Merge pull request #736 from ItzCrazyKns/master

Merge master into feat/deep-research

.github/workflows/docker-build.yaml

@@ -8,15 +8,12 @@ on:
     types: [published]
 
 jobs:
-  build-and-push:
+  build-amd64:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
         uses: actions/checkout@v3
 
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v2
-
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v2
         with:
@@ -33,28 +30,109 @@ jobs:
         id: version
         run: echo "RELEASE_VERSION=${GITHUB_REF#refs/tags/}" >> $GITHUB_ENV
 
-      - name: Build and push Docker image
+      - name: Build and push AMD64 Docker image
         if: github.ref == 'refs/heads/master' && github.event_name == 'push'
         run: |
-          docker buildx create --use
-          DOCKERFILE=app.dockerfile; \
-          IMAGE_NAME=perplexica; \
-          docker buildx build --platform linux/amd64,linux/arm64 \
-            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:main \
+          DOCKERFILE=app.dockerfile
+          IMAGE_NAME=perplexica
+          docker buildx build --platform linux/amd64 \
+            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:amd64 \
             --cache-to=type=inline \
+            --provenance false \
             -f $DOCKERFILE \
-            -t itzcrazykns1337/${IMAGE_NAME}:main \
+            -t itzcrazykns1337/${IMAGE_NAME}:amd64 \
             --push .
 
-      - name: Build and push release Docker image
+      - name: Build and push AMD64 release Docker image
         if: github.event_name == 'release'
         run: |
-          docker buildx create --use
-          DOCKERFILE=app.dockerfile; \
-          IMAGE_NAME=perplexica; \
-          docker buildx build --platform linux/amd64,linux/arm64 \
-            --cache-from=type=registry,ref=itzcrazykns1337/${IMAGE_NAME}:${{ env.RELEASE_VERSION }} \
+          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}:${{ env.RELEASE_VERSION }} \
+            -t itzcrazykns1337/${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 }}

CONTRIBUTING.md

@@ -1,32 +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.
-  - All of the focus modes are created using the Meta Search Agent class present in `src/search/metaSearchAgent.ts`. The main logic behind Perplexica lies there.
+- **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. Run `npm run db:push` to set up the local sqlite.
-5. 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

@@ -109,14 +109,13 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
 
 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. Rename the `.env.example` file to `.env` in the `ui` folder and fill in all necessary fields.
-4. After populating the configuration and environment files, run `npm i` in both the `ui` folder and the root directory.
-5. Install the dependencies and then execute `npm run build` in both the `ui` folder and the root directory.
-6. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
+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
 
@@ -154,7 +153,7 @@ For more details, check out the full documentation [here](https://github.com/Itz
 
 ## Expose Perplexica to network
 
-You can access Perplexica over your home network by following our networking guide [here](https://github.com/ItzCrazyKns/Perplexica/blob/master/docs/installation/NETWORKING.md).
+Perplexica runs on Next.js and handles all API requests. It works right away on the same network and stays accessible even with port forwarding.
 
 ## One-Click Deployment
 

app.dockerfile

@@ -1,9 +1,9 @@
-FROM node:20.18.0-alpine AS builder
+FROM node:20.18.0-slim AS builder
 
 WORKDIR /home/perplexica
 
 COPY package.json yarn.lock ./
-RUN yarn install --frozen-lockfile
+RUN yarn install --frozen-lockfile --network-timeout 600000
 
 COPY tsconfig.json next.config.mjs next-env.d.ts postcss.config.js drizzle.config.ts tailwind.config.ts ./
 COPY src ./src
@@ -12,7 +12,7 @@ COPY public ./public
 RUN mkdir -p /home/perplexica/data
 RUN yarn build
 
-FROM node:20.18.0-alpine
+FROM node:20.18.0-slim
 
 WORKDIR /home/perplexica
 

docs/API/SEARCH.md

@@ -6,9 +6,9 @@ Perplexica’s Search API makes it easy to use our AI-powered search engine. You
 
 ## Endpoint
 
-### **POST** `http://localhost:3001/api/search`
+### **POST** `http://localhost:3000/api/search`
 
-**Note**: Replace `3001` with any other port if you've changed the default PORT
+**Note**: Replace `3000` with any other port if you've changed the default PORT
 
 ### Request
 
@@ -20,11 +20,11 @@ The API accepts a JSON object in the request body, where you define the focus mo
 {
   "chatModel": {
     "provider": "openai",
-    "model": "gpt-4o-mini"
+    "name": "gpt-4o-mini"
   },
   "embeddingModel": {
     "provider": "openai",
-    "model": "text-embedding-3-large"
+    "name": "text-embedding-3-large"
   },
   "optimizationMode": "speed",
   "focusMode": "webSearch",
@@ -32,24 +32,26 @@ The API accepts a JSON object in the request body, where you define the focus mo
   "history": [
     ["human", "Hi, how are you?"],
     ["assistant", "I am doing well, how can I help you today?"]
-  ]
+  ],
+  "systemInstructions": "Focus on providing technical details about Perplexica's architecture.",
+  "stream": false
 }
 ```
 
 ### 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:3001/api/models`. Make sure to use the key value (For example "gpt-4o-mini" instead of the display name "GPT 4 omni mini").
+- **`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`).
-  - `model`: The specific model from the chosen provider (e.g., `gpt-4o-mini`).
+  - `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:3001/api/models`. Make sure to use the key value (For example "text-embedding-3-large" instead of the display name "Text Embedding 3 Large").
+- **`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`).
-  - `model`: The specific embedding model (e.g., `text-embedding-3-large`).
+  - `name`: The specific embedding model (e.g., `text-embedding-3-large`).
 
 - **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:
 
@@ -62,6 +64,8 @@ The API accepts a JSON object in the request body, where you define the focus mo
 
 - **`query`** (string, required): The search query or question.
 
+- **`systemInstructions`** (string, optional): Custom instructions provided by the user to guide the AI's response. These instructions are treated as user preferences and have lower priority than the system's core instructions. For example, you can specify a particular writing style, format, or focus area.
+
 - **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
 
   ```json
@@ -71,11 +75,13 @@ The API accepts a JSON object in the request body, where you define the focus mo
   ]
   ```
 
+- **`stream`** (boolean, optional): When set to `true`, enables streaming responses. Default is `false`.
+
 ### Response
 
 The response from the API includes both the final message and the sources used to generate that message.
 
-#### Example Response
+#### Standard Response (stream: false)
 
