Merge pull request #736 from ItzCrazyKns/master

Merge master into feat/deep-research

.github/workflows/docker-build.yaml

@@ -0,0 +1,138 @@
+name: Build & Push Docker Images
+
+on:
+  push:
+    branches:
+      - master
+  release:
+    types: [published]
+
+jobs:
+  build-amd64:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          install: true
+
+      - name: Log in to DockerHub
+        uses: docker/login-action@v2
+        with:
+          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/}" >> $GITHUB_ENV
+
+      - name: Build and push AMD64 Docker image
+        if: github.ref == 'refs/heads/master' && github.event_name == 'push'
+        run: |
+          DOCKERFILE=app.dockerfile
+          IMAGE_NAME=perplexica
+          docker buildx build --platform linux/amd64 \
+            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:amd64 \
+            --cache-to=type=inline \
+            --provenance false \
+            -f $DOCKERFILE \
+            -t itzcrazykns1337/${IMAGE_NAME}:amd64 \
+            --push .
+
+      - name: Build and push AMD64 release Docker image
+        if: github.event_name == 'release'
+        run: |
+          DOCKERFILE=app.dockerfile
+          IMAGE_NAME=perplexica
+          docker buildx build --platform linux/amd64 \
+            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-amd64 \
+            --cache-to=type=inline \
+            --provenance false \
+            -f $DOCKERFILE \
+            -t itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-amd64 \
+            --push .
+
+  build-arm64:
+    runs-on: ubuntu-24.04-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          install: true
+
+      - name: Log in to DockerHub
+        uses: docker/login-action@v2
+        with:
+          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/}" >> $GITHUB_ENV
+
+      - name: Build and push ARM64 Docker image
+        if: github.ref == 'refs/heads/master' && github.event_name == 'push'
+        run: |
+          DOCKERFILE=app.dockerfile
+          IMAGE_NAME=perplexica
+          docker buildx build --platform linux/arm64 \
+            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:arm64 \
+            --cache-to=type=inline \
+            --provenance false \
+            -f $DOCKERFILE \
+            -t itzcrazykns1337/${IMAGE_NAME}:arm64 \
+            --push .
+
+      - name: Build and push ARM64 release Docker image
+        if: github.event_name == 'release'
+        run: |
+          DOCKERFILE=app.dockerfile
+          IMAGE_NAME=perplexica
+          docker buildx build --platform linux/arm64 \
+            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-arm64 \
+            --cache-to=type=inline \
+            --provenance false \
+            -f $DOCKERFILE \
+            -t itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-arm64 \
+            --push .
+
+  manifest:
+    needs: [build-amd64, build-arm64]
+    runs-on: ubuntu-latest
+    steps:
+      - name: Log in to DockerHub
+        uses: docker/login-action@v2
+        with:
+          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/}" >> $GITHUB_ENV
+
+      - name: Create and push multi-arch manifest for main
+        if: github.ref == 'refs/heads/master' && github.event_name == 'push'
+        run: |
+          IMAGE_NAME=perplexica
+          docker manifest create itzcrazykns1337/${IMAGE_NAME}:main \
+            --amend itzcrazykns1337/${IMAGE_NAME}:amd64 \
+            --amend itzcrazykns1337/${IMAGE_NAME}:arm64
+          docker manifest push itzcrazykns1337/${IMAGE_NAME}:main
+
+      - name: Create and push multi-arch manifest for releases
+        if: github.event_name == 'release'
+        run: |
+          IMAGE_NAME=perplexica
+          docker manifest create itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }} \
+            --amend itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-amd64 \
+            --amend itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}-arm64
+          docker manifest push itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }}

.gitignore

@@ -4,8 +4,9 @@ npm-debug.log
 yarn-error.log
 
 # Build output
-/.next/
-/out/
+.next/
+out/
+dist/
 
 # IDE/Editor specific
 .vscode/
@@ -31,4 +32,8 @@ logs/
 
 # Miscellaneous
 .DS_Store
-Thumbs.db
+Thumbs.db
+
+# Db
+db.sqlite
+/searxng

.prettierignore

@@ -35,4 +35,7 @@ coverage
 *.swp
 
 # Ignore all files with the .DS_Store extension (macOS specific)
-.DS_Store
+.DS_Store
+
+# Ignore all files in uploads directory
+uploads

.prettierrc.js

@@ -6,7 +6,6 @@ const config = {
   endOfLine: 'auto',
   singleQuote: true,
   tabWidth: 2,
-  semi: true,
 };
 
 module.exports = config;

CONTRIBUTING.md

@@ -1,30 +1,43 @@
 # How to Contribute to Perplexica
 
-Hey there, thanks for deciding to contribute to Perplexica. Anything you help with will support the development of Perplexica and will make it better. Let's walk you through the key aspects to ensure your contributions are effective and in harmony with the project's setup.
+Thanks for your interest in contributing to Perplexica! Your help makes this project better. This guide explains how to contribute effectively.
+
+Perplexica is a modern AI chat application with advanced search capabilities.
 
 ## Project Structure
 
-Perplexica's design consists of two main domains:
+Perplexica's codebase is organized as follows:
 
-- **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.
+- **UI Components and Pages**:
+  - **Components (`src/components`)**: Reusable UI components.
+  - **Pages and Routes (`src/app`)**: Next.js app directory structure with page components.
+    - Main app routes include: home (`/`), chat (`/c`), discover (`/discover`), library (`/library`), and settings (`/settings`).
+  - **API Routes (`src/app/api`)**: API endpoints implemented with Next.js API routes.
+    - `/api/chat`: Handles chat interactions.
+    - `/api/search`: Provides direct access to Perplexica's search capabilities.
+    - Other endpoints for models, files, and suggestions.
+- **Backend Logic (`src/lib`)**: Contains all the backend functionality including search, database, and API logic.
+  - The search functionality is present inside `src/lib/search` directory.
+  - All of the focus modes are implemented using the Meta Search Agent class in `src/lib/search/metaSearchAgent.ts`.
+  - Database functionality is in `src/lib/db`.
+  - Chat model and embedding model providers are managed in `src/lib/providers`.
+  - Prompt templates and LLM chain definitions are in `src/lib/prompts` and `src/lib/chains` respectively.
+
+## API Documentation
+
+Perplexica exposes several API endpoints for programmatic access, including:
+
+- **Search API**: Access Perplexica's advanced search capabilities directly via the `/api/search` endpoint. For detailed documentation, see `docs/api/search.md`.
 
 ## Setting Up Your Environment
 
 Before diving into coding, setting up your local environment is key. Here's what you need to do:
 
-### Backend
-
 1. In the root directory, locate the `sample.config.toml` file.
-2. Rename it to `config.toml` and fill in the necessary configuration fields specific to the backend.
-3. Run `npm install` to install dependencies.
-4. Use `npm run dev` to start the backend in development mode.
-
-### Frontend
-
-1. Navigate to the `ui` folder and repeat the process of renaming `.env.example` to `.env`, making sure to provide the frontend-specific variables.
-2. Execute `npm install` within the `ui` directory to get the frontend dependencies ready.
-3. Launch the frontend development server with `npm run dev`.
+2. Rename it to `config.toml` and fill in the necessary configuration fields.
+3. Run `npm install` to install all dependencies.
+4. Run `npm run db:push` to set up the local sqlite database.
+5. Use `npm run dev` to start the application in development mode.
 
 **Please note**: Docker configurations are present for setting up production environments, whereas `npm run dev` is used for development purposes.
 

README.md

@@ -1,6 +1,24 @@
 # 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
 
-![preview](.assets/perplexica-screenshot.png)
+<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?)
 
 ## Table of Contents <!-- omit in toc -->
 
@@ -10,8 +28,10 @@
 - [Installation](#installation)
   - [Getting Started with Docker (Recommended)](#getting-started-with-docker-recommended)
   - [Non-Docker Installation](#non-docker-installation)
-  - [Ollama connection errors](#ollama-connection-errors)
+  - [Ollama Connection Errors](#ollama-connection-errors)
 - [Using as a Search Engine](#using-as-a-search-engine)
+- [Using Perplexica's API](#using-perplexicas-api)
+- [Expose Perplexica to a network](#expose-perplexica-to-network)
 - [One-Click Deployment](#one-click-deployment)
 - [Upcoming Features](#upcoming-features)
 - [Support Us](#support-us)
@@ -39,12 +59,13 @@ Want to know more about its architecture and how it works? You can read it [here
   - **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:
   - **All Mode:** Searches the entire web to find the best results.
-  - **Writing Assistant Mode:** Helpful for writing tasks that does not require searching the web.
+  - **Writing Assistant Mode:** Helpful for writing tasks that do not require searching the web.
   - **Academic Search Mode:** Finds articles and papers, ideal for academic research.
   - **YouTube Search Mode:** Finds YouTube videos based on the search query.
   - **Wolfram Alpha Search Mode:** Answers queries that need calculations or data analysis using Wolfram Alpha.
   - **Reddit Search Mode:** Searches Reddit for discussions and opinions related to the query.
 - **Current Information:** Some search tools might give you outdated info because they use data from crawling bots and convert them into embeddings and store them in a index. Unlike them, Perplexica uses SearxNG, a metasearch engine to get the results and rerank and get the most relevant source out of it, ensuring you always get the latest information without the overhead of daily data updates.
+- **API**: Integrate Perplexica into your existing applications and make use of its capibilities.
 
 It has many more features like image and video search. Some of the planned features are mentioned in [upcoming features](#upcoming-features).
 
@@ -67,7 +88,8 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
 
    - `OPENAI`: Your OpenAI API key. **You only need to fill this if you wish to use OpenAI's models**.
    - `OLLAMA`: Your Ollama API URL. You should enter it as `http://host.docker.internal:PORT_NUMBER`. If you installed Ollama on port 11434, use `http://host.docker.internal:11434`. For other ports, adjust accordingly. **You need to fill this if you wish to use Ollama's models instead of OpenAI's**.
-   - `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**
+   - `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.
+   - `ANTHROPIC`: Your Anthropic API key. **You only need to fill this if you wish to use Anthropic models**.
 
      **Note**: You can change these after starting Perplexica from the settings dialog.
 
@@ -85,25 +107,34 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
 
 ### Non-Docker Installation
 
-1. Clone the repository and rename the `sample.config.toml` file to `config.toml` in the root directory. Ensure you complete all required fields in this file.
-2. Rename the `.env.example` file to `.env` in the `ui` folder and fill in all necessary fields.
-3. After populating the configuration and environment files, run `npm i` in both the `ui` folder and the root directory.
-4. Install the dependencies and then execute `npm run build` in both the `ui` folder and the root directory.
-5. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
+1. Install SearXNG and allow `JSON` format in the SearXNG settings.
+2. Clone the repository and rename the `sample.config.toml` file to `config.toml` in the root directory. Ensure you complete all required fields in this file.
+3. After populating the configuration run `npm i`.
+4. Install the dependencies and then execute `npm run build`.
+5. Finally, start the app by running `npm rum start`
 
 **Note**: Using Docker is recommended as it simplifies the setup process, especially for managing environment variables and dependencies.
 
-See the [installation documentation](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/installation) for more information like exposing it your network, etc.
+See the [installation documentation](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/installation) for more information like updating, etc.
 
-### Ollama connection errors
+### Ollama Connection Errors
 
-If you're facing an Ollama connection error, it is often related to the backend not being able to connect to Ollama's API. How can you fix it? You can fix it by updating your Ollama API URL in the settings menu to the following:
+If you're encountering an Ollama connection error, it is likely due to the backend being unable to connect to Ollama's API. To fix this issue you can:
 
-On Windows: `http://host.docker.internal:11434`<br>
-On Mac: `http://host.docker.internal:11434`<br>
-On Linux: `http://private_ip_of_computer_hosting_ollama:11434`
+1. **Check your Ollama API URL:** Ensure that the API URL is correctly set in the settings menu.
+2. **Update API URL Based on OS:**
 
-You need to edit the ports accordingly.
+   - **Windows:** Use `http://host.docker.internal:11434`
+   - **Mac:** Use `http://host.docker.internal:11434`
+   - **Linux:** Use `http://<private_ip_of_host>:11434`
+
+   Adjust the port number if you're using a different one.
+
+3. **Linux Users - Expose Ollama to Network:**
+
+   - Inside `/etc/systemd/system/ollama.service`, you need to add `Environment="OLLAMA_HOST=0.0.0.0"`. Then restart Ollama by `systemctl restart ollama`. For more information see [Ollama docs](https://github.com/ollama/ollama/blob/main/docs/faq.md#setting-environment-variables-on-linux)
+
+   - Ensure that the port (default is 11434) is not blocked by your firewall.
 
 ## Using as a Search Engine
 
@@ -114,17 +145,30 @@ If you wish to use Perplexica as an alternative to traditional search engines li
 3. Add a new site search with the following URL: `http://localhost:3000/?q=%s`. Replace `localhost` with your IP address or domain name, and `3000` with the port number if Perplexica is not hosted locally.
 4. Click the add button. Now, you can use Perplexica directly from your browser's search bar.
 
+## Using Perplexica's API
+
+Perplexica also provides an API for developers looking to integrate its powerful search engine into their own applications. You can run searches, use multiple models and get answers to your queries.
+
+For more details, check out the full documentation [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/API/SEARCH.md).
+
+## Expose Perplexica to network
+
+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)
 
 ## Upcoming Features
 
-- [ ] Finalizing Copilot Mode
 - [x] Add settings page
 - [x] Adding support for local LLMs
-- [ ] Adding Discover and History Saving features
+- [x] History Saving features
 - [x] Introducing various Focus Modes
+- [x] Adding API support
+- [x] Adding Discover
+- [ ] Finalizing Copilot Mode
 
 ## Support Us
 
@@ -132,11 +176,11 @@ If you find Perplexica useful, consider giving us a star on GitHub. This helps m
 
 ### Donations
 
-We also accept donations to help sustain our project. If you would like to contribute, you can use the following button to make a donation in cryptocurrency. Thank you for your support!
+We also accept donations to help sustain our project. If you would like to contribute, you can use the following options to donate. Thank you for your support!
 
-<a href="https://nowpayments.io/donation?api_key=RFFKJH1-GRR4DQG-HFV1DZP-00G6MMK&source=lk_donation&medium=referral" target="_blank">
-  <img src="https://nowpayments.io/images/embeds/donation-button-white.svg" alt="Crypto donation button by NOWPayments">
-</a>
+| Ethereum                                              |
+| ----------------------------------------------------- |
+| Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` |
 
 ## Contribution
 

app.dockerfile

@@ -1,15 +1,27 @@
-FROM node:alpine
-
-ARG NEXT_PUBLIC_WS_URL
-ARG NEXT_PUBLIC_API_URL
-ENV NEXT_PUBLIC_WS_URL=${NEXT_PUBLIC_WS_URL}
-ENV NEXT_PUBLIC_API_URL=${NEXT_PUBLIC_API_URL}
+FROM node:20.18.0-slim AS builder
 
 WORKDIR /home/perplexica
 
-COPY ui /home/perplexica/
+COPY package.json yarn.lock ./
+RUN yarn install --frozen-lockfile --network-timeout 600000
 
-RUN yarn install
+COPY tsconfig.json next.config.mjs next-env.d.ts postcss.config.js drizzle.config.ts tailwind.config.ts ./
+COPY src ./src
+COPY public ./public
+
+RUN mkdir -p /home/perplexica/data
 RUN yarn build
 
-CMD ["yarn", "start"]
+FROM node:20.18.0-slim
+
+WORKDIR /home/perplexica
+
+COPY --from=builder /home/perplexica/public ./public
+COPY --from=builder /home/perplexica/.next/static ./public/_next/static
+
+COPY --from=builder /home/perplexica/.next/standalone ./
+COPY --from=builder /home/perplexica/data ./data
+
+RUN mkdir /home/perplexica/uploads
+
+CMD ["node", "server.js"]

backend.dockerfile

@@ -1,18 +0,0 @@
-FROM node:buster-slim
-
-ARG SEARXNG_API_URL
-
-WORKDIR /home/perplexica
-
-COPY src /home/perplexica/src
-COPY tsconfig.json /home/perplexica/
-COPY config.toml /home/perplexica/
-COPY package.json /home/perplexica/
-COPY yarn.lock /home/perplexica/
-
-RUN sed -i "s|SEARXNG = \".*\"|SEARXNG = \"${SEARXNG_API_URL}\"|g" /home/perplexica/config.toml
-
-RUN yarn install
-RUN yarn build
-
-CMD ["yarn", "start"]

data/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitignore

docker-compose.yaml

@@ -7,33 +7,28 @@ services:
       - 4000:8080
     networks:
       - perplexica-network
+    restart: unless-stopped
 
-  perplexica-backend:
-    build:
-      context: .
-      dockerfile: backend.dockerfile
-      args:
-        - SEARXNG_API_URL=http://searxng:8080
-    depends_on:
-      - searxng
-    ports:
-      - 3001:3001
-    networks:
-      - perplexica-network
-
-  perplexica-frontend:
+  app:
+    image: itzcrazykns1337/perplexica:main
     build:
       context: .
       dockerfile: app.dockerfile
-      args:
-        - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-        - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-    depends_on:
-      - perplexica-backend
+    environment:
+      - SEARXNG_API_URL=http://searxng:8080
     ports:
       - 3000:3000
     networks:
       - perplexica-network
+    volumes:
+      - backend-dbstore:/home/perplexica/data
+      - uploads:/home/perplexica/uploads
+      - ./config.toml:/home/perplexica/config.toml
+    restart: unless-stopped
 
 networks:
   perplexica-network:
+
+volumes:
+  backend-dbstore:
+  uploads:

