Merge 303992c82c into 7ec201d011

feat: add Gemini 2.0 Flash Exp models

CONTRIBUTING.md

@@ -8,6 +8,7 @@ Perplexica's design consists of two main domains:
 
 - **Frontend (`ui` directory)**: This is a Next.js application holding all user interface components. It's a self-contained environment that manages everything the user interacts with.
 - **Backend (root and `src` directory)**: The backend logic is situated in the `src` folder, but the root directory holds the main `package.json` for backend dependency management.
+  - All of the focus modes are created using the Meta Search Agent class present in `src/search/metaSearchAgent.ts`. The main logic behind Perplexica lies there.
 
 ## Setting Up Your Environment
 

README.md

@@ -1,5 +1,8 @@
 # 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
 
+[![Discord](https://dcbadge.vercel.app/api/server/26aArMy8tT?style=flat&compact=true)](https://discord.gg/26aArMy8tT)
+
+
 ![preview](.assets/perplexica-screenshot.png?)
 
 ## Table of Contents <!-- omit in toc -->

docs/API/SEARCH.md

@@ -79,24 +79,24 @@ The response from the API includes both the final message and the sources used t
 
 ```json
 {
-	"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
+  "message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
-	"sources": [
+  "sources": [
-		{
+    {
-			"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
+      "pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
-			"metadata": {
+      "metadata": {
-				"title": "What is Perplexica, and how does it function as an AI-powered search ...",
+        "title": "What is Perplexica, and how does it function as an AI-powered search ...",
-				"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
+        "url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
-			}
+      }
-		},
+    },
-		{
+    {
-			"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
+      "pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
-			"metadata": {
+      "metadata": {
-				"title": "Sahar Mor's Post",
+        "title": "Sahar Mor's Post",
-				"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
+        "url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
-			}
+      }
-		}
+    }
         ....
-	]
+  ]
 }
 ```
 

docs/architecture/README.md

@@ -1,4 +1,4 @@
-## Perplexica's Architecture
+# Perplexica's Architecture
 
 Perplexica's architecture consists of the following key components:
 

docs/architecture/WORKING.md

@@ -1,4 +1,4 @@
-## How does Perplexica work?
+# How does Perplexica work?
 
 Curious about how Perplexica works? Don't worry, we'll cover it here. Before we begin, make sure you've read about the architecture of Perplexica to ensure you understand what it's made up of. Haven't read it? You can read it [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/architecture/README.md).
 
@@ -10,10 +10,10 @@ We'll understand how Perplexica works by taking an example of a scenario where a
 4. After the information is retrieved, it is based on keyword-based search. We then convert the information into embeddings and the query as well, then we perform a similarity search to find the most relevant sources to answer the query.
 5. After all this is done, the sources are passed to the response generator. This chain takes all the chat history, the query, and the sources. It generates a response that is streamed to the UI.
 
-### How are the answers cited?
+## How are the answers cited?
 
 The LLMs are prompted to do so. We've prompted them so well that they cite the answers themselves, and using some UI magic, we display it to the user.
 
-### Image and Video Search
+## Image and Video Search
 
 Image and video searches are conducted in a similar manner. A query is always generated first, then we search the web for images and videos that match the query. These results are then returned to the user.

docs/installation/NETWORKING.md

@@ -10,27 +10,27 @@ This guide will show you how to make Perplexica available over a network. Follow
 
 3. Stop and remove the existing Perplexica containers and images:
 
-```
+   ```bash
-docker compose down --rmi all
+   docker compose down --rmi all
-```
+   ```
 
 4. Open the `docker-compose.yaml` file in a text editor like Notepad++
 
 5. Replace `127.0.0.1` with the IP address of the server Perplexica is running on in these two lines:
 
-```
+   ```bash
-args:
+   args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
+     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
+     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-```
+   ```
 
 6. Save and close the `docker-compose.yaml` file
 
 7. Rebuild and restart the Perplexica container:
 
-```
+   ```bash
-docker compose up -d --build
+   docker compose up -d --build
-```
+   ```
 
 ## macOS
 
@@ -38,37 +38,37 @@ docker compose up -d --build
 
 2. Navigate to the directory with the `docker-compose.yaml` file:
 
-```
+   ```bash
-cd /path/to/docker-compose.yaml
+   cd /path/to/docker-compose.yaml
-```
+   ```
 
 3. Stop and remove existing containers and images:
 
-```
+   ```bash
-docker compose down --rmi all
+   docker compose down --rmi all
-```
+   ```
 
 4. Open `docker-compose.yaml` in a text editor like Sublime Text:
 
-```
+   ```bash
-nano docker-compose.yaml
+   nano docker-compose.yaml
-```
+   ```
 
 5. Replace `127.0.0.1` with the server IP in these lines:
 
-```
+   ```bash
-args:
+   args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
+     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
+     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-```
+   ```
 
 6. Save and exit the editor
 
 7. Rebuild and restart Perplexica:
 
-```
+   ```bash
-docker compose up -d --build
+   docker compose up -d --build
-```
+   ```
 
 ## Linux
 
@@ -76,34 +76,34 @@ docker compose up -d --build
 
 2. Navigate to the `docker-compose.yaml` directory:
 
-```
+   ```bash
-cd /path/to/docker-compose.yaml
+   cd /path/to/docker-compose.yaml
-```
+   ```
 
 3. Stop and remove containers and images:
 
-```
+   ```bash
-docker compose down --rmi all
+   docker compose down --rmi all
-```
+   ```
 