 ```json
 {
@@ -100,6 +106,28 @@ The response from the API includes both the final message and the sources used t
 }
 ```
 
+#### Streaming Response (stream: true)
+
+When streaming is enabled, the API returns a stream of newline-delimited JSON objects. Each line contains a complete, valid JSON object. The response has Content-Type: application/json.
+
+Example of streamed response objects:
+
+```
+{"type":"init","data":"Stream connected"}
+{"type":"sources","data":[{"pageContent":"...","metadata":{"title":"...","url":"..."}},...]}
+{"type":"response","data":"Perplexica is an "}
+{"type":"response","data":"innovative, open-source "}
+{"type":"response","data":"AI-powered search engine..."}
+{"type":"done"}
+```
+
+Clients should process each line as a separate JSON object. The different message types include:
+
+- **`init`**: Initial connection message
+- **`sources`**: All sources used for the response
+- **`response`**: Chunks of the generated answer text
+- **`done`**: Indicates the stream is complete
+
 ### Fields in the Response
 
 - **`message`** (string): The search result, generated based on the query and focus mode.

docs/architecture/WORKING.md

@@ -4,7 +4,7 @@ Curious about how Perplexica works? Don't worry, we'll cover it here. Before we
 
 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.

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:
-
-   ```bash
-   docker compose down --rmi all
-   ```
-
-4. Open the `docker-compose.yaml` file in a text editor like Notepad++
-
-5. Replace `127.0.0.1` with the IP address of the server Perplexica is running on in these two lines:
-
-   ```bash
-   args:
-     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-   ```
-
-6. Save and close the `docker-compose.yaml` file
-
-7. Rebuild and restart the Perplexica container:
-
-   ```bash
-   docker compose up -d --build
-   ```
-
-## macOS
-
-1. Open the Terminal application
-
-2. Navigate to the directory with the `docker-compose.yaml` file:
-
-   ```bash
-   cd /path/to/docker-compose.yaml
-   ```
-
-3. Stop and remove existing containers and images:
-
-   ```bash
-   docker compose down --rmi all
-   ```
-
-4. Open `docker-compose.yaml` in a text editor like Sublime Text:
-
-   ```bash
-   nano docker-compose.yaml
-   ```
-
-5. Replace `127.0.0.1` with the server IP in these lines:
-
-   ```bash
-   args:
-     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-   ```
-
-6. Save and exit the editor
-
-7. Rebuild and restart Perplexica:
-
-   ```bash
-   docker compose up -d --build
-   ```
-
-## Linux
-
-1. Open the terminal
-
-2. Navigate to the `docker-compose.yaml` directory:
-
-   ```bash
-   cd /path/to/docker-compose.yaml
-   ```
-
-3. Stop and remove containers and images:
-
-   ```bash
-   docker compose down --rmi all
-   ```
-
-4. Edit `docker-compose.yaml`:
-
-   ```bash
-   nano docker-compose.yaml
-   ```
-
-5. Replace `127.0.0.1` with the server IP:
-
-   ```bash
-   args:
-     - NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
-     - NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
-   ```
-
-6. Save and exit the editor
-
-7. Rebuild and restart Perplexica:
-
-   ```bash
-   docker compose up -d --build
-   ```

docs/installation/UPDATING.md

@@ -39,11 +39,8 @@ To update Perplexica to the latest version, follow these steps:
 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. Execute `npm i` in both the `ui` folder and the root directory.
-
-5. Once the packages are updated, execute `npm run build` in both the `ui` folder and the root directory.
-
-6. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
+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`
 
 ---

package.json

@@ -1,6 +1,6 @@
 {
   "name": "perplexica-frontend",
-  "version": "1.10.0-rc3",
+  "version": "1.10.2",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
@@ -15,11 +15,14 @@
     "@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",
     "@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",

sample.config.toml

@@ -1,5 +1,4 @@
 [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")
 
@@ -23,5 +22,8 @@ MODEL_NAME = ""
 [MODELS.OLLAMA]
 API_URL = "" # Ollama API URL - http://host.docker.internal:11434
 
+[MODELS.DEEPSEEK]
+API_KEY = ""
+
 [API_ENDPOINTS]
 SEARXNG = "" # SearxNG API URL - http://localhost:32768

src/app/api/chat/route.ts

@@ -20,67 +20,11 @@ import {
   getCustomOpenaiApiUrl,
   getCustomOpenaiModelName,
 } from '@/lib/config';
+import { searchHandlers } from '@/lib/search';
 
 export const runtime = 'nodejs';
 export const dynamic = 'force-dynamic';
 
-const searchHandlers: Record<string, MetaSearchAgent> = {
-  webSearch: new MetaSearchAgent({
-    activeEngines: [],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-    summarizer: true,
-  }),
-  academicSearch: new MetaSearchAgent({
-    activeEngines: ['arxiv', 'google scholar', 'pubmed'],
-    queryGeneratorPrompt: prompts.academicSearchRetrieverPrompt,
-    responsePrompt: prompts.academicSearchResponsePrompt,
-    rerank: true,
-    rerankThreshold: 0,
-    searchWeb: true,
-    summarizer: false,
-  }),
-  writingAssistant: new MetaSearchAgent({
-    activeEngines: [],
-    queryGeneratorPrompt: '',
-    responsePrompt: prompts.writingAssistantPrompt,
-    rerank: true,
-    rerankThreshold: 0,
-    searchWeb: false,
-    summarizer: false,
-  }),
-  wolframAlphaSearch: new MetaSearchAgent({
-    activeEngines: ['wolframalpha'],
-    queryGeneratorPrompt: prompts.wolframAlphaSearchRetrieverPrompt,
-    responsePrompt: prompts.wolframAlphaSearchResponsePrompt,
-    rerank: false,
-    rerankThreshold: 0,
-    searchWeb: true,
-    summarizer: false,
-  }),
-  youtubeSearch: new MetaSearchAgent({
-    activeEngines: ['youtube'],
-    queryGeneratorPrompt: prompts.youtubeSearchRetrieverPrompt,
-    responsePrompt: prompts.youtubeSearchResponsePrompt,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-    summarizer: false,
-  }),
-  redditSearch: new MetaSearchAgent({
-    activeEngines: ['reddit'],
-    queryGeneratorPrompt: prompts.redditSearchRetrieverPrompt,
-    responsePrompt: prompts.redditSearchResponsePrompt,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-    summarizer: false,
-  }),
-};
-
 type Message = {
   messageId: string;
   chatId: string;
@@ -105,6 +49,7 @@ type Body = {
   files: Array<string>;
   chatModel: ChatModel;
   embeddingModel: EmbeddingModel;
+  systemInstructions: string;
 };
 
 const handleEmitterEvents = async (
@@ -334,6 +279,7 @@ export const POST = async (req: Request) => {
       embedding,
       body.optimizationMode,
       body.files,
+      body.systemInstructions,
     );
 
     const responseStream = new TransformStream();
@@ -351,9 +297,9 @@ export const POST = async (req: Request) => {
       },
     });
   } catch (err) {
-    console.error('An error ocurred while processing chat request:', err);
+    console.error('An error occurred while processing chat request:', err);
     return Response.json(
-      { message: 'An error ocurred while processing chat request' },
+      { message: 'An error occurred while processing chat request' },
       { status: 500 },
     );
   }

src/app/api/config/route.ts

@@ -7,6 +7,7 @@ import {
   getGroqApiKey,
   getOllamaApiEndpoint,
   getOpenaiApiKey,
+  getDeepseekApiKey,
   updateConfig,
 } from '@/lib/config';
 import {
@@ -53,15 +54,16 @@ export const GET = async (req: Request) => {
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
+    config['deepseekApiKey'] = getDeepseekApiKey();
     config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
     config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
     config['customOpenaiModelName'] = getCustomOpenaiModelName();
 
     return Response.json({ ...config }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while getting config:', err);
+    console.error('An error occurred while getting config:', err);
     return Response.json(
-      { message: 'An error ocurred while getting config' },
+      { message: 'An error occurred while getting config' },
       { status: 500 },
     );
   }
@@ -88,6 +90,9 @@ export const POST = async (req: Request) => {
         OLLAMA: {
           API_URL: config.ollamaApiUrl,
         },
+        DEEPSEEK: {
+          API_KEY: config.deepseekApiKey,
+        },
         CUSTOM_OPENAI: {
           API_URL: config.customOpenaiApiUrl,
           API_KEY: config.customOpenaiApiKey,
@@ -100,9 +105,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ message: 'Config updated' }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while updating config:', err);