docs/API/SEARCH.md

@@ -0,0 +1,145 @@
+# Perplexica Search API Documentation
+
+## Overview
+
+Perplexica’s Search API makes it easy to use our AI-powered search engine. You can run different types of searches, pick the models you want to use, and get the most recent info. Follow the following headings to learn more about Perplexica's search API.
+
+## Endpoint
+
+### **POST** `http://localhost:3000/api/search`
+
+**Note**: Replace `3000` with any other port if you've changed the default PORT
+
+### Request
+
+The API accepts a JSON object in the request body, where you define the focus mode, chat models, embedding models, and your query.
+
+#### Request Body Structure
+
+```json
+{
+  "chatModel": {
+    "provider": "openai",
+    "name": "gpt-4o-mini"
+  },
+  "embeddingModel": {
+    "provider": "openai",
+    "name": "text-embedding-3-large"
+  },
+  "optimizationMode": "speed",
+  "focusMode": "webSearch",
+  "query": "What is Perplexica",
+  "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
+}
+```
+
+### Request Parameters
+
+- **`chatModel`** (object, optional): Defines the chat model to be used for the query. For model details you can send a GET request at `http://localhost:3000/api/models`. Make sure to use the key value (For example "gpt-4o-mini" instead of the display name "GPT 4 omni mini").
+
+  - `provider`: Specifies the provider for the chat model (e.g., `openai`, `ollama`).
+  - `name`: The specific model from the chosen provider (e.g., `gpt-4o-mini`).
+  - Optional fields for custom OpenAI configuration:
+    - `customOpenAIBaseURL`: If you’re using a custom OpenAI instance, provide the base URL.
+    - `customOpenAIKey`: The API key for a custom OpenAI instance.
+
+- **`embeddingModel`** (object, optional): Defines the embedding model for similarity-based searching. For model details you can send a GET request at `http://localhost:3000/api/models`. Make sure to use the key value (For example "text-embedding-3-large" instead of the display name "Text Embedding 3 Large").
+
+  - `provider`: The provider for the embedding model (e.g., `openai`).
+  - `name`: The specific embedding model (e.g., `text-embedding-3-large`).
+
+- **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:
+
+  - `webSearch`, `academicSearch`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
+
+- **`optimizationMode`** (string, optional): Specifies the optimization mode to control the balance between performance and quality. Available modes:
+
+  - `speed`: Prioritize speed and return the fastest answer.
+  - `balanced`: Provide a balanced answer with good speed and reasonable quality.
+
+- **`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
+  [
+    ["human", "What is Perplexica?"],
+    ["assistant", "Perplexica is an AI-powered search engine..."]
+  ]
+  ```
+
+- **`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.
+
+#### Standard Response (stream: false)
+
+```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].",
+  "sources": [
+    {
+      "pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
+      "metadata": {
+        "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"
+      }
+    },
+    {
+      "pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
+      "metadata": {
+        "title": "Sahar Mor's Post",
+        "url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
+      }
+    }
+        ....
+  ]
+}
+```
+
+#### 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.
+- **`sources`** (array): A list of sources that were used to generate the search result. Each source includes:
+  - `pageContent`: A snippet of the relevant content from the source.
+  - `metadata`: Metadata about the source, including:
+    - `title`: The title of the webpage.
+    - `url`: The URL of the webpage.
+
+### Error Handling
+
+If an error occurs during the search process, the API will return an appropriate error message with an HTTP status code.
+
+- **400**: If the request is malformed or missing required fields (e.g., no focus mode or query).
+- **500**: If an internal server error occurs during the search.

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

@@ -1,19 +1,19 @@
-## 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).
 
 We'll understand how Perplexica works by taking an example of a scenario where a user asks: "How does an A.C. work?". We'll break down the process into steps to make it easier to understand. The steps are as follows:
 
-1. The message is sent via WS to the backend server where it invokes the chain. The chain will depend on your focus mode. For this example, let's assume we use the "webSearch" focus mode.
+1. The message is sent to the `/api/chat` route where it invokes the chain. The chain will depend on your focus mode. For this example, let's assume we use the "webSearch" focus mode.
 2. The chain is now invoked; first, the message is passed to another chain where it first predicts (using the chat history and the question) whether there is a need for sources and searching the web. If there is, it will generate a query (in accordance with the chat history) for searching the web that we'll take up later. If not, the chain will end there, and then the answer generator chain, also known as the response generator, will be started.
 3. The query returned by the first chain is passed to SearXNG to search the web for information.
 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

@@ -1,109 +0,0 @@
-# Expose Perplexica to a network
-
-This guide will show you how to make Perplexica available over a network. Follow these steps to allow computers on the same network to interact with Perplexica. Choose the instructions that match the operating system you are using.
-
-## Windows
-
-1. Open PowerShell as Administrator
-
-2. Navigate to the directory containing the `docker-compose.yaml` file
-
-3. Stop and remove the existing Perplexica containers and images:
-
-```
-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:
-
-```
-args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:31338/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:31338
-```
-
-6. Save and close the `docker-compose.yaml` file
-
-7. Rebuild and restart the Perplexica container:
-
-```
-docker compose up -d --build
-```
-
-## macOS
-
-1. Open the Terminal application
-
-2. Navigate to the directory with the `docker-compose.yaml` file:
-
-```
-cd /path/to/docker-compose.yaml
-```
-
-3. Stop and remove existing containers and images:
-
-```
-docker compose down --rmi all
-```
-
-4. Open `docker-compose.yaml` in a text editor like Sublime Text:
-
-```
-nano docker-compose.yaml
-```
-
-5. Replace `127.0.0.1` with the server IP in these lines:
-
-```
-args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:31338/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:31338
-```
-
-6. Save and exit the editor
-
-7. Rebuild and restart Perplexica:
-
-```
-docker compose up -d --build
-```
-
-## Linux
-
-1. Open the terminal
-
-2. Navigate to the `docker-compose.yaml` directory:
-
-```
-cd /path/to/docker-compose.yaml
-```
-
-3. Stop and remove containers and images:
-
-```
-docker compose down --rmi all
-```
-
-4. Edit `docker-compose.yaml`:
-
-```
-nano docker-compose.yaml
-```
-
-5. Replace `127.0.0.1` with the server IP:
-
-```
-args:
-  - NEXT_PUBLIC_API_URL=http://127.0.0.1:31338/api
-  - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:31338
-```
-
-6. Save and exit the editor
-
-7. Rebuild and restart Perplexica:
-
-```
-docker compose up -d --build
-```

docs/installation/UPDATING.md

@@ -0,0 +1,46 @@
+# Update Perplexica to the latest version
+
+To update Perplexica to the latest version, follow these steps:
+
+## For Docker users
+
+1. Clone the latest version of Perplexica from GitHub:
+
+   ```bash
+   git clone https://github.com/ItzCrazyKns/Perplexica.git
+   ```
+
+2. Navigate to the project directory.
+
+3. Check for changes in the configuration files. If the `sample.config.toml` file contains new fields, delete your existing `config.toml` file, rename `sample.config.toml` to `config.toml`, and update the configuration accordingly.
+
+4. Pull the latest images from the registry.
+
+   ```bash
+   docker compose pull
+   ```
+
+5. Update and recreate the containers.
+
+   ```bash
+   docker compose up -d
+   ```
+
+6. Once the command completes, go to http://localhost:3000 and verify the latest changes.
+
+## For non-Docker users
+
+1. Clone the latest version of Perplexica from GitHub:
+
+   ```bash
+   git clone https://github.com/ItzCrazyKns/Perplexica.git
+   ```
+
+2. Navigate to the project directory.
+
+3. Check for changes in the configuration files. If the `sample.config.toml` file contains new fields, delete your existing `config.toml` file, rename `sample.config.toml` to `config.toml`, and update the configuration accordingly.
+4. After populating the configuration run `npm i`.
+5. Install the dependencies and then execute `npm run build`.
+6. Finally, start the app by running `npm rum start`
+
+---

drizzle.config.ts

@@ -0,0 +1,10 @@
+import { defineConfig } from 'drizzle-kit';
+
+export default defineConfig({
+  dialect: 'sqlite',
+  schema: './src/lib/db/schema.ts',
+  out: './drizzle',
+  dbCredentials: {
+    url: './data/db.sqlite',
+  },
+});

next-env.d.ts

@@ -0,0 +1,5 @@
+/// <reference types="next" />
+/// <reference types="next/image-types/global" />
+
+// NOTE: This file should not be edited
+// see https://nextjs.org/docs/app/api-reference/config/typescript for more information.

next.config.mjs

@@ -1,5 +1,6 @@
 /** @type {import('next').NextConfig} */
 const nextConfig = {
+  output: 'standalone',
   images: {
     remotePatterns: [
       {
@@ -7,6 +8,7 @@ const nextConfig = {
       },
     ],
   },
+  serverExternalPackages: ['pdf-parse'],
 };
 
 export default nextConfig;

package.json

@@ -1,37 +1,65 @@
 {
-  "name": "perplexica-backend",
-  "version": "1.5.0",
+  "name": "perplexica-frontend",
+  "version": "1.10.2",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
-    "start": "node dist/app.js",
-    "build": "tsc",
-    "dev": "nodemon src/app.ts",
-    "format": "prettier . --check",
-    "format:write": "prettier . --write"
-  },
-  "devDependencies": {
-    "@types/cors": "^2.8.17",
-    "@types/express": "^4.17.21",
-    "@types/readable-stream": "^4.0.11",
-    "nodemon": "^3.1.0",
-    "prettier": "^3.2.5",
-    "ts-node": "^10.9.2",
-    "typescript": "^5.4.3"
+    "dev": "next dev",
+    "build": "npm run db:push && next build",
+    "start": "next start",
+    "lint": "next lint",
+    "format:write": "prettier . --write",
+    "db:push": "drizzle-kit push"
   },
   "dependencies": {
+    "@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/openai": "^0.0.25",
-    "@xenova/transformers": "^2.17.1",
-    "axios": "^1.6.8",
+    "@langchain/textsplitters": "^0.1.0",
+    "@tailwindcss/typography": "^0.5.12",
+    "@xenova/transformers": "^2.17.2",
+    "axios": "^1.8.3",
+    "better-sqlite3": "^11.9.1",
+    "clsx": "^2.1.0",
     "compute-cosine-similarity": "^1.1.0",
     "compute-dot": "^1.1.0",
-    "cors": "^2.8.5",
-    "dotenv": "^16.4.5",
-    "express": "^4.19.2",
+    "drizzle-orm": "^0.40.1",
+    "html-to-text": "^9.0.5",
     "langchain": "^0.1.30",
-    "winston": "^3.13.0",
-    "ws": "^8.16.0",
+    "lucide-react": "^0.363.0",
+    "markdown-to-jsx": "^7.7.2",
+    "next": "^15.2.2",
+    "next-themes": "^0.3.0",
+    "pdf-parse": "^1.1.1",
+    "react": "^18",
+    "react-dom": "^18",
+    "react-text-to-speech": "^0.14.5",
+    "react-textarea-autosize": "^8.5.3",
+    "sonner": "^1.4.41",
+    "tailwind-merge": "^2.2.2",
+    "winston": "^3.17.0",
+    "yet-another-react-lightbox": "^3.17.2",
     "zod": "^3.22.4"
+  },
+  "devDependencies": {
+    "@types/better-sqlite3": "^7.6.12",
+    "@types/html-to-text": "^9.0.4",
+    "@types/node": "^20",
+    "@types/pdf-parse": "^1.1.4",
+    "@types/react": "^18",
+    "@types/react-dom": "^18",
+    "autoprefixer": "^10.0.1",
+    "drizzle-kit": "^0.30.5",
+    "eslint": "^8",
+    "eslint-config-next": "14.1.4",
+    "postcss": "^8",
+    "prettier": "^3.2.5",
+    "tailwindcss": "^3.3.0",
+    "typescript": "^5"
   }
 }

sample.config.toml

@@ -1,11 +1,29 @@
 [GENERAL]
-PORT = 3001 # Port to run the server on
 SIMILARITY_MEASURE = "cosine" # "cosine" or "dot"
+KEEP_ALIVE = "5m" # How long to keep Ollama models loaded into memory. (Instead of using -1 use "-1m")
 
-[API_KEYS]
-OPENAI = "" # OpenAI API key - sk-1234567890abcdef1234567890abcdef
-GROQ = "" # Groq API key - gsk_1234567890abcdef1234567890abcdef
+[MODELS.OPENAI]
+API_KEY = ""
+
+[MODELS.GROQ]
+API_KEY = ""
+
+[MODELS.ANTHROPIC]
+API_KEY = ""
+
+[MODELS.GEMINI]
+API_KEY = ""
+
+[MODELS.CUSTOM_OPENAI]
+API_KEY = ""
+API_URL = ""
+MODEL_NAME = ""
+
+[MODELS.OLLAMA]
+API_URL = "" # Ollama API URL - http://host.docker.internal:11434
+
+[MODELS.DEEPSEEK]
+API_KEY = ""
 
 [API_ENDPOINTS]
-SEARXNG = "http://localhost:32768" # SearxNG API URL
-OLLAMA = "" # Ollama API URL - http://host.docker.internal:11434
+SEARXNG = "" # SearxNG API URL - http://localhost:32768

src/agents/academicSearchAgent.ts

@@ -1,265 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  PromptTemplate,
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../lib/searxng';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import computeSimilarity from '../utils/computeSimilarity';
-import logger from '../utils/logger';
-
-const basicAcademicSearchRetrieverPrompt = `
-You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
-If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
-
-Example:
-1. Follow up question: How does stable diffusion work?
-Rephrased: Stable diffusion working
-
-2. Follow up question: What is linear algebra?
-Rephrased: Linear algebra
-
-3. Follow up question: What is the third law of thermodynamics?
-Rephrased: Third law of thermodynamics
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
-`;
-
-const basicAcademicSearchResponsePrompt = `
-    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.
-
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
-    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.
-    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.
-    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.
-    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.
-
-    Aything 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 
-    talk about the context in your response. 
-
-    <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?'.
-    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()}
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalSourceRetriever'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'sources', data: event.data.output }),
-      );
-    }
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-const createBasicAcademicSearchRetrieverChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    PromptTemplate.fromTemplate(basicAcademicSearchRetrieverPrompt),
-    llm,
-    strParser,
-    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
-        return { query: '', docs: [] };
-      }
-
-      const res = await searchSearxng(input, {
-        language: 'en',
-        engines: [
-          'arxiv',
-          'google scholar',
-          'internetarchivescholar',
-          'pubmed',
-        ],
-      });
-
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
-
-      return { query: input, docs: documents };
-    }),
-  ]);
-};
-
-const createBasicAcademicSearchAnsweringChain = (
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const basicAcademicSearchRetrieverChain =
-    createBasicAcademicSearchRetrieverChain(llm);
-
-  const processDocs = async (docs: Document[]) => {
-    return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
-      .join('\n');
-  };
-
-  const rerankDocs = async ({
-    query,
-    docs,
-  }: {
-    query: string;
-    docs: Document[];
-  }) => {
-    if (docs.length === 0) {
-      return docs;
-    }
-
-    const docsWithContent = docs.filter(
-      (doc) => doc.pageContent && doc.pageContent.length > 0,
-    );
-
-    const [docEmbeddings, queryEmbedding] = await Promise.all([
-      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
-      embeddings.embedQuery(query),
-    ]);
-
-    const similarity = docEmbeddings.map((docEmbedding, i) => {
-      const sim = computeSimilarity(queryEmbedding, docEmbedding);
-
-      return {
-        index: i,
-        similarity: sim,
-      };
-    });
-
-    const sortedDocs = similarity
-      .sort((a, b) => b.similarity - a.similarity)
-      .slice(0, 15)
-      .map((sim) => docsWithContent[sim.index]);
-
-    return sortedDocs;
-  };
-
-  return RunnableSequence.from([
-    RunnableMap.from({
-      query: (input: BasicChainInput) => input.query,
-      chat_history: (input: BasicChainInput) => input.chat_history,
-      context: RunnableSequence.from([
-        (input) => ({
-          query: input.query,
-          chat_history: formatChatHistoryAsString(input.chat_history),
-        }),
-        basicAcademicSearchRetrieverChain
-          .pipe(rerankDocs)
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(processDocs),
-      ]),
-    }),
-    ChatPromptTemplate.fromMessages([
-      ['system', basicAcademicSearchResponsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const basicAcademicSearch = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const basicAcademicSearchAnsweringChain =
-      createBasicAcademicSearchAnsweringChain(llm, embeddings);
-
-    const stream = basicAcademicSearchAnsweringChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in academic search: ${err}`);
-  }
-
-  return emitter;
-};
-
-const handleAcademicSearch = (
-  message: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = basicAcademicSearch(message, history, llm, embeddings);
-  return emitter;
-};
-
-export default handleAcademicSearch;

src/agents/redditSearchAgent.ts

@@ -1,260 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  PromptTemplate,
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../lib/searxng';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import computeSimilarity from '../utils/computeSimilarity';
-import logger from '../utils/logger';
-
-const basicRedditSearchRetrieverPrompt = `
-You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
-If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
-
-Example:
-1. Follow up question: Which company is most likely to create an AGI
-Rephrased: Which company is most likely to create an AGI
-
-2. Follow up question: Is Earth flat?
-Rephrased: Is Earth flat?
-
-3. Follow up question: Is there life on Mars?
-Rephrased: Is there life on Mars?
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
-`;
-
-const basicRedditSearchResponsePrompt = `
-    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.
-
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
-    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.
-    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.
-    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.
-    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.
-
-    Aything 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 
-    talk about the context in your response. 
-
-    <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?'.
-    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()}
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalSourceRetriever'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'sources', data: event.data.output }),
-      );
-    }
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-const createBasicRedditSearchRetrieverChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    PromptTemplate.fromTemplate(basicRedditSearchRetrieverPrompt),
-    llm,
-    strParser,
-    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
-        return { query: '', docs: [] };
-      }
-
-      const res = await searchSearxng(input, {
-        language: 'en',
-        engines: ['reddit'],
-      });
-
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content ? result.content : result.title,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
-
-      return { query: input, docs: documents };
-    }),
-  ]);
-};
-
-const createBasicRedditSearchAnsweringChain = (
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const basicRedditSearchRetrieverChain =
-    createBasicRedditSearchRetrieverChain(llm);
-
-  const processDocs = async (docs: Document[]) => {
-    return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
-      .join('\n');
-  };
-
-  const rerankDocs = async ({
-    query,
-    docs,
-  }: {
-    query: string;
-    docs: Document[];
-  }) => {
-    if (docs.length === 0) {
-      return docs;
-    }
-
-    const docsWithContent = docs.filter(
-      (doc) => doc.pageContent && doc.pageContent.length > 0,
-    );
-
-    const [docEmbeddings, queryEmbedding] = await Promise.all([
-      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
-      embeddings.embedQuery(query),
-    ]);
-
-    const similarity = docEmbeddings.map((docEmbedding, i) => {
-      const sim = computeSimilarity(queryEmbedding, docEmbedding);
-
-      return {
-        index: i,
-        similarity: sim,
-      };
-    });
-
-    const sortedDocs = similarity
-      .sort((a, b) => b.similarity - a.similarity)
-      .slice(0, 15)
-      .filter((sim) => sim.similarity > 0.3)
-      .map((sim) => docsWithContent[sim.index]);
-
-    return sortedDocs;
-  };
-
-  return RunnableSequence.from([
-    RunnableMap.from({
-      query: (input: BasicChainInput) => input.query,
-      chat_history: (input: BasicChainInput) => input.chat_history,
-      context: RunnableSequence.from([
-        (input) => ({
-          query: input.query,
-          chat_history: formatChatHistoryAsString(input.chat_history),
-        }),
-        basicRedditSearchRetrieverChain
-          .pipe(rerankDocs)
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(processDocs),
-      ]),
-    }),
-    ChatPromptTemplate.fromMessages([
-      ['system', basicRedditSearchResponsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const basicRedditSearch = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const basicRedditSearchAnsweringChain =
-      createBasicRedditSearchAnsweringChain(llm, embeddings);
-    const stream = basicRedditSearchAnsweringChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in RedditSearch: ${err}`);
-  }
-
-  return emitter;
-};
-
-const handleRedditSearch = (
-  message: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = basicRedditSearch(message, history, llm, embeddings);
-  return emitter;
-};
-
-export default handleRedditSearch;

src/agents/webSearchAgent.ts

@@ -1,261 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  PromptTemplate,
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../lib/searxng';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import computeSimilarity from '../utils/computeSimilarity';
-import logger from '../utils/logger';
-
-const basicSearchRetrieverPrompt = `
-You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
-If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
-
-Example:
-1. Follow up question: What is the capital of France?
-Rephrased: Capital of france
-
-2. Follow up question: What is the population of New York City?
-Rephrased: Population of New York City
-
-3. Follow up question: What is Docker?
-Rephrased: What is Docker
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
-`;
-
-const basicWebSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries.
-
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
-    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.
-    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.
-    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.
-    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.
-
-    Aything 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 
-    talk about the context in your response. 
-
-    <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?'.
-    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()}
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalSourceRetriever'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'sources', data: event.data.output }),
-      );
-    }
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    PromptTemplate.fromTemplate(basicSearchRetrieverPrompt),
-    llm,
-    strParser,
-    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
-        return { query: '', docs: [] };
-      }
-
-      const res = await searchSearxng(input, {
-        language: 'en',
-      });
-
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
-
-      return { query: input, docs: documents };
-    }),
-  ]);
-};
-
-const createBasicWebSearchAnsweringChain = (
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const basicWebSearchRetrieverChain = createBasicWebSearchRetrieverChain(llm);
-
-  const processDocs = async (docs: Document[]) => {
-    return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
-      .join('\n');
-  };
-
-  const rerankDocs = async ({
-    query,
-    docs,
-  }: {
-    query: string;
-    docs: Document[];
-  }) => {
-    if (docs.length === 0) {
-      return docs;
-    }
-
-    const docsWithContent = docs.filter(
-      (doc) => doc.pageContent && doc.pageContent.length > 0,
-    );
-
-    const [docEmbeddings, queryEmbedding] = await Promise.all([
-      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
-      embeddings.embedQuery(query),
-    ]);
-
-    const similarity = docEmbeddings.map((docEmbedding, i) => {
-      const sim = computeSimilarity(queryEmbedding, docEmbedding);
-
-      return {
-        index: i,
-        similarity: sim,
-      };
-    });
-
-    const sortedDocs = similarity
-      .sort((a, b) => b.similarity - a.similarity)
-      .filter((sim) => sim.similarity > 0.5)
-      .slice(0, 15)
-      .map((sim) => docsWithContent[sim.index]);
-
-    return sortedDocs;
-  };
-
-  return RunnableSequence.from([
-    RunnableMap.from({
-      query: (input: BasicChainInput) => input.query,
-      chat_history: (input: BasicChainInput) => input.chat_history,
-      context: RunnableSequence.from([
-        (input) => ({
-          query: input.query,
-          chat_history: formatChatHistoryAsString(input.chat_history),
-        }),
-        basicWebSearchRetrieverChain
-          .pipe(rerankDocs)
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(processDocs),
-      ]),
-    }),
-    ChatPromptTemplate.fromMessages([
-      ['system', basicWebSearchResponsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const basicWebSearch = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const basicWebSearchAnsweringChain = createBasicWebSearchAnsweringChain(
-      llm,
-      embeddings,
-    );
-
-    const stream = basicWebSearchAnsweringChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in websearch: ${err}`);
-  }
-
-  return emitter;
-};
-
-const handleWebSearch = (
-  message: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = basicWebSearch(message, history, llm, embeddings);
-  return emitter;
-};
-
-export default handleWebSearch;

src/agents/wolframAlphaSearchAgent.ts

@@ -1,219 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  PromptTemplate,
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../lib/searxng';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import logger from '../utils/logger';
-
-const basicWolframAlphaSearchRetrieverPrompt = `
-You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
-If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
-
-Example:
-1. Follow up question: What is the atomic radius of S?
-Rephrased: Atomic radius of S
-
-2. Follow up question: What is linear algebra?
-Rephrased: Linear algebra
-
-3. Follow up question: What is the third law of thermodynamics?
-Rephrased: Third law of thermodynamics
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
-`;
-
-const basicWolframAlphaSearchResponsePrompt = `
-    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.
-
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
-    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.
-    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.
-    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.
-    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.
-
-    Aything 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 
-    talk about the context in your response. 
-
-    <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?'.
-    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()}
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalSourceRetriever'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'sources', data: event.data.output }),
-      );
-    }
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-const createBasicWolframAlphaSearchRetrieverChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    PromptTemplate.fromTemplate(basicWolframAlphaSearchRetrieverPrompt),
-    llm,
-    strParser,
-    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
-        return { query: '', docs: [] };
-      }
-
-      const res = await searchSearxng(input, {
-        language: 'en',
-        engines: ['wolframalpha'],
-      });
-
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
-
-      return { query: input, docs: documents };
-    }),
-  ]);
-};
-
-const createBasicWolframAlphaSearchAnsweringChain = (llm: BaseChatModel) => {
-  const basicWolframAlphaSearchRetrieverChain =
-    createBasicWolframAlphaSearchRetrieverChain(llm);
-
-  const processDocs = (docs: Document[]) => {
-    return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
-      .join('\n');
-  };
-
-  return RunnableSequence.from([
-    RunnableMap.from({
-      query: (input: BasicChainInput) => input.query,
-      chat_history: (input: BasicChainInput) => input.chat_history,
-      context: RunnableSequence.from([
-        (input) => ({
-          query: input.query,
-          chat_history: formatChatHistoryAsString(input.chat_history),
-        }),
-        basicWolframAlphaSearchRetrieverChain
-          .pipe(({ query, docs }) => {
-            return docs;
-          })
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(processDocs),
-      ]),
-    }),
-    ChatPromptTemplate.fromMessages([
-      ['system', basicWolframAlphaSearchResponsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const basicWolframAlphaSearch = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const basicWolframAlphaSearchAnsweringChain =
-      createBasicWolframAlphaSearchAnsweringChain(llm);
-    const stream = basicWolframAlphaSearchAnsweringChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in WolframAlphaSearch: ${err}`);
-  }
-
-  return emitter;
-};
-
-const handleWolframAlphaSearch = (
-  message: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = basicWolframAlphaSearch(message, history, llm);
-  return emitter;
-};
-
-export default handleWolframAlphaSearch;

src/agents/writingAssistant.ts

@@ -1,90 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import { RunnableSequence } from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import eventEmitter from 'events';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import logger from '../utils/logger';
-
-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.
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-const createWritingAssistantChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    ChatPromptTemplate.fromMessages([
-      ['system', writingAssistantPrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const handleWritingAssistant = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const writingAssistantChain = createWritingAssistantChain(llm);
-    const stream = writingAssistantChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in writing assistant: ${err}`);
-  }
-
-  return emitter;