 4. Edit `docker-compose.yaml`:
 
-```
+   ```bash
-nano docker-compose.yaml
+   nano docker-compose.yaml
-```
+   ```
 
 5. Replace `127.0.0.1` with the server IP:
 
-```
+   ```bash
-args:
+   args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
+     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
+     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-```
+   ```
 
 6. Save and exit the editor
 
 7. Rebuild and restart Perplexica:
 
-```
+   ```bash
-docker compose up -d --build
+   docker compose up -d --build
-```
+   ```

docs/installation/UPDATING.md

@@ -6,23 +6,23 @@ To update Perplexica to the latest version, follow these steps:
 
 1. Clone the latest version of Perplexica from GitHub:
 
-```bash
+   ```bash
-   git clone https://github.com/ItzCrazyKns/Perplexica.git
+      git clone https://github.com/ItzCrazyKns/Perplexica.git
-```
+   ```
 
 2. Navigate to the Project Directory.
 
 3. Pull latest images from registry.
 
-```bash
+   ```bash
-docker compose pull
+   docker compose pull
-```
+   ```
 
 4. Update and Recreate containers.
 
-```bash
+   ```bash
-docker compose up -d
+   docker compose up -d
-```
+   ```
 
 5. Once the command completes running go to http://localhost:3000 and verify the latest changes.
 
@@ -30,9 +30,9 @@ docker compose up -d
 
 1. Clone the latest version of Perplexica from GitHub:
 
-```bash
+   ```bash
-   git clone https://github.com/ItzCrazyKns/Perplexica.git
+      git clone https://github.com/ItzCrazyKns/Perplexica.git
-```
+   ```
 
 2. Navigate to the Project Directory
 3. Execute `npm i` in both the `ui` folder and the root directory.

src/config.ts

@@ -16,9 +16,10 @@ interface Config {
     ANTHROPIC: string;
     GEMINI: string;
   };
-  API_ENDPOINTS: {
+  API_ENDPOINTS: {  
-    SEARXNG: string;
     OLLAMA: string;
+    LMSTUDIO: string;
+    SEARXNG: string;
   };
 }
 
@@ -51,6 +52,8 @@ export const getSearxngApiEndpoint = () =>
 
 export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;
 
+export const getLMStudioApiEndpoint = () => loadConfig().API_ENDPOINTS.LMSTUDIO;
+
 export const updateConfig = (config: RecursivePartial<Config>) => {
   const currentConfig = loadConfig();
 
@@ -72,6 +75,27 @@ export const updateConfig = (config: RecursivePartial<Config>) => {
     }
   }
 
+  /*
+export const updateConfig = (config: RecursivePartial<Config>) => {
+  const currentConfig = loadConfig();
+
+  // Merge existing config with new values
+  const mergedConfig: RecursivePartial<Config> = {
+    GENERAL: {
+      ...currentConfig.GENERAL,
+      ...config.GENERAL,
+    },
+    API_KEYS: {
+      ...currentConfig.API_KEYS,
+      ...config.API_KEYS,
+    },
+    API_ENDPOINTS: {
+      ...currentConfig.API_ENDPOINTS,
+      ...config.API_ENDPOINTS,
+    },
+  };
+*/
+
   fs.writeFileSync(
     path.join(__dirname, `../${configFileName}`),
     toml.stringify(config),

src/lib/outputParsers/lineOutputParser.ts

@@ -19,6 +19,8 @@ class LineOutputParser extends BaseOutputParser<string> {
   lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
 
   async parse(text: string): Promise<string> {
+    text = text.trim() || '';
+
     const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
     const startKeyIndex = text.indexOf(`<${this.key}>`);
     const endKeyIndex = text.indexOf(`</${this.key}>`);

src/lib/outputParsers/listLineOutputParser.ts

@@ -19,11 +19,13 @@ class LineListOutputParser extends BaseOutputParser<string[]> {
   lc_namespace = ['langchain', 'output_parsers', 'line_list_output_parser'];
 
   async parse(text: string): Promise<string[]> {
+    text = text.trim() || '';
+
     const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
     const startKeyIndex = text.indexOf(`<${this.key}>`);
     const endKeyIndex = text.indexOf(`</${this.key}>`);
 
-    if (startKeyIndex === -1 && endKeyIndex === -1) {
+    if (startKeyIndex === -1 || endKeyIndex === -1) {
       return [];
     }
 

src/lib/providers/anthropic.ts

@@ -9,12 +9,20 @@ export const loadAnthropicChatModels = async () => {
 
   try {
     const chatModels = {
-      'claude-3-5-sonnet-20240620': {
+      'claude-3-5-sonnet-20241022': {
         displayName: 'Claude 3.5 Sonnet',
         model: new ChatAnthropic({
           temperature: 0.7,
           anthropicApiKey: anthropicApiKey,
-          model: 'claude-3-5-sonnet-20240620',
+          model: 'claude-3-5-sonnet-20241022',
+        }),
+      },
+      'claude-3-5-haiku-20241022': {
+        displayName: 'Claude 3.5 Haiku',
+        model: new ChatAnthropic({
+          temperature: 0.7,
+          anthropicApiKey: anthropicApiKey,
+          model: 'claude-3-5-haiku-20241022',
         }),
       },
       'claude-3-opus-20240229': {