+    console.error('An error occurred while updating config:', err);
     return Response.json(
-      { message: 'An error ocurred while updating config' },
+      { message: 'An error occurred while updating config' },
       { status: 500 },
     );
   }

src/app/api/discover/route.ts

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

src/app/api/images/route.ts

@@ -74,9 +74,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ images }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching images: ${err}`);
+    console.error(`An error occurred while searching images: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching images' },
+      { message: 'An error occurred while searching images' },
       { status: 500 },
     );
   }

src/app/api/models/route.ts

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

src/app/api/search/route.ts

@@ -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

@@ -72,9 +72,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ suggestions }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while generating suggestions: ${err}`);
+    console.error(`An error occurred while generating suggestions: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while generating suggestions' },
+      { message: 'An error occurred while generating suggestions' },
       { status: 500 },
     );
   }

src/app/api/videos/route.ts

@@ -74,9 +74,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ videos }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching videos: ${err}`);
+    console.error(`An error occurred while searching videos: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching videos' },
+      { message: 'An error occurred while searching videos' },
       { status: 500 },
     );
   }

src/app/settings/page.tsx

@@ -20,6 +20,7 @@ interface SettingsType {
   anthropicApiKey: string;
   geminiApiKey: string;
   ollamaApiUrl: string;
+  deepseekApiKey: string;
   customOpenaiApiKey: string;
   customOpenaiApiUrl: string;
   customOpenaiModelName: string;
@@ -54,6 +55,38 @@ const Input = ({ className, isSaving, onSave, ...restProps }: InputProps) => {
   );
 };
 
+interface TextareaProps extends React.InputHTMLAttributes<HTMLTextAreaElement> {
+  isSaving?: boolean;
+  onSave?: (value: string) => void;
+}
+
+const Textarea = ({
+  className,
+  isSaving,
+  onSave,
+  ...restProps
+}: TextareaProps) => {
+  return (
+    <div className="relative">
+      <textarea
+        placeholder="Any special instructions for the LLM"
+        className="placeholder:text-sm text-sm w-full flex items-center justify-between p-3 bg-light-secondary dark:bg-dark-secondary rounded-lg hover:bg-light-200 dark:hover:bg-dark-200 transition-colors"
+        rows={4}
+        onBlur={(e) => onSave?.(e.target.value)}
+        {...restProps}
+      />
+      {isSaving && (
+        <div className="absolute right-3 top-3">
+          <Loader2
+            size={16}
+            className="animate-spin text-black/70 dark:text-white/70"
+          />
+        </div>
+      )}
+    </div>
+  );
+};
+
 const Select = ({
   className,
   options,
@@ -111,6 +144,7 @@ const Page = () => {
   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(() => {
@@ -172,6 +206,8 @@ const Page = () => {
         localStorage.getItem('autoVideoSearch') === 'true',
       );
 
+      setSystemInstructions(localStorage.getItem('systemInstructions')!);
+
       setIsLoading(false);
     };
 
@@ -328,6 +364,8 @@ const Page = () => {
         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);
@@ -473,6 +511,19 @@ const Page = () => {
               </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">
@@ -788,6 +839,25 @@ const Page = () => {
                     onSave={(value) => saveConfig('geminiApiKey', value)}
                   />
                 </div>
+
+                <div className="flex flex-col space-y-1">
+                  <p className="text-black/70 dark:text-white/70 text-sm">
+                    Deepseek API Key
+                  </p>
+                  <Input
+                    type="text"
+                    placeholder="Deepseek API Key"
+                    value={config.deepseekApiKey}
+                    isSaving={savingStates['deepseekApiKey']}
+                    onChange={(e) => {
+                      setConfig((prev) => ({
+                        ...prev!,
+                        deepseekApiKey: e.target.value,
+                      }));
+                    }}
+                    onSave={(value) => saveConfig('deepseekApiKey', value)}
+                  />
+                </div>
               </div>
             </SettingsSection>
           </div>

src/components/ChatWindow.tsx

@@ -363,20 +363,18 @@ const ChatWindow = ({ id }: { id?: string }) => {
 
       if (data.type === 'sources') {
         sources = data.data;
-        if (!added) {
-          setMessages((prevMessages) => [
-            ...prevMessages,
-            {
-              content: '',
-              messageId: data.messageId,
-              chatId: chatId!,
-              role: 'assistant',
-              sources: sources,
-              createdAt: new Date(),
-            },
-          ]);
-          added = true;
-        }
+        setMessages((prevMessages) => [
+          ...prevMessages,
+          {
+            content: '',
+            messageId: data.messageId,
+            chatId: chatId!,
+            role: 'assistant',
+            sources: sources,
+            createdAt: new Date(),
+          },
+        ]);
+        added = true;
         setMessageAppeared(true);
       }
 
@@ -394,20 +392,20 @@ const ChatWindow = ({ id }: { id?: string }) => {
             },
           ]);
           added = true;
+          setMessageAppeared(true);
+        } else {
+          setMessages((prev) =>
+            prev.map((message) => {
+              if (message.messageId === data.messageId) {
+                return { ...message, content: message.content + data.data };
+              }
+
+              return message;
+            }),
+          );
         }
 
-        setMessages((prev) =>
-          prev.map((message) => {
-            if (message.messageId === data.messageId) {
-              return { ...message, content: message.content + data.data };
-            }
-
-            return message;
-          }),
-        );
-
         recievedMessage += data.data;
-        setMessageAppeared(true);
       }
 
       if (data.type === 'messageEnd') {
@@ -480,6 +478,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
           name: embeddingModelProvider.name,
           provider: embeddingModelProvider.provider,
         },
+        systemInstructions: localStorage.getItem('systemInstructions'),
       }),
     });
 

src/components/MessageBox.tsx

@@ -12,13 +12,18 @@ import {
   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,
@@ -43,28 +48,72 @@ 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="${message.sources?.[number - 1]?.metadata?.url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
+      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' && (
@@ -111,11 +160,13 @@ const MessageBox = ({
                   Answer
                 </h3>
               </div>
+
               <Markdown
                 className={cn(
                   'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
                   'max-w-none break-words text-black dark:text-white',
                 )}
+                options={markdownOverrides}
               >
                 {parsedMessage}
               </Markdown>

src/components/MessageInputActions/Optimization.tsx

@@ -76,13 +76,11 @@ const Optimization = ({
               <PopoverButton
                 onClick={() => setOptimizationMode(mode.key)}
                 key={i}
-                disabled={mode.key === 'quality'}
                 className={cn(
                   'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition',
                   optimizationMode === mode.key
                     ? 'bg-light-secondary dark:bg-dark-secondary'
                     : 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
-                  mode.key === 'quality' && 'opacity-50 cursor-not-allowed',
                 )}
               >
                 <div className="flex flex-row items-center space-x-1 text-black dark:text-white">

src/components/Sidebar.tsx

@@ -16,8 +16,6 @@ const VerticalIconContainer = ({ children }: { children: ReactNode }) => {
 const Sidebar = ({ children }: { children: React.ReactNode }) => {