-};
-
-export default handleWritingAssistant;

src/agents/youtubeSearchAgent.ts

@@ -1,261 +0,0 @@
-import { BaseMessage } from '@langchain/core/messages';
-import {
-  PromptTemplate,
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-} from '@langchain/core/prompts';
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../lib/searxng';
-import type { StreamEvent } from '@langchain/core/tracers/log_stream';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import computeSimilarity from '../utils/computeSimilarity';
-import logger from '../utils/logger';
-
-const basicYoutubeSearchRetrieverPrompt = `
-You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
-If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
-
-Example:
-1. Follow up question: How does an A.C work?
-Rephrased: A.C working
-
-2. Follow up question: Linear algebra explanation video
-Rephrased: What is linear algebra?
-
-3. Follow up question: What is theory of relativity?
-Rephrased: What is theory of relativity?
-
-Conversation:
-{chat_history}
-
-Follow up question: {query}
-Rephrased question:
-`;
-
-const basicYoutubeSearchResponsePrompt = `
-    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.
-
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
-    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.
-    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.
-    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.
-    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.
-
-    Aything 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 
-    talk about the context in your response. 
-
-    <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?'.
-    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()}
-`;
-
-const strParser = new StringOutputParser();
-
-const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
-  emitter: eventEmitter,
-) => {
-  for await (const event of stream) {
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalSourceRetriever'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'sources', data: event.data.output }),
-      );
-    }
-    if (
-      event.event === 'on_chain_stream' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: event.data.chunk }),
-      );
-    }
-    if (
-      event.event === 'on_chain_end' &&
-      event.name === 'FinalResponseGenerator'
-    ) {
-      emitter.emit('end');
-    }
-  }
-};
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-const createBasicYoutubeSearchRetrieverChain = (llm: BaseChatModel) => {
-  return RunnableSequence.from([
-    PromptTemplate.fromTemplate(basicYoutubeSearchRetrieverPrompt),
-    llm,
-    strParser,
-    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
-        return { query: '', docs: [] };
-      }
-
-      const res = await searchSearxng(input, {
-        language: 'en',
-        engines: ['youtube'],
-      });
-
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content ? result.content : result.title,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
-
-      return { query: input, docs: documents };
-    }),
-  ]);
-};
-
-const createBasicYoutubeSearchAnsweringChain = (
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const basicYoutubeSearchRetrieverChain =
-    createBasicYoutubeSearchRetrieverChain(llm);
-
-  const processDocs = async (docs: Document[]) => {
-    return docs
-      .map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
-      .join('\n');
-  };
-
-  const rerankDocs = async ({
-    query,
-    docs,
-  }: {
-    query: string;
-    docs: Document[];
-  }) => {
-    if (docs.length === 0) {
-      return docs;
-    }
-
-    const docsWithContent = docs.filter(
-      (doc) => doc.pageContent && doc.pageContent.length > 0,
-    );
-
-    const [docEmbeddings, queryEmbedding] = await Promise.all([
-      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
-      embeddings.embedQuery(query),
-    ]);
-
-    const similarity = docEmbeddings.map((docEmbedding, i) => {
-      const sim = computeSimilarity(queryEmbedding, docEmbedding);
-
-      return {
-        index: i,
-        similarity: sim,
-      };
-    });
-
-    const sortedDocs = similarity
-      .sort((a, b) => b.similarity - a.similarity)
-      .slice(0, 15)
-      .filter((sim) => sim.similarity > 0.3)
-      .map((sim) => docsWithContent[sim.index]);
-
-    return sortedDocs;
-  };
-
-  return RunnableSequence.from([
-    RunnableMap.from({
-      query: (input: BasicChainInput) => input.query,
-      chat_history: (input: BasicChainInput) => input.chat_history,
-      context: RunnableSequence.from([
-        (input) => ({
-          query: input.query,
-          chat_history: formatChatHistoryAsString(input.chat_history),
-        }),
-        basicYoutubeSearchRetrieverChain
-          .pipe(rerankDocs)
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(processDocs),
-      ]),
-    }),
-    ChatPromptTemplate.fromMessages([
-      ['system', basicYoutubeSearchResponsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]),
-    llm,
-    strParser,
-  ]).withConfig({
-    runName: 'FinalResponseGenerator',
-  });
-};
-
-const basicYoutubeSearch = (
-  query: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = new eventEmitter();
-
-  try {
-    const basicYoutubeSearchAnsweringChain =
-      createBasicYoutubeSearchAnsweringChain(llm, embeddings);
-
-    const stream = basicYoutubeSearchAnsweringChain.streamEvents(
-      {
-        chat_history: history,
-        query: query,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    handleStream(stream, emitter);
-  } catch (err) {
-    emitter.emit(
-      'error',
-      JSON.stringify({ data: 'An error has occurred please try again later' }),
-    );
-    logger.error(`Error in youtube search: ${err}`);
-  }
-
-  return emitter;
-};
-
-const handleYoutubeSearch = (
-  message: string,
-  history: BaseMessage[],
-  llm: BaseChatModel,
-  embeddings: Embeddings,
-) => {
-  const emitter = basicYoutubeSearch(message, history, llm, embeddings);
-  return emitter;
-};
-
-export default handleYoutubeSearch;

src/app.ts

@@ -1,30 +0,0 @@
-import { startWebSocketServer } from './websocket';
-import express from 'express';
-import cors from 'cors';
-import http from 'http';
-import routes from './routes';
-import { getPort } from './config';
-import logger from './utils/logger';
-
-const port = getPort();
-
-const app = express();
-const server = http.createServer(app);
-
-const corsOptions = {
-  origin: '*',
-};
-
-app.use(cors(corsOptions));
-app.use(express.json());
-
-app.use('/api', routes);
-app.get('/api', (_, res) => {
-  res.status(200).json({ status: 'ok' });
-});
-
-server.listen(port, () => {
-  logger.info(`Server is running on port ${port}`);
-});
-
-startWebSocketServer(server);

src/app/api/chat/route.ts

@@ -0,0 +1,306 @@
+import prompts from '@/lib/prompts';
+import MetaSearchAgent from '@/lib/search/metaSearchAgent';
+import crypto from 'crypto';
+import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { EventEmitter } from 'stream';
+import {
+  chatModelProviders,
+  embeddingModelProviders,
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '@/lib/providers';
+import db from '@/lib/db';
+import { chats, messages as messagesSchema } from '@/lib/db/schema';
+import { and, eq, gt } from 'drizzle-orm';
+import { getFileDetails } from '@/lib/utils/files';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { ChatOpenAI } from '@langchain/openai';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+import { searchHandlers } from '@/lib/search';
+
+export const runtime = 'nodejs';
+export const dynamic = 'force-dynamic';
+
+type Message = {
+  messageId: string;
+  chatId: string;
+  content: string;
+};
+
+type ChatModel = {
+  provider: string;
+  name: string;
+};
+
+type EmbeddingModel = {
+  provider: string;
+  name: string;
+};
+
+type Body = {
+  message: Message;
+  optimizationMode: 'speed' | 'balanced' | 'quality';
+  focusMode: string;
+  history: Array<[string, string]>;
+  files: Array<string>;
+  chatModel: ChatModel;
+  embeddingModel: EmbeddingModel;
+  systemInstructions: string;
+};
+
+const handleEmitterEvents = async (
+  stream: EventEmitter,
+  writer: WritableStreamDefaultWriter,
+  encoder: TextEncoder,
+  aiMessageId: string,
+  chatId: string,
+) => {
+  let recievedMessage = '';
+  let sources: any[] = [];
+
+  stream.on('data', (data) => {
+    const parsedData = JSON.parse(data);
+    if (parsedData.type === 'response') {
+      writer.write(
+        encoder.encode(
+          JSON.stringify({
+            type: 'message',
+            data: parsedData.data,
+            messageId: aiMessageId,
+          }) + '\n',
+        ),
+      );
+
+      recievedMessage += parsedData.data;
+    } else if (parsedData.type === 'sources') {
+      writer.write(
+        encoder.encode(
+          JSON.stringify({
+            type: 'sources',
+            data: parsedData.data,
+            messageId: aiMessageId,
+          }) + '\n',
+        ),
+      );
+
+      sources = parsedData.data;
+    }
+  });
+  stream.on('end', () => {
+    writer.write(
+      encoder.encode(
+        JSON.stringify({
+          type: 'messageEnd',
+          messageId: aiMessageId,
+        }) + '\n',
+      ),
+    );
+    writer.close();
+
+    db.insert(messagesSchema)
+      .values({
+        content: recievedMessage,
+        chatId: chatId,
+        messageId: aiMessageId,
+        role: 'assistant',
+        metadata: JSON.stringify({
+          createdAt: new Date(),
+          ...(sources && sources.length > 0 && { sources }),
+        }),
+      })
+      .execute();
+  });
+  stream.on('error', (data) => {
+    const parsedData = JSON.parse(data);
+    writer.write(
+      encoder.encode(
+        JSON.stringify({
+          type: 'error',
+          data: parsedData.data,
+        }),
+      ),
+    );
+    writer.close();
+  });
+};
+
+const handleHistorySave = async (
+  message: Message,
+  humanMessageId: string,
+  focusMode: string,
+  files: string[],
+) => {
+  const chat = await db.query.chats.findFirst({
+    where: eq(chats.id, message.chatId),
+  });
+
+  if (!chat) {
+    await db
+      .insert(chats)
+      .values({
+        id: message.chatId,
+        title: message.content,
+        createdAt: new Date().toString(),
+        focusMode: focusMode,
+        files: files.map(getFileDetails),
+      })
+      .execute();
+  }
+
+  const messageExists = await db.query.messages.findFirst({
+    where: eq(messagesSchema.messageId, humanMessageId),
+  });
+
+  if (!messageExists) {
+    await db
+      .insert(messagesSchema)
+      .values({
+        content: message.content,
+        chatId: message.chatId,
+        messageId: humanMessageId,
+        role: 'user',
+        metadata: JSON.stringify({
+          createdAt: new Date(),
+        }),
+      })
+      .execute();
+  } else {
+    await db
+      .delete(messagesSchema)
+      .where(
+        and(
+          gt(messagesSchema.id, messageExists.id),
+          eq(messagesSchema.chatId, message.chatId),
+        ),
+      )
+      .execute();
+  }
+};
+
+export const POST = async (req: Request) => {
+  try {
+    const body = (await req.json()) as Body;
+    const { message } = body;
+
+    if (message.content === '') {
+      return Response.json(
+        {
+          message: 'Please provide a message to process',
+        },
+        { status: 400 },
+      );
+    }
+
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
+
+    const chatModelProvider =
+      chatModelProviders[
+        body.chatModel?.provider || Object.keys(chatModelProviders)[0]
+      ];
+    const chatModel =
+      chatModelProvider[
+        body.chatModel?.name || Object.keys(chatModelProvider)[0]
+      ];
+
+    const embeddingProvider =
+      embeddingModelProviders[
+        body.embeddingModel?.provider || Object.keys(embeddingModelProviders)[0]
+      ];
+    const embeddingModel =
+      embeddingProvider[
+        body.embeddingModel?.name || Object.keys(embeddingProvider)[0]
+      ];
+
+    let llm: BaseChatModel | undefined;
+    let embedding = embeddingModel.model;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        openAIApiKey: getCustomOpenaiApiKey(),
+        modelName: getCustomOpenaiModelName(),
+        temperature: 0.7,
+        configuration: {
+          baseURL: getCustomOpenaiApiUrl(),
+        },
+      }) as unknown as BaseChatModel;
+    } else if (chatModelProvider && chatModel) {
+      llm = chatModel.model;
+    }
+
+    if (!llm) {
+      return Response.json({ error: 'Invalid chat model' }, { status: 400 });
+    }
+
+    if (!embedding) {
+      return Response.json(
+        { error: 'Invalid embedding model' },
+        { status: 400 },
+      );
+    }
+
+    const humanMessageId =
+      message.messageId ?? crypto.randomBytes(7).toString('hex');
+    const aiMessageId = crypto.randomBytes(7).toString('hex');
+
+    const history: BaseMessage[] = body.history.map((msg) => {
+      if (msg[0] === 'human') {
+        return new HumanMessage({
+          content: msg[1],
+        });
+      } else {
+        return new AIMessage({
+          content: msg[1],
+        });
+      }
+    });
+
+    const handler = searchHandlers[body.focusMode];
+
+    if (!handler) {
+      return Response.json(
+        {
+          message: 'Invalid focus mode',
+        },
+        { status: 400 },
+      );
+    }
+
+    const stream = await handler.searchAndAnswer(
+      message.content,
+      history,
+      llm,
+      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);
+    handleHistorySave(message, humanMessageId, body.focusMode, body.files);
+
+    return new Response(responseStream.readable, {
+      headers: {
+        'Content-Type': 'text/event-stream',
+        Connection: 'keep-alive',
+        'Cache-Control': 'no-cache, no-transform',
+      },
+    });
+  } catch (err) {
+    console.error('An error occurred while processing chat request:', err);
+    return Response.json(
+      { message: 'An error occurred while processing chat request' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/chats/[id]/route.ts

@@ -0,0 +1,69 @@
+import db from '@/lib/db';
+import { chats, messages } from '@/lib/db/schema';
+import { eq } from 'drizzle-orm';
+
+export const GET = async (
+  req: Request,
+  { params }: { params: Promise<{ id: string }> },
+) => {
+  try {
+    const { id } = await params;
+
+    const chatExists = await db.query.chats.findFirst({
+      where: eq(chats.id, id),
+    });
+
+    if (!chatExists) {
+      return Response.json({ message: 'Chat not found' }, { status: 404 });
+    }
+
+    const chatMessages = await db.query.messages.findMany({
+      where: eq(messages.chatId, id),
+    });
+
+    return Response.json(
+      {
+        chat: chatExists,
+        messages: chatMessages,
+      },
+      { status: 200 },
+    );
+  } catch (err) {
+    console.error('Error in getting chat by id: ', err);
+    return Response.json(
+      { message: 'An error has occurred.' },
+      { status: 500 },
+    );
+  }
+};
+
+export const DELETE = async (
+  req: Request,
+  { params }: { params: Promise<{ id: string }> },
+) => {
+  try {
+    const { id } = await params;
+
+    const chatExists = await db.query.chats.findFirst({
+      where: eq(chats.id, id),
+    });
+
+    if (!chatExists) {
+      return Response.json({ message: 'Chat not found' }, { status: 404 });
+    }
+
+    await db.delete(chats).where(eq(chats.id, id)).execute();
+    await db.delete(messages).where(eq(messages.chatId, id)).execute();
+
+    return Response.json(
+      { message: 'Chat deleted successfully' },
+      { status: 200 },
+    );
+  } catch (err) {
+    console.error('Error in deleting chat by id: ', err);
+    return Response.json(
+      { message: 'An error has occurred.' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/chats/route.ts

@@ -0,0 +1,15 @@
+import db from '@/lib/db';
+
+export const GET = async (req: Request) => {
+  try {
+    let chats = await db.query.chats.findMany();
+    chats = chats.reverse();
+    return Response.json({ chats: chats }, { status: 200 });
+  } catch (err) {
+    console.error('Error in getting chats: ', err);
+    return Response.json(
+      { message: 'An error has occurred.' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/config/route.ts

@@ -0,0 +1,114 @@
+import {
+  getAnthropicApiKey,
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+  getGeminiApiKey,
+  getGroqApiKey,
+  getOllamaApiEndpoint,
+  getOpenaiApiKey,
+  getDeepseekApiKey,
+  updateConfig,
+} from '@/lib/config';
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '@/lib/providers';
+
+export const GET = async (req: Request) => {
+  try {
+    const config: Record<string, any> = {};
+
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
+
+    config['chatModelProviders'] = {};
+    config['embeddingModelProviders'] = {};
+
+    for (const provider in chatModelProviders) {
+      config['chatModelProviders'][provider] = Object.keys(
+        chatModelProviders[provider],
+      ).map((model) => {
+        return {
+          name: model,
+          displayName: chatModelProviders[provider][model].displayName,
+        };
+      });
+    }
+
+    for (const provider in embeddingModelProviders) {
+      config['embeddingModelProviders'][provider] = Object.keys(
+        embeddingModelProviders[provider],
+      ).map((model) => {
+        return {
+          name: model,
+          displayName: embeddingModelProviders[provider][model].displayName,
+        };
+      });
+    }
+
+    config['openaiApiKey'] = getOpenaiApiKey();
+    config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    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 occurred while getting config:', err);
+    return Response.json(
+      { message: 'An error occurred while getting config' },
+      { status: 500 },
+    );
+  }
+};
+
+export const POST = async (req: Request) => {
+  try {
+    const config = await req.json();
+
+    const updatedConfig = {
+      MODELS: {
+        OPENAI: {
+          API_KEY: config.openaiApiKey,
+        },
+        GROQ: {
+          API_KEY: config.groqApiKey,
+        },
+        ANTHROPIC: {
+          API_KEY: config.anthropicApiKey,
+        },
+        GEMINI: {
+          API_KEY: config.geminiApiKey,
+        },
+        OLLAMA: {
+          API_URL: config.ollamaApiUrl,
+        },
+        DEEPSEEK: {
+          API_KEY: config.deepseekApiKey,
+        },
+        CUSTOM_OPENAI: {
+          API_URL: config.customOpenaiApiUrl,
+          API_KEY: config.customOpenaiApiKey,
+          MODEL_NAME: config.customOpenaiModelName,
+        },
+      },
+    };
+
+    updateConfig(updatedConfig);
+
+    return Response.json({ message: 'Config updated' }, { status: 200 });
+  } catch (err) {
+    console.error('An error occurred while updating config:', err);
+    return Response.json(
+      { message: 'An error occurred while updating config' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/discover/route.ts

@@ -0,0 +1,61 @@
+import { searchSearxng } from '@/lib/searxng';
+
+const articleWebsites = [
+  'yahoo.com',
+  'www.exchangewire.com',
+  'businessinsider.com',
+  /* 'wired.com',
+  'mashable.com',
+  'theverge.com',
+  'gizmodo.com',
+  'cnet.com',
+  'venturebeat.com', */
+];
+
+const topics = ['AI', 'tech']; /* TODO: Add UI to customize this */
+
+export const GET = async (req: Request) => {
+  try {
+    const data = (
+      await Promise.all([
+        ...new Array(articleWebsites.length * topics.length)
+          .fill(0)
+          .map(async (_, i) => {
+            return (
+              await searchSearxng(
+                `site:${articleWebsites[i % articleWebsites.length]} ${
+                  topics[i % topics.length]
+                }`,
+                {
+                  engines: ['bing news'],
+                  pageno: 1,
+                },
+              )
+            ).results;
+          }),
+      ])
+    )
+      .map((result) => result)
+      .flat()
+      .sort(() => Math.random() - 0.5);
+
+    return Response.json(
+      {
+        blogs: data,
+      },
+      {
+        status: 200,
+      },
+    );
+  } catch (err) {
+    console.error(`An error occurred in discover route: ${err}`);
+    return Response.json(
+      {
+        message: 'An error has occurred',
+      },
+      {
+        status: 500,
+      },
+    );
+  }
+};

src/app/api/images/route.ts

@@ -0,0 +1,83 @@
+import handleImageSearch from '@/lib/chains/imageSearchAgent';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+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';
+
+interface ChatModel {
+  provider: string;
+  model: string;
+}
+
+interface ImageSearchBody {
+  query: string;
+  chatHistory: any[];
+  chatModel?: ChatModel;
+}
+
+export const POST = async (req: Request) => {
+  try {
+    const body: ImageSearchBody = await req.json();
+
+    const chatHistory = body.chatHistory
+      .map((msg: any) => {
+        if (msg.role === 'user') {
+          return new HumanMessage(msg.content);
+        } else if (msg.role === 'assistant') {
+          return new AIMessage(msg.content);
+        }
+      })
+      .filter((msg) => msg !== undefined) as BaseMessage[];
+
+    const chatModelProviders = await getAvailableChatModelProviders();
+
+    const chatModelProvider =
+      chatModelProviders[
+        body.chatModel?.provider || Object.keys(chatModelProviders)[0]
+      ];
+    const chatModel =
+      chatModelProvider[
+        body.chatModel?.model || Object.keys(chatModelProvider)[0]
+      ];
+
+    let llm: BaseChatModel | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        openAIApiKey: getCustomOpenaiApiKey(),
+        modelName: getCustomOpenaiModelName(),
+        temperature: 0.7,
+        configuration: {
+          baseURL: getCustomOpenaiApiUrl(),
+        },
+      }) as unknown as BaseChatModel;
+    } else if (chatModelProvider && chatModel) {
+      llm = chatModel.model;
+    }
+
+    if (!llm) {
+      return Response.json({ error: 'Invalid chat model' }, { status: 400 });
+    }
+
+    const images = await handleImageSearch(
+      {
+        chat_history: chatHistory,
+        query: body.query,
+      },
+      llm,
+    );
+
+    return Response.json({ images }, { status: 200 });
+  } catch (err) {
+    console.error(`An error occurred while searching images: ${err}`);
+    return Response.json(
+      { message: 'An error occurred while searching images' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/models/route.ts

@@ -0,0 +1,47 @@
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '@/lib/providers';
+
+export const GET = async (req: Request) => {
+  try {
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
+
+    Object.keys(chatModelProviders).forEach((provider) => {
+      Object.keys(chatModelProviders[provider]).forEach((model) => {
+        delete (chatModelProviders[provider][model] as { model?: unknown })
+          .model;
+      });
+    });
+
+    Object.keys(embeddingModelProviders).forEach((provider) => {
+      Object.keys(embeddingModelProviders[provider]).forEach((model) => {
+        delete (embeddingModelProviders[provider][model] as { model?: unknown })
+          .model;
+      });
+    });
+
+    return Response.json(
+      {
+        chatModelProviders,
+        embeddingModelProviders,
+      },
+      {
+        status: 200,
+      },
+    );
+  } catch (err) {
+    console.error('An error occurred while fetching models', err);
+    return Response.json(
+      {
+        message: 'An error has occurred.',
+      },
+      {
+        status: 500,
+      },
+    );
+  }
+};

src/app/api/search/route.ts

@@ -0,0 +1,270 @@
+import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import type { Embeddings } from '@langchain/core/embeddings';
+import { ChatOpenAI } from '@langchain/openai';
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '@/lib/providers';
+import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+import { MetaSearchAgentType } from '@/lib/search/metaSearchAgent';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+import { searchHandlers } from '@/lib/search';
+
+interface chatModel {
+  provider: string;
+  name: string;
+  customOpenAIKey?: string;
+  customOpenAIBaseURL?: string;
+}
+
+interface embeddingModel {
+  provider: string;
+  name: string;
+}
+
+interface ChatRequestBody {
+  optimizationMode: 'speed' | 'balanced';
+  focusMode: string;
+  chatModel?: chatModel;
+  embeddingModel?: embeddingModel;
+  query: string;
+  history: Array<[string, string]>;
+  stream?: boolean;
+  systemInstructions?: string;
+}
+
+export const POST = async (req: Request) => {
+  try {
+    const body: ChatRequestBody = await req.json();
+
+    if (!body.focusMode || !body.query) {
+      return Response.json(
+        { message: 'Missing focus mode or query' },
+        { status: 400 },
+      );
+    }
+
+    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'
+        ? new HumanMessage({ content: msg[1] })
+        : new AIMessage({ content: msg[1] });
+    });
+
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
+
+    const chatModelProvider =
+      body.chatModel?.provider || Object.keys(chatModelProviders)[0];
+    const chatModel =
+      body.chatModel?.name ||
+      Object.keys(chatModelProviders[chatModelProvider])[0];
+
+    const embeddingModelProvider =
+      body.embeddingModel?.provider || Object.keys(embeddingModelProviders)[0];
+    const embeddingModel =
+      body.embeddingModel?.name ||
+      Object.keys(embeddingModelProviders[embeddingModelProvider])[0];
+
+    let llm: BaseChatModel | undefined;
+    let embeddings: Embeddings | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        modelName: body.chatModel?.name || getCustomOpenaiModelName(),
+        openAIApiKey:
+          body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
+        temperature: 0.7,
+        configuration: {
+          baseURL:
+            body.chatModel?.customOpenAIBaseURL || getCustomOpenaiApiUrl(),
+        },
+      }) as unknown as BaseChatModel;
+    } else if (
+      chatModelProviders[chatModelProvider] &&
+      chatModelProviders[chatModelProvider][chatModel]
+    ) {
+      llm = chatModelProviders[chatModelProvider][chatModel]
+        .model as unknown as BaseChatModel | undefined;
+    }
+
+    if (
+      embeddingModelProviders[embeddingModelProvider] &&
+      embeddingModelProviders[embeddingModelProvider][embeddingModel]
+    ) {
+      embeddings = embeddingModelProviders[embeddingModelProvider][
+        embeddingModel
+      ].model as Embeddings | undefined;
+    }
+
+    if (!llm || !embeddings) {
+      return Response.json(
+        { message: 'Invalid model selected' },
+        { status: 400 },
+      );
+    }
+
+    const searchHandler: MetaSearchAgentType = searchHandlers[body.focusMode];
+
+    if (!searchHandler) {
+      return Response.json({ message: 'Invalid focus mode' }, { status: 400 });
+    }
+
+    const emitter = await searchHandler.searchAndAnswer(
+      body.query,
+      history,
+      llm,
+      embeddings,
+      body.optimizationMode,
+      [],
+      body.systemInstructions || '',
+    );
+
+    if (!body.stream) {
+      return new Promise(
+        (
+          resolve: (value: Response) => void,
+          reject: (value: Response) => void,
+        ) => {
+          let message = '';
+          let sources: any[] = [];
+
+          emitter.on('data', (data: string) => {
+            try {
+              const parsedData = JSON.parse(data);
+              if (parsedData.type === 'response') {
+                message += parsedData.data;
+              } else if (parsedData.type === 'sources') {
+                sources = parsedData.data;
+              }
+            } catch (error) {
+              reject(
+                Response.json(
+                  { message: 'Error parsing data' },
+                  { status: 500 },
+                ),
+              );
+            }
+          });
+
+          emitter.on('end', () => {
+            resolve(Response.json({ message, sources }, { status: 200 }));
+          });
+
+          emitter.on('error', (error: any) => {
+            reject(
+              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(
+      { message: 'An error has occurred.' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/suggestions/route.ts

@@ -0,0 +1,81 @@
+import generateSuggestions from '@/lib/chains/suggestionGeneratorAgent';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+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';
+
+interface ChatModel {
+  provider: string;
+  model: string;
+}
+
+interface SuggestionsGenerationBody {
+  chatHistory: any[];
+  chatModel?: ChatModel;
+}
+
+export const POST = async (req: Request) => {
+  try {
+    const body: SuggestionsGenerationBody = await req.json();
+
+    const chatHistory = body.chatHistory
+      .map((msg: any) => {
+        if (msg.role === 'user') {
+          return new HumanMessage(msg.content);
+        } else if (msg.role === 'assistant') {
+          return new AIMessage(msg.content);
+        }
+      })
+      .filter((msg) => msg !== undefined) as BaseMessage[];
+
+    const chatModelProviders = await getAvailableChatModelProviders();
+
+    const chatModelProvider =
+      chatModelProviders[
+        body.chatModel?.provider || Object.keys(chatModelProviders)[0]
+      ];
+    const chatModel =
+      chatModelProvider[
+        body.chatModel?.model || Object.keys(chatModelProvider)[0]
+      ];
+
+    let llm: BaseChatModel | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        openAIApiKey: getCustomOpenaiApiKey(),
+        modelName: getCustomOpenaiModelName(),
+        temperature: 0.7,
+        configuration: {
+          baseURL: getCustomOpenaiApiUrl(),
+        },
+      }) as unknown as BaseChatModel;
+    } else if (chatModelProvider && chatModel) {
+      llm = chatModel.model;
+    }
+
+    if (!llm) {
+      return Response.json({ error: 'Invalid chat model' }, { status: 400 });
+    }
+
+    const suggestions = await generateSuggestions(
+      {
+        chat_history: chatHistory,
+      },
+      llm,
+    );
+
+    return Response.json({ suggestions }, { status: 200 });
+  } catch (err) {
+    console.error(`An error occurred while generating suggestions: ${err}`);
+    return Response.json(
+      { message: 'An error occurred while generating suggestions' },
+      { status: 500 },
+    );
+  }
+};

src/app/api/uploads/route.ts

@@ -0,0 +1,134 @@
+import { NextResponse } from 'next/server';
+import fs from 'fs';
+import path from 'path';
+import crypto from 'crypto';
+import { getAvailableEmbeddingModelProviders } from '@/lib/providers';
+import { PDFLoader } from '@langchain/community/document_loaders/fs/pdf';
+import { DocxLoader } from '@langchain/community/document_loaders/fs/docx';
+import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
+import { Document } from 'langchain/document';
+
+interface FileRes {
+  fileName: string;
+  fileExtension: string;
+  fileId: string;
+}
+
+const uploadDir = path.join(process.cwd(), 'uploads');
+
+if (!fs.existsSync(uploadDir)) {
+  fs.mkdirSync(uploadDir, { recursive: true });
+}
+
+const splitter = new RecursiveCharacterTextSplitter({
+  chunkSize: 500,
+  chunkOverlap: 100,
+});
+
+export async function POST(req: Request) {
+  try {
+    const formData = await req.formData();
+
+    const files = formData.getAll('files') as File[];
+    const embedding_model = formData.get('embedding_model');
+    const embedding_model_provider = formData.get('embedding_model_provider');
+
+    if (!embedding_model || !embedding_model_provider) {
+      return NextResponse.json(
+        { message: 'Missing embedding model or provider' },
+        { status: 400 },
+      );
+    }
+