src/lib/providers/gemini.ts

@@ -36,6 +36,22 @@ export const loadGeminiChatModels = async () => {
           apiKey: geminiApiKey,
         }),
       },
+      'gemini-2.0-flash-exp': {
+        displayName: 'Gemini 2.0 Flash Exp',
+        model: new ChatGoogleGenerativeAI({
+          modelName: 'gemini-2.0-flash-exp',
+          temperature: 0.7,
+          apiKey: geminiApiKey,
+        }),
+      },
+      'gemini-2.0-flash-thinking-exp-01-21': {
+        displayName: 'Gemini 2.0 Flash Thinking Exp 01-21',
+        model: new ChatGoogleGenerativeAI({
+          modelName: 'gemini-2.0-flash-thinking-exp-01-21',
+          temperature: 0.7,
+          apiKey: geminiApiKey,
+        }),
+      },
     };
 
     return chatModels;

src/lib/providers/groq.ts

@@ -9,6 +9,19 @@ export const loadGroqChatModels = async () => {
 
   try {
     const chatModels = {
+      'llama-3.3-70b-versatile': {
+        displayName: 'Llama 3.3 70B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'llama-3.3-70b-versatile',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
       'llama-3.2-3b-preview': {
         displayName: 'Llama 3.2 3B',
         model: new ChatOpenAI(
@@ -48,19 +61,6 @@ export const loadGroqChatModels = async () => {
           },
         ),
       },
-      'llama-3.1-70b-versatile': {
-        displayName: 'Llama 3.1 70B',
-        model: new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama-3.1-70b-versatile',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-      },
       'llama-3.1-8b-instant': {
         displayName: 'Llama 3.1 8B',
         model: new ChatOpenAI(
@@ -113,19 +113,6 @@ export const loadGroqChatModels = async () => {
           },
         ),
       },
-      'gemma-7b-it': {
-        displayName: 'Gemma 7B',
-        model: new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'gemma-7b-it',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-      },
       'gemma2-9b-it': {
         displayName: 'Gemma2 9B',
         model: new ChatOpenAI(

src/lib/providers/index.ts

@@ -4,6 +4,7 @@ import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
 import { loadAnthropicChatModels } from './anthropic';
 import { loadTransformersEmbeddingsModels } from './transformers';
 import { loadGeminiChatModels, loadGeminiEmbeddingsModels } from './gemini';
+import { loadLMStudioChatModels, loadLMStudioEmbeddingsModels } from './lmstudio';
 
 const chatModelProviders = {
   openai: loadOpenAIChatModels,
@@ -11,6 +12,7 @@ const chatModelProviders = {
   ollama: loadOllamaChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
+  lm_studio: loadLMStudioChatModels,
 };
 
 const embeddingModelProviders = {
@@ -18,6 +20,7 @@ const embeddingModelProviders = {
   local: loadTransformersEmbeddingsModels,
   ollama: loadOllamaEmbeddingsModels,
   gemini: loadGeminiEmbeddingsModels,
+  lm_studio: loadLMStudioEmbeddingsModels,
 };
 
 export const getAvailableChatModelProviders = async () => {

src/lib/providers/lmstudio.ts

@@ -0,0 +1,89 @@
+import { OpenAIEmbeddings } from '@langchain/openai';
+import { ChatOpenAI } from '@langchain/openai';
+import { getKeepAlive, getLMStudioApiEndpoint } from '../../config';
+import logger from '../../utils/logger';
+import axios from 'axios';
+
+interface LMStudioModel {
+  id: string;
+  // add other properties if LM Studio API provides them
+}
+
+interface ChatModelConfig {
+  displayName: string;
+  model: ChatOpenAI;
+}
+
+export const loadLMStudioChatModels = async (): Promise<Record<string, ChatModelConfig>> => {
+  const lmStudioEndpoint = getLMStudioApiEndpoint();
+
+  if (!lmStudioEndpoint) {
+    logger.debug('LM Studio endpoint not configured, skipping');
+    return {};
+  }
+
+  try {
+    const response = await axios.get<{ data: LMStudioModel[] }>(`${lmStudioEndpoint}/models`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const lmStudioModels = response.data.data;
+
+    const chatModels = lmStudioModels.reduce<Record<string, ChatModelConfig>>((acc, model) => {
+      acc[model.id] = {
+        displayName: model.id,
+        model: new ChatOpenAI({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: lmStudioEndpoint,
+          },
+          modelName: model.id,
+          temperature: 0.7,
+        }),
+      };
+      return acc;
+    }, {});
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading LM Studio models: ${err}`);
+    return {};
+  }
+};
+
+export const loadLMStudioEmbeddingsModels = async () => {
+  const lmStudioEndpoint = getLMStudioApiEndpoint();
+
+  if (!lmStudioEndpoint) return {};
+
+  try {
+    const response = await axios.get(`${lmStudioEndpoint}/models`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const lmStudioModels = response.data.data;
+
+    const embeddingsModels = lmStudioModels.reduce((acc, model) => {
+      acc[model.id] = {
+        displayName: model.id,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: 'lm-studio', // Dummy key required by LangChain
+          configuration: {
+            baseURL: lmStudioEndpoint,
+          },
+          modelName: model.id,
+        }),
+      };
+      return acc;
+    }, {});
+
+    return embeddingsModels;
+  } catch (err) {
+    logger.error(`Error loading LM Studio embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/ollama.ts

@@ -2,6 +2,7 @@ import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
 import { getKeepAlive, getOllamaApiEndpoint } from '../../config';
 import logger from '../../utils/logger';
 import { ChatOllama } from '@langchain/community/chat_models/ollama';
+import axios from 'axios';
 
 export const loadOllamaChatModels = async () => {
   const ollamaEndpoint = getOllamaApiEndpoint();
@@ -10,13 +11,13 @@ export const loadOllamaChatModels = async () => {
   if (!ollamaEndpoint) return {};
 
   try {
-    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+    const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
       headers: {
         'Content-Type': 'application/json',
       },
     });
 