   const segments = useSelectedLayoutSegments();
 
-  const [isSettingsOpen, setIsSettingsOpen] = useState(false);
-
   const navLinks = [
     {
       icon: Home,

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/lib/chains/imageSearchAgent.ts

@@ -58,6 +58,8 @@ 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'],
       });

src/lib/chains/videoSearchAgent.ts

@@ -59,6 +59,8 @@ const createVideoSearchChain = (llm: BaseChatModel) => {
     llm,
     strParser,
     RunnableLambda.from(async (input: string) => {
+      input = input.replace(/<think>.*?<\/think>/g, '');
+
       const res = await searchSearxng(input, {
         engines: ['youtube'],
       });

src/lib/config.ts

@@ -6,7 +6,6 @@ const configFileName = 'config.toml';
 
 interface Config {
   GENERAL: {
-    PORT: number;
     SIMILARITY_MEASURE: string;
     KEEP_ALIVE: string;
   };
@@ -26,6 +25,9 @@ interface Config {
     OLLAMA: {
       API_URL: string;
     };
+    DEEPSEEK: {
+      API_KEY: string;
+    };
     CUSTOM_OPENAI: {
       API_URL: string;
       API_KEY: string;
@@ -46,8 +48,6 @@ const loadConfig = () =>
     fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
   ) as any as Config;
 
-export const getPort = () => loadConfig().GENERAL.PORT;
-
 export const getSimilarityMeasure = () =>
   loadConfig().GENERAL.SIMILARITY_MEASURE;
 
@@ -62,10 +62,12 @@ export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
 export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
 
 export const getSearxngApiEndpoint = () =>
-  loadConfig().API_ENDPOINTS.SEARXNG || process.env.SEARXNG_API_URL;
+  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;
 

src/lib/huggingfaceTransformer.ts

@@ -0,0 +1,82 @@
+import { Embeddings, type EmbeddingsParams } from '@langchain/core/embeddings';
+import { chunkArray } from '@langchain/core/utils/chunk_array';
+
+export interface HuggingFaceTransformersEmbeddingsParams
+  extends EmbeddingsParams {
+  modelName: string;
+
+  model: string;
+
+  timeout?: number;
+
+  batchSize?: number;
+
+  stripNewLines?: boolean;
+}
+
+export class HuggingFaceTransformersEmbeddings
+  extends Embeddings
+  implements HuggingFaceTransformersEmbeddingsParams
+{
+  modelName = 'Xenova/all-MiniLM-L6-v2';
+
+  model = 'Xenova/all-MiniLM-L6-v2';
+
+  batchSize = 512;
+
+  stripNewLines = true;
+
+  timeout?: number;
+
+  private pipelinePromise: Promise<any> | undefined;
+
+  constructor(fields?: Partial<HuggingFaceTransformersEmbeddingsParams>) {
+    super(fields ?? {});
+
+    this.modelName = fields?.model ?? fields?.modelName ?? this.model;
+    this.model = this.modelName;
+    this.stripNewLines = fields?.stripNewLines ?? this.stripNewLines;
+    this.timeout = fields?.timeout;
+  }
+
+  async embedDocuments(texts: string[]): Promise<number[][]> {
+    const batches = chunkArray(
+      this.stripNewLines ? texts.map((t) => t.replace(/\n/g, ' ')) : texts,
+      this.batchSize,
+    );
+
+    const batchRequests = batches.map((batch) => this.runEmbedding(batch));
+    const batchResponses = await Promise.all(batchRequests);
+    const embeddings: number[][] = [];
+
+    for (let i = 0; i < batchResponses.length; i += 1) {
+      const batchResponse = batchResponses[i];
+      for (let j = 0; j < batchResponse.length; j += 1) {
+        embeddings.push(batchResponse[j]);
+      }
+    }
+
+    return embeddings;
+  }
+
+  async embedQuery(text: string): Promise<number[]> {
+    const data = await this.runEmbedding([
+      this.stripNewLines ? text.replace(/\n/g, ' ') : text,
+    ]);
+    return data[0];
+  }
+
+  private async runEmbedding(texts: string[]) {
+    const { pipeline } = await import('@xenova/transformers');
+
+    const pipe = await (this.pipelinePromise ??= pipeline(
+      'feature-extraction',
+      this.model,
+    ));
+
+    return this.caller.call(async () => {
+      const output = await pipe(texts, { pooling: 'mean', normalize: true });
+      return output.tolist();
+    });
+  }
+}

src/lib/prompts/academicSearch.ts

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

src/lib/prompts/redditSearch.ts

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

src/lib/prompts/webSearch.ts

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

src/lib/prompts/wolframAlpha.ts

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

src/lib/prompts/writingAssistant.ts

@@ -7,6 +7,10 @@ You have to cite the answer using [number] notation. You must cite the sentences
 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

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

src/lib/providers/anthropic.ts

@@ -1,4 +1,4 @@
-import { ChatOpenAI } from '@langchain/openai';
+import { ChatAnthropic } from '@langchain/anthropic';
 import { ChatModel } from '.';
 import { getAnthropicApiKey } from '../config';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
@@ -45,13 +45,10 @@ export const loadAnthropicChatModels = async () => {
     anthropicChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: anthropicApiKey,
+        model: new ChatAnthropic({
+          apiKey: anthropicApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://api.anthropic.com/v1/',
-          },
         }) as unknown as BaseChatModel,
       };
     });

src/lib/providers/deepseek.ts

@@ -0,0 +1,44 @@
+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

@@ -1,10 +1,17 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+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',
@@ -14,8 +21,8 @@ const geminiChatModels: Record<string, string>[] = [
     key: 'gemini-2.0-flash-lite',
   },
   {
-    displayName: 'Gemini 2.0 Pro Experimental',
-    key: 'gemini-2.0-pro-exp-02-05',
+    displayName: 'Gemini 2.0 Flash Thinking Experimental',
+    key: 'gemini-2.0-flash-thinking-exp-01-21',
   },
   {
     displayName: 'Gemini 1.5 Flash',
@@ -33,8 +40,12 @@ const geminiChatModels: Record<string, string>[] = [
 
 const geminiEmbeddingModels: Record<string, string>[] = [
   {
-    displayName: 'Gemini Embedding',
-    key: 'gemini-embedding-exp',
+    displayName: 'Text Embedding 004',
+    key: 'models/text-embedding-004',
+  },
+  {
+    displayName: 'Embedding 001',
+    key: 'models/embedding-001',
   },
 ];
 
@@ -49,13 +60,10 @@ export const loadGeminiChatModels = async () => {
     geminiChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: geminiApiKey,
+        model: new ChatGoogleGenerativeAI({
+          apiKey: geminiApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as BaseChatModel,
       };
     });
@@ -78,12 +86,9 @@ export const loadGeminiEmbeddingModels = async () => {
     geminiEmbeddingModels.forEach((model) => {
       embeddingModels[model.key] = {
         displayName: model.displayName,
-        model: new OpenAIEmbeddings({
-          openAIApiKey: geminiApiKey,
+        model: new GoogleGenerativeAIEmbeddings({
+          apiKey: geminiApiKey,
           modelName: model.key,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as Embeddings,
       };
     });

src/lib/providers/groq.ts

@@ -48,10 +48,6 @@ const groqChatModels: Record<string, string>[] = [
     displayName: 'DeepSeek R1 Distill Qwen 32B (Preview)',
     key: 'deepseek-r1-distill-qwen-32b',
   },
-  {
-    displayName: 'DeepSeek R1 Distill Llama 70B SpecDec (Preview)',
-    key: 'deepseek-r1-distill-llama-70b-specdec',
-  },
   {
     displayName: 'DeepSeek R1 Distill Llama 70B (Preview)',
     key: 'deepseek-r1-distill-llama-70b',
@@ -76,6 +72,14 @@ const groqChatModels: Record<string, string>[] = [
     displayName: 'Llama 3.2 90B Vision Preview (Preview)',
     key: 'llama-3.2-90b-vision-preview',
   },
+  /* {
+    displayName: 'Llama 4 Maverick 17B 128E Instruct (Preview)',
+    key: 'meta-llama/llama-4-maverick-17b-128e-instruct',
+  }, */
+  {
+    displayName: 'Llama 4 Scout 17B 16E Instruct (Preview)',
+    key: 'meta-llama/llama-4-scout-17b-16e-instruct',
+  },
 ];
 
 export const loadGroqChatModels = async () => {

src/lib/providers/index.ts

@@ -11,6 +11,8 @@ import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
 import { loadGroqChatModels } from './groq';
 import { loadAnthropicChatModels } from './anthropic';
 import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
+import { loadTransformersEmbeddingsModels } from './transformers';
+import { loadDeepseekChatModels } from './deepseek';
 
 export interface ChatModel {
   displayName: string;
@@ -31,6 +33,7 @@ export const chatModelProviders: Record<
   groq: loadGroqChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
+  deepseek: loadDeepseekChatModels,