+    const embeddingModels = await getAvailableEmbeddingModelProviders();
+    const provider =
+      embedding_model_provider ?? Object.keys(embeddingModels)[0];
+    const embeddingModel =
+      embedding_model ?? Object.keys(embeddingModels[provider as string])[0];
+
+    let embeddingsModel =
+      embeddingModels[provider as string]?.[embeddingModel as string]?.model;
+    if (!embeddingsModel) {
+      return NextResponse.json(
+        { message: 'Invalid embedding model selected' },
+        { status: 400 },
+      );
+    }
+
+    const processedFiles: FileRes[] = [];
+
+    await Promise.all(
+      files.map(async (file: any) => {
+        const fileExtension = file.name.split('.').pop();
+        if (!['pdf', 'docx', 'txt'].includes(fileExtension!)) {
+          return NextResponse.json(
+            { message: 'File type not supported' },
+            { status: 400 },
+          );
+        }
+
+        const uniqueFileName = `${crypto.randomBytes(16).toString('hex')}.${fileExtension}`;
+        const filePath = path.join(uploadDir, uniqueFileName);
+
+        const buffer = Buffer.from(await file.arrayBuffer());
+        fs.writeFileSync(filePath, new Uint8Array(buffer));
+
+        let docs: any[] = [];
+        if (fileExtension === 'pdf') {
+          const loader = new PDFLoader(filePath);
+          docs = await loader.load();
+        } else if (fileExtension === 'docx') {
+          const loader = new DocxLoader(filePath);
+          docs = await loader.load();
+        } else if (fileExtension === 'txt') {
+          const text = fs.readFileSync(filePath, 'utf-8');
+          docs = [
+            new Document({ pageContent: text, metadata: { title: file.name } }),
+          ];
+        }
+
+        const splitted = await splitter.splitDocuments(docs);
+
+        const extractedDataPath = filePath.replace(/\.\w+$/, '-extracted.json');
+        fs.writeFileSync(
+          extractedDataPath,
+          JSON.stringify({
+            title: file.name,
+            contents: splitted.map((doc) => doc.pageContent),
+          }),
+        );
+
+        const embeddings = await embeddingsModel.embedDocuments(
+          splitted.map((doc) => doc.pageContent),
+        );
+        const embeddingsDataPath = filePath.replace(
+          /\.\w+$/,
+          '-embeddings.json',
+        );
+        fs.writeFileSync(
+          embeddingsDataPath,
+          JSON.stringify({
+            title: file.name,
+            embeddings,
+          }),
+        );
+
+        processedFiles.push({
+          fileName: file.name,
+          fileExtension: fileExtension,
+          fileId: uniqueFileName.replace(/\.\w+$/, ''),
+        });
+      }),
+    );
+
+    return NextResponse.json({
+      files: processedFiles,
+    });
+  } catch (error) {
+    console.error('Error uploading file:', error);
+    return NextResponse.json(
+      { message: 'An error has occurred.' },
+      { status: 500 },
+    );
+  }
+}

src/app/api/videos/route.ts

@@ -0,0 +1,83 @@
+import handleVideoSearch from '@/lib/chains/videoSearchAgent';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+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';
+
+interface ChatModel {
+  provider: string;
+  model: string;
+}
+
+interface VideoSearchBody {
+  query: string;
+  chatHistory: any[];
+  chatModel?: ChatModel;
+}
+
+export const POST = async (req: Request) => {
+  try {
+    const body: VideoSearchBody = await req.json();
+
+    const chatHistory = body.chatHistory
+      .map((msg: any) => {
+        if (msg.role === 'user') {
+          return new HumanMessage(msg.content);
+        } else if (msg.role === 'assistant') {
+          return new AIMessage(msg.content);
+        }
+      })
+      .filter((msg) => msg !== undefined) as BaseMessage[];
+
+    const chatModelProviders = await getAvailableChatModelProviders();
+
+    const chatModelProvider =
+      chatModelProviders[
+        body.chatModel?.provider || Object.keys(chatModelProviders)[0]
+      ];
+    const chatModel =
+      chatModelProvider[
+        body.chatModel?.model || Object.keys(chatModelProvider)[0]
+      ];
+
+    let llm: BaseChatModel | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        openAIApiKey: getCustomOpenaiApiKey(),
+        modelName: getCustomOpenaiModelName(),
+        temperature: 0.7,
+        configuration: {
+          baseURL: getCustomOpenaiApiUrl(),
+        },
+      }) as unknown as BaseChatModel;
+    } else if (chatModelProvider && chatModel) {
+      llm = chatModel.model;
+    }
+
+    if (!llm) {
+      return Response.json({ error: 'Invalid chat model' }, { status: 400 });
+    }
+
+    const videos = await handleVideoSearch(
+      {
+        chat_history: chatHistory,
+        query: body.query,
+      },
+      llm,
+    );
+
+    return Response.json({ videos }, { status: 200 });
+  } catch (err) {
+    console.error(`An error occurred while searching videos: ${err}`);
+    return Response.json(
+      { message: 'An error occurred while searching videos' },
+      { status: 500 },
+    );
+  }
+};

src/app/c/[chatId]/page.tsx

@@ -0,0 +1,9 @@
+import ChatWindow from '@/components/ChatWindow';
+import React from 'react';
+
+const Page = ({ params }: { params: Promise<{ chatId: string }> }) => {
+  const { chatId } = React.use(params);
+  return <ChatWindow id={chatId} />;
+};
+
+export default Page;

src/app/discover/page.tsx

@@ -0,0 +1,113 @@
+'use client';
+
+import { Search } from 'lucide-react';
+import { useEffect, useState } from 'react';
+import Link from 'next/link';
+import { toast } from 'sonner';
+
+interface Discover {
+  title: string;
+  content: string;
+  url: string;
+  thumbnail: string;
+}
+
+const Page = () => {
+  const [discover, setDiscover] = useState<Discover[] | null>(null);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    const fetchData = async () => {
+      try {
+        const res = await fetch(`/api/discover`, {
+          method: 'GET',
+          headers: {
+            'Content-Type': 'application/json',
+          },
+        });
+
+        const data = await res.json();
+
+        if (!res.ok) {
+          throw new Error(data.message);
+        }
+
+        data.blogs = data.blogs.filter((blog: Discover) => blog.thumbnail);
+
+        setDiscover(data.blogs);
+      } catch (err: any) {
+        console.error('Error fetching data:', err.message);
+        toast.error('Error fetching data');
+      } finally {
+        setLoading(false);
+      }
+    };
+
+    fetchData();
+  }, []);
+
+  return loading ? (
+    <div className="flex flex-row items-center justify-center min-h-screen">
+      <svg
+        aria-hidden="true"
+        className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
+        viewBox="0 0 100 101"
+        fill="none"
+        xmlns="http://www.w3.org/2000/svg"
+      >
+        <path
+          d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
+          fill="currentColor"
+        />
+        <path
+          d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
+          fill="currentFill"
+        />
+      </svg>
+    </div>
+  ) : (
+    <>
+      <div>
+        <div className="flex flex-col pt-4">
+          <div className="flex items-center">
+            <Search />
+            <h1 className="text-3xl font-medium p-2">Discover</h1>
+          </div>
+          <hr className="border-t border-[#2B2C2C] my-4 w-full" />
+        </div>
+
+        <div className="grid lg:grid-cols-3 sm:grid-cols-2 grid-cols-1 gap-4 pb-28 lg:pb-8 w-full justify-items-center lg:justify-items-start">
+          {discover &&
+            discover?.map((item, i) => (
+              <Link
+                href={`/?q=Summary: ${item.url}`}
+                key={i}
+                className="max-w-sm rounded-lg overflow-hidden bg-light-secondary dark:bg-dark-secondary hover:-translate-y-[1px] transition duration-200"
+                target="_blank"
+              >
+                <img
+                  className="object-cover w-full aspect-video"
+                  src={
+                    new URL(item.thumbnail).origin +
+                    new URL(item.thumbnail).pathname +
+                    `?id=${new URL(item.thumbnail).searchParams.get('id')}`
+                  }
+                  alt={item.title}
+                />
+                <div className="px-6 py-4">
+                  <div className="font-bold text-lg mb-2">
+                    {item.title.slice(0, 100)}...
+                  </div>
+                  <p className="text-black-70 dark:text-white/70 text-sm">
+                    {item.content.slice(0, 100)}...
+                  </p>
+                </div>
+              </Link>
+            ))}
+        </div>
+      </div>
+    </>
+  );
+};
+
+export default Page;

src/app/layout.tsx

@@ -4,6 +4,7 @@ import './globals.css';
 import { cn } from '@/lib/utils';
 import Sidebar from '@/components/Sidebar';
 import { Toaster } from 'sonner';
+import ThemeProvider from '@/components/theme/Provider';
 
 const montserrat = Montserrat({
   weight: ['300', '400', '500', '700'],
@@ -24,18 +25,20 @@ export default function RootLayout({
   children: React.ReactNode;
 }>) {
   return (
-    <html className="h-full" lang="en">
+    <html className="h-full" lang="en" suppressHydrationWarning>
       <body className={cn('h-full', montserrat.className)}>
-        <Sidebar>{children}</Sidebar>
-        <Toaster
-          toastOptions={{
-            unstyled: true,
-            classNames: {
-              toast:
-                'bg-[#111111] text-white rounded-lg p-4 flex flex-row items-center space-x-2',
-            },
-          }}
-        />
+        <ThemeProvider>
+          <Sidebar>{children}</Sidebar>
+          <Toaster
+            toastOptions={{
+              unstyled: true,
+              classNames: {
+                toast:
+                  'bg-light-primary dark:bg-dark-secondary dark:text-white/70 text-black-70 rounded-lg p-4 flex flex-row items-center space-x-2',
+              },
+            }}
+          />
+        </ThemeProvider>
       </body>
     </html>
   );

src/app/library/layout.tsx

@@ -0,0 +1,12 @@
+import { Metadata } from 'next';
+import React from 'react';
+
+export const metadata: Metadata = {
+  title: 'Library - Perplexica',
+};
+
+const Layout = ({ children }: { children: React.ReactNode }) => {
+  return <div>{children}</div>;
+};
+
+export default Layout;

src/app/library/page.tsx

@@ -0,0 +1,114 @@
+'use client';
+
+import DeleteChat from '@/components/DeleteChat';
+import { cn, formatTimeDifference } from '@/lib/utils';
+import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react';
+import Link from 'next/link';
+import { useEffect, useState } from 'react';
+
+export interface Chat {
+  id: string;
+  title: string;
+  createdAt: string;
+  focusMode: string;
+}
+
+const Page = () => {
+  const [chats, setChats] = useState<Chat[]>([]);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    const fetchChats = async () => {
+      setLoading(true);
+
+      const res = await fetch(`/api/chats`, {
+        method: 'GET',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+      });
+
+      const data = await res.json();
+
+      setChats(data.chats);
+      setLoading(false);
+    };
+
+    fetchChats();
+  }, []);
+
+  return loading ? (
+    <div className="flex flex-row items-center justify-center min-h-screen">
+      <svg
+        aria-hidden="true"
+        className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
+        viewBox="0 0 100 101"
+        fill="none"
+        xmlns="http://www.w3.org/2000/svg"
+      >
+        <path
+          d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
+          fill="currentColor"
+        />
+        <path
+          d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
+          fill="currentFill"
+        />
+      </svg>
+    </div>
+  ) : (
+    <div>
+      <div className="flex flex-col pt-4">
+        <div className="flex items-center">
+          <BookOpenText />
+          <h1 className="text-3xl font-medium p-2">Library</h1>
+        </div>
+        <hr className="border-t border-[#2B2C2C] my-4 w-full" />
+      </div>
+      {chats.length === 0 && (
+        <div className="flex flex-row items-center justify-center min-h-screen">
+          <p className="text-black/70 dark:text-white/70 text-sm">
+            No chats found.
+          </p>
+        </div>
+      )}
+      {chats.length > 0 && (
+        <div className="flex flex-col pb-20 lg:pb-2">
+          {chats.map((chat, i) => (
+            <div
+              className={cn(
+                'flex flex-col space-y-4 py-6',
+                i !== chats.length - 1
+                  ? 'border-b border-white-200 dark:border-dark-200'
+                  : '',
+              )}
+              key={i}
+            >
+              <Link
+                href={`/c/${chat.id}`}
+                className="text-black dark:text-white lg:text-xl font-medium truncate transition duration-200 hover:text-[#24A0ED] dark:hover:text-[#24A0ED] cursor-pointer"
+              >
+                {chat.title}
+              </Link>
+              <div className="flex flex-row items-center justify-between w-full">
+                <div className="flex flex-row items-center space-x-1 lg:space-x-1.5 text-black/70 dark:text-white/70">
+                  <ClockIcon size={15} />
+                  <p className="text-xs">
+                    {formatTimeDifference(new Date(), chat.createdAt)} Ago
+                  </p>
+                </div>
+                <DeleteChat
+                  chatId={chat.id}
+                  chats={chats}
+                  setChats={setChats}
+                />
+              </div>
+            </div>
+          ))}
+        </div>
+      )}
+    </div>
+  );
+};
+
+export default Page;

src/app/settings/page.tsx

@@ -0,0 +1,870 @@
+'use client';
+
+import { Settings as SettingsIcon, ArrowLeft, Loader2 } from 'lucide-react';
+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 Link from 'next/link';
+
+interface SettingsType {
+  chatModelProviders: {
+    [key: string]: [Record<string, any>];
+  };
+  embeddingModelProviders: {
+    [key: string]: [Record<string, any>];
+  };
+  openaiApiKey: string;
+  groqApiKey: string;
+  anthropicApiKey: string;
+  geminiApiKey: string;
+  ollamaApiUrl: string;
+  deepseekApiKey: string;
+  customOpenaiApiKey: string;
+  customOpenaiApiUrl: string;
+  customOpenaiModelName: string;
+}
+
+interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
+  isSaving?: boolean;
+  onSave?: (value: string) => void;
+}
+
+const Input = ({ className, isSaving, onSave, ...restProps }: InputProps) => {
+  return (
+    <div className="relative">
+      <input
+        {...restProps}
+        className={cn(
+          'bg-light-secondary dark:bg-dark-secondary w-full px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
+          isSaving && 'pr-10',
+          className,
+        )}
+        onBlur={(e) => onSave?.(e.target.value)}
+      />
+      {isSaving && (
+        <div className="absolute right-3 top-1/2 -translate-y-1/2">
+          <Loader2
+            size={16}
+            className="animate-spin text-black/70 dark:text-white/70"
+          />
+        </div>
+      )}
+    </div>
+  );
+};
+
+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,
+  ...restProps
+}: React.SelectHTMLAttributes<HTMLSelectElement> & {
+  options: { value: string; label: string; disabled?: boolean }[];
+}) => {
+  return (
+    <select
+      {...restProps}
+      className={cn(
+        'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
+        className,
+      )}
+    >
+      {options.map(({ label, value, disabled }) => (
+        <option key={value} value={value} disabled={disabled}>
+          {label}
+        </option>
+      ))}
+    </select>
+  );
+};
+
+const SettingsSection = ({
+  title,
+  children,
+}: {
+  title: string;
+  children: React.ReactNode;
+}) => (
+  <div className="flex flex-col space-y-4 p-4 bg-light-secondary/50 dark:bg-dark-secondary/50 rounded-xl border border-light-200 dark:border-dark-200">
+    <h2 className="text-black/90 dark:text-white/90 font-medium">{title}</h2>
+    {children}
+  </div>
+);
+
+const Page = () => {
+  const [config, setConfig] = useState<SettingsType | null>(null);
+  const [chatModels, setChatModels] = useState<Record<string, any>>({});
+  const [embeddingModels, setEmbeddingModels] = useState<Record<string, any>>(
+    {},
+  );
+  const [selectedChatModelProvider, setSelectedChatModelProvider] = useState<
+    string | null
+  >(null);
+  const [selectedChatModel, setSelectedChatModel] = useState<string | null>(
+    null,
+  );
+  const [selectedEmbeddingModelProvider, setSelectedEmbeddingModelProvider] =
+    useState<string | null>(null);
+  const [selectedEmbeddingModel, setSelectedEmbeddingModel] = useState<
+    string | null
+  >(null);
+  const [isLoading, setIsLoading] = useState(false);
+  const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
+  const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
+  const [systemInstructions, setSystemInstructions] = useState<string>('');
+  const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
+
+  useEffect(() => {
+    const fetchConfig = async () => {
+      setIsLoading(true);
+      const res = await fetch(`/api/config`, {
+        headers: {
+          'Content-Type': 'application/json',
+        },
+      });
+
+      const data = (await res.json()) as SettingsType;
+      setConfig(data);
+
+      const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
+      const embeddingModelProvidersKeys = Object.keys(
+        data.embeddingModelProviders || {},
+      );
+
+      const defaultChatModelProvider =
+        chatModelProvidersKeys.length > 0 ? chatModelProvidersKeys[0] : '';
+      const defaultEmbeddingModelProvider =
+        embeddingModelProvidersKeys.length > 0
+          ? embeddingModelProvidersKeys[0]
+          : '';
+
+      const chatModelProvider =
+        localStorage.getItem('chatModelProvider') ||
+        defaultChatModelProvider ||
+        '';
+      const chatModel =
+        localStorage.getItem('chatModel') ||
+        (data.chatModelProviders &&
+        data.chatModelProviders[chatModelProvider]?.length > 0
+          ? data.chatModelProviders[chatModelProvider][0].name
+          : undefined) ||
+        '';
+      const embeddingModelProvider =
+        localStorage.getItem('embeddingModelProvider') ||
+        defaultEmbeddingModelProvider ||
+        '';
+      const embeddingModel =
+        localStorage.getItem('embeddingModel') ||
+        (data.embeddingModelProviders &&
+          data.embeddingModelProviders[embeddingModelProvider]?.[0].name) ||
+        '';
+
+      setSelectedChatModelProvider(chatModelProvider);
+      setSelectedChatModel(chatModel);
+      setSelectedEmbeddingModelProvider(embeddingModelProvider);
+      setSelectedEmbeddingModel(embeddingModel);
+      setChatModels(data.chatModelProviders || {});
+      setEmbeddingModels(data.embeddingModelProviders || {});
+
+      setAutomaticImageSearch(
+        localStorage.getItem('autoImageSearch') === 'true',
+      );
+      setAutomaticVideoSearch(
+        localStorage.getItem('autoVideoSearch') === 'true',
+      );
+
+      setSystemInstructions(localStorage.getItem('systemInstructions')!);
+
+      setIsLoading(false);
+    };
+
+    fetchConfig();
+  }, []);
+
+  const saveConfig = async (key: string, value: any) => {
+    setSavingStates((prev) => ({ ...prev, [key]: true }));
+
+    try {
+      const updatedConfig = {
+        ...config,
+        [key]: value,
+      } as SettingsType;
+
+      const response = await fetch(`/api/config`, {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+        body: JSON.stringify(updatedConfig),
+      });
+
+      if (!response.ok) {
+        throw new Error('Failed to update config');
+      }
+
+      setConfig(updatedConfig);
+
+      if (
+        key.toLowerCase().includes('api') ||
+        key.toLowerCase().includes('url')
+      ) {
+        const res = await fetch(`/api/config`, {
+          headers: {
+            'Content-Type': 'application/json',
+          },
+        });
+
+        if (!res.ok) {
+          throw new Error('Failed to fetch updated config');
+        }
+
+        const data = await res.json();
+
+        setChatModels(data.chatModelProviders || {});
+        setEmbeddingModels(data.embeddingModelProviders || {});
+
+        const currentChatProvider = selectedChatModelProvider;
+        const newChatProviders = Object.keys(data.chatModelProviders || {});
+
+        if (!currentChatProvider && newChatProviders.length > 0) {
+          const firstProvider = newChatProviders[0];
+          const firstModel = data.chatModelProviders[firstProvider]?.[0]?.name;
+
+          if (firstModel) {
+            setSelectedChatModelProvider(firstProvider);
+            setSelectedChatModel(firstModel);
+            localStorage.setItem('chatModelProvider', firstProvider);
+            localStorage.setItem('chatModel', firstModel);
+          }
+        } else if (
+          currentChatProvider &&
+          (!data.chatModelProviders ||
+            !data.chatModelProviders[currentChatProvider] ||
+            !Array.isArray(data.chatModelProviders[currentChatProvider]) ||
+            data.chatModelProviders[currentChatProvider].length === 0)
+        ) {
+          const firstValidProvider = Object.entries(
+            data.chatModelProviders || {},
+          ).find(
+            ([_, models]) => Array.isArray(models) && models.length > 0,
+          )?.[0];
+
+          if (firstValidProvider) {
+            setSelectedChatModelProvider(firstValidProvider);
+            setSelectedChatModel(
+              data.chatModelProviders[firstValidProvider][0].name,
+            );
+            localStorage.setItem('chatModelProvider', firstValidProvider);
+            localStorage.setItem(
+              'chatModel',
+              data.chatModelProviders[firstValidProvider][0].name,
+            );
+          } else {
+            setSelectedChatModelProvider(null);
+            setSelectedChatModel(null);
+            localStorage.removeItem('chatModelProvider');
+            localStorage.removeItem('chatModel');
+          }
+        }
+
+        const currentEmbeddingProvider = selectedEmbeddingModelProvider;
+        const newEmbeddingProviders = Object.keys(
+          data.embeddingModelProviders || {},
+        );
+
+        if (!currentEmbeddingProvider && newEmbeddingProviders.length > 0) {
+          const firstProvider = newEmbeddingProviders[0];
+          const firstModel =
+            data.embeddingModelProviders[firstProvider]?.[0]?.name;
+
+          if (firstModel) {
+            setSelectedEmbeddingModelProvider(firstProvider);
+            setSelectedEmbeddingModel(firstModel);
+            localStorage.setItem('embeddingModelProvider', firstProvider);
+            localStorage.setItem('embeddingModel', firstModel);
+          }
+        } else if (
+          currentEmbeddingProvider &&
+          (!data.embeddingModelProviders ||
+            !data.embeddingModelProviders[currentEmbeddingProvider] ||
+            !Array.isArray(
+              data.embeddingModelProviders[currentEmbeddingProvider],
+            ) ||
+            data.embeddingModelProviders[currentEmbeddingProvider].length === 0)
+        ) {
+          const firstValidProvider = Object.entries(
+            data.embeddingModelProviders || {},
+          ).find(
+            ([_, models]) => Array.isArray(models) && models.length > 0,
+          )?.[0];
+
+          if (firstValidProvider) {
+            setSelectedEmbeddingModelProvider(firstValidProvider);
+            setSelectedEmbeddingModel(
+              data.embeddingModelProviders[firstValidProvider][0].name,
+            );
+            localStorage.setItem('embeddingModelProvider', firstValidProvider);
+            localStorage.setItem(
+              'embeddingModel',
+              data.embeddingModelProviders[firstValidProvider][0].name,
+            );
+          } else {
+            setSelectedEmbeddingModelProvider(null);
+            setSelectedEmbeddingModel(null);
+            localStorage.removeItem('embeddingModelProvider');
+            localStorage.removeItem('embeddingModel');
+          }
+        }
+
+        setConfig(data);
+      }
+
+      if (key === 'automaticImageSearch') {
+        localStorage.setItem('autoImageSearch', value.toString());
+      } else if (key === 'automaticVideoSearch') {
+        localStorage.setItem('autoVideoSearch', value.toString());
+      } else if (key === 'chatModelProvider') {
+        localStorage.setItem('chatModelProvider', value);
+      } else if (key === 'chatModel') {
+        localStorage.setItem('chatModel', value);
+      } else if (key === 'embeddingModelProvider') {
+        localStorage.setItem('embeddingModelProvider', value);
+      } else if (key === 'embeddingModel') {
+        localStorage.setItem('embeddingModel', value);
+      } else if (key === 'systemInstructions') {
+        localStorage.setItem('systemInstructions', value);
+      }
+    } catch (err) {
+      console.error('Failed to save:', err);
+      setConfig((prev) => ({ ...prev! }));
+    } finally {
+      setTimeout(() => {
+        setSavingStates((prev) => ({ ...prev, [key]: false }));
+      }, 500);
+    }
+  };
+
+  return (
+    <div className="max-w-3xl mx-auto">
+      <div className="flex flex-col pt-4">
+        <div className="flex items-center space-x-2">
+          <Link href="/" className="lg:hidden">
+            <ArrowLeft className="text-black/70 dark:text-white/70" />
+          </Link>
+          <div className="flex flex-row space-x-0.5 items-center">
+            <SettingsIcon size={23} />
+            <h1 className="text-3xl font-medium p-2">Settings</h1>
+          </div>
+        </div>
+        <hr className="border-t border-[#2B2C2C] my-4 w-full" />
+      </div>
+
+      {isLoading ? (
+        <div className="flex flex-row items-center justify-center min-h-[50vh]">
+          <svg
+            aria-hidden="true"
+            className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
+            viewBox="0 0 100 101"
+            fill="none"
+            xmlns="http://www.w3.org/2000/svg"
+          >
+            <path
+              d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
+              fill="currentColor"
+            />
+            <path
+              d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
+              fill="currentFill"
+            />
+          </svg>
+        </div>
+      ) : (
+        config && (
+          <div className="flex flex-col space-y-6 pb-28 lg:pb-8">
+            <SettingsSection title="Appearance">
+              <div className="flex flex-col space-y-1">
+                <p className="text-black/70 dark:text-white/70 text-sm">
+                  Theme
+                </p>
+                <ThemeSwitcher />
+              </div>
+            </SettingsSection>
+
+            <SettingsSection title="Automatic Search">
+              <div className="flex flex-col space-y-4">
+                <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">
+                      <ImagesIcon
+                        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 Image Search
+                      </p>
+                      <p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
+                        Automatically search for relevant images in chat
+                        responses
+                      </p>
+                    </div>
+                  </div>
+                  <Switch
+                    checked={automaticImageSearch}
+                    onChange={(checked) => {
+                      setAutomaticImageSearch(checked);
+                      saveConfig('automaticImageSearch', checked);
+                    }}
+                    className={cn(
+                      automaticImageSearch
+                        ? '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(
+                        automaticImageSearch
+                          ? 'translate-x-6'
+                          : 'translate-x-1',
+                        'inline-block h-4 w-4 transform rounded-full bg-white transition-transform',
+                      )}
+                    />
+                  </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">
+                      <VideoIcon
+                        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 Video Search
+                      </p>
+                      <p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
+                        Automatically search for relevant videos in chat
+                        responses
+                      </p>
+                    </div>
+                  </div>
+                  <Switch
+                    checked={automaticVideoSearch}
+                    onChange={(checked) => {
+                      setAutomaticVideoSearch(checked);
+                      saveConfig('automaticVideoSearch', checked);
+                    }}
+                    className={cn(
+                      automaticVideoSearch
+                        ? '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(
+                        automaticVideoSearch
+                          ? '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>
+
+            <SettingsSection title="Model Settings">
+              {config.chatModelProviders && (
+                <div className="flex flex-col space-y-4">
+                  <div className="flex flex-col space-y-1">
+                    <p className="text-black/70 dark:text-white/70 text-sm">
+                      Chat Model Provider
+                    </p>
+                    <Select
+                      value={selectedChatModelProvider ?? undefined}
+                      onChange={(e) => {
+                        const value = e.target.value;
+                        setSelectedChatModelProvider(value);
+                        saveConfig('chatModelProvider', value);
+                        const firstModel =
+                          config.chatModelProviders[value]?.[0]?.name;
+                        if (firstModel) {
+                          setSelectedChatModel(firstModel);
+                          saveConfig('chatModel', firstModel);
+                        }
+                      }}
+                      options={Object.keys(config.chatModelProviders).map(
+                        (provider) => ({
+                          value: provider,
+                          label:
+                            provider.charAt(0).toUpperCase() +
+                            provider.slice(1),
+                        }),
+                      )}
+                    />
+                  </div>
+
+                  {selectedChatModelProvider &&
+                    selectedChatModelProvider != 'custom_openai' && (
+                      <div className="flex flex-col space-y-1">
+                        <p className="text-black/70 dark:text-white/70 text-sm">
+                          Chat Model
+                        </p>
+                        <Select
+                          value={selectedChatModel ?? undefined}
+                          onChange={(e) => {
+                            const value = e.target.value;
+                            setSelectedChatModel(value);
+                            saveConfig('chatModel', value);
+                          }}
+                          options={(() => {
+                            const chatModelProvider =
+                              config.chatModelProviders[
+                                selectedChatModelProvider
+                              ];
+                            return chatModelProvider