-    const { models: ollamaModels } = (await response.json()) as any;
+    const { models: ollamaModels } = response.data;
 
     const chatModels = ollamaModels.reduce((acc, model) => {
       acc[model.model] = {
@@ -45,13 +46,13 @@ export const loadOllamaEmbeddingsModels = async () => {
   if (!ollamaEndpoint) return {};
 
   try {
-    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+    const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
       headers: {
         'Content-Type': 'application/json',
       },
     });
 
-    const { models: ollamaModels } = (await response.json()) as any;
+    const { models: ollamaModels } = response.data;
 
     const embeddingsModels = ollamaModels.reduce((acc, model) => {
       acc[model.model] = {

src/prompts/academicSearch.ts

@@ -20,23 +20,46 @@ Rephrased question:
 `;
 
 export const academicSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
+   You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
+    Your task is to provide answers that are:
-    You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
-    You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
-    Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
-    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.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
-    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].
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
-    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.
 
-    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
+    ### Formatting Instructions
-    talk about the context in your response. 
+    - **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
+    - **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
+    - **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
+    - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
+    - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
+    - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+
+    ### Citation Requirements
+    - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
+    - Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
+    - Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
+    - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
+    - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
+    - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+
+    ### Special Instructions
+    - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
+    - 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.
+    - You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
+    Current date & time in ISO format (UTC timezone) is: {date}.
-    Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;

src/prompts/redditSearch.ts

@@ -20,23 +20,46 @@ Rephrased question:
 `;
 
 export const redditSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
+    You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
+    Your task is to provide answers that are:
-    You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
-    You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
-    Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
-    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.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
-    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].
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
-    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.
 
-    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    ### Formatting Instructions
-    talk about the context in your response.
+    - **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
+    - **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
+    - **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
+    - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
+    - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
+    - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+
+    ### Citation Requirements
+    - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
+    - Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
+    - Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
+    - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
+    - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
+    - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+
+    ### Special Instructions
+    - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
+    - 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.
+    - You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
+    Current date & time in ISO format (UTC timezone) is: {date}.
-    Anything between the \`context\` is retrieved from Reddit and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;

src/prompts/webSearch.ts

@@ -62,25 +62,45 @@ Rephrased question:
 `;
 
 export const webSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are also an expert at summarizing web pages or documents and searching for content in them.
+    You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
+    Your task is to provide answers that are:
-    You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
-    You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
-    If the query contains some links and the user asks to answer from those links you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to answer the user's query.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
-    If the user asks to summarize content from some links, you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to summarize the text. The content provided inside the \`context\` block will be already summarized by another model so you just need to use that content to answer the user's query.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
-    Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
-    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.
 
-    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    ### Formatting Instructions
-    talk about the context in your response.
+    - **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
+    - **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
+    - **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
+    - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
+    - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
+    - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+
+    ### Citation Requirements
+    - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
+    - Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
+    - Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
+    - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
+    - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
+    - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+
+    ### Special Instructions
+    - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
+    - 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.
+
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'. You do not need to do this for summarization tasks.
+    Current date & time in ISO format (UTC timezone) is: {date}.
-    Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;

src/prompts/wolframAlpha.ts

@@ -20,23 +20,46 @@ Rephrased question:
 `;
 
 export const wolframAlphaSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. 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.
+    You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
+    Your task is to provide answers that are:
-    You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
-    You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
-    Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
-    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.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
-    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].
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
-    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.
 
-    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
+    ### Formatting Instructions
-    talk about the context in your response. 
+    - **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
+    - **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
+    - **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
+    - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
+    - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
+    - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+
+    ### Citation Requirements
+    - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
+    - Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
+    - Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
+    - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
+    - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
+    - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+
+    ### Special Instructions
+    - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
+    - 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.
+    - 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.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
+    Current date & time in ISO format (UTC timezone) is: {date}.
-    Anything between the \`context\` is retrieved from Wolfram Alpha and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;

src/prompts/youtubeSearch.ts

@@ -20,23 +20,46 @@ Rephrased question:
 `;
 
 export const youtubeSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. 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 transcript.
+    You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
+    Your task is to provide answers that are:
-    You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
-    You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
-    Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
-    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.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
-    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].
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
-    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.
 
-    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    ### Formatting Instructions
-    talk about the context in your response.
+    - **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
+    - **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
+    - **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
+    - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
+    - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
+    - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+
+    ### Citation Requirements
+    - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
+    - Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
+    - Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
+    - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
+    - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
+    - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+
+    ### Special Instructions
+    - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
+    - 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.
+    - 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
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
+    Current date & time in ISO format (UTC timezone) is: {date}.
-    Anything between the \`context\` is retrieved from Youtube and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;

src/routes/config.ts

@@ -6,6 +6,7 @@ import {
 import {
   getGroqApiKey,
   getOllamaApiEndpoint,
+  getLMStudioApiEndpoint,
   getAnthropicApiKey,
   getGeminiApiKey,
   getOpenaiApiKey,
@@ -51,10 +52,11 @@ router.get('/', async (_, res) => {
 
     config['openaiApiKey'] = getOpenaiApiKey();
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
-    
+
     res.status(200).json(config);
   } catch (err: any) {
     res.status(500).json({ message: 'An error has occurred.' });
@@ -74,6 +76,7 @@ router.post('/', async (req, res) => {
     },
     API_ENDPOINTS: {
       OLLAMA: config.ollamaApiUrl,
+      LMSTUDIO: config.lmStudioApiUrl,
     },
   };
 