 };
 
 export const embeddingModelProviders: Record<
@@ -40,6 +43,7 @@ export const embeddingModelProviders: Record<
   openai: loadOpenAIEmbeddingModels,
   ollama: loadOllamaEmbeddingModels,
   gemini: loadGeminiEmbeddingModels,
+  transformers: loadTransformersEmbeddingsModels,
 };
 
 export const getAvailableChatModelProviders = async () => {

src/lib/providers/transformers.ts

@@ -0,0 +1,31 @@
+import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
+
+export const loadTransformersEmbeddingsModels = async () => {
+  try {
+    const embeddingModels = {
+      'xenova-bge-small-en-v1.5': {
+        displayName: 'BGE Small',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/bge-small-en-v1.5',
+        }),
+      },
+      'xenova-gte-small': {
+        displayName: 'GTE Small',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/gte-small',
+        }),
+      },
+      'xenova-bert-base-multilingual-uncased': {
+        displayName: 'Bert Multilingual',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/bert-base-multilingual-uncased',
+        }),
+      },
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    console.error(`Error loading Transformers embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/search/index.ts

@@ -0,0 +1,59 @@
+import MetaSearchAgent from '@/lib/search/metaSearchAgent';
+import prompts from '../prompts';
+
+export const searchHandlers: Record<string, MetaSearchAgent> = {
+  webSearch: new MetaSearchAgent({
+    activeEngines: [],
+    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
+    responsePrompt: prompts.webSearchResponsePrompt,
+    rerank: true,
+    rerankThreshold: 0.3,
+    searchWeb: true,
+    summarizer: true,
+  }),
+  academicSearch: new MetaSearchAgent({
+    activeEngines: ['arxiv', 'google scholar', 'pubmed'],
+    queryGeneratorPrompt: prompts.academicSearchRetrieverPrompt,
+    responsePrompt: prompts.academicSearchResponsePrompt,
+    rerank: true,
+    rerankThreshold: 0,
+    searchWeb: true,
+    summarizer: false,
+  }),
+  writingAssistant: new MetaSearchAgent({
+    activeEngines: [],
+    queryGeneratorPrompt: '',
+    responsePrompt: prompts.writingAssistantPrompt,
+    rerank: true,
+    rerankThreshold: 0,
+    searchWeb: false,
+    summarizer: false,
+  }),
+  wolframAlphaSearch: new MetaSearchAgent({
+    activeEngines: ['wolframalpha'],
+    queryGeneratorPrompt: prompts.wolframAlphaSearchRetrieverPrompt,
+    responsePrompt: prompts.wolframAlphaSearchResponsePrompt,
+    rerank: false,
+    rerankThreshold: 0,
+    searchWeb: true,
+    summarizer: false,
+  }),
+  youtubeSearch: new MetaSearchAgent({
+    activeEngines: ['youtube'],
+    queryGeneratorPrompt: prompts.youtubeSearchRetrieverPrompt,
+    responsePrompt: prompts.youtubeSearchResponsePrompt,
+    rerank: true,
+    rerankThreshold: 0.3,
+    searchWeb: true,
+    summarizer: false,
+  }),
+  redditSearch: new MetaSearchAgent({
+    activeEngines: ['reddit'],
+    queryGeneratorPrompt: prompts.redditSearchRetrieverPrompt,
+    responsePrompt: prompts.redditSearchResponsePrompt,
+    rerank: true,
+    rerankThreshold: 0.3,
+    searchWeb: true,
+    summarizer: false,
+  }),
+};

src/lib/search/metaSearchAgent.ts

@@ -6,24 +6,20 @@ import {
   MessagesPlaceholder,
   PromptTemplate,
 } from '@langchain/core/prompts';
-import {
-  RunnableLambda,
-  RunnableMap,
-  RunnableSequence,
-} from '@langchain/core/runnables';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
 import LineListOutputParser from '../outputParsers/listLineOutputParser';
 import LineOutputParser from '../outputParsers/lineOutputParser';
 import { getDocumentsFromLinks } from '../utils/documents';
 import { Document } from 'langchain/document';
-import { searchSearxng } from '../searxng';
+import { searchSearxng, SearxngSearchResult } from '../searxng';
 import path from 'node:path';
 import fs from 'node:fs';
 import computeSimilarity from '../utils/computeSimilarity';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import { StreamEvent } from '@langchain/core/tracers/log_stream';
+import { EventEmitter } from 'node:stream';
 
 export interface MetaSearchAgentType {
   searchAndAnswer: (
@@ -33,6 +29,7 @@ export interface MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) => Promise<eventEmitter>;
 }
 
@@ -46,7 +43,7 @@ interface Config {
   activeEngines: string[];
 }
 
-type BasicChainInput = {
+type SearchInput = {
   chat_history: BaseMessage[];
   query: string;
 };
@@ -59,233 +56,385 @@ class MetaSearchAgent implements MetaSearchAgentType {
     this.config = config;
   }
 
-  private async createSearchRetrieverChain(llm: BaseChatModel) {
+  private async searchSources(
+    llm: BaseChatModel,
+    input: SearchInput,
+    emitter: EventEmitter,
+  ) {
     (llm as unknown as ChatOpenAI).temperature = 0;
 
-    return RunnableSequence.from([
-      PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
-      llm,
-      this.strParser,
-      RunnableLambda.from(async (input: string) => {
-        const linksOutputParser = new LineListOutputParser({
-          key: 'links',
-        });
+    const chatPrompt = PromptTemplate.fromTemplate(
+      this.config.queryGeneratorPrompt,
+    );
 
-        const questionOutputParser = new LineOutputParser({
-          key: 'question',
-        });
+    const processedChatPrompt = await chatPrompt.invoke({
+      chat_history: formatChatHistoryAsString(input.chat_history),
+      query: input.query,
+    });
 
-        const links = await linksOutputParser.parse(input);
-        let question = this.config.summarizer
-          ? await questionOutputParser.parse(input)
-          : input;
+    const llmRes = await llm.invoke(processedChatPrompt);
+    const messageStr = await this.strParser.invoke(llmRes);
 
-        if (question === 'not_needed') {
-          return { query: '', docs: [] };
+    const linksOutputParser = new LineListOutputParser({
+      key: 'links',
+    });
+
+    const questionOutputParser = new LineOutputParser({
+      key: 'question',
+    });
+
+    const links = await linksOutputParser.parse(messageStr);
+    let question = this.config.summarizer
+      ? await questionOutputParser.parse(messageStr)
+      : messageStr;
+
+    if (question === 'not_needed') {
+      return { query: '', docs: [] };
+    }
+
+    if (links.length > 0) {
+      if (question.length === 0) {
+        question = 'summarize';
+      }
+
+      let docs: Document[] = [];
+
+      const linkDocs = await getDocumentsFromLinks({ links });
+
+      const docGroups: Document[] = [];
+
+      linkDocs.map((doc) => {
+        const URLDocExists = docGroups.find(
+          (d) =>
+            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
+        );
+
+        if (!URLDocExists) {
+          docGroups.push({
+            ...doc,
+            metadata: {
+              ...doc.metadata,
+              totalDocs: 1,
+            },
+          });
         }
 
-        if (links.length > 0) {
-          if (question.length === 0) {
-            question = 'summarize';
-          }
+        const docIndex = docGroups.findIndex(
+          (d) =>
+            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
+        );
 
-          let docs: Document[] = [];
-
-          const linkDocs = await getDocumentsFromLinks({ links });
-
-          const docGroups: Document[] = [];
-
-          linkDocs.map((doc) => {
-            const URLDocExists = docGroups.find(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (!URLDocExists) {
-              docGroups.push({
-                ...doc,
-                metadata: {
-                  ...doc.metadata,
-                  totalDocs: 1,
-                },
-              });
-            }
-
-            const docIndex = docGroups.findIndex(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (docIndex !== -1) {
-              docGroups[docIndex].pageContent =
-                docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
-              docGroups[docIndex].metadata.totalDocs += 1;
-            }
-          });
-
-          await Promise.all(
-            docGroups.map(async (doc) => {
-              const res = await llm.invoke(`
-            You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the 
-            text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
-            If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
-            
-            - **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
-            - **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