+                              ? chatModelProvider.length > 0
+                                ? chatModelProvider.map((model) => ({
+                                    value: model.name,
+                                    label: model.displayName,
+                                  }))
+                                : [
+                                    {
+                                      value: '',
+                                      label: 'No models available',
+                                      disabled: true,
+                                    },
+                                  ]
+                              : [
+                                  {
+                                    value: '',
+                                    label:
+                                      'Invalid provider, please check backend logs',
+                                    disabled: true,
+                                  },
+                                ];
+                          })()}
+                        />
+                      </div>
+                    )}
+                </div>
+              )}
+
+              {selectedChatModelProvider &&
+                selectedChatModelProvider === 'custom_openai' && (
+                  <div className="flex flex-col space-y-4">
+                    <div className="flex flex-col space-y-1">
+                      <p className="text-black/70 dark:text-white/70 text-sm">
+                        Model Name
+                      </p>
+                      <Input
+                        type="text"
+                        placeholder="Model name"
+                        value={config.customOpenaiModelName}
+                        isSaving={savingStates['customOpenaiModelName']}
+                        onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
+                          setConfig((prev) => ({
+                            ...prev!,
+                            customOpenaiModelName: e.target.value,
+                          }));
+                        }}
+                        onSave={(value) =>
+                          saveConfig('customOpenaiModelName', value)
+                        }
+                      />
+                    </div>
+                    <div className="flex flex-col space-y-1">
+                      <p className="text-black/70 dark:text-white/70 text-sm">
+                        Custom OpenAI API Key
+                      </p>
+                      <Input
+                        type="text"
+                        placeholder="Custom OpenAI API Key"
+                        value={config.customOpenaiApiKey}
+                        isSaving={savingStates['customOpenaiApiKey']}
+                        onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
+                          setConfig((prev) => ({
+                            ...prev!,
+                            customOpenaiApiKey: e.target.value,
+                          }));
+                        }}
+                        onSave={(value) =>
+                          saveConfig('customOpenaiApiKey', value)
+                        }
+                      />
+                    </div>
+                    <div className="flex flex-col space-y-1">
+                      <p className="text-black/70 dark:text-white/70 text-sm">
+                        Custom OpenAI Base URL
+                      </p>
+                      <Input
+                        type="text"
+                        placeholder="Custom OpenAI Base URL"
+                        value={config.customOpenaiApiUrl}
+                        isSaving={savingStates['customOpenaiApiUrl']}
+                        onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
+                          setConfig((prev) => ({
+                            ...prev!,
+                            customOpenaiApiUrl: e.target.value,
+                          }));
+                        }}
+                        onSave={(value) =>
+                          saveConfig('customOpenaiApiUrl', value)
+                        }
+                      />
+                    </div>
+                  </div>
+                )}
+
+              {config.embeddingModelProviders && (
+                <div className="flex flex-col space-y-4 mt-4 pt-4 border-t border-light-200 dark:border-dark-200">
+                  <div className="flex flex-col space-y-1">
+                    <p className="text-black/70 dark:text-white/70 text-sm">
+                      Embedding Model Provider
+                    </p>
+                    <Select
+                      value={selectedEmbeddingModelProvider ?? undefined}
+                      onChange={(e) => {
+                        const value = e.target.value;
+                        setSelectedEmbeddingModelProvider(value);
+                        saveConfig('embeddingModelProvider', value);
+                        const firstModel =
+                          config.embeddingModelProviders[value]?.[0]?.name;
+                        if (firstModel) {
+                          setSelectedEmbeddingModel(firstModel);
+                          saveConfig('embeddingModel', firstModel);
+                        }
+                      }}
+                      options={Object.keys(config.embeddingModelProviders).map(
+                        (provider) => ({
+                          value: provider,
+                          label:
+                            provider.charAt(0).toUpperCase() +
+                            provider.slice(1),
+                        }),
+                      )}
+                    />
+                  </div>
+
+                  {selectedEmbeddingModelProvider && (
+                    <div className="flex flex-col space-y-1">
+                      <p className="text-black/70 dark:text-white/70 text-sm">
+                        Embedding Model
+                      </p>
+                      <Select
+                        value={selectedEmbeddingModel ?? undefined}
+                        onChange={(e) => {
+                          const value = e.target.value;
+                          setSelectedEmbeddingModel(value);
+                          saveConfig('embeddingModel', value);
+                        }}
+                        options={(() => {
+                          const embeddingModelProvider =
+                            config.embeddingModelProviders[
+                              selectedEmbeddingModelProvider
+                            ];
+                          return embeddingModelProvider
+                            ? embeddingModelProvider.length > 0
+                              ? embeddingModelProvider.map((model) => ({
+                                  value: model.name,
+                                  label: model.displayName,
+                                }))
+                              : [
+                                  {
+                                    value: '',
+                                    label: 'No models available',
+                                    disabled: true,
+                                  },
+                                ]
+                            : [
+                                {
+                                  value: '',
+                                  label:
+                                    'Invalid provider, please check backend logs',
+                                  disabled: true,
+                                },
+                              ];
+                        })()}
+                      />
+                    </div>
+                  )}
+                </div>
+              )}
+            </SettingsSection>
+
+            <SettingsSection title="API Keys">
+              <div className="flex flex-col space-y-4">
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    OpenAI API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="OpenAI API Key"
+                    value={config.openaiApiKey}
+                    isSaving={savingStates['openaiApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        openaiApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('openaiApiKey', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Ollama API URL
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Ollama API URL"
+                    value={config.ollamaApiUrl}
+                    isSaving={savingStates['ollamaApiUrl']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        ollamaApiUrl: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('ollamaApiUrl', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    GROQ API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="GROQ API Key"
+                    value={config.groqApiKey}
+                    isSaving={savingStates['groqApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        groqApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('groqApiKey', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Anthropic API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Anthropic API key"
+                    value={config.anthropicApiKey}
+                    isSaving={savingStates['anthropicApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        anthropicApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('anthropicApiKey', value)}
+                  />
+                </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Gemini API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Gemini API key"
+                    value={config.geminiApiKey}
+                    isSaving={savingStates['geminiApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        geminiApiKey: e.target.value,
+                      }));
+                    }}
+                    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>
+            </SettingsSection>
+          </div>
+        )
+      )}
+    </div>
+  );
+};
+
+export default Page;

src/components/Chat.tsx

@@ -2,7 +2,7 @@
 
 import { Fragment, useEffect, useRef, useState } from 'react';
 import MessageInput from './MessageInput';
-import { Message } from './ChatWindow';
+import { File, Message } from './ChatWindow';
 import MessageBox from './MessageBox';
 import MessageBoxLoading from './MessageBoxLoading';
 
@@ -12,12 +12,20 @@ const Chat = ({
   sendMessage,
   messageAppeared,
   rewrite,
+  fileIds,
+  setFileIds,
+  files,
+  setFiles,
 }: {
   messages: Message[];
   sendMessage: (message: string) => void;
   loading: boolean;
   messageAppeared: boolean;
   rewrite: (messageId: string) => void;
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  files: File[];
+  setFiles: (files: File[]) => void;
 }) => {
   const [dividerWidth, setDividerWidth] = useState(0);
   const dividerRef = useRef<HTMLDivElement | null>(null);
@@ -40,11 +48,17 @@ const Chat = ({
   });
 
   useEffect(() => {
-    messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
+    const scroll = () => {
+      messageEnd.current?.scrollIntoView({ behavior: 'smooth' });
+    };
 
     if (messages.length === 1) {
       document.title = `${messages[0].content.substring(0, 30)} - Perplexica`;
     }
+
+    if (messages[messages.length - 1]?.role == 'user') {
+      scroll();
+    }
   }, [messages]);
 
   return (
@@ -53,7 +67,7 @@ const Chat = ({
         const isLast = i === messages.length - 1;
 
         return (
-          <Fragment key={msg.id}>
+          <Fragment key={msg.messageId}>
             <MessageBox
               key={i}
               message={msg}
@@ -66,7 +80,7 @@ const Chat = ({
               sendMessage={sendMessage}
             />
             {!isLast && msg.role === 'assistant' && (
-              <div className="h-px w-full bg-[#1C1C1C]" />
+              <div className="h-px w-full bg-light-secondary dark:bg-dark-secondary" />
             )}
           </Fragment>
         );
@@ -78,7 +92,14 @@ const Chat = ({
           className="bottom-24 lg:bottom-10 fixed z-40"
           style={{ width: dividerWidth }}
         >
-          <MessageInput loading={loading} sendMessage={sendMessage} />
+          <MessageInput
+            loading={loading}
+            sendMessage={sendMessage}
+            fileIds={fileIds}
+            setFileIds={setFileIds}
+            files={files}
+            setFiles={setFiles}
+          />
         </div>
       )}
     </div>

src/components/ChatWindow.tsx

@@ -0,0 +1,610 @@
+'use client';
+
+import { useEffect, useRef, useState } from 'react';
+import { Document } from '@langchain/core/documents';
+import Navbar from './Navbar';
+import Chat from './Chat';
+import EmptyChat from './EmptyChat';
+import crypto from 'crypto';
+import { toast } from 'sonner';
+import { useSearchParams } from 'next/navigation';
+import { getSuggestions } from '@/lib/actions';
+import { Settings } from 'lucide-react';
+import Link from 'next/link';
+import NextError from 'next/error';
+
+export type Message = {
+  messageId: string;
+  chatId: string;
+  createdAt: Date;
+  content: string;
+  role: 'user' | 'assistant';
+  suggestions?: string[];
+  sources?: Document[];
+};
+
+export interface File {
+  fileName: string;
+  fileExtension: string;
+  fileId: string;
+}
+
+interface ChatModelProvider {
+  name: string;
+  provider: string;
+}
+
+interface EmbeddingModelProvider {
+  name: string;
+  provider: string;
+}
+
+const checkConfig = async (
+  setChatModelProvider: (provider: ChatModelProvider) => void,
+  setEmbeddingModelProvider: (provider: EmbeddingModelProvider) => void,
+  setIsConfigReady: (ready: boolean) => void,
+  setHasError: (hasError: boolean) => void,
+) => {
+  try {
+    let chatModel = localStorage.getItem('chatModel');
+    let chatModelProvider = localStorage.getItem('chatModelProvider');
+    let embeddingModel = localStorage.getItem('embeddingModel');
+    let embeddingModelProvider = localStorage.getItem('embeddingModelProvider');
+
+    const autoImageSearch = localStorage.getItem('autoImageSearch');
+    const autoVideoSearch = localStorage.getItem('autoVideoSearch');
+
+    if (!autoImageSearch) {
+      localStorage.setItem('autoImageSearch', 'true');
+    }
+
+    if (!autoVideoSearch) {
+      localStorage.setItem('autoVideoSearch', 'false');
+    }
+
+    const providers = await fetch(`/api/models`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    }).then(async (res) => {
+      if (!res.ok)
+        throw new Error(
+          `Failed to fetch models: ${res.status} ${res.statusText}`,
+        );
+      return res.json();
+    });
+
+    if (
+      !chatModel ||
+      !chatModelProvider ||
+      !embeddingModel ||
+      !embeddingModelProvider
+    ) {
+      if (!chatModel || !chatModelProvider) {
+        const chatModelProviders = providers.chatModelProviders;
+
+        chatModelProvider =
+          chatModelProvider || Object.keys(chatModelProviders)[0];
+
+        chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+
+        if (!chatModelProviders || Object.keys(chatModelProviders).length === 0)
+          return toast.error('No chat models available');
+      }
+
+      if (!embeddingModel || !embeddingModelProvider) {
+        const embeddingModelProviders = providers.embeddingModelProviders;
+
+        if (
+          !embeddingModelProviders ||
+          Object.keys(embeddingModelProviders).length === 0
+        )
+          return toast.error('No embedding models available');
+
+        embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
+        embeddingModel = Object.keys(
+          embeddingModelProviders[embeddingModelProvider],
+        )[0];
+      }
+
+      localStorage.setItem('chatModel', chatModel!);
+      localStorage.setItem('chatModelProvider', chatModelProvider);
+      localStorage.setItem('embeddingModel', embeddingModel!);
+      localStorage.setItem('embeddingModelProvider', embeddingModelProvider);
+    } else {
+      const chatModelProviders = providers.chatModelProviders;
+      const embeddingModelProviders = providers.embeddingModelProviders;
+
+      if (
+        Object.keys(chatModelProviders).length > 0 &&
+        !chatModelProviders[chatModelProvider]
+      ) {
+        const chatModelProvidersKeys = Object.keys(chatModelProviders);
+        chatModelProvider =
+          chatModelProvidersKeys.find(
+            (key) => Object.keys(chatModelProviders[key]).length > 0,
+          ) || chatModelProvidersKeys[0];
+
+        localStorage.setItem('chatModelProvider', chatModelProvider);
+      }
+
+      if (
+        chatModelProvider &&
+        !chatModelProviders[chatModelProvider][chatModel]
+      ) {
+        chatModel = Object.keys(
+          chatModelProviders[
+            Object.keys(chatModelProviders[chatModelProvider]).length > 0
+              ? chatModelProvider
+              : Object.keys(chatModelProviders)[0]
+          ],
+        )[0];
+        localStorage.setItem('chatModel', chatModel);
+      }
+
+      if (
+        Object.keys(embeddingModelProviders).length > 0 &&
+        !embeddingModelProviders[embeddingModelProvider]
+      ) {
+        embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
+        localStorage.setItem('embeddingModelProvider', embeddingModelProvider);
+      }
+
+      if (
+        embeddingModelProvider &&
+        !embeddingModelProviders[embeddingModelProvider][embeddingModel]
+      ) {
+        embeddingModel = Object.keys(
+          embeddingModelProviders[embeddingModelProvider],
+        )[0];
+        localStorage.setItem('embeddingModel', embeddingModel);
+      }
+    }
+
+    setChatModelProvider({
+      name: chatModel!,
+      provider: chatModelProvider,
+    });
+
+    setEmbeddingModelProvider({
+      name: embeddingModel!,
+      provider: embeddingModelProvider,
+    });
+
+    setIsConfigReady(true);
+  } catch (err) {
+    console.error('An error occurred while checking the configuration:', err);
+    setIsConfigReady(false);
+    setHasError(true);
+  }
+};
+
+const loadMessages = async (
+  chatId: string,
+  setMessages: (messages: Message[]) => void,
+  setIsMessagesLoaded: (loaded: boolean) => void,
+  setChatHistory: (history: [string, string][]) => void,
+  setFocusMode: (mode: string) => void,
+  setNotFound: (notFound: boolean) => void,
+  setFiles: (files: File[]) => void,
+  setFileIds: (fileIds: string[]) => void,
+) => {
+  const res = await fetch(`/api/chats/${chatId}`, {
+    method: 'GET',
+    headers: {
+      'Content-Type': 'application/json',
+    },
+  });
+
+  if (res.status === 404) {
+    setNotFound(true);
+    setIsMessagesLoaded(true);
+    return;
+  }
+
+  const data = await res.json();
+
+  const messages = data.messages.map((msg: any) => {
+    return {
+      ...msg,
+      ...JSON.parse(msg.metadata),
+    };
+  }) as Message[];
+
+  setMessages(messages);
+
+  const history = messages.map((msg) => {
+    return [msg.role, msg.content];
+  }) as [string, string][];
+
+  console.debug(new Date(), 'app:messages_loaded');
+
+  document.title = messages[0].content;
+
+  const files = data.chat.files.map((file: any) => {
+    return {
+      fileName: file.name,
+      fileExtension: file.name.split('.').pop(),
+      fileId: file.fileId,
+    };
+  });
+
+  setFiles(files);
+  setFileIds(files.map((file: File) => file.fileId));
+
+  setChatHistory(history);
+  setFocusMode(data.chat.focusMode);
+  setIsMessagesLoaded(true);
+};
+
+const ChatWindow = ({ id }: { id?: string }) => {
+  const searchParams = useSearchParams();
+  const initialMessage = searchParams.get('q');
+
+  const [chatId, setChatId] = useState<string | undefined>(id);
+  const [newChatCreated, setNewChatCreated] = useState(false);
+
+  const [chatModelProvider, setChatModelProvider] = useState<ChatModelProvider>(
+    {
+      name: '',
+      provider: '',
+    },
+  );
+
+  const [embeddingModelProvider, setEmbeddingModelProvider] =
+    useState<EmbeddingModelProvider>({
+      name: '',
+      provider: '',
+    });
+
+  const [isConfigReady, setIsConfigReady] = useState(false);
+  const [hasError, setHasError] = useState(false);
+  const [isReady, setIsReady] = useState(false);
+
+  useEffect(() => {
+    checkConfig(
+      setChatModelProvider,
+      setEmbeddingModelProvider,
+      setIsConfigReady,
+      setHasError,
+    );
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, []);
+
+  const [loading, setLoading] = useState(false);
+  const [messageAppeared, setMessageAppeared] = useState(false);
+
+  const [chatHistory, setChatHistory] = useState<[string, string][]>([]);
+  const [messages, setMessages] = useState<Message[]>([]);
+
+  const [files, setFiles] = useState<File[]>([]);
+  const [fileIds, setFileIds] = useState<string[]>([]);
+
+  const [focusMode, setFocusMode] = useState('webSearch');
+  const [optimizationMode, setOptimizationMode] = useState('speed');
+
+  const [isMessagesLoaded, setIsMessagesLoaded] = useState(false);
+
+  const [notFound, setNotFound] = useState(false);
+
+  useEffect(() => {
+    if (
+      chatId &&
+      !newChatCreated &&
+      !isMessagesLoaded &&
+      messages.length === 0
+    ) {
+      loadMessages(
+        chatId,
+        setMessages,
+        setIsMessagesLoaded,
+        setChatHistory,
+        setFocusMode,
+        setNotFound,
+        setFiles,
+        setFileIds,
+      );
+    } else if (!chatId) {
+      setNewChatCreated(true);
+      setIsMessagesLoaded(true);
+      setChatId(crypto.randomBytes(20).toString('hex'));
+    }
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, []);
+
+  const messagesRef = useRef<Message[]>([]);
+
+  useEffect(() => {
+    messagesRef.current = messages;
+  }, [messages]);
+
+  useEffect(() => {
+    if (isMessagesLoaded && isConfigReady) {
+      setIsReady(true);
+      console.debug(new Date(), 'app:ready');
+    } else {
+      setIsReady(false);
+    }
+  }, [isMessagesLoaded, isConfigReady]);
+
+  const sendMessage = async (message: string, messageId?: string) => {
+    if (loading) return;
+    if (!isConfigReady) {
+      toast.error('Cannot send message before the configuration is ready');
+      return;
+    }
+
+    setLoading(true);
+    setMessageAppeared(false);
+
+    let sources: Document[] | undefined = undefined;
+    let recievedMessage = '';
+    let added = false;
+
+    messageId = messageId ?? crypto.randomBytes(7).toString('hex');
+
+    setMessages((prevMessages) => [
+      ...prevMessages,
+      {
+        content: message,
+        messageId: messageId,
+        chatId: chatId!,
+        role: 'user',
+        createdAt: new Date(),
+      },
+    ]);
+
+    const messageHandler = async (data: any) => {
+      if (data.type === 'error') {
+        toast.error(data.data);
+        setLoading(false);
+        return;
+      }
+
+      if (data.type === 'sources') {
+        sources = data.data;
+        setMessages((prevMessages) => [
+          ...prevMessages,
+          {
+            content: '',
+            messageId: data.messageId,
+            chatId: chatId!,
+            role: 'assistant',
+            sources: sources,
+            createdAt: new Date(),
+          },
+        ]);
+        added = true;
+        setMessageAppeared(true);
+      }
+
+      if (data.type === 'message') {
+        if (!added) {
+          setMessages((prevMessages) => [
+            ...prevMessages,
+            {
+              content: data.data,
+              messageId: data.messageId,
+              chatId: chatId!,
+              role: 'assistant',
+              sources: sources,
+              createdAt: new Date(),
+            },
+          ]);
+          added = true;
+          setMessageAppeared(true);
+        } else {
+          setMessages((prev) =>
+            prev.map((message) => {
+              if (message.messageId === data.messageId) {
+                return { ...message, content: message.content + data.data };
+              }
+
+              return message;
+            }),
+          );
+        }
+
+        recievedMessage += data.data;
+      }
+
+      if (data.type === 'messageEnd') {
+        setChatHistory((prevHistory) => [
+          ...prevHistory,
+          ['human', message],
+          ['assistant', recievedMessage],
+        ]);
+
+        setLoading(false);
+
+        const lastMsg = messagesRef.current[messagesRef.current.length - 1];
+
+        const autoImageSearch = localStorage.getItem('autoImageSearch');
+        const autoVideoSearch = localStorage.getItem('autoVideoSearch');
+
+        if (autoImageSearch === 'true') {
+          document
+            .getElementById(`search-images-${lastMsg.messageId}`)
+            ?.click();
+        }
+
+        if (autoVideoSearch === 'true') {
+          document
+            .getElementById(`search-videos-${lastMsg.messageId}`)
+            ?.click();
+        }
+
+        if (
+          lastMsg.role === 'assistant' &&
+          lastMsg.sources &&
+          lastMsg.sources.length > 0 &&
+          !lastMsg.suggestions
+        ) {
+          const suggestions = await getSuggestions(messagesRef.current);
+          setMessages((prev) =>
+            prev.map((msg) => {
+              if (msg.messageId === lastMsg.messageId) {
+                return { ...msg, suggestions: suggestions };
+              }
+              return msg;
+            }),
+          );
+        }
+      }
+    };
+
+    const res = await fetch('/api/chat', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        content: message,
+        message: {
+          messageId: messageId,
+          chatId: chatId!,
+          content: message,
+        },
+        chatId: chatId!,
+        files: fileIds,
+        focusMode: focusMode,
+        optimizationMode: optimizationMode,
+        history: chatHistory,
+        chatModel: {
+          name: chatModelProvider.name,
+          provider: chatModelProvider.provider,
+        },
+        embeddingModel: {
+          name: embeddingModelProvider.name,
+          provider: embeddingModelProvider.provider,
+        },
+        systemInstructions: localStorage.getItem('systemInstructions'),
+      }),
+    });
+
+    if (!res.body) throw new Error('No response body');
+
+    const reader = res.body?.getReader();
+    const decoder = new TextDecoder('utf-8');
+
+    let partialChunk = '';
+
+    while (true) {
+      const { value, done } = await reader.read();
+      if (done) break;
+
+      partialChunk += decoder.decode(value, { stream: true });
+
+      try {
+        const messages = partialChunk.split('\n');
+        for (const msg of messages) {
+          if (!msg.trim()) continue;
+          const json = JSON.parse(msg);
+          messageHandler(json);
+        }
+        partialChunk = '';
+      } catch (error) {
+        console.warn('Incomplete JSON, waiting for next chunk...');
+      }
+    }
+  };
+
+  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)];
+    });
+    setChatHistory((prev) => {
+      return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
+    });
+
+    sendMessage(message.content, message.messageId);
+  };
+
+  useEffect(() => {
+    if (isReady && initialMessage && isConfigReady) {
+      sendMessage(initialMessage);
+    }
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [isConfigReady, isReady, initialMessage]);
+
+  if (hasError) {
+    return (
+      <div className="relative">
+        <div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
+          <Link href="/settings">
+            <Settings className="cursor-pointer lg:hidden" />
+          </Link>
+        </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>
+      </div>
+    );
+  }
+
+  return isReady ? (
+    notFound ? (
+      <NextError statusCode={404} />
+    ) : (
+      <div>
+        {messages.length > 0 ? (
+          <>
+            <Navbar chatId={chatId!} messages={messages} />
+            <Chat
+              loading={loading}
+              messages={messages}
+              sendMessage={sendMessage}
+              messageAppeared={messageAppeared}
+              rewrite={rewrite}
+              fileIds={fileIds}
+              setFileIds={setFileIds}
+              files={files}
+              setFiles={setFiles}
+            />
+          </>
+        ) : (
+          <EmptyChat
+            sendMessage={sendMessage}
+            focusMode={focusMode}
+            setFocusMode={setFocusMode}
+            optimizationMode={optimizationMode}
+            setOptimizationMode={setOptimizationMode}
+            fileIds={fileIds}
+            setFileIds={setFileIds}
+            files={files}
+            setFiles={setFiles}
+          />
+        )}
+      </div>
+    )
+  ) : (
+    <div className="flex flex-row items-center justify-center min-h-screen">
+      <svg
+        aria-hidden="true"
+        className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
+        viewBox="0 0 100 101"
+        fill="none"
+        xmlns="http://www.w3.org/2000/svg"
+      >
+        <path
+          d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
+          fill="currentColor"
+        />
+        <path
+          d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
+          fill="currentFill"
+        />
+      </svg>
+    </div>
+  );
+};
+
+export default ChatWindow;

src/components/DeleteChat.tsx

@@ -0,0 +1,125 @@
+import { Trash } from 'lucide-react';
+import {
+  Description,
+  Dialog,
+  DialogBackdrop,
+  DialogPanel,
+  DialogTitle,
+  Transition,
+  TransitionChild,
+} from '@headlessui/react';
+import { Fragment, useState } from 'react';
+import { toast } from 'sonner';
+import { Chat } from '@/app/library/page';
+
+const DeleteChat = ({
+  chatId,
+  chats,
+  setChats,
+  redirect = false,
+}: {
+  chatId: string;
+  chats: Chat[];
+  setChats: (chats: Chat[]) => void;
+  redirect?: boolean;
+}) => {
+  const [confirmationDialogOpen, setConfirmationDialogOpen] = useState(false);
+  const [loading, setLoading] = useState(false);
+
+  const handleDelete = async () => {
+    setLoading(true);
+    try {
+      const res = await fetch(`/api/chats/${chatId}`, {
+        method: 'DELETE',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+      });
+
+      if (res.status != 200) {
+        throw new Error('Failed to delete chat');
+      }
+
+      const newChats = chats.filter((chat) => chat.id !== chatId);
+
+      setChats(newChats);
+
+      if (redirect) {
+        window.location.href = '/';
+      }
+    } catch (err: any) {
+      toast.error(err.message);
+    } finally {
+      setConfirmationDialogOpen(false);
+      setLoading(false);
+    }
+  };
+
+  return (
+    <>
+      <button
+        onClick={() => {
+          setConfirmationDialogOpen(true);
+        }}
+        className="bg-transparent text-red-400 hover:scale-105 transition duration-200"
+      >
+        <Trash size={17} />
+      </button>
+      <Transition appear show={confirmationDialogOpen} as={Fragment}>
+        <Dialog
+          as="div"
+          className="relative z-50"
+          onClose={() => {
+            if (!loading) {
+              setConfirmationDialogOpen(false);
+            }
+          }}
+        >
+          <DialogBackdrop className="fixed inset-0 bg-black/30" />
+          <div className="fixed inset-0 overflow-y-auto">
+            <div className="flex min-h-full items-center justify-center p-4 text-center">
+              <TransitionChild
+                as={Fragment}
+                enter="ease-out duration-200"
+                enterFrom="opacity-0 scale-95"
+                enterTo="opacity-100 scale-100"
+                leave="ease-in duration-100"
+                leaveFrom="opacity-100 scale-200"
+                leaveTo="opacity-0 scale-95"
+              >
+                <DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
+                  <DialogTitle className="text-lg font-medium leading-6 dark:text-white">