src/search/metaSearchAgent.ts

@@ -211,7 +211,11 @@ class MetaSearchAgent implements MetaSearchAgentType {
           const documents = res.results.map(
             (result) =>
               new Document({
-                pageContent: result.content,
+                pageContent:
+                  result.content ||
+                  (this.config.activeEngines.includes('youtube')
+                    ? result.title
+                    : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
                 metadata: {
                   title: result.title,
                   url: result.url,
@@ -236,6 +240,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
       RunnableMap.from({
         query: (input: BasicChainInput) => input.query,
         chat_history: (input: BasicChainInput) => input.chat_history,
+        date: () => new Date().toISOString(),
         context: RunnableLambda.from(async (input: BasicChainInput) => {
           const processedHistory = formatChatHistoryAsString(
             input.chat_history,
@@ -413,7 +418,10 @@ class MetaSearchAgent implements MetaSearchAgentType {
 
   private processDocs(docs: Document[]) {
     return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
+      .map(
+        (_, index) =>
+          `${index + 1}. ${docs[index].metadata.title} ${docs[index].pageContent}`,
+      )
       .join('\n');
   }
 

src/websocket/messageHandler.ts

@@ -5,7 +5,7 @@ import type { Embeddings } from '@langchain/core/embeddings';
 import logger from '../utils/logger';
 import db from '../db';
 import { chats, messages as messagesSchema } from '../db/schema';
-import { eq, asc, gt } from 'drizzle-orm';
+import { eq, asc, gt, and } from 'drizzle-orm';
 import crypto from 'crypto';
 import { getFileDetails } from '../utils/files';
 import MetaSearchAgent, {
@@ -238,7 +238,12 @@ export const handleMessage = async (
           } else {
             await db
               .delete(messagesSchema)
-              .where(gt(messagesSchema.id, messageExists.id))
+              .where(
+                and(
+                  gt(messagesSchema.id, messageExists.id),
+                  eq(messagesSchema.chatId, parsedMessage.chatId),
+                ),
+              )
               .execute();
           }
         } catch (err) {

ui/components/ChatWindow.tsx

@@ -9,7 +9,9 @@ import crypto from 'crypto';
 import { toast } from 'sonner';
 import { useSearchParams } from 'next/navigation';
 import { getSuggestions } from '@/lib/actions';
-import Error from 'next/error';
+import { Settings } from 'lucide-react';
+import SettingsDialog from './SettingsDialog';
+import NextError from 'next/error';
 
 export type Message = {
   messageId: string;
@@ -32,17 +34,38 @@ const useSocket = (
   setIsWSReady: (ready: boolean) => void,
   setError: (error: boolean) => void,
 ) => {
-  const [ws, setWs] = useState<WebSocket | null>(null);
+  const wsRef = useRef<WebSocket | null>(null);
+  const reconnectTimeoutRef = useRef<NodeJS.Timeout>();
+  const retryCountRef = useRef(0);
+  const isCleaningUpRef = useRef(false);
+  const MAX_RETRIES = 3;
+  const INITIAL_BACKOFF = 1000; // 1 second
+
+  const getBackoffDelay = (retryCount: number) => {
+    return Math.min(INITIAL_BACKOFF * Math.pow(2, retryCount), 10000); // Cap at 10 seconds
+  };
 
   useEffect(() => {
-    if (!ws) {
+    const connectWs = async () => {
-      const connectWs = async () => {
+      if (wsRef.current?.readyState === WebSocket.OPEN) {
+        wsRef.current.close();
+      }
+
+      try {
         let chatModel = localStorage.getItem('chatModel');
         let chatModelProvider = localStorage.getItem('chatModelProvider');
         let embeddingModel = localStorage.getItem('embeddingModel');
         let embeddingModelProvider = localStorage.getItem(
           'embeddingModelProvider',
         );
+        let openAIBaseURL =
+          chatModelProvider === 'custom_openai'
+            ? localStorage.getItem('openAIBaseURL')
+            : null;
+        let openAIPIKey =
+          chatModelProvider === 'custom_openai'
+            ? localStorage.getItem('openAIApiKey')
+            : null;
 
         const providers = await fetch(
           `${process.env.NEXT_PUBLIC_API_URL}/models`,
@@ -51,7 +74,13 @@ const useSocket = (
               'Content-Type': 'application/json',
             },
           },
-        ).then(async (res) => await res.json());
+        ).then(async (res) => {
+          if (!res.ok)
+            throw new Error(
+              `Failed to fetch models: ${res.status} ${res.statusText}`,
+            );
+          return res.json();
+        });
 
         if (
           !chatModel ||
@@ -62,16 +91,18 @@ const useSocket = (
           if (!chatModel || !chatModelProvider) {
             const chatModelProviders = providers.chatModelProviders;
 