-            - **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
-
-            The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
-
-            <example>
-            1. \`<text>
-            Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. 
-            It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications 
-            by using containers.
-            </text>
-
-            <query>
-            What is Docker and how does it work?
-            </query>
-
-            Response:
-            Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application 
-            deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in 
-            any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
-            \`
-            2. \`<text>
-            The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
-            relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
-            on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
-            Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
-            General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
-            realm, including astronomy.
-            </text>
-
-            <query>
-            summarize
-            </query>
-
-            Response:
-            The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
-            relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
-            relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
-            1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
-            \`
-            </example>
-
-            Everything below is the actual data you will be working with. Good luck!
-
-            <query>
-            ${question}
-            </query>
-
-            <text>
-            ${doc.pageContent}
-            </text>
-
-            Make sure to answer the query in the summary.
-          `);
-
-              const document = new Document({
-                pageContent: res.content as string,
-                metadata: {
-                  title: doc.metadata.title,
-                  url: doc.metadata.url,
-                },
-              });
-
-              docs.push(document);
-            }),
-          );
-
-          return { query: question, docs: docs };
-        } else {
-          const res = await searchSearxng(question, {
-            language: 'en',
-            engines: this.config.activeEngines,
-          });
-
-          const documents = res.results.map(
-            (result) =>
-              new Document({
-                pageContent:
-                  result.content ||
-                  (this.config.activeEngines.includes('youtube')
-                    ? result.title
-                    : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
-                metadata: {
-                  title: result.title,
-                  url: result.url,
-                  ...(result.img_src && { img_src: result.img_src }),
-                },
-              }),
-          );
-
-          return { query: question, docs: documents };
+        if (docIndex !== -1) {
+          docGroups[docIndex].pageContent =
+            docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
+          docGroups[docIndex].metadata.totalDocs += 1;
         }
-      }),
-    ]);
+      });
+
+      await Promise.all(
+        docGroups.map(async (doc) => {
+          const res = await llm.invoke(`
+        You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the 
+        text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
+        If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
+        
+        - **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
+        - **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
+        - **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
+
+        The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
+
+        <example>
+        1. \`<text>
+        Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. 
+        It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications 
+        by using containers.
+        </text>
+
+        <query>
+        What is Docker and how does it work?
+        </query>
+
+        Response:
+        Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application 
+        deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in 
+        any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
+        \`
+        2. \`<text>
+        The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
+        relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
+        on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
+        Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
+        General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
+        realm, including astronomy.
+        </text>
+
+        <query>
+        summarize
+        </query>
+
+        Response:
+        The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
+        relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
+        relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
+        1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
+        \`
+        </example>
+
+        Everything below is the actual data you will be working with. Good luck!
+
+        <query>
+        ${question}
+        </query>
+
+        <text>
+        ${doc.pageContent}
+        </text>
+
+        Make sure to answer the query in the summary.
+      `);
+
+          const document = new Document({
+            pageContent: res.content as string,
+            metadata: {
+              title: doc.metadata.title,
+              url: doc.metadata.url,
+            },
+          });
+
+          docs.push(document);
+        }),
+      );
+
+      return { query: question, docs: docs };
+    } else {
+      question = question.replace(/<think>.*?<\/think>/g, '');
+
+      const res = await searchSearxng(question, {
+        language: 'en',
+        engines: this.config.activeEngines,
+      });
+
+      const documents = res.results.map(
+        (result) =>
+          new Document({
+            pageContent:
+              result.content ||
+              (this.config.activeEngines.includes('youtube')
+                ? result.title
+                : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
+            metadata: {
+              title: result.title,
+              url: result.url,
+              ...(result.img_src && { img_src: result.img_src }),
+            },
+          }),
+      );
+
+      return { query: question, docs: documents };
+    }
   }
 
-  private async createAnsweringChain(
+  private async performDeepResearch(
+    llm: BaseChatModel,
+    input: SearchInput,
+    emitter: EventEmitter,
+  ) {
+    (llm as unknown as ChatOpenAI).temperature = 0;
+
+    const queryGenPrompt = PromptTemplate.fromTemplate(
+      this.config.queryGeneratorPrompt,
+    );
+
+    const formattedChatPrompt = await queryGenPrompt.invoke({
+      chat_history: formatChatHistoryAsString(input.chat_history),
+      query: input.query,
+    });
+
+    let i = 0;
+    let currentQuery = await this.strParser.invoke(
+      await llm.invoke(formattedChatPrompt),
+    );
+    const originalQuery = currentQuery;
+    const pastQueries: string[] = [];
+    const results: SearxngSearchResult[] = [];
+
+    while (i < 10) {
+      const res = await searchSearxng(currentQuery, {
+        language: 'en',
+        engines: this.config.activeEngines,
+      });
+
+      results.push(...res.results);
+
+      const reflectorPrompt = PromptTemplate.fromTemplate(`
+          You are an LLM that is tasked with reflecting on the results of a search query.
+
+          ## Goal
+          You will be given question of the user, a list of search results collected from the web to answer that question along with past queries made to collect those results. You have to analyze the results based on user's question and do the following:
+          
+          1. Identify unexplored areas or areas with less detailed information in the results and generate a new query that focuses on those areas. The new queries should be more specific and a similar query shall not exist in past queries which will be provided to you. Make sure to include keywords that you're looking for because the new query will be used to search the web for information on that topic. Make sure the query contains only 1 question and is not too long to ensure it is Search Engine friendly.