+                    Delete Confirmation
+                  </DialogTitle>
+                  <Description className="text-sm dark:text-white/70 text-black/70">
+                    Are you sure you want to delete this chat?
+                  </Description>
+                  <div className="flex flex-row items-end justify-end space-x-4 mt-6">
+                    <button
+                      onClick={() => {
+                        if (!loading) {
+                          setConfirmationDialogOpen(false);
+                        }
+                      }}
+                      className="text-black/50 dark:text-white/50 text-sm hover:text-black/70 hover:dark:text-white/70 transition duration-200"
+                    >
+                      Cancel
+                    </button>
+                    <button
+                      onClick={handleDelete}
+                      className="text-red-400 text-sm hover:text-red-500 transition duration200"
+                    >
+                      Delete
+                    </button>
+                  </div>
+                </DialogPanel>
+              </TransitionChild>
+            </div>
+          </div>
+        </Dialog>
+      </Transition>
+    </>
+  );
+};
+
+export default DeleteChat;

src/components/EmptyChat.tsx

@@ -0,0 +1,57 @@
+import { Settings } from 'lucide-react';
+import EmptyChatMessageInput from './EmptyChatMessageInput';
+import { useState } from 'react';
+import { File } from './ChatWindow';
+import Link from 'next/link';
+
+const EmptyChat = ({
+  sendMessage,
+  focusMode,
+  setFocusMode,
+  optimizationMode,
+  setOptimizationMode,
+  fileIds,
+  setFileIds,
+  files,
+  setFiles,
+}: {
+  sendMessage: (message: string) => void;
+  focusMode: string;
+  setFocusMode: (mode: string) => void;
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  files: File[];
+  setFiles: (files: File[]) => void;
+}) => {
+  const [isSettingsOpen, setIsSettingsOpen] = useState(false);
+
+  return (
+    <div className="relative">
+      <div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
+        <Link href="/settings">
+          <Settings className="cursor-pointer lg:hidden" />
+        </Link>
+      </div>
+      <div className="flex flex-col items-center justify-center min-h-screen max-w-screen-sm mx-auto p-2 space-y-8">
+        <h2 className="text-black/70 dark:text-white/70 text-3xl font-medium -mt-8">
+          Research begins here.
+        </h2>
+        <EmptyChatMessageInput
+          sendMessage={sendMessage}
+          focusMode={focusMode}
+          setFocusMode={setFocusMode}
+          optimizationMode={optimizationMode}
+          setOptimizationMode={setOptimizationMode}
+          fileIds={fileIds}
+          setFileIds={setFileIds}
+          files={files}
+          setFiles={setFiles}
+        />
+      </div>
+    </div>
+  );
+};
+
+export default EmptyChat;

src/components/EmptyChatMessageInput.tsx

@@ -0,0 +1,114 @@
+import { ArrowRight } from 'lucide-react';
+import { useEffect, useRef, useState } from 'react';
+import TextareaAutosize from 'react-textarea-autosize';
+import CopilotToggle from './MessageInputActions/Copilot';
+import Focus from './MessageInputActions/Focus';
+import Optimization from './MessageInputActions/Optimization';
+import Attach from './MessageInputActions/Attach';
+import { File } from './ChatWindow';
+
+const EmptyChatMessageInput = ({
+  sendMessage,
+  focusMode,
+  setFocusMode,
+  optimizationMode,
+  setOptimizationMode,
+  fileIds,
+  setFileIds,
+  files,
+  setFiles,
+}: {
+  sendMessage: (message: string) => void;
+  focusMode: string;
+  setFocusMode: (mode: string) => void;
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  files: File[];
+  setFiles: (files: File[]) => void;
+}) => {
+  const [copilotEnabled, setCopilotEnabled] = useState(false);
+  const [message, setMessage] = useState('');
+
+  const inputRef = useRef<HTMLTextAreaElement | null>(null);
+
+  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);
+
+    inputRef.current?.focus();
+
+    return () => {
+      document.removeEventListener('keydown', handleKeyDown);
+    };
+  }, []);
+
+  return (
+    <form
+      onSubmit={(e) => {
+        e.preventDefault();
+        sendMessage(message);
+        setMessage('');
+      }}
+      onKeyDown={(e) => {
+        if (e.key === 'Enter' && !e.shiftKey) {
+          e.preventDefault();
+          sendMessage(message);
+          setMessage('');
+        }
+      }}
+      className="w-full"
+    >
+      <div className="flex flex-col bg-light-secondary dark:bg-dark-secondary px-5 pt-5 pb-2 rounded-lg w-full border border-light-200 dark:border-dark-200">
+        <TextareaAutosize
+          ref={inputRef}
+          value={message}
+          onChange={(e) => setMessage(e.target.value)}
+          minRows={2}
+          className="bg-transparent placeholder:text-black/50 dark:placeholder:text-white/50 text-sm text-black dark:text-white resize-none focus:outline-none w-full max-h-24 lg:max-h-36 xl:max-h-48"
+          placeholder="Ask anything..."
+        />
+        <div className="flex flex-row items-center justify-between mt-4">
+          <div className="flex flex-row items-center space-x-2 lg:space-x-4">
+            <Focus focusMode={focusMode} setFocusMode={setFocusMode} />
+            <Attach
+              fileIds={fileIds}
+              setFileIds={setFileIds}
+              files={files}
+              setFiles={setFiles}
+              showText
+            />
+          </div>
+          <div className="flex flex-row items-center space-x-1 sm:space-x-4">
+            <Optimization
+              optimizationMode={optimizationMode}
+              setOptimizationMode={setOptimizationMode}
+            />
+            <button
+              disabled={message.trim().length === 0}
+              className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 disabled:bg-[#e0e0dc] dark:disabled:bg-[#ececec21] hover:bg-opacity-85 transition duration-100 rounded-full p-2"
+            >
+              <ArrowRight className="bg-background" size={17} />
+            </button>
+          </div>
+        </div>
+      </div>
+    </form>
+  );
+};
+
+export default EmptyChatMessageInput;

src/components/Layout.tsx

@@ -1,6 +1,6 @@
 const Layout = ({ children }: { children: React.ReactNode }) => {
   return (
-    <main className="lg:pl-20 bg-[#0A0A0A] min-h-screen">
+    <main className="lg:pl-20 bg-light-primary dark:bg-dark-primary min-h-screen">
       <div className="max-w-screen-lg lg:mx-auto mx-4">{children}</div>
     </main>
   );

src/components/MessageActions/Copy.tsx

@@ -19,7 +19,7 @@ const Copy = ({
         setCopied(true);
         setTimeout(() => setCopied(false), 1000);
       }}
-      className="p-2 text-white/70 rounded-xl hover:bg-[#1c1c1c] transition duration-200 hover:text-white"
+      className="p-2 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
     >
       {copied ? <Check size={18} /> : <ClipboardList size={18} />}
     </button>

src/components/MessageActions/Rewrite.tsx

@@ -10,7 +10,7 @@ const Rewrite = ({
   return (
     <button
       onClick={() => rewrite(messageId)}
-      className="py-2 px-3 text-white/70 rounded-xl hover:bg-[#1c1c1c] transition duration-200 hover:text-white flex flex-row items-center space-x-1"
+      className="py-2 px-3 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white flex flex-row items-center space-x-1"
     >
       <ArrowLeftRight size={18} />
       <p className="text-xs font-medium">Rewrite</p>

src/components/MessageBox.tsx

@@ -7,19 +7,23 @@ import { cn } from '@/lib/utils';
 import {
   BookCopy,
   Disc3,
-  Share,
   Volume2,
   StopCircle,
   Layers3,
   Plus,
 } from 'lucide-react';
-import Markdown from 'markdown-to-jsx';
+import Markdown, { MarkdownToJSX } from 'markdown-to-jsx';
 import Copy from './MessageActions/Copy';
 import Rewrite from './MessageActions/Rewrite';
 import MessageSources from './MessageSources';
 import SearchImages from './SearchImages';
 import SearchVideos from './SearchVideos';
 import { useSpeech } from 'react-text-to-speech';
+import ThinkBox from './ThinkBox';
+
+const ThinkTagProcessor = ({ children }: { children: React.ReactNode }) => {
+  return <ThinkBox content={children as string} />;
+};
 
 const MessageBox = ({
   message,
@@ -44,33 +48,83 @@ const MessageBox = ({
   const [speechMessage, setSpeechMessage] = useState(message.content);
 
   useEffect(() => {
+    const citationRegex = /\[([^\]]+)\]/g;
     const regex = /\[(\d+)\]/g;
+    let processedMessage = message.content;
+
+    if (message.role === 'assistant' && message.content.includes('<think>')) {
+      const openThinkTag = processedMessage.match(/<think>/g)?.length || 0;
+      const closeThinkTag = processedMessage.match(/<\/think>/g)?.length || 0;
+
+      if (openThinkTag > closeThinkTag) {
+        processedMessage += '</think> <a> </a>'; // The extra <a> </a> is to prevent the the think component from looking bad
+      }
+    }
 
     if (
       message.role === 'assistant' &&
       message?.sources &&
       message.sources.length > 0
     ) {
-      return setParsedMessage(
-        message.content.replace(
-          regex,
-          (_, number) =>
-            `<a href="${message.sources?.[number - 1]?.metadata?.url}" target="_blank" className="bg-[#1C1C1C] px-1 rounded ml-1 no-underline text-xs text-white/70 relative">${number}</a>`,
+      setParsedMessage(
+        processedMessage.replace(
+          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;
+          },
         ),
       );
+      return;
     }
 
     setSpeechMessage(message.content.replace(regex, ''));
-    setParsedMessage(message.content);
+    setParsedMessage(processedMessage);
   }, [message.content, message.sources, message.role]);
 
   const { speechStatus, start, stop } = useSpeech({ text: speechMessage });
 
+  const markdownOverrides: MarkdownToJSX.Options = {
+    overrides: {
+      think: {
+        component: ThinkTagProcessor,
+      },
+    },
+  };
+
   return (
     <div>
       {message.role === 'user' && (
-        <div className={cn('w-full', messageIndex === 0 ? 'pt-16' : 'pt-8')}>
-          <h2 className="text-white font-medium text-3xl lg:w-9/12">
+        <div
+          className={cn(
+            'w-full',
+            messageIndex === 0 ? 'pt-16' : 'pt-8',
+            'break-words',
+          )}
+        >
+          <h2 className="text-black dark:text-white font-medium text-3xl lg:w-9/12">
             {message.content}
           </h2>
         </div>
@@ -85,8 +139,10 @@ const MessageBox = ({
             {message.sources && message.sources.length > 0 && (
               <div className="flex flex-col space-y-2">
                 <div className="flex flex-row items-center space-x-2">
-                  <BookCopy className="text-white" size={20} />
-                  <h3 className="text-white font-medium text-xl">Sources</h3>
+                  <BookCopy className="text-black dark:text-white" size={20} />
+                  <h3 className="text-black dark:text-white font-medium text-xl">
+                    Sources
+                  </h3>
                 </div>
                 <MessageSources sources={message.sources} />
               </div>
@@ -95,23 +151,32 @@ const MessageBox = ({
               <div className="flex flex-row items-center space-x-2">
                 <Disc3
                   className={cn(
-                    'text-white',
+                    'text-black dark:text-white',
                     isLast && loading ? 'animate-spin' : 'animate-none',
                   )}
                   size={20}
                 />
-                <h3 className="text-white font-medium text-xl">Answer</h3>
+                <h3 className="text-black dark:text-white font-medium text-xl">
+                  Answer
+                </h3>
               </div>
-              <Markdown className="prose max-w-none break-words prose-invert prose-p:leading-relaxed prose-pre:p-0 text-white text-sm md:text-base font-medium">
+
+              <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',
+                )}
+                options={markdownOverrides}
+              >
                 {parsedMessage}
               </Markdown>
               {loading && isLast ? null : (
-                <div className="flex flex-row items-center justify-between w-full text-white py-4 -mx-2">
+                <div className="flex flex-row items-center justify-between w-full text-black dark:text-white py-4 -mx-2">
                   <div className="flex flex-row items-center space-x-1">
-                    {/*  <button className="p-2 text-white/70 rounded-xl hover:bg-[#1c1c1c] transition duration-200 hover:text-white">
+                    {/*  <button className="p-2 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black text-black dark:hover:text-white">
                       <Share size={18} />
                     </button> */}
-                    <Rewrite rewrite={rewrite} messageId={message.id} />
+                    <Rewrite rewrite={rewrite} messageId={message.messageId} />
                   </div>
                   <div className="flex flex-row items-center space-x-1">
                     <Copy initialMessage={message.content} message={message} />
@@ -123,7 +188,7 @@ const MessageBox = ({
                           start();
                         }
                       }}
-                      className="p-2 text-white/70 rounded-xl hover:bg-[#1c1c1c] transition duration-200 hover:text-white"
+                      className="p-2 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
                     >
                       {speechStatus === 'started' ? (
                         <StopCircle size={18} />
@@ -140,8 +205,8 @@ const MessageBox = ({
                 message.role === 'assistant' &&
                 !loading && (
                   <>
-                    <div className="h-px w-full bg-[#1C1C1C]" />
-                    <div className="flex flex-col space-y-3 text-white">
+                    <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>
@@ -152,7 +217,7 @@ const MessageBox = ({
                             className="flex flex-col space-y-3 text-sm"
                             key={i}
                           >
-                            <div className="h-px w-full bg-[#1C1C1C]" />
+                            <div className="h-px w-full bg-light-secondary dark:bg-dark-secondary" />
                             <div
                               onClick={() => {
                                 sendMessage(suggestion);
@@ -162,7 +227,10 @@ const MessageBox = ({
                               <p className="transition duration-200 hover:text-[#24A0ED]">
                                 {suggestion}
                               </p>
-                              <Plus size={20} className="text-[#24A0ED]" />
+                              <Plus
+                                size={20}
+                                className="text-[#24A0ED] flex-shrink-0"
+                              />
                             </div>
                           </div>
                         ))}
@@ -175,11 +243,13 @@ const MessageBox = ({
           <div className="lg:sticky lg:top-20 flex flex-col items-center space-y-3 w-full lg:w-3/12 z-30 h-full pb-4">
             <SearchImages
               query={history[messageIndex - 1].content}
-              chat_history={history.slice(0, messageIndex - 1)}
+              chatHistory={history.slice(0, messageIndex - 1)}
+              messageId={message.messageId}
             />
             <SearchVideos
-              chat_history={history.slice(0, messageIndex - 1)}
+              chatHistory={history.slice(0, messageIndex - 1)}
               query={history[messageIndex - 1].content}
+              messageId={message.messageId}
             />
           </div>
         </div>

src/components/MessageBoxLoading.tsx

@@ -0,0 +1,11 @@
+const MessageBoxLoading = () => {
+  return (
+    <div className="flex flex-col space-y-2 w-full lg:w-9/12 bg-light-primary dark:bg-dark-primary animate-pulse rounded-lg py-3">
+      <div className="h-2 rounded-full w-full bg-light-secondary dark:bg-dark-secondary" />
+      <div className="h-2 rounded-full w-9/12 bg-light-secondary dark:bg-dark-secondary" />
+      <div className="h-2 rounded-full w-10/12 bg-light-secondary dark:bg-dark-secondary" />
+    </div>
+  );
+};
+
+export default MessageBoxLoading;

src/components/MessageInput.tsx

@@ -1,15 +1,26 @@
 import { cn } from '@/lib/utils';
 import { ArrowUp } from 'lucide-react';
-import { useEffect, useState } from 'react';
+import { useEffect, useRef, useState } from 'react';
 import TextareaAutosize from 'react-textarea-autosize';
-import { Attach, CopilotToggle } from './MessageInputActions';
+import Attach from './MessageInputActions/Attach';
+import CopilotToggle from './MessageInputActions/Copilot';
+import { File } from './ChatWindow';
+import AttachSmall from './MessageInputActions/AttachSmall';
 
 const MessageInput = ({
   sendMessage,
   loading,
+  fileIds,
+  setFileIds,
+  files,
+  setFiles,
 }: {
   sendMessage: (message: string) => void;
   loading: boolean;
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  files: File[];
+  setFiles: (files: File[]) => void;
 }) => {
   const [copilotEnabled, setCopilotEnabled] = useState(false);
   const [message, setMessage] = useState('');
@@ -24,6 +35,30 @@ const MessageInput = ({
     }
   }, [textareaRows, mode, message]);
 
+  const inputRef = useRef<HTMLTextAreaElement | null>(null);
+
+  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);
+    };
+  }, []);
+
   return (
     <form
       onSubmit={(e) => {
@@ -40,18 +75,26 @@ const MessageInput = ({
         }
       }}
       className={cn(
-        'bg-[#111111] p-4 flex items-center overflow-hidden border border-[#1C1C1C]',
+        'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200',
         mode === 'multi' ? 'flex-col rounded-lg' : 'flex-row rounded-full',
       )}
     >
-      {mode === 'single' && <Attach />}
+      {mode === 'single' && (
+        <AttachSmall
+          fileIds={fileIds}
+          setFileIds={setFileIds}
+          files={files}
+          setFiles={setFiles}
+        />
+      )}
       <TextareaAutosize
+        ref={inputRef}
         value={message}
         onChange={(e) => setMessage(e.target.value)}
         onHeightChange={(height, props) => {
           setTextareaRows(Math.ceil(height / props.rowHeight));
         }}
-        className="transition bg-transparent placeholder:text-white/50 placeholder:text-sm text-sm text-white resize-none focus:outline-none w-full px-2 max-h-24 lg:max-h-36 xl:max-h-48 flex-grow flex-shrink"
+        className="transition bg-transparent dark:placeholder:text-white/50 placeholder:text-sm text-sm dark:text-white resize-none focus:outline-none w-full px-2 max-h-24 lg:max-h-36 xl:max-h-48 flex-grow flex-shrink"
         placeholder="Ask a follow-up"
       />
       {mode === 'single' && (
@@ -62,7 +105,7 @@ const MessageInput = ({
           />
           <button
             disabled={message.trim().length === 0 || loading}
-            className="bg-[#24A0ED] text-white disabled:text-white/50 hover:bg-opacity-85 transition duration-100 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>
@@ -70,7 +113,12 @@ const MessageInput = ({
       )}
       {mode === 'multi' && (
         <div className="flex flex-row items-center justify-between w-full pt-2">
-          <Attach />
+          <AttachSmall
+            fileIds={fileIds}
+            setFileIds={setFileIds}
+            files={files}
+            setFiles={setFiles}
+          />
           <div className="flex flex-row items-center space-x-4">
             <CopilotToggle
               copilotEnabled={copilotEnabled}
@@ -78,7 +126,7 @@ const MessageInput = ({
             />
             <button
               disabled={message.trim().length === 0 || loading}
-              className="bg-[#24A0ED] text-white disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#ececec21] rounded-full p-2"
+              className="bg-[#24A0ED] text-white text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
             >
               <ArrowUp className="bg-background" size={17} />
             </button>

src/components/MessageInputActions/Attach.tsx

@@ -0,0 +1,185 @@
+import { cn } from '@/lib/utils';
+import {
+  Popover,
+  PopoverButton,
+  PopoverPanel,
+  Transition,
+} from '@headlessui/react';
+import { CopyPlus, File, LoaderCircle, Plus, Trash } from 'lucide-react';
+import { Fragment, useRef, useState } from 'react';
+import { File as FileType } from '../ChatWindow';
+
+const Attach = ({
+  fileIds,
+  setFileIds,
+  showText,
+  files,
+  setFiles,
+}: {
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  showText?: boolean;
+  files: FileType[];
+  setFiles: (files: FileType[]) => void;
+}) => {
+  const [loading, setLoading] = useState(false);
+  const fileInputRef = useRef<any>();
+
+  const handleChange = async (e: React.ChangeEvent<HTMLInputElement>) => {
+    setLoading(true);
+    const data = new FormData();
+
+    for (let i = 0; i < e.target.files!.length; i++) {
+      data.append('files', e.target.files![i]);
+    }
+
+    const embeddingModelProvider = localStorage.getItem(
+      'embeddingModelProvider',
+    );
+    const embeddingModel = localStorage.getItem('embeddingModel');
+
+    data.append('embedding_model_provider', embeddingModelProvider!);
+    data.append('embedding_model', embeddingModel!);
+
+    const res = await fetch(`/api/uploads`, {
+      method: 'POST',
+      body: data,
+    });
+
+    const resData = await res.json();
+
+    setFiles([...files, ...resData.files]);
+    setFileIds([...fileIds, ...resData.files.map((file: any) => file.fileId)]);
+    setLoading(false);
+  };
+
+  return loading ? (
+    <div className="flex flex-row items-center justify-between space-x-1">
+      <LoaderCircle size={18} className="text-sky-400 animate-spin" />
+      <p className="text-sky-400 inline whitespace-nowrap text-xs font-medium">
+        Uploading..
+      </p>
+    </div>
+  ) : files.length > 0 ? (
+    <Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
+      <PopoverButton
+        type="button"
+        className={cn(
+          'flex flex-row items-center justify-between space-x-1 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',
+          files.length > 0 ? '-ml-2 lg:-ml-3' : '',
+        )}
+      >
+        {files.length > 1 && (
+          <>
+            <File size={19} className="text-sky-400" />
+            <p className="text-sky-400 inline whitespace-nowrap text-xs font-medium">
+              {files.length} files
+            </p>
+          </>
+        )}
+
+        {files.length === 1 && (
+          <>
+            <File size={18} className="text-sky-400" />
+            <p className="text-sky-400 text-xs font-medium">
+              {files[0].fileName.length > 10
+                ? files[0].fileName.replace(/\.\w+$/, '').substring(0, 3) +
+                  '...' +
+                  files[0].fileExtension
+                : files[0].fileName}
+            </p>
+          </>
+        )}
+      </PopoverButton>
+      <Transition
+        as={Fragment}
+        enter="transition ease-out duration-150"
+        enterFrom="opacity-0 translate-y-1"
+        enterTo="opacity-100 translate-y-0"
+        leave="transition ease-in duration-150"
+        leaveFrom="opacity-100 translate-y-0"
+        leaveTo="opacity-0 translate-y-1"
+      >
+        <PopoverPanel className="absolute z-10 w-64 md:w-[350px] right-0">
+          <div className="bg-light-primary dark:bg-dark-primary border rounded-md border-light-200 dark:border-dark-200 w-full max-h-[200px] md:max-h-none overflow-y-auto flex flex-col">
+            <div className="flex flex-row items-center justify-between px-3 py-2">
+              <h4 className="text-black dark:text-white font-medium text-sm">
+                Attached files
+              </h4>
+              <div className="flex flex-row items-center space-x-4">
+                <button
+                  type="button"
+                  onClick={() => fileInputRef.current.click()}
+                  className="flex flex-row items-center space-x-1 text-black/70 dark:text-white/70 hover:text-black hover:dark:text-white transition duration-200"
+                >
+                  <input
+                    type="file"
+                    onChange={handleChange}
+                    ref={fileInputRef}
+                    accept=".pdf,.docx,.txt"
+                    multiple
+                    hidden
+                  />
+                  <Plus size={18} />
+                  <p className="text-xs">Add</p>
+                </button>
+                <button
+                  onClick={() => {
+                    setFiles([]);
+                    setFileIds([]);
+                  }}
+                  className="flex flex-row items-center space-x-1 text-black/70 dark:text-white/70 hover:text-black hover:dark:text-white transition duration-200"
+                >
+                  <Trash size={14} />
+                  <p className="text-xs">Clear</p>
+                </button>
+              </div>
+            </div>
+            <div className="h-[0.5px] mx-2 bg-white/10" />
+            <div className="flex flex-col items-center">
+              {files.map((file, i) => (
+                <div
+                  key={i}
+                  className="flex flex-row items-center justify-start w-full space-x-3 p-3"
+                >
+                  <div className="bg-dark-100 flex items-center justify-center w-10 h-10 rounded-md">
+                    <File size={16} className="text-white/70" />
+                  </div>
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    {file.fileName.length > 25
+                      ? file.fileName.replace(/\.\w+$/, '').substring(0, 25) +
+                        '...' +
+                        file.fileExtension
+                      : file.fileName}
+                  </p>
+                </div>
+              ))}
+            </div>
+          </div>
+        </PopoverPanel>
+      </Transition>
+    </Popover>
+  ) : (
+    <button
+      type="button"
+      onClick={() => fileInputRef.current.click()}
+      className={cn(
+        'flex flex-row items-center space-x-1 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white',
+        showText ? '' : 'p-2',
+      )}
+    >
+      <input
+        type="file"
+        onChange={handleChange}
+        ref={fileInputRef}
+        accept=".pdf,.docx,.txt"
+        multiple
+        hidden
+      />
+      <CopyPlus size={showText ? 18 : undefined} />
+      {showText && <p className="text-xs font-medium pl-[1px]">Attach</p>}
+    </button>
+  );
+};
+
+export default Attach;

src/components/MessageInputActions/AttachSmall.tsx

@@ -0,0 +1,153 @@
+import { cn } from '@/lib/utils';
+import {
+  Popover,
+  PopoverButton,
+  PopoverPanel,
+  Transition,
+} from '@headlessui/react';
+import { CopyPlus, File, LoaderCircle, Plus, Trash } from 'lucide-react';
+import { Fragment, useRef, useState } from 'react';
+import { File as FileType } from '../ChatWindow';
+
+const AttachSmall = ({
+  fileIds,
+  setFileIds,
+  files,
+  setFiles,
+}: {
+  fileIds: string[];
+  setFileIds: (fileIds: string[]) => void;
+  files: FileType[];
+  setFiles: (files: FileType[]) => void;
+}) => {
+  const [loading, setLoading] = useState(false);
+  const fileInputRef = useRef<any>();
+
+  const handleChange = async (e: React.ChangeEvent<HTMLInputElement>) => {
+    setLoading(true);
+    const data = new FormData();
+
+    for (let i = 0; i < e.target.files!.length; i++) {
+      data.append('files', e.target.files![i]);
+    }
+
+    const embeddingModelProvider = localStorage.getItem(
+      'embeddingModelProvider',
+    );
+    const embeddingModel = localStorage.getItem('embeddingModel');
+
+    data.append('embedding_model_provider', embeddingModelProvider!);
+    data.append('embedding_model', embeddingModel!);
+
+    const res = await fetch(`/api/uploads`, {
+      method: 'POST',
+      body: data,
+    });
+
+    const resData = await res.json();
+
+    setFiles([...files, ...resData.files]);
+    setFileIds([...fileIds, ...resData.files.map((file: any) => file.fileId)]);
+    setLoading(false);
+  };
+
+  return loading ? (
+    <div className="flex flex-row items-center justify-between space-x-1 p-1">
+      <LoaderCircle size={20} className="text-sky-400 animate-spin" />
+    </div>
+  ) : files.length > 0 ? (
+    <Popover className="max-w-[15rem] md:max-w-md lg:max-w-lg">
+      <PopoverButton
+        type="button"
+        className="flex flex-row items-center justify-between space-x-1 p-1 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"
+      >
+        <File size={20} className="text-sky-400" />
+      </PopoverButton>
+      <Transition
+        as={Fragment}
+        enter="transition ease-out duration-150"
+        enterFrom="opacity-0 translate-y-1"
+        enterTo="opacity-100 translate-y-0"
+        leave="transition ease-in duration-150"
+        leaveFrom="opacity-100 translate-y-0"
+        leaveTo="opacity-0 translate-y-1"
+      >
+        <PopoverPanel className="absolute z-10 w-64 md:w-[350px] bottom-14 -ml-3">
+          <div className="bg-light-primary dark:bg-dark-primary border rounded-md border-light-200 dark:border-dark-200 w-full max-h-[200px] md:max-h-none overflow-y-auto flex flex-col">
+            <div className="flex flex-row items-center justify-between px-3 py-2">
+              <h4 className="text-black dark:text-white font-medium text-sm">
+                Attached files
+              </h4>
+              <div className="flex flex-row items-center space-x-4">
+                <button
+                  type="button"
+                  onClick={() => fileInputRef.current.click()}
+                  className="flex flex-row items-center space-x-1 text-black/70 dark:text-white/70 hover:text-black hover:dark:text-white transition duration-200"
+                >
+                  <input
+                    type="file"
+                    onChange={handleChange}
+                    ref={fileInputRef}
+                    accept=".pdf,.docx,.txt"
+                    multiple
+                    hidden
+                  />
+                  <Plus size={18} />
+                  <p className="text-xs">Add</p>
+                </button>
+                <button
+                  onClick={() => {
+                    setFiles([]);
+                    setFileIds([]);
+                  }}
+                  className="flex flex-row items-center space-x-1 text-black/70 dark:text-white/70 hover:text-black hover:dark:text-white transition duration-200"
+                >
+                  <Trash size={14} />
+                  <p className="text-xs">Clear</p>
+                </button>
+              </div>
+            </div>
+            <div className="h-[0.5px] mx-2 bg-white/10" />
+            <div className="flex flex-col items-center">
+              {files.map((file, i) => (
+                <div
+                  key={i}
+                  className="flex flex-row items-center justify-start w-full space-x-3 p-3"
+                >
+                  <div className="bg-dark-100 flex items-center justify-center w-10 h-10 rounded-md">
+                    <File size={16} className="text-white/70" />
+                  </div>
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    {file.fileName.length > 25
+                      ? file.fileName.replace(/\.\w+$/, '').substring(0, 25) +
+                        '...' +
+                        file.fileExtension
+                      : file.fileName}