-            chatModelProvider = Object.keys(chatModelProviders)[0];
+            chatModelProvider =
+              chatModelProvider || Object.keys(chatModelProviders)[0];
 
             if (chatModelProvider === 'custom_openai') {
               toast.error(
-                'Seems like you are using the custom OpenAI provider, please open the settings and configure the API key and base URL',
+                'Seems like you are using the custom OpenAI provider, please open the settings and enter a model name to use.',
               );
               setError(true);
               return;
             } else {
               chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+
               if (
                 !chatModelProviders ||
                 Object.keys(chatModelProviders).length === 0
@@ -108,18 +139,42 @@ const useSocket = (
 
           if (
             Object.keys(chatModelProviders).length > 0 &&
-            !chatModelProviders[chatModelProvider]
+            (((!openAIBaseURL || !openAIPIKey) &&
+              chatModelProvider === 'custom_openai') ||
+              !chatModelProviders[chatModelProvider])
           ) {
-            chatModelProvider = Object.keys(chatModelProviders)[0];
+            const chatModelProvidersKeys = Object.keys(chatModelProviders);
+            chatModelProvider =
+              chatModelProvidersKeys.find(
+                (key) => Object.keys(chatModelProviders[key]).length > 0,
+              ) || chatModelProvidersKeys[0];
+
+            if (
+              chatModelProvider === 'custom_openai' &&
+              (!openAIBaseURL || !openAIPIKey)
+            ) {
+              toast.error(
+                'Seems like you are using the custom OpenAI provider, please open the settings and configure the API key and base URL',
+              );
+              setError(true);
+              return;
+            }
+
             localStorage.setItem('chatModelProvider', chatModelProvider);
           }
 
           if (
             chatModelProvider &&
-            chatModelProvider != 'custom_openai' &&
+            (!openAIBaseURL || !openAIPIKey) &&
             !chatModelProviders[chatModelProvider][chatModel]
           ) {
-            chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+            chatModel = Object.keys(
+              chatModelProviders[
+                Object.keys(chatModelProviders[chatModelProvider]).length > 0
+                  ? chatModelProvider
+                  : Object.keys(chatModelProviders)[0]
+              ],
+            )[0];
             localStorage.setItem('chatModel', chatModel);
           }
 
@@ -168,6 +223,7 @@ const useSocket = (
         wsURL.search = searchParams.toString();
 
         const ws = new WebSocket(wsURL.toString());
+        wsRef.current = ws;
 
         const timeoutId = setTimeout(() => {
           if (ws.readyState !== 1) {
@@ -183,11 +239,16 @@ const useSocket = (
             const interval = setInterval(() => {
               if (ws.readyState === 1) {
                 setIsWSReady(true);
+                setError(false);
+                if (retryCountRef.current > 0) {
+                  toast.success('Connection restored.');
+                }
+                retryCountRef.current = 0;
                 clearInterval(interval);
               }
             }, 5);
             clearTimeout(timeoutId);
-            console.log('[DEBUG] opened');
+            console.debug(new Date(), 'ws:connected');
           }
           if (data.type === 'error') {
             toast.error(data.data);
@@ -196,24 +257,68 @@ const useSocket = (
 
         ws.onerror = () => {
           clearTimeout(timeoutId);
-          setError(true);
+          setIsWSReady(false);
           toast.error('WebSocket connection error.');
         };
 
         ws.onclose = () => {
           clearTimeout(timeoutId);
-          setError(true);
+          setIsWSReady(false);
-          console.log('[DEBUG] closed');
+          console.debug(new Date(), 'ws:disconnected');
+          if (!isCleaningUpRef.current) {
+            toast.error('Connection lost. Attempting to reconnect...');
+            attemptReconnect();
+          }
         };
+      } catch (error) {
+        console.debug(new Date(), 'ws:error', error);
+        setIsWSReady(false);
+        attemptReconnect();
+      }
+    };
 
-        setWs(ws);
+    const attemptReconnect = () => {
-      };
+      retryCountRef.current += 1;
 
-      connectWs();
+      if (retryCountRef.current > MAX_RETRIES) {
-    }
+        console.debug(new Date(), 'ws:max_retries');
-  }, [ws, url, setIsWSReady, setError]);
+        setError(true);
+        toast.error(
+          'Unable to connect to server after multiple attempts. Please refresh the page to try again.',
+        );
+        return;
+      }
 
-  return ws;
+      const backoffDelay = getBackoffDelay(retryCountRef.current);
+      console.debug(
+        new Date(),
+        `ws:retry attempt=${retryCountRef.current}/${MAX_RETRIES} delay=${backoffDelay}ms`,
+      );
+
+      if (reconnectTimeoutRef.current) {
+        clearTimeout(reconnectTimeoutRef.current);
+      }
+
+      reconnectTimeoutRef.current = setTimeout(() => {
+        connectWs();
+      }, backoffDelay);
+    };
+
+    connectWs();
+
+    return () => {
+      if (reconnectTimeoutRef.current) {
+        clearTimeout(reconnectTimeoutRef.current);
+      }
+      if (wsRef.current?.readyState === WebSocket.OPEN) {
+        wsRef.current.close();
+        isCleaningUpRef.current = true;
+        console.debug(new Date(), 'ws:cleanup');
+      }
+    };
+  }, [url, setIsWSReady, setError]);
+
+  return wsRef.current;
 };
 
 const loadMessages = async (
@@ -257,7 +362,7 @@ const loadMessages = async (
     return [msg.role, msg.content];
   }) as [string, string][];
 
-  console.log('[DEBUG] messages loaded');
+  console.debug(new Date(), 'app:messages_loaded');
 
   document.title = messages[0].content;
 
@@ -310,6 +415,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
   const [notFound, setNotFound] = useState(false);
 