+          2. You'll have to generate a description explaining what you are doing for example "I am looking for more information about X" or "Understanding how X works" etc. The description should be short and concise.
+          
+          ## Output format
+
+          You need to output in XML format and do not generate any other text. ake sure to not include any other text in the output or start a conversation in the output. The output should be in the following format:
+
+          <query>(query)</query>
+          <description>(description)</description>
+
+          ## Example
+          Say the user asked "What is Llama 4 by Meta?" and let search results contain information about Llama 4 being an LLM and very little information about its features. You can output:
+
+          <query>Llama 4 features</query> // Generate queries that capture keywords for SEO and not making words like "How", "What", "Why" etc.
+          <description>Looking for new features in Llama 4</description>
+
+          or something like
+
+          <query>How is Llama 4 better than its previous generation models</query>
+          <description>Understanding the difference between Llama 4 and previous generation models.</description>
+          
+          ## BELOW IS THE ACTUAL DATA YOU WILL BE WORKING WITH. IT IS NOT A PART OF EXAMPLES. YOU'LL HAVE TO GENERATE YOUR ANSWER BASED ON THIS DATA.
+          <user_question>\n{question}\n</user_question>
+          <search_results>\n{search_results}\n</search_results>
+          <past_queries>\n{past_queries}\n</past_queries>
+
+          Response:
+      `);
+
+      const formattedReflectorPrompt = await reflectorPrompt.invoke({
+        question: originalQuery,
+        search_results: results
+          .map(
+            (result) => `<result>${result.title} - ${result.content}</result>`,
+          )
+          .join('\n'),
+        past_queries: pastQueries.map((q) => `<query>${q}</query>`).join('\n'),
+      });
+
+      const feedback = await this.strParser.invoke(
+        await llm.invoke(formattedReflectorPrompt),
+      );
+
+      console.log(`Feedback: ${feedback}`);
+
+      const queryOutputParser = new LineOutputParser({
+        key: 'query',
+      });
+
+      const descriptionOutputParser = new LineOutputParser({
+        key: 'description',
+      });
+
+      currentQuery = await queryOutputParser.parse(feedback);
+      const description = await descriptionOutputParser.parse(feedback);
+      console.log(`Query: ${currentQuery}`);
+      console.log(`Description: ${description}`);
+
+      pastQueries.push(currentQuery);
+      ++i;
+    }
+
+    const uniqueResults: SearxngSearchResult[] = [];
+
+    results.forEach((res) => {
+      const exists = uniqueResults.find((r) => r.url === res.url);
+
+      if (!exists) {
+        uniqueResults.push(res);
+      } else {
+        exists.content += `\n\n` + res.content;
+      }
+    });
+
+    const documents = uniqueResults /* .slice(0, 50) */
+      .map(
+        (r) =>
+          new Document({
+            pageContent: r.content || '',
+            metadata: {
+              title: r.title,
+              url: r.url,
+              ...(r.img_src && { img_src: r.img_src }),
+            },
+          }),
+      );
+
+    return documents;
+  }
+
+  private async streamAnswer(
     llm: BaseChatModel,
     fileIds: string[],
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
+    systemInstructions: string,
+    input: SearchInput,
+    emitter: EventEmitter,
   ) {
-    return RunnableSequence.from([
-      RunnableMap.from({
-        query: (input: BasicChainInput) => input.query,
-        chat_history: (input: BasicChainInput) => input.chat_history,
-        date: () => new Date().toISOString(),
-        context: RunnableLambda.from(async (input: BasicChainInput) => {
-          const processedHistory = formatChatHistoryAsString(
-            input.chat_history,
-          );
+    const chatPrompt = ChatPromptTemplate.fromMessages([
+      ['system', this.config.responsePrompt],
+      new MessagesPlaceholder('chat_history'),
+      ['user', '{query}'],
+    ]);
 
-          let docs: Document[] | null = null;
-          let query = input.query;
+    let context = '';
 
-          if (this.config.searchWeb) {
-            const searchRetrieverChain =
-              await this.createSearchRetrieverChain(llm);
+    if (optimizationMode === 'speed' || optimizationMode === 'balanced') {
+      let docs: Document[] | null = null;
+      let query = input.query;
 
-            const searchRetrieverResult = await searchRetrieverChain.invoke({
-              chat_history: processedHistory,
-              query,
-            });
+      if (this.config.searchWeb) {
+        const searchResults = await this.searchSources(llm, input, emitter);
 
-            query = searchRetrieverResult.query;
-            docs = searchRetrieverResult.docs;
-          }
+        query = searchResults.query;
+        docs = searchResults.docs;
+      }
 
-          const sortedDocs = await this.rerankDocs(
-            query,
-            docs ?? [],
-            fileIds,
-            embeddings,
-            optimizationMode,
-          );
+      const sortedDocs = await this.rerankDocs(
+        query,
+        docs ?? [],
+        fileIds,
+        embeddings,
+        optimizationMode,
+      );
 
-          return sortedDocs;
-        })
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(this.processDocs),
-      }),
-      ChatPromptTemplate.fromMessages([
-        ['system', this.config.responsePrompt],
-        new MessagesPlaceholder('chat_history'),
-        ['user', '{query}'],
-      ]),
-      llm,
-      this.strParser,
-    ]).withConfig({
-      runName: 'FinalResponseGenerator',
+      emitter.emit(
+        'data',
+        JSON.stringify({ type: 'sources', data: sortedDocs }),
+      );
+
+      context = this.processDocs(sortedDocs);
+    } else if (optimizationMode === 'quality') {
+      let docs: Document[] = [];
+
+      docs = await this.performDeepResearch(llm, input, emitter);
+
+      emitter.emit('data', JSON.stringify({ type: 'sources', data: docs }));
+
+      context = this.processDocs(docs);
+    }
+
+    const formattedChatPrompt = await chatPrompt.invoke({
+      query: input.query,
+      chat_history: input.chat_history,
+      date: new Date().toISOString(),
+      context: context,
+      systemInstructions: systemInstructions,
     });
+
+    const llmRes = await llm.stream(formattedChatPrompt);
+
+    for await (const data of llmRes) {
+      const messageStr = await this.strParser.invoke(data);
+
+      emitter.emit(
+        'data',
+        JSON.stringify({ type: 'response', data: messageStr }),
+      );
+    }
+
+    emitter.emit('end');
   }
 
   private async rerankDocs(
@@ -421,44 +570,13 @@ class MetaSearchAgent implements MetaSearchAgentType {
     return docs
       .map(
         (_, index) =>
-          `${index + 1}. ${docs[index].metadata.title} ${docs[index].pageContent}`,
+          `${index + 1}. ${docs[index].metadata.title} ${
+            docs[index].pageContent
+          }`,
       )
       .join('\n');
   }
 
-  private async handleStream(
-    stream: AsyncGenerator<StreamEvent, any, any>,
-    emitter: eventEmitter,
-  ) {
-    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');
-      }
-    }
-  }
-
   async searchAndAnswer(
     message: string,
     history: BaseMessage[],
@@ -466,28 +584,23 @@ class MetaSearchAgent implements MetaSearchAgentType {
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
     fileIds: string[],
+    systemInstructions: string,
   ) {
     const emitter = new eventEmitter();
 
-    const answeringChain = await this.createAnsweringChain(
+    this.streamAnswer(
       llm,
       fileIds,
       embeddings,
       optimizationMode,
-    );
-
-    const stream = answeringChain.streamEvents(
+      systemInstructions,
       {
         chat_history: history,
         query: message,
       },
-      {
-        version: 'v1',
-      },
+      emitter,
     );
 
-    this.handleStream(stream, emitter);
-
     return emitter;
   }
 }

src/lib/searxng.ts

@@ -8,7 +8,7 @@ interface SearxngSearchOptions {
   pageno?: number;
 }
 
-interface SearxngSearchResult {
+export interface SearxngSearchResult {
   title: string;
   url: string;
   img_src?: string;

yarn.lock

@@ -12,6 +12,19 @@
   resolved "https://registry.yarnpkg.com/@alloc/quick-lru/-/quick-lru-5.2.0.tgz#7bf68b20c0a350f936915fcae06f58e32007ce30"
   integrity sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==
 