+                  </p>
+                </div>
+              ))}
+            </div>
+          </div>
+        </PopoverPanel>
+      </Transition>
+    </Popover>
+  ) : (
+    <button
+      type="button"
+      onClick={() => fileInputRef.current.click()}
+      className="flex flex-row items-center space-x-1 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white p-1"
+    >
+      <input
+        type="file"
+        onChange={handleChange}
+        ref={fileInputRef}
+        accept=".pdf,.docx,.txt"
+        multiple
+        hidden
+      />
+      <CopyPlus size={20} />
+    </button>
+  );
+};
+
+export default AttachSmall;

src/components/MessageInputActions/Copilot.tsx

@@ -0,0 +1,43 @@
+import { cn } from '@/lib/utils';
+import { Switch } from '@headlessui/react';
+
+const CopilotToggle = ({
+  copilotEnabled,
+  setCopilotEnabled,
+}: {
+  copilotEnabled: boolean;
+  setCopilotEnabled: (enabled: boolean) => void;
+}) => {
+  return (
+    <div className="group flex flex-row items-center space-x-1 active:scale-95 duration-200 transition cursor-pointer">
+      <Switch
+        checked={copilotEnabled}
+        onChange={setCopilotEnabled}
+        className="bg-light-secondary dark:bg-dark-secondary border border-light-200/70 dark:border-dark-200 relative inline-flex h-5 w-10 sm:h-6 sm:w-11 items-center rounded-full"
+      >
+        <span className="sr-only">Copilot</span>
+        <span
+          className={cn(
+            copilotEnabled
+              ? 'translate-x-6 bg-[#24A0ED]'
+              : 'translate-x-1 bg-black/50 dark:bg-white/50',
+            'inline-block h-3 w-3 sm:h-4 sm:w-4 transform rounded-full transition-all duration-200',
+          )}
+        />
+      </Switch>
+      <p
+        onClick={() => setCopilotEnabled(!copilotEnabled)}
+        className={cn(
+          'text-xs font-medium transition-colors duration-150 ease-in-out',
+          copilotEnabled
+            ? 'text-[#24A0ED]'
+            : 'text-black/50 dark:text-white/50 group-hover:text-black dark:group-hover:text-white',
+        )}
+      >
+        Copilot
+      </p>
+    </div>
+  );
+};
+
+export default CopilotToggle;

src/components/MessageInputActions/Focus.tsx

@@ -0,0 +1,131 @@
+import {
+  BadgePercent,
+  ChevronDown,
+  Globe,
+  Pencil,
+  ScanEye,
+  SwatchBook,
+} from 'lucide-react';
+import { cn } from '@/lib/utils';
+import {
+  Popover,
+  PopoverButton,
+  PopoverPanel,
+  Transition,
+} from '@headlessui/react';
+import { SiReddit, SiYoutube } from '@icons-pack/react-simple-icons';
+import { Fragment } from 'react';
+
+const focusModes = [
+  {
+    key: 'webSearch',
+    title: 'All',
+    description: 'Searches across all of the internet',
+    icon: <Globe size={20} />,
+  },
+  {
+    key: 'academicSearch',
+    title: 'Academic',
+    description: 'Search in published academic papers',
+    icon: <SwatchBook size={20} />,
+  },
+  {
+    key: 'writingAssistant',
+    title: 'Writing',
+    description: 'Chat without searching the web',
+    icon: <Pencil size={16} />,
+  },
+  {
+    key: 'wolframAlphaSearch',
+    title: 'Wolfram Alpha',
+    description: 'Computational knowledge engine',
+    icon: <BadgePercent size={20} />,
+  },
+  {
+    key: 'youtubeSearch',
+    title: 'Youtube',
+    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 = ({
+  focusMode,
+  setFocusMode,
+}: {
+  focusMode: string;
+  setFocusMode: (mode: string) => void;
+}) => {
+  return (
+    <Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg mt-[6.5px]">
+      <PopoverButton
+        type="button"
+        className=" 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"
+      >
+        {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 hidden lg:block">
+              {focusModes.find((mode) => mode.key === focusMode)?.title}
+            </p>
+            <ChevronDown size={20} className="-translate-x-1" />
+          </div>
+        ) : (
+          <div className="flex flex-row items-center space-x-1">
+            <ScanEye size={20} />
+            <p className="text-xs font-medium hidden lg:block">Focus</p>
+          </div>
+        )}
+      </PopoverButton>
+      <Transition
+        as={Fragment}
+        enter="transition ease-out duration-150"
+        enterFrom="opacity-0 translate-y-1"
+        enterTo="opacity-100 translate-y-0"
+        leave="transition ease-in duration-150"
+        leaveFrom="opacity-100 translate-y-0"
+        leaveTo="opacity-0 translate-y-1"
+      >
+        <PopoverPanel className="absolute z-10 w-64 md:w-[500px] left-0">
+          <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 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">
+            {focusModes.map((mode, i) => (
+              <PopoverButton
+                onClick={() => setFocusMode(mode.key)}
+                key={i}
+                className={cn(
+                  'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-2 duration-200 cursor-pointer transition',
+                  focusMode === mode.key
+                    ? 'bg-light-secondary dark:bg-dark-secondary'
+                    : 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
+                )}
+              >
+                <div
+                  className={cn(
+                    'flex flex-row items-center space-x-1',
+                    focusMode === mode.key
+                      ? 'text-[#24A0ED]'
+                      : 'text-black dark:text-white',
+                  )}
+                >
+                  {mode.icon}
+                  <p className="text-sm font-medium">{mode.title}</p>
+                </div>
+                <p className="text-black/70 dark:text-white/70 text-xs">
+                  {mode.description}
+                </p>
+              </PopoverButton>
+            ))}
+          </div>
+        </PopoverPanel>
+      </Transition>
+    </Popover>
+  );
+};
+
+export default Focus;

src/components/MessageInputActions/Optimization.tsx

@@ -0,0 +1,102 @@
+import { ChevronDown, Sliders, Star, Zap } from 'lucide-react';
+import { cn } from '@/lib/utils';
+import {
+  Popover,
+  PopoverButton,
+  PopoverPanel,
+  Transition,
+} from '@headlessui/react';
+import { Fragment } from 'react';
+
+const OptimizationModes = [
+  {
+    key: 'speed',
+    title: 'Speed',
+    description: 'Prioritize speed and get the quickest possible answer.',
+    icon: <Zap size={20} className="text-[#FF9800]" />,
+  },
+  {
+    key: 'balanced',
+    title: 'Balanced',
+    description: 'Find the right balance between speed and accuracy',
+    icon: <Sliders size={20} className="text-[#4CAF50]" />,
+  },
+  {
+    key: 'quality',
+    title: 'Quality (Soon)',
+    description: 'Get the most thorough and accurate answer',
+    icon: (
+      <Star
+        size={16}
+        className="text-[#2196F3] dark:text-[#BBDEFB] fill-[#BBDEFB] dark:fill-[#2196F3]"
+      />
+    ),
+  },
+];
+
+const Optimization = ({
+  optimizationMode,
+  setOptimizationMode,
+}: {
+  optimizationMode: string;
+  setOptimizationMode: (mode: string) => void;
+}) => {
+  return (
+    <Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
+      <PopoverButton
+        type="button"
+        className="p-2 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
+      >
+        <div className="flex flex-row items-center space-x-1">
+          {
+            OptimizationModes.find((mode) => mode.key === optimizationMode)
+              ?.icon
+          }
+          <p className="text-xs font-medium">
+            {
+              OptimizationModes.find((mode) => mode.key === optimizationMode)
+                ?.title
+            }
+          </p>
+          <ChevronDown size={20} />
+        </div>
+      </PopoverButton>
+      <Transition
+        as={Fragment}
+        enter="transition ease-out duration-150"
+        enterFrom="opacity-0 translate-y-1"
+        enterTo="opacity-100 translate-y-0"
+        leave="transition ease-in duration-150"
+        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">
+            {OptimizationModes.map((mode, i) => (
+              <PopoverButton
+                onClick={() => setOptimizationMode(mode.key)}
+                key={i}
+                className={cn(
+                  'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition',
+                  optimizationMode === mode.key
+                    ? 'bg-light-secondary dark:bg-dark-secondary'
+                    : 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
+                )}
+              >
+                <div className="flex flex-row items-center space-x-1 text-black dark:text-white">
+                  {mode.icon}
+                  <p className="text-sm font-medium">{mode.title}</p>
+                </div>
+                <p className="text-black/70 dark:text-white/70 text-xs">
+                  {mode.description}
+                </p>
+              </PopoverButton>
+            ))}
+          </div>
+        </PopoverPanel>
+      </Transition>
+    </Popover>
+  );
+};
+
+export default Optimization;

src/components/MessageSources.tsx

@@ -0,0 +1,163 @@
+/* eslint-disable @next/next/no-img-element */
+import {
+  Dialog,
+  DialogPanel,
+  DialogTitle,
+  Transition,
+  TransitionChild,
+} from '@headlessui/react';
+import { Document } from '@langchain/core/documents';
+import { File } from 'lucide-react';
+import { Fragment, useState } from 'react';
+
+const MessageSources = ({ sources }: { sources: Document[] }) => {
+  const [isDialogOpen, setIsDialogOpen] = useState(false);
+
+  const closeModal = () => {
+    setIsDialogOpen(false);
+    document.body.classList.remove('overflow-hidden-scrollable');
+  };
+
+  const openModal = () => {
+    setIsDialogOpen(true);
+    document.body.classList.add('overflow-hidden-scrollable');
+  };
+
+  return (
+    <div className="grid grid-cols-2 lg:grid-cols-4 gap-2">
+      {sources.slice(0, 3).map((source, i) => (
+        <a
+          className="bg-light-100 hover:bg-light-200 dark:bg-dark-100 dark:hover:bg-dark-200 transition duration-200 rounded-lg p-3 flex flex-col space-y-2 font-medium"
+          key={i}
+          href={source.metadata.url}
+          target="_blank"
+        >
+          <p className="dark:text-white text-xs overflow-hidden whitespace-nowrap text-ellipsis">
+            {source.metadata.title}
+          </p>
+          <div className="flex flex-row items-center justify-between">
+            <div className="flex flex-row items-center space-x-1">
+              {source.metadata.url === 'File' ? (
+                <div className="bg-dark-200 hover:bg-dark-100 transition duration-200 flex items-center justify-center w-6 h-6 rounded-full">
+                  <File size={12} className="text-white/70" />
+                </div>
+              ) : (
+                <img
+                  src={`https://s2.googleusercontent.com/s2/favicons?domain_url=${source.metadata.url}`}
+                  width={16}
+                  height={16}
+                  alt="favicon"
+                  className="rounded-lg h-4 w-4"
+                />
+              )}
+              <p className="text-xs text-black/50 dark:text-white/50 overflow-hidden whitespace-nowrap text-ellipsis">
+                {source.metadata.url.replace(/.+\/\/|www.|\..+/g, '')}
+              </p>
+            </div>
+            <div className="flex flex-row items-center space-x-1 text-black/50 dark:text-white/50 text-xs">
+              <div className="bg-black/50 dark:bg-white/50 h-[4px] w-[4px] rounded-full" />
+              <span>{i + 1}</span>
+            </div>
+          </div>
+        </a>
+      ))}
+      {sources.length > 3 && (
+        <button
+          onClick={openModal}
+          className="bg-light-100 hover:bg-light-200 dark:bg-dark-100 dark:hover:bg-dark-200 transition duration-200 rounded-lg p-3 flex flex-col space-y-2 font-medium"
+        >
+          <div className="flex flex-row items-center space-x-1">
+            {sources.slice(3, 6).map((source, i) => {
+              return source.metadata.url === 'File' ? (
+                <div
+                  key={i}
+                  className="bg-dark-200 hover:bg-dark-100 transition duration-200 flex items-center justify-center w-6 h-6 rounded-full"
+                >
+                  <File size={12} className="text-white/70" />
+                </div>
+              ) : (
+                <img
+                  key={i}
+                  src={`https://s2.googleusercontent.com/s2/favicons?domain_url=${source.metadata.url}`}
+                  width={16}
+                  height={16}
+                  alt="favicon"
+                  className="rounded-lg h-4 w-4"
+                />
+              );
+            })}
+          </div>
+          <p className="text-xs text-black/50 dark:text-white/50">
+            View {sources.length - 3} more
+          </p>
+        </button>
+      )}
+      <Transition appear show={isDialogOpen} as={Fragment}>
+        <Dialog as="div" className="relative z-50" onClose={closeModal}>
+          <div className="fixed inset-0 overflow-y-auto">
+            <div className="flex min-h-full items-center justify-center p-4 text-center">
+              <TransitionChild
+                as={Fragment}
+                enter="ease-out duration-200"
+                enterFrom="opacity-0 scale-95"
+                enterTo="opacity-100 scale-100"
+                leave="ease-in duration-100"
+                leaveFrom="opacity-100 scale-200"
+                leaveTo="opacity-0 scale-95"
+              >
+                <DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
+                  <DialogTitle className="text-lg font-medium leading-6 dark:text-white">
+                    Sources
+                  </DialogTitle>
+                  <div className="grid grid-cols-2 gap-2 overflow-auto max-h-[300px] mt-2 pr-2">
+                    {sources.map((source, i) => (
+                      <a
+                        className="bg-light-secondary hover:bg-light-200 dark:bg-dark-secondary dark:hover:bg-dark-200 border border-light-200 dark:border-dark-200 transition duration-200 rounded-lg p-3 flex flex-col space-y-2 font-medium"
+                        key={i}
+                        href={source.metadata.url}
+                        target="_blank"
+                      >
+                        <p className="dark:text-white text-xs overflow-hidden whitespace-nowrap text-ellipsis">
+                          {source.metadata.title}
+                        </p>
+                        <div className="flex flex-row items-center justify-between">
+                          <div className="flex flex-row items-center space-x-1">
+                            {source.metadata.url === 'File' ? (
+                              <div className="bg-dark-200 hover:bg-dark-100 transition duration-200 flex items-center justify-center w-6 h-6 rounded-full">
+                                <File size={12} className="text-white/70" />
+                              </div>
+                            ) : (
+                              <img
+                                src={`https://s2.googleusercontent.com/s2/favicons?domain_url=${source.metadata.url}`}
+                                width={16}
+                                height={16}
+                                alt="favicon"
+                                className="rounded-lg h-4 w-4"
+                              />
+                            )}
+                            <p className="text-xs text-black/50 dark:text-white/50 overflow-hidden whitespace-nowrap text-ellipsis">
+                              {source.metadata.url.replace(
+                                /.+\/\/|www.|\..+/g,
+                                '',
+                              )}
+                            </p>
+                          </div>
+                          <div className="flex flex-row items-center space-x-1 text-black/50 dark:text-white/50 text-xs">
+                            <div className="bg-black/50 dark:bg-white/50 h-[4px] w-[4px] rounded-full" />
+                            <span>{i + 1}</span>
+                          </div>
+                        </div>
+                      </a>
+                    ))}
+                  </div>
+                </DialogPanel>
+              </TransitionChild>
+            </div>
+          </div>
+        </Dialog>
+      </Transition>
+    </div>
+  );
+};
+
+export default MessageSources;

src/components/Navbar.tsx

@@ -2,8 +2,15 @@ import { Clock, Edit, Share, Trash } from 'lucide-react';
 import { Message } from './ChatWindow';
 import { useEffect, useState } from 'react';
 import { formatTimeDifference } from '@/lib/utils';
+import DeleteChat from './DeleteChat';
 
-const Navbar = ({ messages }: { messages: Message[] }) => {
+const Navbar = ({
+  chatId,
+  messages,
+}: {
+  messages: Message[];
+  chatId: string;
+}) => {
   const [title, setTitle] = useState<string>('');
   const [timeAgo, setTimeAgo] = useState<string>('');
 
@@ -38,25 +45,25 @@ const Navbar = ({ messages }: { messages: Message[] }) => {
   }, []);
 
   return (
-    <div className="fixed z-40 top-0 left-0 right-0 px-4 lg:pl-[104px] lg:pr-6 lg:px-8 flex flex-row items-center justify-between w-full py-4 text-sm text-white/70 border-b bg-[#0A0A0A] border-[#1C1C1C]">
-      <Edit
-        size={17}
+    <div className="fixed z-40 top-0 left-0 right-0 px-4 lg:pl-[104px] lg:pr-6 lg:px-8 flex flex-row items-center justify-between w-full py-4 text-sm text-black dark:text-white/70 border-b bg-light-primary dark:bg-dark-primary border-light-100 dark:border-dark-200">
+      <a
+        href="/"
         className="active:scale-95 transition duration-100 cursor-pointer lg:hidden"
-      />
+      >
+        <Edit size={17} />
+      </a>
       <div className="hidden lg:flex flex-row items-center justify-center space-x-2">
         <Clock size={17} />
         <p className="text-xs">{timeAgo} ago</p>
       </div>
       <p className="hidden lg:flex">{title}</p>
+
       <div className="flex flex-row items-center space-x-4">
         <Share
           size={17}
           className="active:scale-95 transition duration-100 cursor-pointer"
         />
-        <Trash
-          size={17}
-          className="text-red-400 active:scale-95 transition duration-100 cursor-pointer"
-        />
+        <DeleteChat redirect chatId={chatId} chats={[]} setChats={() => {}} />
       </div>
     </div>
   );

src/components/SearchImages.tsx

@@ -13,10 +13,12 @@ type Image = {
 
 const SearchImages = ({
   query,
-  chat_history,
+  chatHistory,
+  messageId,
 }: {
   query: string;
-  chat_history: Message[];
+  chatHistory: Message[];
+  messageId: string;
 }) => {
   const [images, setImages] = useState<Image[] | null>(null);
   const [loading, setLoading] = useState(false);
@@ -27,31 +29,38 @@ const SearchImages = ({
     <>
       {!loading && images === null && (
         <button
+          id={`search-images-${messageId}`}
           onClick={async () => {
             setLoading(true);
 
             const chatModelProvider = localStorage.getItem('chatModelProvider');
             const chatModel = localStorage.getItem('chatModel');
 
-            const res = await fetch(
-              `${process.env.NEXT_PUBLIC_API_URL}/images`,
-              {
-                method: 'POST',
-                headers: {
-                  'Content-Type': 'application/json',
-                },
-                body: JSON.stringify({
-                  query: query,
-                  chat_history: chat_history,
-                  chat_model_provider: chatModelProvider,
-                  chat_model: chatModel,
-                }),
+            const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
+            const customOpenAIKey = localStorage.getItem('openAIApiKey');
+
+            const res = await fetch(`/api/images`, {
+              method: 'POST',
+              headers: {
+                'Content-Type': 'application/json',
               },
-            );
+              body: JSON.stringify({
+                query: query,
+                chatHistory: chatHistory,
+                chatModel: {
+                  provider: chatModelProvider,
+                  model: chatModel,
+                  ...(chatModelProvider === 'custom_openai' && {
+                    customOpenAIBaseURL: customOpenAIBaseURL,
+                    customOpenAIKey: customOpenAIKey,
+                  }),
+                },
+              }),
+            });
 
             const data = await res.json();
 
-            const images = data.images;
+            const images = data.images ?? [];
             setImages(images);
             setSlides(
               images.map((image: Image) => {
@@ -62,7 +71,7 @@ const SearchImages = ({
             );
             setLoading(false);
           }}
-          className="border border-dashed border-[#1C1C1C] hover:bg-[#1c1c1c] active:scale-95 duration-200 transition px-4 py-2 flex flex-row items-center justify-between rounded-lg text-white text-sm w-full"
+          className="border border-dashed border-light-200 dark:border-dark-200 hover:bg-light-200 dark:hover:bg-dark-200 active:scale-95 duration-200 transition px-4 py-2 flex flex-row items-center justify-between rounded-lg dark:text-white text-sm w-full"
         >
           <div className="flex flex-row items-center space-x-2">
             <ImagesIcon size={17} />
@@ -76,7 +85,7 @@ const SearchImages = ({
           {[...Array(4)].map((_, i) => (
             <div
               key={i}
-              className="bg-[#1C1C1C] h-32 w-full rounded-lg animate-pulse aspect-video object-cover"
+              className="bg-light-secondary dark:bg-dark-secondary h-32 w-full rounded-lg animate-pulse aspect-video object-cover"
             />
           ))}
         </div>
@@ -120,7 +129,7 @@ const SearchImages = ({
             {images.length > 4 && (
               <button
                 onClick={() => setOpen(true)}
-                className="bg-[#111111] hover:bg-[#1c1c1c] transition duration-200 active:scale-95 hover:scale-[1.02] h-auto w-full rounded-lg flex flex-col justify-between text-white p-2"
+                className="bg-light-100 hover:bg-light-200 dark:bg-dark-100 dark:hover:bg-dark-200 transition duration-200 active:scale-95 hover:scale-[1.02] h-auto w-full rounded-lg flex flex-col justify-between text-white p-2"
               >
                 <div className="flex flex-row items-center space-x-1">
                   {images.slice(3, 6).map((image, i) => (
@@ -132,7 +141,7 @@ const SearchImages = ({
                     />
                   ))}
                 </div>
-                <p className="text-white/70 text-xs">
+                <p className="text-black/70 dark:text-white/70 text-xs">
                   View {images.length - 3} more
                 </p>
               </button>

src/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';
@@ -26,45 +26,56 @@ declare module 'yet-another-react-lightbox' {
 
 const Searchvideos = ({
   query,
-  chat_history,
+  chatHistory,
+  messageId,
 }: {
   query: string;
-  chat_history: Message[];
+  chatHistory: Message[];
+  messageId: string;
 }) => {
   const [videos, setVideos] = useState<Video[] | null>(null);
   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 (
     <>
       {!loading && videos === null && (
         <button
+          id={`search-videos-${messageId}`}
           onClick={async () => {
             setLoading(true);
 
             const chatModelProvider = localStorage.getItem('chatModelProvider');
             const chatModel = localStorage.getItem('chatModel');
 
-            const res = await fetch(
-              `${process.env.NEXT_PUBLIC_API_URL}/videos`,
-              {
-                method: 'POST',
-                headers: {
-                  'Content-Type': 'application/json',
-                },
-                body: JSON.stringify({
-                  query: query,
-                  chat_history: chat_history,
-                  chat_model_provider: chatModelProvider,
-                  chat_model: chatModel,
-                }),
+            const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
+            const customOpenAIKey = localStorage.getItem('openAIApiKey');
+
+            const res = await fetch(`/api/videos`, {
+              method: 'POST',
+              headers: {
+                'Content-Type': 'application/json',
               },
-            );
+              body: JSON.stringify({
+                query: query,
+                chatHistory: chatHistory,
+                chatModel: {
+                  provider: chatModelProvider,
+                  model: chatModel,
+                  ...(chatModelProvider === 'custom_openai' && {
+                    customOpenAIBaseURL: customOpenAIBaseURL,
+                    customOpenAIKey: customOpenAIKey,
+                  }),
+                },
+              }),
+            });
 
             const data = await res.json();
 
-            const videos = data.videos;
+            const videos = data.videos ?? [];
             setVideos(videos);
             setSlides(
               videos.map((video: Video) => {
@@ -77,7 +88,7 @@ const Searchvideos = ({
             );
             setLoading(false);
           }}
-          className="border border-dashed border-[#1C1C1C] hover:bg-[#1c1c1c] active:scale-95 duration-200 transition px-4 py-2 flex flex-row items-center justify-between rounded-lg text-white text-sm w-full"
+          className="border border-dashed border-light-200 dark:border-dark-200 hover:bg-light-200 dark:hover:bg-dark-200 active:scale-95 duration-200 transition px-4 py-2 flex flex-row items-center justify-between rounded-lg dark:text-white text-sm w-full"
         >
           <div className="flex flex-row items-center space-x-2">
             <VideoIcon size={17} />
@@ -91,7 +102,7 @@ const Searchvideos = ({
           {[...Array(4)].map((_, i) => (
             <div
               key={i}
-              className="bg-[#1C1C1C] h-32 w-full rounded-lg animate-pulse aspect-video object-cover"
+              className="bg-light-secondary dark:bg-dark-secondary h-32 w-full rounded-lg animate-pulse aspect-video object-cover"
             />
           ))}
         </div>
@@ -118,7 +129,7 @@ const Searchvideos = ({
                       alt={video.title}
                       className="relative h-full w-full aspect-video object-cover rounded-lg"
                     />
-                    <div className="absolute bg-black/70 text-white/70 px-2 py-1 flex flex-row items-center space-x-1 bottom-1 right-1 rounded-md">
+                    <div className="absolute bg-white/70 dark:bg-black/70 text-black/70 dark:text-white/70 px-2 py-1 flex flex-row items-center space-x-1 bottom-1 right-1 rounded-md">
                       <PlayCircle size={15} />
                       <p className="text-xs">Video</p>
                     </div>
@@ -142,7 +153,7 @@ const Searchvideos = ({
                       alt={video.title}
                       className="relative h-full w-full aspect-video object-cover rounded-lg"
                     />
-                    <div className="absolute bg-black/70 text-white/70 px-2 py-1 flex flex-row items-center space-x-1 bottom-1 right-1 rounded-md">
+                    <div className="absolute bg-white/70 dark:bg-black/70 text-black/70 dark:text-white/70 px-2 py-1 flex flex-row items-center space-x-1 bottom-1 right-1 rounded-md">
                       <PlayCircle size={15} />
                       <p className="text-xs">Video</p>
                     </div>
@@ -151,7 +162,7 @@ const Searchvideos = ({
             {videos.length > 4 && (
               <button
                 onClick={() => setOpen(true)}
-                className="bg-[#111111] hover:bg-[#1c1c1c] transition duration-200 active:scale-95 hover:scale-[1.02] h-auto w-full rounded-lg flex flex-col justify-between text-white p-2"
+                className="bg-light-100 hover:bg-light-200 dark:bg-dark-100 dark:hover:bg-dark-200 transition duration-200 active:scale-95 hover:scale-[1.02] h-auto w-full rounded-lg flex flex-col justify-between text-white p-2"
               >
                 <div className="flex flex-row items-center space-x-1">
                   {videos.slice(3, 6).map((video, i) => (
@@ -163,7 +174,7 @@ const Searchvideos = ({
                     />
                   ))}
                 </div>
-                <p className="text-white/70 text-xs">
+                <p className="text-black/70 dark:text-white/70 text-xs">
                   View {videos.length - 3} more
                 </p>
               </button>
@@ -173,18 +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.type === 'video-slide' ? (
+              slide: ({ 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;
+              },
             }}
           />
         </>

src/components/Sidebar.tsx

@@ -4,21 +4,23 @@ import { cn } from '@/lib/utils';
 import { BookOpenText, Home, Search, SquarePen, Settings } from 'lucide-react';
 import Link from 'next/link';
 import { useSelectedLayoutSegments } from 'next/navigation';
-import React, { Fragment, useState } from 'react';
+import React, { useState, type ReactNode } from 'react';
 import Layout from './Layout';
-import { Dialog, Transition } from '@headlessui/react';
-import SettingsDialog from './SettingsDialog';
+
+const VerticalIconContainer = ({ children }: { children: ReactNode }) => {
+  return (
+    <div className="flex flex-col items-center gap-y-3 w-full">{children}</div>
+  );
+};
 
 const Sidebar = ({ children }: { children: React.ReactNode }) => {
   const segments = useSelectedLayoutSegments();
 
-  const [isSettingsOpen, setIsSettingsOpen] = useState(false);
-
   const navLinks = [
     {
       icon: Home,
       href: '/',
-      active: segments.length === 0,
+      active: segments.length === 0 || segments.includes('c'),
       label: 'Home',
     },
     {
@@ -38,50 +40,50 @@ const Sidebar = ({ children }: { children: React.ReactNode }) => {
   return (
     <div>
       <div className="hidden lg:fixed lg:inset-y-0 lg:z-50 lg:flex lg:w-20 lg:flex-col">
-        <div className="flex grow flex-col items-center justify-between gap-y-5 overflow-y-auto bg-[#111111] px-2 py-8">
+        <div className="flex grow flex-col items-center justify-between gap-y-5 overflow-y-auto bg-light-secondary dark:bg-dark-secondary px-2 py-8">
           <a href="/">
-            <SquarePen className="text-white cursor-pointer" />
+            <SquarePen className="cursor-pointer" />
           </a>
-          <div className="flex flex-col items-center gap-y-3 w-full">
+          <VerticalIconContainer>
             {navLinks.map((link, i) => (
               <Link
                 key={i}
                 href={link.href}
                 className={cn(
-                  'relative flex flex-row items-center justify-center cursor-pointer hover:bg-white/10 hover:text-white duration-150 transition w-full py-2 rounded-lg',
-                  link.active ? 'text-white' : 'text-white/70',
+                  'relative flex flex-row items-center justify-center cursor-pointer hover:bg-black/10 dark:hover:bg-white/10 duration-150 transition w-full py-2 rounded-lg',
+                  link.active
+                    ? 'text-black dark:text-white'
+                    : 'text-black/70 dark:text-white/70',
                 )}
               >
                 <link.icon />
                 {link.active && (
-                  <div className="absolute right-0 -mr-2 h-full w-1 rounded-l-lg bg-white" />
+                  <div className="absolute right-0 -mr-2 h-full w-1 rounded-l-lg bg-black dark:bg-white" />
                 )}
               </Link>
             ))}
-          </div>
