatModelProviders = async () => {

src/lib/providers/lmstudio.ts

@@ -0,0 +1,100 @@
+import { getKeepAlive, getLMStudioApiEndpoint } from '../config';
+import axios from 'axios';
+import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'lmstudio',
+  displayName: 'LM Studio',
+};
+import { ChatOpenAI } from '@langchain/openai';
+import { OpenAIEmbeddings } from '@langchain/openai';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { Embeddings } from '@langchain/core/embeddings';
+
+interface LMStudioModel {
+  id: string;
+  name?: string;
+}
+
+const ensureV1Endpoint = (endpoint: string): string =>
+  endpoint.endsWith('/v1') ? endpoint : `${endpoint}/v1`;
+
+const checkServerAvailability = async (endpoint: string): Promise<boolean> => {
+  try {
+    await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+    return true;
+  } catch {
+    return false;
+  }
+};
+
+export const loadLMStudioChatModels = async () => {
+  const endpoint = getLMStudioApiEndpoint();
+
+  if (!endpoint) return {};
+  if (!(await checkServerAvailability(endpoint))) return {};
+
+  try {
+    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+
+    const chatModels: Record<string, ChatModel> = {};
+
+    response.data.data.forEach((model: LMStudioModel) => {
+      chatModels[model.id] = {
+        displayName: model.name || model.id,
+        model: new ChatOpenAI({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: ensureV1Endpoint(endpoint),
+          },
+          modelName: model.id,
+          temperature: 0.7,
+          streaming: true,
+          maxRetries: 3,
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading LM Studio models: ${err}`);
+    return {};
+  }
+};
+
+export const loadLMStudioEmbeddingsModels = async () => {
+  const endpoint = getLMStudioApiEndpoint();
+
+  if (!endpoint) return {};
+  if (!(await checkServerAvailability(endpoint))) return {};
+
+  try {
+    const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
+      headers: { 'Content-Type': 'application/json' },
+    });
+
+    const embeddingsModels: Record<string, EmbeddingModel> = {};
+
+    response.data.data.forEach((model: LMStudioModel) => {
+      embeddingsModels[model.id] = {
+        displayName: model.name || model.id,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: ensureV1Endpoint(endpoint),
+          },
+          modelName: model.id,
+        }) as unknown as Embeddings,
+      };
+    });
+
+    return embeddingsModels;
+  } catch (err) {
+    console.error(`Error loading LM Studio embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/ollama.ts

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

src/lib/providers/openai.ts

@@ -1,6 +1,11 @@
 import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
 import { getOpenaiApiKey } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
+
+export const PROVIDER_INFO = {
+  key: 'openai',
+  displayName: 'OpenAI',
+};
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { Embeddings } from '@langchain/core/embeddings';
 
@@ -25,6 +30,18 @@ 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>[] = [

src/lib/providers/transformers.ts

@@ -1,5 +1,10 @@
 import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
 
+export const PROVIDER_INFO = {
+  key: 'transformers',
+  displayName: 'Hugging Face',
+};
+
 export const loadTransformersEmbeddingsModels = async () => {
   try {
     const embeddingModels = {

src/lib/search/index.ts

@@ -20,15 +20,24 @@ export const searchHandlers: Record<string, MetaSearchAgent> = {
     searchWeb: true,
     summarizer: false,
   }),
-  writingAssistant: new MetaSearchAgent({
+  localResearch: new MetaSearchAgent({
     activeEngines: [],
     queryGeneratorPrompt: '',
-    responsePrompt: prompts.writingAssistantPrompt,
+    responsePrompt: prompts.localResearchPrompt,
     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,

src/lib/search/metaSearchAgent.ts

@@ -33,6 +33,7 @@ export interface MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) => Promise<eventEmitter>;
 }
 
@@ -236,9 +237,11 @@ class MetaSearchAgent implements MetaSearchAgentType {
     fileIds: string[],
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
+    systemInstructions: string,
   ) {
     return RunnableSequence.from([
       RunnableMap.from({
+        systemInstructions: () => systemInstructions,
         query: (input: BasicChainInput) => input.query,
         chat_history: (input: BasicChainInput) => input.chat_history,
         date: () => new Date().toISOString(),
@@ -431,13 +434,13 @@ class MetaSearchAgent implements MetaSearchAgentType {
   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 }),
@@ -456,6 +459,50 @@ class MetaSearchAgent implements MetaSearchAgentType {
         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');
       }
     }
@@ -468,6 +515,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) {
     const emitter = new eventEmitter();
 
@@ -476,6 +524,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
       fileIds,
       embeddings,
       optimizationMode,
+      systemInstructions,
     );
 
     const stream = answeringChain.streamEvents(
@@ -488,7 +537,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
       },
     );
 
-    this.handleStream(stream, emitter);
+    this.handleStream(stream, emitter, llm);
 
     return emitter;
   }

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({