+  const [isSettingsOpen, setIsSettingsOpen] = useState(false);
+
   useEffect(() => {
     if (
       chatId &&
@@ -339,7 +446,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
     return () => {
       if (ws?.readyState === 1) {
         ws.close();
-        console.log('[DEBUG] closed');
+        console.debug(new Date(), 'ws:cleanup');
       }
     };
     // eslint-disable-next-line react-hooks/exhaustive-deps
@@ -354,12 +461,18 @@ const ChatWindow = ({ id }: { id?: string }) => {
   useEffect(() => {
     if (isMessagesLoaded && isWSReady) {
       setIsReady(true);
-      console.log('[DEBUG] ready');
+      console.debug(new Date(), 'app:ready');
+    } else {
+      setIsReady(false);
     }
   }, [isMessagesLoaded, isWSReady]);
 
   const sendMessage = async (message: string, messageId?: string) => {
     if (loading) return;
+    if (!ws || ws.readyState !== WebSocket.OPEN) {
+      toast.error('Cannot send message while disconnected');
+      return;
+    }
 
     setLoading(true);
     setMessageAppeared(false);
@@ -370,7 +483,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
     messageId = messageId ?? crypto.randomBytes(7).toString('hex');
 
-    ws?.send(
+    ws.send(
       JSON.stringify({
         type: 'message',
         message: {
@@ -514,17 +627,26 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
   if (hasError) {
     return (
-      <div className="flex flex-col items-center justify-center min-h-screen">
+      <div className="relative">
-        <p className="dark:text-white/70 text-black/70 text-sm">
+        <div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
-          Failed to connect to the server. Please try again later.
+          <Settings
-        </p>
+            className="cursor-pointer lg:hidden"
+            onClick={() => setIsSettingsOpen(true)}
+          />
+        </div>
+        <div className="flex flex-col items-center justify-center min-h-screen">
+          <p className="dark:text-white/70 text-black/70 text-sm">
+            Failed to connect to the server. Please try again later.
+          </p>
+        </div>
+        <SettingsDialog isOpen={isSettingsOpen} setIsOpen={setIsSettingsOpen} />
       </div>
     );
   }
 
   return isReady ? (
     notFound ? (
-      <Error statusCode={404} />
+      <NextError statusCode={404} />
     ) : (
       <div>
         {messages.length > 0 ? (

ui/components/MessageBox.tsx

@@ -11,6 +11,8 @@ import {
   StopCircle,
   Layers3,
   Plus,
+  Brain,
+  ChevronDown,
 } from 'lucide-react';
 import Markdown from 'markdown-to-jsx';
 import Copy from './MessageActions/Copy';
@@ -41,26 +43,48 @@ const MessageBox = ({
 }) => {
   const [parsedMessage, setParsedMessage] = useState(message.content);
   const [speechMessage, setSpeechMessage] = useState(message.content);
+  const [thinking, setThinking] = useState<string>('');
+  const [answer, setAnswer] = useState<string>('');
+  const [isThinkingExpanded, setIsThinkingExpanded] = useState(false);
 
   useEffect(() => {
     const regex = /\[(\d+)\]/g;
 
-    if (
+    // First check for thinking content
-      message.role === 'assistant' &&
+    const match = message.content.match(/<think>(.*?)<\/think>(.*)/s);
-      message?.sources &&
+    if (match) {
-      message.sources.length > 0
+      const [_, thinkingContent, answerContent] = match;
-    ) {
+      setThinking(thinkingContent.trim());
-      return setParsedMessage(
+      setAnswer(answerContent.trim());
-        message.content.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>`,
-        ),
-      );
-    }
 
-    setSpeechMessage(message.content.replace(regex, ''));
+      // Process the answer part for sources if needed
-    setParsedMessage(message.content);
+      if (message.role === 'assistant' && message?.sources && message.sources.length > 0) {
+        setParsedMessage(
+          answerContent.trim().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>`,
+          ),
+        );
+      } else {
+        setParsedMessage(answerContent.trim());
+      }
+      setSpeechMessage(answerContent.trim().replace(regex, ''));
+    } else {
+      // No thinking content - process as before
+      if (message.role === 'assistant' && message?.sources && message.sources.length > 0) {
+        setParsedMessage(
+          message.content.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>`,
+          ),
+        );
+      } else {
+        setParsedMessage(message.content);
+      }
+      setSpeechMessage(message.content.replace(regex, ''));
+    }
   }, [message.content, message.sources, message.role]);
 
   const { speechStatus, start, stop } = useSpeech({ text: speechMessage });
@@ -81,6 +105,37 @@ const MessageBox = ({
             ref={dividerRef}
             className="flex flex-col space-y-6 w-full lg:w-9/12"
           >
+            {thinking && (
+              <div className="flex flex-col space-y-2 mb-4">
+                <button 
+                  onClick={() => setIsThinkingExpanded(!isThinkingExpanded)}
+                  className="flex flex-row items-center space-x-2 group text-black/70 dark:text-white/70 hover:text-black dark:hover:text-white transition duration-200"
+                >
+                  <Brain size={20} />
+                  <h3 className="font-medium text-xl">View Thinking</h3>
+                  <ChevronDown 
+                    size={16}
+                    className={cn(
+                      "transition-transform duration-200",
+                      isThinkingExpanded ? "rotate-180" : ""
+                    )} 
+                  />
+                </button>
+                
+                {isThinkingExpanded && (
+                  <div className="rounded-lg bg-light-secondary/50 dark:bg-dark-secondary/50 p-4">
+                    <Markdown
+                      className={cn(
+                        'prose dark:prose-invert text-sm leading-relaxed',
+                        'max-w-none break-words'
+                      )}
+                    >
+                      {thinking}
+                    </Markdown>
+                  </div>
+                )}
+              </div>
+            )}
             {message.sources && message.sources.length > 0 && (
               <div className="flex flex-col space-y-2">
                 <div className="flex flex-row items-center space-x-2">
@@ -107,8 +162,8 @@ const MessageBox = ({
               </div>
               <Markdown
                 className={cn(
-                  'prose dark:prose-invert prose-p:leading-relaxed prose-pre:p-0',
+                  '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 text-sm md:text-base font-medium',
+                  'max-w-none break-words text-black dark:text-white',
                 )}
               >
                 {parsedMessage}
@@ -199,4 +254,3 @@ const MessageBox = ({
   );
 };
 