-          <Settings
-            onClick={() => setIsSettingsOpen(!isSettingsOpen)}
-            className="text-white cursor-pointer"
-          />
-          <SettingsDialog
-            isOpen={isSettingsOpen}
-            setIsOpen={setIsSettingsOpen}
-          />
+          </VerticalIconContainer>
+
+          <Link href="/settings">
+            <Settings className="cursor-pointer" />
+          </Link>
         </div>
       </div>
 
-      <div className="fixed bottom-0 w-full z-50 flex flex-row items-center gap-x-6 bg-[#111111] px-4 py-4 shadow-sm lg:hidden">
+      <div className="fixed bottom-0 w-full z-50 flex flex-row items-center gap-x-6 bg-light-primary dark:bg-dark-primary px-4 py-4 shadow-sm lg:hidden">
         {navLinks.map((link, i) => (
           <Link
             href={link.href}
             key={i}
             className={cn(
               'relative flex flex-col items-center space-y-1 text-center w-full',
-              link.active ? 'text-white' : 'text-white/70',
+              link.active
+                ? 'text-black dark:text-white'
+                : 'text-black dark:text-white/70',
             )}
           >
             {link.active && (
-              <div className="absolute top-0 -mt-4 h-1 w-full rounded-b-lg bg-white" />
+              <div className="absolute top-0 -mt-4 h-1 w-full rounded-b-lg bg-black dark:bg-white" />
             )}
             <link.icon />
             <p className="text-xs">{link.label}</p>

src/components/ThinkBox.tsx

@@ -0,0 +1,43 @@
+'use client';
+
+import { useState } from 'react';
+import { cn } from '@/lib/utils';
+import { ChevronDown, ChevronUp, BrainCircuit } from 'lucide-react';
+
+interface ThinkBoxProps {
+  content: string;
+}
+
+const ThinkBox = ({ content }: ThinkBoxProps) => {
+  const [isExpanded, setIsExpanded] = useState(false);
+
+  return (
+    <div className="my-4 bg-light-secondary/50 dark:bg-dark-secondary/50 rounded-xl border border-light-200 dark:border-dark-200 overflow-hidden">
+      <button
+        onClick={() => setIsExpanded(!isExpanded)}
+        className="w-full flex items-center justify-between px-4 py-1 text-black/90 dark:text-white/90 hover:bg-light-200 dark:hover:bg-dark-200 transition duration-200"
+      >
+        <div className="flex items-center space-x-2">
+          <BrainCircuit
+            size={20}
+            className="text-[#9C27B0] dark:text-[#CE93D8]"
+          />
+          <p className="font-medium text-sm">Thinking Process</p>
+        </div>
+        {isExpanded ? (
+          <ChevronUp size={18} className="text-black/70 dark:text-white/70" />
+        ) : (
+          <ChevronDown size={18} className="text-black/70 dark:text-white/70" />
+        )}
+      </button>
+
+      {isExpanded && (
+        <div className="px-4 py-3 text-black/80 dark:text-white/80 text-sm border-t border-light-200 dark:border-dark-200 bg-light-100/50 dark:bg-dark-100/50 whitespace-pre-wrap">
+          {content}
+        </div>
+      )}
+    </div>
+  );
+};
+
+export default ThinkBox;

src/components/theme/Provider.tsx

@@ -0,0 +1,16 @@
+'use client';
+import { ThemeProvider } from 'next-themes';
+
+const ThemeProviderComponent = ({
+  children,
+}: {
+  children: React.ReactNode;
+}) => {
+  return (
+    <ThemeProvider attribute="class" enableSystem={false} defaultTheme="dark">
+      {children}
+    </ThemeProvider>
+  );
+};
+
+export default ThemeProviderComponent;

src/components/theme/Switcher.tsx

@@ -0,0 +1,60 @@
+'use client';
+import { useTheme } from 'next-themes';
+import { useCallback, useEffect, useState } from 'react';
+import Select from '../ui/Select';
+
+type Theme = 'dark' | 'light' | 'system';
+
+const ThemeSwitcher = ({ className }: { className?: string }) => {
+  const [mounted, setMounted] = useState(false);
+
+  const { theme, setTheme } = useTheme();
+
+  const isTheme = useCallback((t: Theme) => t === theme, [theme]);
+
+  const handleThemeSwitch = (theme: Theme) => {
+    setTheme(theme);
+  };
+
+  useEffect(() => {
+    setMounted(true);
+  }, []);
+
+  useEffect(() => {
+    if (isTheme('system')) {
+      const preferDarkScheme = window.matchMedia(
+        '(prefers-color-scheme: dark)',
+      );
+
+      const detectThemeChange = (event: MediaQueryListEvent) => {
+        const theme: Theme = event.matches ? 'dark' : 'light';
+        setTheme(theme);
+      };
+
+      preferDarkScheme.addEventListener('change', detectThemeChange);
+
+      return () => {
+        preferDarkScheme.removeEventListener('change', detectThemeChange);
+      };
+    }
+  }, [isTheme, setTheme, theme]);
+
+  // Avoid Hydration Mismatch
+  if (!mounted) {
+    return null;
+  }
+
+  return (
+    <Select
+      className={className}
+      value={theme}
+      onChange={(e) => handleThemeSwitch(e.target.value as Theme)}
+      options={[
+        { value: 'light', label: 'Light' },
+        { value: 'dark', label: 'Dark' },
+      ]}
+    />
+  );
+};
+
+export default ThemeSwitcher;

src/components/ui/Select.tsx

@@ -0,0 +1,28 @@
+import { cn } from '@/lib/utils';
+import { SelectHTMLAttributes } from 'react';
+
+interface SelectProps extends SelectHTMLAttributes<HTMLSelectElement> {
+  options: { value: string; label: string; disabled?: boolean }[];
+}
+
+export const Select = ({ className, options, ...restProps }: SelectProps) => {
+  return (
+    <select
+      {...restProps}
+      className={cn(
+        'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
+        className,
+      )}
+    >
+      {options.map(({ label, value, disabled }) => {
+        return (
+          <option key={value} value={value} disabled={disabled}>
+            {label}
+          </option>
+        );
+      })}
+    </select>
+  );
+};
+
+export default Select;

src/config.ts

@@ -1,69 +0,0 @@
-import fs from 'fs';
-import path from 'path';
-import toml from '@iarna/toml';
-
-const configFileName = 'config.toml';
-
-interface Config {
-  GENERAL: {
-    PORT: number;
-    SIMILARITY_MEASURE: string;
-  };
-  API_KEYS: {
-    OPENAI: string;
-    GROQ: string;
-  };
-  API_ENDPOINTS: {
-    SEARXNG: string;
-    OLLAMA: string;
-  };
-}
-
-type RecursivePartial<T> = {
-  [P in keyof T]?: RecursivePartial<T[P]>;
-};
-
-const loadConfig = () =>
-  toml.parse(
-    fs.readFileSync(path.join(__dirname, `../${configFileName}`), 'utf-8'),
-  ) as any as Config;
-
-export const getPort = () => loadConfig().GENERAL.PORT;
-
-export const getSimilarityMeasure = () =>
-  loadConfig().GENERAL.SIMILARITY_MEASURE;
-
-export const getOpenaiApiKey = () => loadConfig().API_KEYS.OPENAI;
-
-export const getGroqApiKey = () => loadConfig().API_KEYS.GROQ;
-
-export const getSearxngApiEndpoint = () => loadConfig().API_ENDPOINTS.SEARXNG;
-
-export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;
-
-export const updateConfig = (config: RecursivePartial<Config>) => {
-  const currentConfig = loadConfig();
-
-  for (const key in currentConfig) {
-    if (!config[key]) config[key] = {};
-
-    if (typeof currentConfig[key] === 'object' && currentConfig[key] !== null) {
-      for (const nestedKey in currentConfig[key]) {
-        if (
-          !config[key][nestedKey] &&
-          currentConfig[key][nestedKey] &&
-          config[key][nestedKey] !== ''
-        ) {
-          config[key][nestedKey] = currentConfig[key][nestedKey];
-        }
-      }
-    } else if (currentConfig[key] && config[key] !== '') {
-      config[key] = currentConfig[key];
-    }
-  }
-
-  fs.writeFileSync(
-    path.join(__dirname, `../${configFileName}`),
-    toml.stringify(config),
-  );
-};

src/lib/actions.ts

@@ -4,15 +4,24 @@ export const getSuggestions = async (chatHisory: Message[]) => {
   const chatModel = localStorage.getItem('chatModel');
   const chatModelProvider = localStorage.getItem('chatModelProvider');
 
-  const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/suggestions`, {
+  const customOpenAIKey = localStorage.getItem('openAIApiKey');
+  const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
+
+  const res = await fetch(`/api/suggestions`, {
     method: 'POST',
     headers: {
       'Content-Type': 'application/json',
     },
     body: JSON.stringify({
-      chat_history: chatHisory,
-      chat_model: chatModel,
-      chat_model_provider: chatModelProvider,
+      chatHistory: chatHisory,
+      chatModel: {
+        provider: chatModelProvider,
+        model: chatModel,
+        ...(chatModelProvider === 'custom_openai' && {
+          customOpenAIKey,
+          customOpenAIBaseURL,
+        }),
+      },
     }),
   });
 

src/lib/chains/imageSearchAgent.ts

@@ -7,7 +7,7 @@ import { PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
-import { searchSearxng } from '../lib/searxng';
+import { searchSearxng } from '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const imageSearchChainPrompt = `
@@ -36,6 +36,12 @@ type ImageSearchChainInput = {
   query: string;
 };
 
+interface ImageSearchResult {
+  img_src: string;
+  url: string;
+  title: string;
+}
+
 const strParser = new StringOutputParser();
 
 const createImageSearchChain = (llm: BaseChatModel) => {
@@ -52,11 +58,13 @@ const createImageSearchChain = (llm: BaseChatModel) => {
     llm,
     strParser,
     RunnableLambda.from(async (input: string) => {
+      input = input.replace(/<think>.*?<\/think>/g, '');
+
       const res = await searchSearxng(input, {
         engines: ['bing images', 'google images'],
       });
 
-      const images = [];
+      const images: ImageSearchResult[] = [];
 
       res.results.forEach((result) => {
         if (result.img_src && result.url && result.title) {

src/lib/chains/suggestionGeneratorAgent.ts

@@ -1,5 +1,5 @@
 import { RunnableSequence, RunnableMap } from '@langchain/core/runnables';
-import ListLineOutputParser from '../lib/outputParsers/listLineOutputParser';
+import ListLineOutputParser from '../outputParsers/listLineOutputParser';
 import { PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
@@ -47,7 +47,7 @@ const generateSuggestions = (
   input: SuggestionGeneratorInput,
   llm: BaseChatModel,
 ) => {
-  (llm as ChatOpenAI).temperature = 0;
+  (llm as unknown as ChatOpenAI).temperature = 0;
   const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
   return suggestionGeneratorChain.invoke(input);
 };

src/lib/chains/videoSearchAgent.ts

@@ -7,7 +7,7 @@ import { PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
-import { searchSearxng } from '../lib/searxng';
+import { searchSearxng } from '../searxng';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 
 const VideoSearchChainPrompt = `
@@ -36,6 +36,13 @@ type VideoSearchChainInput = {
   query: string;
 };
 
+interface VideoSearchResult {
+  img_src: string;
+  url: string;
+  title: string;
+  iframe_src: string;
+}
+
 const strParser = new StringOutputParser();
 
 const createVideoSearchChain = (llm: BaseChatModel) => {
@@ -52,11 +59,13 @@ const createVideoSearchChain = (llm: BaseChatModel) => {
     llm,
     strParser,
     RunnableLambda.from(async (input: string) => {
+      input = input.replace(/<think>.*?<\/think>/g, '');
+
       const res = await searchSearxng(input, {
         engines: ['youtube'],
       });
 
-      const videos = [];
+      const videos: VideoSearchResult[] = [];
 
       res.results.forEach((result) => {
         if (

src/lib/config.ts

@@ -0,0 +1,118 @@
+import fs from 'fs';
+import path from 'path';
+import toml from '@iarna/toml';
+
+const configFileName = 'config.toml';
+
+interface Config {
+  GENERAL: {
+    SIMILARITY_MEASURE: string;
+    KEEP_ALIVE: string;
+  };
+  MODELS: {
+    OPENAI: {
+      API_KEY: string;
+    };
+    GROQ: {
+      API_KEY: string;
+    };
+    ANTHROPIC: {
+      API_KEY: string;
+    };
+    GEMINI: {
+      API_KEY: string;
+    };
+    OLLAMA: {
+      API_URL: string;
+    };
+    DEEPSEEK: {
+      API_KEY: string;
+    };
+    CUSTOM_OPENAI: {
+      API_URL: string;
+      API_KEY: string;
+      MODEL_NAME: string;
+    };
+  };
+  API_ENDPOINTS: {
+    SEARXNG: string;
+  };
+}
+
+type RecursivePartial<T> = {
+  [P in keyof T]?: RecursivePartial<T[P]>;
+};
+
+const loadConfig = () =>
+  toml.parse(
+    fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
+  ) as any as Config;
+
+export const getSimilarityMeasure = () =>
+  loadConfig().GENERAL.SIMILARITY_MEASURE;
+
+export const getKeepAlive = () => loadConfig().GENERAL.KEEP_ALIVE;
+
+export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
+
+export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
+
+export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
+
+export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
+
+export const getSearxngApiEndpoint = () =>
+  process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
+
+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;
+
+export const getCustomOpenaiApiUrl = () =>
+  loadConfig().MODELS.CUSTOM_OPENAI.API_URL;
+
+export const getCustomOpenaiModelName = () =>
+  loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
+
+const mergeConfigs = (current: any, update: any): any => {
+  if (update === null || update === undefined) {
+    return current;
+  }
+
+  if (typeof current !== 'object' || current === null) {
+    return update;
+  }
+
+  const result = { ...current };
+
+  for (const key in update) {
+    if (Object.prototype.hasOwnProperty.call(update, key)) {
+      const updateValue = update[key];
+
+      if (
+        typeof updateValue === 'object' &&
+        updateValue !== null &&
+        typeof result[key] === 'object' &&
+        result[key] !== null
+      ) {
+        result[key] = mergeConfigs(result[key], updateValue);
+      } else if (updateValue !== undefined) {
+        result[key] = updateValue;
+      }
+    }
+  }
+
+  return result;
+};
+
+export const updateConfig = (config: RecursivePartial<Config>) => {
+  const currentConfig = loadConfig();
+  const mergedConfig = mergeConfigs(currentConfig, config);
+  fs.writeFileSync(
+    path.join(path.join(process.cwd(), `${configFileName}`)),
+    toml.stringify(mergedConfig),
+  );
+};

src/lib/db/index.ts

@@ -0,0 +1,11 @@
+import { drizzle } from 'drizzle-orm/better-sqlite3';
+import Database from 'better-sqlite3';
+import * as schema from './schema';
+import path from 'path';
+
+const sqlite = new Database(path.join(process.cwd(), 'data/db.sqlite'));
+const db = drizzle(sqlite, {
+  schema: schema,
+});
+
+export default db;

src/lib/db/schema.ts

@@ -0,0 +1,28 @@
+import { sql } from 'drizzle-orm';
+import { text, integer, sqliteTable } from 'drizzle-orm/sqlite-core';
+
+export const messages = sqliteTable('messages', {
+  id: integer('id').primaryKey(),
+  content: text('content').notNull(),
+  chatId: text('chatId').notNull(),
+  messageId: text('messageId').notNull(),
+  role: text('type', { enum: ['assistant', 'user'] }),
+  metadata: text('metadata', {
+    mode: 'json',
+  }),
+});
+
+interface File {
+  name: string;
+  fileId: string;
+}
+
+export const chats = sqliteTable('chats', {
+  id: text('id').primaryKey(),
+  title: text('title').notNull(),
+  createdAt: text('createdAt').notNull(),
+  focusMode: text('focusMode').notNull(),
+  files: text('files', { mode: 'json' })
+    .$type<File[]>()
+    .default(sql`'[]'`),
+});

src/lib/huggingfaceTransformer.ts

@@ -28,7 +28,7 @@ export class HuggingFaceTransformersEmbeddings
 
   timeout?: number;
 
-  private pipelinePromise: Promise<any>;
+  private pipelinePromise: Promise<any> | undefined;
 
   constructor(fields?: Partial<HuggingFaceTransformersEmbeddingsParams>) {
     super(fields ?? {});

src/lib/outputParsers/lineOutputParser.ts

@@ -0,0 +1,48 @@
+import { BaseOutputParser } from '@langchain/core/output_parsers';
+
+interface LineOutputParserArgs {
+  key?: string;
+}
+
+class LineOutputParser extends BaseOutputParser<string> {
+  private key = 'questions';
+
+  constructor(args?: LineOutputParserArgs) {
+    super();
+    this.key = args?.key ?? this.key;
+  }
+
+  static lc_name() {
+    return 'LineOutputParser';
+  }
+
+  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}>`);
+
+    if (startKeyIndex === -1 || endKeyIndex === -1) {
+      return '';
+    }
+
+    const questionsStartIndex =
+      startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
+    const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
+    const line = text
+      .slice(questionsStartIndex, questionsEndIndex)
+      .trim()
+      .replace(regex, '');
+
+    return line;
+  }
+
+  getFormatInstructions(): string {
+    throw new Error('Not implemented.');
+  }
+}
+
+export default LineOutputParser;

src/lib/outputParsers/listLineOutputParser.ts

@@ -9,7 +9,7 @@ class LineListOutputParser extends BaseOutputParser<string[]> {
 
   constructor(args?: LineListOutputParserArgs) {
     super();
-    this.key = args.key ?? this.key;
+    this.key = args?.key ?? this.key;
   }
 
   static lc_name() {
@@ -19,9 +19,16 @@ 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) {
+      return [];
+    }
+
     const questionsStartIndex =
       startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
     const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;

src/lib/prompts/academicSearch.ts

@@ -0,0 +1,69 @@
+export const academicSearchRetrieverPrompt = `
+You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
+If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
+
+Example:
+1. Follow up question: How does stable diffusion work?
+Rephrased: Stable diffusion working
+
+2. Follow up question: What is linear algebra?
+Rephrased: Linear algebra
+
+3. Follow up question: What is the third law of thermodynamics?
+Rephrased: Third law of thermodynamics
+
+Conversation:
+{chat_history}
+
+Follow up question: {query}
+Rephrased question:
+`;
+
+export const academicSearchResponsePrompt = `
+   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.
+
+    Your task is to provide answers that are:
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
+
+    ### Formatting Instructions
+    - **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.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
+
+    <context>
+    {context}
+    </context>
+
+    Current date & time in ISO format (UTC timezone) is: {date}.
+`;

src/lib/prompts/index.ts

@@ -0,0 +1,32 @@
+import {
+  academicSearchResponsePrompt,
+  academicSearchRetrieverPrompt,
+} from './academicSearch';
+import {
+  redditSearchResponsePrompt,
+  redditSearchRetrieverPrompt,
+} from './redditSearch';
+import { webSearchResponsePrompt, webSearchRetrieverPrompt } from './webSearch';
+import {
+  wolframAlphaSearchResponsePrompt,
+  wolframAlphaSearchRetrieverPrompt,
+} from './wolframAlpha';
+import { writingAssistantPrompt } from './writingAssistant';
+import {
+  youtubeSearchResponsePrompt,
+  youtubeSearchRetrieverPrompt,
+} from './youtubeSearch';
+
+export default {
+  webSearchResponsePrompt,
+  webSearchRetrieverPrompt,
+  academicSearchResponsePrompt,
+  academicSearchRetrieverPrompt,
+  redditSearchResponsePrompt,
+  redditSearchRetrieverPrompt,
+  wolframAlphaSearchResponsePrompt,
+  wolframAlphaSearchRetrieverPrompt,
+  writingAssistantPrompt,
+  youtubeSearchResponsePrompt,
+  youtubeSearchRetrieverPrompt,
+};

src/lib/prompts/redditSearch.ts

@@ -0,0 +1,69 @@
+export const redditSearchRetrieverPrompt = `
+You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
+If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
+
+Example:
+1. Follow up question: Which company is most likely to create an AGI
+Rephrased: Which company is most likely to create an AGI
+
+2. Follow up question: Is Earth flat?
+Rephrased: Is Earth flat?
+
+3. Follow up question: Is there life on Mars?
+Rephrased: Is there life on Mars?
+
+Conversation:
+{chat_history}
+
+Follow up question: {query}
+Rephrased question:
+`;
+
+export const redditSearchResponsePrompt = `
+    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.
+
+    Your task is to provide answers that are:
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
+
+    ### Formatting Instructions
+    - **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.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
+
+    <context>
+    {context}
+    </context>
+
+    Current date & time in ISO format (UTC timezone) is: {date}.
+`;

src/lib/prompts/webSearch.ts

@@ -0,0 +1,110 @@
+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 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.
+
+There are several examples attached for your reference inside the below \`examples\` XML block
+
+<examples>
+1. Follow up question: What is the capital of France
+Rephrased question:\`
+<question>
+Capital of france
+</question>
+\`
+
+2. Hi, how are you?
+Rephrased question\`
+<question>
+not_needed
+</question>
+\`
+
+3. Follow up question: What is Docker?
+Rephrased question: \`
+<question>
+What is Docker
+</question>
+\`
+
+4. Follow up question: Can you tell me what is X from https://example.com
+Rephrased question: \`
+<question>
+Can you tell me what is X?
+</question>
+
+<links>
+https://example.com
+</links>
+\`
+
+5. Follow up question: Summarize the content from https://example.com
+Rephrased question: \`
+<question>
+summarize
+</question>
+
+<links>
+https://example.com
+</links>
+\`
+</examples>
+
+Anything below is the part of the actual conversation and you need to use conversation and the follow-up question to rephrase the follow-up question as a standalone question based on the guidelines shared above.
+
+<conversation>
+{chat_history}
+</conversation>
+
+Follow up question: {query}
+Rephrased question:
+`;
+
+export const webSearchResponsePrompt = `
+    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.
+
+    Your task is to provide answers that are:
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
+
+    ### Formatting Instructions
+    - **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.
+
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
+
+    <context>
+    {context}
+    </context>
+
+    Current date & time in ISO format (UTC timezone) is: {date}.
+`;

src/lib/prompts/wolframAlpha.ts

@@ -0,0 +1,69 @@
+export const wolframAlphaSearchRetrieverPrompt = `
+You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
+If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
+
+Example:
+1. Follow up question: What is the atomic radius of S?
+Rephrased: Atomic radius of S
+
+2. Follow up question: What is linear algebra?
+Rephrased: Linear algebra
+
+3. Follow up question: What is the third law of thermodynamics?
+Rephrased: Third law of thermodynamics
+
+Conversation:
+{chat_history}
+
+Follow up question: {query}
+Rephrased question:
+`;
+
+export const wolframAlphaSearchResponsePrompt = `
+    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.
+
+    Your task is to provide answers that are:
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
+
+    ### Formatting Instructions
+    - **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.
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
+
+    <context>
+    {context}
+    </context>
+
+    Current date & time in ISO format (UTC timezone) is: {date}.
+`;

src/lib/prompts/writingAssistant.ts

@@ -0,0 +1,17 @@
+export const writingAssistantPrompt = `
+You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query. 
+Since you are a writing assistant, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode.
+You will be shared a context that can contain information from files user has uploaded to get answers from. You will have to generate answers upon that.
+
+You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
+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/youtubeSearch.ts

@@ -0,0 +1,69 @@
+export const youtubeSearchRetrieverPrompt = `
+You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
+If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
+
+Example:
+1. Follow up question: How does an A.C work?
+Rephrased: A.C working
+
+2. Follow up question: Linear algebra explanation video
+Rephrased: What is linear algebra?
+
+3. Follow up question: What is theory of relativity?
+Rephrased: What is theory of relativity?
+
+Conversation:
+{chat_history}
+
+Follow up question: {query}
+Rephrased question:
+`;
+
+export const youtubeSearchResponsePrompt = `
+    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.
+
+    Your task is to provide answers that are:
+    - **Informative and relevant**: Thoroughly address the user's query using the given context.
+    - **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
+    - **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
+    - **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
+    - **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
+
+    ### Formatting Instructions
+    - **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
+    
+    ### 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.
+    - Provide explanations or historical context as needed to enhance understanding.
+    - End with a conclusion or overall perspective if relevant.
+
+    <context>
+    {context}
+    </context>
+
+    Current date & time in ISO format (UTC timezone) is: {date}.
+`;

src/lib/providers.ts

@@ -1,187 +0,0 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { ChatOllama } from '@langchain/community/chat_models/ollama';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
-import { HuggingFaceTransformersEmbeddings } from './huggingfaceTransformer';
-import {
-  getGroqApiKey,
-  getOllamaApiEndpoint,
-  getOpenaiApiKey,
-} from '../config';
-import logger from '../utils/logger';
-
-export const getAvailableChatModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const groqApiKey = getGroqApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'GPT-3.5 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-3.5-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4',
-          temperature: 0.7,
-        }),
-        'GPT-4 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4 omni': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4o',
-          temperature: 0.7,
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI models: ${err}`);
-    }
-  }
-
-  if (groqApiKey) {
-    try {
-      models['groq'] = {
-        'LLaMA3 8b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-8b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'LLaMA3 70b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-70b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Mixtral 8x7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'mixtral-8x7b-32768',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Gemma 7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'gemma-7b-it',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-      };
-    } catch (err) {
-      logger.error(`Error loading Groq models: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new ChatOllama({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-          temperature: 0.7,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama models: ${err}`);
-    }
-  }
-
-  models['custom_openai'] = {};
-
-  return models;
-};
-
-export const getAvailableEmbeddingModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'Text embedding 3 small': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-small',
-        }),
-        'Text embedding 3 large': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-large',
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI embeddings: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new OllamaEmbeddings({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama embeddings: ${err}`);
-    }
-  }
-
-  try {
-    models['local'] = {
-      'BGE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bge-small-en-v1.5',
-      }),
-      'GTE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/gte-small',
-      }),
-      'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bert-base-multilingual-uncased',
-      }),
-    };
-  } catch (err) {
-    logger.error(`Error loading local embeddings: ${err}`);
-  }
-
-  return models;
-};

src/lib/providers/anthropic.ts

@@ -0,0 +1,61 @@
+import { ChatAnthropic } from '@langchain/anthropic';
+import { ChatModel } from '.';
+import { getAnthropicApiKey } from '../config';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+
+const anthropicChatModels: Record<string, string>[] = [
+  {
+    displayName: 'Claude 3.7 Sonnet',
+    key: 'claude-3-7-sonnet-20250219',
+  },
+  {
+    displayName: 'Claude 3.5 Haiku',
+    key: 'claude-3-5-haiku-20241022',
+  },
+  {
+    displayName: 'Claude 3.5 Sonnet v2',
+    key: 'claude-3-5-sonnet-20241022',
+  },
+  {
+    displayName: 'Claude 3.5 Sonnet',
+    key: 'claude-3-5-sonnet-20240620',
+  },
+  {
+    displayName: 'Claude 3 Opus',
+    key: 'claude-3-opus-20240229',
+  },
+  {
+    displayName: 'Claude 3 Sonnet',
+    key: 'claude-3-sonnet-20240229',
+  },
+  {
+    displayName: 'Claude 3 Haiku',
+    key: 'claude-3-haiku-20240307',
+  },
+];
+
+export const loadAnthropicChatModels = async () => {
+  const anthropicApiKey = getAnthropicApiKey();
+
+  if (!anthropicApiKey) return {};
+
+  try {
+    const chatModels: Record<string, ChatModel> = {};
+
+    anthropicChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatAnthropic({
+          apiKey: anthropicApiKey,
+          modelName: model.key,
+          temperature: 0.7,
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading Anthropic models: ${err}`);
+    return {};
+  }
+};

src/lib/providers/deepseek.ts

@@ -0,0 +1,44 @@
+import { ChatOpenAI } from '@langchain/openai';
+import { getDeepseekApiKey } from '../config';
+import { ChatModel } from '.';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+
+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

@@ -0,0 +1,101 @@
+import {
+  ChatGoogleGenerativeAI,
+  GoogleGenerativeAIEmbeddings,
+} from '@langchain/google-genai';
+import { getGeminiApiKey } from '../config';
+import { ChatModel, EmbeddingModel } from '.';
+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',
+  },
+  {
+    displayName: 'Gemini 2.0 Flash-Lite',
+    key: 'gemini-2.0-flash-lite',
+  },
+  {
+    displayName: 'Gemini 2.0 Flash Thinking Experimental',
+    key: 'gemini-2.0-flash-thinking-exp-01-21',
+  },
+  {
+    displayName: 'Gemini 1.5 Flash',
+    key: 'gemini-1.5-flash',
+  },
+  {
+    displayName: 'Gemini 1.5 Flash-8B',
+    key: 'gemini-1.5-flash-8b',
+  },
+  {
+    displayName: 'Gemini 1.5 Pro',
+    key: 'gemini-1.5-pro',
+  },
+];
+
+const geminiEmbeddingModels: Record<string, string>[] = [
+  {
+    displayName: 'Text Embedding 004',
+    key: 'models/text-embedding-004',
+  },
+  {
+    displayName: 'Embedding 001',
+    key: 'models/embedding-001',
+  },
+];
+
+export const loadGeminiChatModels = async () => {
+  const geminiApiKey = getGeminiApiKey();
+
+  if (!geminiApiKey) return {};
+
+  try {
+    const chatModels: Record<string, ChatModel> = {};
+
+    geminiChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatGoogleGenerativeAI({
+          apiKey: geminiApiKey,
+          modelName: model.key,
+          temperature: 0.7,
+        }) as unknown as BaseChatModel,
+      };
+    });
+
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading Gemini models: ${err}`);
+    return {};
+  }
+};
+
+export const loadGeminiEmbeddingModels = async () => {
+  const geminiApiKey = getGeminiApiKey();
+
+  if (!geminiApiKey) return {};
+
+  try {
+    const embeddingModels: Record<string, EmbeddingModel> = {};
+
+    geminiEmbeddingModels.forEach((model) => {
+      embeddingModels[model.key] = {
+        displayName: model.displayName,
+        model: new GoogleGenerativeAIEmbeddings({
+          apiKey: geminiApiKey,
+          modelName: model.key,
+        }) as unknown as Embeddings,
+      };
+    });
+
+    return embeddingModels;
+  } catch (err) {
+    console.error(`Error loading OpenAI embeddings models: ${err}`);
+    return {};
+  }
+};