-export default MessageBox;

ui/components/MessageInputActions/Focus.tsx

@@ -83,7 +83,7 @@ const Focus = ({
         {focusMode !== 'webSearch' ? (
           <div className="flex flex-row items-center space-x-1">
             {focusModes.find((mode) => mode.key === focusMode)?.icon}
-            <p className="text-xs font-medium">
+            <p className="text-xs font-medium hidden lg:block">
               {focusModes.find((mode) => mode.key === focusMode)?.title}
             </p>
             <ChevronDown size={20} className="-translate-x-1" />
@@ -91,7 +91,7 @@ const Focus = ({
         ) : (
           <div className="flex flex-row items-center space-x-1">
             <ScanEye size={20} />
-            <p className="text-xs font-medium">Focus</p>
+            <p className="text-xs font-medium hidden lg:block">Focus</p>
           </div>
         )}
       </PopoverButton>

ui/components/SearchVideos.tsx

@@ -1,6 +1,6 @@
 /* eslint-disable @next/next/no-img-element */
 import { PlayCircle, PlayIcon, PlusIcon, VideoIcon } from 'lucide-react';
-import { useState } from 'react';
+import { useRef, useState } from 'react';
 import Lightbox, { GenericSlide, VideoSlide } from 'yet-another-react-lightbox';
 import 'yet-another-react-lightbox/styles.css';
 import { Message } from './ChatWindow';
@@ -35,6 +35,8 @@ const Searchvideos = ({
   const [loading, setLoading] = useState(false);
   const [open, setOpen] = useState(false);
   const [slides, setSlides] = useState<VideoSlide[]>([]);
+  const [currentIndex, setCurrentIndex] = useState(0);
+  const videoRefs = useRef<(HTMLIFrameElement | null)[]>([]);
 
   return (
     <>
@@ -182,18 +184,39 @@ const Searchvideos = ({
             open={open}
             close={() => setOpen(false)}
             slides={slides}
+            index={currentIndex}
+            on={{
+              view: ({ index }) => {
+                const previousIframe = videoRefs.current[currentIndex];
+                if (previousIframe?.contentWindow) {
+                  previousIframe.contentWindow.postMessage(
+                    '{"event":"command","func":"pauseVideo","args":""}',
+                    '*',
+                  );
+                }
+
+                setCurrentIndex(index);
+              },
+            }}
             render={{
-              slide: ({ slide }) =>
+              slide: ({ slide }) => {
-                slide.type === 'video-slide' ? (
+                const index = slides.findIndex((s) => s === slide);
+                return slide.type === 'video-slide' ? (
                   <div className="h-full w-full flex flex-row items-center justify-center">
                     <iframe
-                      src={slide.iframe_src}
+                      src={`${slide.iframe_src}${slide.iframe_src.includes('?') ? '&' : '?'}enablejsapi=1`}
+                      ref={(el) => {
+                        if (el) {
+                          videoRefs.current[index] = el;
+                        }
+                      }}
                       className="aspect-video max-h-[95vh] w-[95vw] rounded-2xl md:w-[80vw]"
                       allowFullScreen
                       allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
                     />
                   </div>
-                ) : null,
+                ) : null;
+              },
             }}
           />
         </>

ui/package.json

@@ -18,7 +18,7 @@
     "clsx": "^2.1.0",
     "langchain": "^0.1.30",
     "lucide-react": "^0.363.0",
-    "markdown-to-jsx": "^7.6.2",
+    "markdown-to-jsx": "^7.7.2",
     "next": "14.1.4",
     "next-themes": "^0.3.0",
     "react": "^18",

ui/yarn.lock

@@ -2210,10 +2210,10 @@ lucide-react@^0.363.0:
   resolved "https://registry.yarnpkg.com/lucide-react/-/lucide-react-0.363.0.tgz#2bb1f9d09b830dda86f5118fcd097f87247fe0e3"
   integrity sha512-AlsfPCsXQyQx7wwsIgzcKOL9LwC498LIMAo+c0Es5PkHJa33xwmYAkkSoKoJWWWSYQEStqu58/jT4tL2gi32uQ==
 
-markdown-to-jsx@^7.6.2:
+markdown-to-jsx@^7.7.2:
-  version "7.6.2"
+  version "7.7.2"
-  resolved "https://registry.yarnpkg.com/markdown-to-jsx/-/markdown-to-jsx-7.6.2.tgz#254cbf7d412a37073486c0a2dd52266d2191a793"
+  resolved "https://registry.yarnpkg.com/markdown-to-jsx/-/markdown-to-jsx-7.7.2.tgz#59c1dd64f48b53719311ab140be3cd51cdabccd3"
-  integrity sha512-gEcyiJXzBxmId2Y/kydLbD6KRNccDiUy/Src1cFGn3s2X0LZZ/hUiEc2VisFyA5kUE3SXclTCczjQiAuqKZiFQ==
+  integrity sha512-N3AKfYRvxNscvcIH6HDnDKILp4S8UWbebp+s92Y8SwIq0CuSbLW4Jgmrbjku3CWKjTQO0OyIMS6AhzqrwjEa3g==
 
 md5@^2.3.0:
   version "2.3.0"