+"@anthropic-ai/sdk@^0.37.0":
+  version "0.37.0"
+  resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.37.0.tgz#0018127404ecb9b8a12968068e0c4b3e8bbd6386"
+  integrity sha512-tHjX2YbkUBwEgg0JZU3EFSSAQPoK4qQR/NFYa8Vtzd5UAyXzZksCw2In69Rml4R/TyHPBfRYaLK35XiOe33pjw==
+  dependencies:
+    "@types/node" "^18.11.18"
+    "@types/node-fetch" "^2.6.4"
+    abort-controller "^3.0.0"
+    agentkeepalive "^4.2.1"
+    form-data-encoder "1.7.2"
+    formdata-node "^4.3.2"
+    node-fetch "^2.6.7"
+
 "@anthropic-ai/sdk@^0.9.1":
   version "0.9.1"
   resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.9.1.tgz#b2d2b7bf05c90dce502c9a2e869066870f69ba88"
@@ -374,6 +387,11 @@
   resolved "https://registry.yarnpkg.com/@floating-ui/utils/-/utils-0.2.8.tgz#21a907684723bbbaa5f0974cf7730bd797eb8e62"
   integrity sha512-kym7SodPp8/wloecOpcmSnWJsK7M0E5Wg8UcFA+uO4B9s5d0ywXOEro/8HM9x0rW+TljRzul/14UYz3TleT3ig==
 
+"@google/generative-ai@^0.24.0":
+  version "0.24.0"
+  resolved "https://registry.yarnpkg.com/@google/generative-ai/-/generative-ai-0.24.0.tgz#4d27af7d944c924a27a593c17ad1336535d53846"
+  integrity sha512-fnEITCGEB7NdX0BhoYZ/cq/7WPZ1QS5IzJJfC3Tg/OwkvBetMiVJciyaan297OvE4B9Jg1xvo0zIazX/9sGu1Q==
+
 "@headlessui/react@^2.2.0":
   version "2.2.0"
   resolved "https://registry.yarnpkg.com/@headlessui/react/-/react-2.2.0.tgz#a8e32f0899862849a1ce1615fa280e7891431ab7"
@@ -384,6 +402,11 @@
     "@react-aria/interactions" "^3.21.3"
     "@tanstack/react-virtual" "^3.8.1"
 
+"@huggingface/jinja@^0.2.2":
+  version "0.2.2"
+  resolved "https://registry.yarnpkg.com/@huggingface/jinja/-/jinja-0.2.2.tgz#faeb205a9d6995089bef52655ddd8245d3190627"
+  integrity sha512-/KPde26khDUIPkTGU82jdtTW9UAuvUTumCAbFs/7giR0SxsvZC4hru51PBvpijH6BVkHcROcvZM/lpy5h1jRRA==
+
 "@humanwhocodes/config-array@^0.11.14":
   version "0.11.14"
   resolved "https://registry.yarnpkg.com/@humanwhocodes/config-array/-/config-array-0.11.14.tgz#d78e481a039f7566ecc9660b4ea7fe6b1fec442b"
@@ -570,6 +593,16 @@
     "@jridgewell/resolve-uri" "^3.1.0"
     "@jridgewell/sourcemap-codec" "^1.4.14"
 
+"@langchain/anthropic@^0.3.15":
+  version "0.3.15"
+  resolved "https://registry.yarnpkg.com/@langchain/anthropic/-/anthropic-0.3.15.tgz#0244cdb345cb492eb40aedd681881ebadfbb73f2"
+  integrity sha512-Ar2viYcZ64idgV7EtCBCb36tIkNtPAhQRxSaMTWPHGspFgMfvwRoleVri9e90sCpjpS9xhlHsIQ0LlUS/Atsrw==
+  dependencies:
+    "@anthropic-ai/sdk" "^0.37.0"
+    fast-xml-parser "^4.4.1"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.4"
+
 "@langchain/community@^0.3.36":
   version "0.3.36"
   resolved "https://registry.yarnpkg.com/@langchain/community/-/community-0.3.36.tgz#e4c13b8f928b17e0f9257395f43be2246dfada40"
@@ -635,6 +668,14 @@
     zod "^3.22.4"
     zod-to-json-schema "^3.22.3"
 
+"@langchain/google-genai@^0.1.12":
+  version "0.1.12"
+  resolved "https://registry.yarnpkg.com/@langchain/google-genai/-/google-genai-0.1.12.tgz#6727253bda6f0d87cd74cf0bb6b1e0f398f60f32"
+  integrity sha512-0Ea0E2g63ejCuormVxbuoyJQ5BYN53i2/fb6WP8bMKzyh+y43R13V8JqOtr3e/GmgNyv3ou/VeaZjx7KAvu/0g==
+  dependencies:
+    "@google/generative-ai" "^0.24.0"
+    zod-to-json-schema "^3.22.4"
+
 "@langchain/openai@>=0.1.0 <0.5.0", "@langchain/openai@>=0.2.0 <0.5.0":
   version "0.4.5"
   resolved "https://registry.yarnpkg.com/@langchain/openai/-/openai-0.4.5.tgz#d18e207c3ec3f2ecaa4698a5a5888092f643da52"
@@ -757,6 +798,59 @@
   resolved "https://registry.yarnpkg.com/@pkgjs/parseargs/-/parseargs-0.11.0.tgz#a77ea742fab25775145434eb1d2328cf5013ac33"
   integrity sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg==
 
+"@protobufjs/aspromise@^1.1.1", "@protobufjs/aspromise@^1.1.2":
+  version "1.1.2"
+  resolved "https://registry.yarnpkg.com/@protobufjs/aspromise/-/aspromise-1.1.2.tgz#9b8b0cc663d669a7d8f6f5d0893a14d348f30fbf"
+  integrity sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ==
+
+"@protobufjs/base64@^1.1.2":
+  version "1.1.2"
+  resolved "https://registry.yarnpkg.com/@protobufjs/base64/-/base64-1.1.2.tgz#4c85730e59b9a1f1f349047dbf24296034bb2735"
+  integrity sha512-AZkcAA5vnN/v4PDqKyMR5lx7hZttPDgClv83E//FMNhR2TMcLUhfRUBHCmSl0oi9zMgDDqRUJkSxO3wm85+XLg==
+
+"@protobufjs/codegen@^2.0.4":
+  version "2.0.4"
+  resolved "https://registry.yarnpkg.com/@protobufjs/codegen/-/codegen-2.0.4.tgz#7ef37f0d010fb028ad1ad59722e506d9262815cb"
+  integrity sha512-YyFaikqM5sH0ziFZCN3xDC7zeGaB/d0IUb9CATugHWbd1FRFwWwt4ld4OYMPWu5a3Xe01mGAULCdqhMlPl29Jg==
+
+"@protobufjs/eventemitter@^1.1.0":
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/@protobufjs/eventemitter/-/eventemitter-1.1.0.tgz#355cbc98bafad5978f9ed095f397621f1d066b70"
+  integrity sha512-j9ednRT81vYJ9OfVuXG6ERSTdEL1xVsNgqpkxMsbIabzSo3goCjDIveeGv5d03om39ML71RdmrGNjG5SReBP/Q==
+
+"@protobufjs/fetch@^1.1.0":
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/@protobufjs/fetch/-/fetch-1.1.0.tgz#ba99fb598614af65700c1619ff06d454b0d84c45"
+  integrity sha512-lljVXpqXebpsijW71PZaCYeIcE5on1w5DlQy5WH6GLbFryLUrBD4932W/E2BSpfRJWseIL4v/KPgBFxDOIdKpQ==
+  dependencies:
+    "@protobufjs/aspromise" "^1.1.1"
+    "@protobufjs/inquire" "^1.1.0"
+
+"@protobufjs/float@^1.0.2":
+  version "1.0.2"
+  resolved "https://registry.yarnpkg.com/@protobufjs/float/-/float-1.0.2.tgz#5e9e1abdcb73fc0a7cb8b291df78c8cbd97b87d1"
+  integrity sha512-Ddb+kVXlXst9d+R9PfTIxh1EdNkgoRe5tOX6t01f1lYWOvJnSPDBlG241QLzcyPdoNTsblLUdujGSE4RzrTZGQ==
+
+"@protobufjs/inquire@^1.1.0":
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/@protobufjs/inquire/-/inquire-1.1.0.tgz#ff200e3e7cf2429e2dcafc1140828e8cc638f089"
+  integrity sha512-kdSefcPdruJiFMVSbn801t4vFK7KB/5gd2fYvrxhuJYg8ILrmn9SKSX2tZdV6V+ksulWqS7aXjBcRXl3wHoD9Q==
+
+"@protobufjs/path@^1.1.2":
+  version "1.1.2"
+  resolved "https://registry.yarnpkg.com/@protobufjs/path/-/path-1.1.2.tgz#6cc2b20c5c9ad6ad0dccfd21ca7673d8d7fbf68d"
+  integrity sha512-6JOcJ5Tm08dOHAbdR3GrvP+yUUfkjG5ePsHYczMFLq3ZmMkAD98cDgcT2iA1lJ9NVwFd4tH/iSSoe44YWkltEA==
+
+"@protobufjs/pool@^1.1.0":
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/@protobufjs/pool/-/pool-1.1.0.tgz#09fd15f2d6d3abfa9b65bc366506d6ad7846ff54"
+  integrity sha512-0kELaGSIDBKvcgS4zkjz1PeddatrjYcmMWOlAuAPwAeccUrPHdUqo/J6LiymHHEiJT5NrF1UVwxY14f+fy4WQw==
+
+"@protobufjs/utf8@^1.1.0":
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/@protobufjs/utf8/-/utf8-1.1.0.tgz#a777360b5b39a1a2e5106f8e858f2fd2d060c570"
+  integrity sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw==
+
 "@react-aria/focus@^3.17.1":
   version "3.18.4"
   resolved "https://registry.yarnpkg.com/@react-aria/focus/-/focus-3.18.4.tgz#a6e95896bc8680d1b5bcd855e983fc2c195a1a55"
@@ -872,6 +966,11 @@
   resolved "https://registry.yarnpkg.com/@types/json5/-/json5-0.0.29.tgz#ee28707ae94e11d2b827bcbe5270bcea7f3e71ee"
   integrity sha512-dRLjCWHYg4oaA77cxO64oO+7JwCwnIzkZPdrrC71jQmQtlhM556pwKo5bUzqvZndkVbeFLIIi+9TC40JNF5hNQ==
 
+"@types/long@^4.0.1":
+  version "4.0.2"
+  resolved "https://registry.yarnpkg.com/@types/long/-/long-4.0.2.tgz#b74129719fc8d11c01868010082d483b7545591a"
+  integrity sha512-MqTGEo5bj5t157U6fA/BiDynNkn0YknVdh48CMPkTSpFTVmvao5UQmm7uEF6xBEo7qIMAlY/JSleYaE6VOdpaA==
+
 "@types/node-fetch@^2.6.4":
   version "2.6.11"
   resolved "https://registry.yarnpkg.com/@types/node-fetch/-/node-fetch-2.6.11.tgz#9b39b78665dae0e82a08f02f4967d62c66f95d24"
@@ -887,6 +986,13 @@
   dependencies:
     undici-types "~5.26.4"
 
+"@types/node@>=13.7.0":
+  version "22.13.10"
+  resolved "https://registry.yarnpkg.com/@types/node/-/node-22.13.10.tgz#df9ea358c5ed991266becc3109dc2dc9125d77e4"
+  integrity sha512-I6LPUvlRH+O6VRUqYOcMudhaIdUVWfsjnZavnsraHvpBwaEyMN29ry+0UVJhImYL16xsscu0aske3yA+uPOWfw==
+  dependencies:
+    undici-types "~6.20.0"
+
 "@types/node@^18.11.18":
   version "18.19.30"
   resolved "https://registry.yarnpkg.com/@types/node/-/node-18.19.30.tgz#0b1e6f824ed7ce37ef6e56f8f0d7d0ec2847b327"
@@ -990,6 +1096,17 @@
   resolved "https://registry.yarnpkg.com/@ungap/structured-clone/-/structured-clone-1.2.0.tgz#756641adb587851b5ccb3e095daf27ae581c8406"
   integrity sha512-zuVdFrMJiuCDQUMCzQaD6KL28MjnqqN8XnAqiEq9PNm/hCPTSGfrXCOfwj1ow4LFb/tNymJPwsNbVePc1xFqrQ==
 
+"@xenova/transformers@^2.17.2":
+  version "2.17.2"
+  resolved "https://registry.yarnpkg.com/@xenova/transformers/-/transformers-2.17.2.tgz#7448d73b90f67bced66f39fe2dd656adc891fde5"
+  integrity sha512-lZmHqzrVIkSvZdKZEx7IYY51TK0WDrC8eR0c5IMnBsO8di8are1zzw8BlLhyO2TklZKLN5UffNGs1IJwT6oOqQ==
+  dependencies:
+    "@huggingface/jinja" "^0.2.2"
+    onnxruntime-web "1.14.0"
+    sharp "^0.32.0"
+  optionalDependencies:
+    onnxruntime-node "1.14.0"
+
 abort-controller@^3.0.0:
   version "3.0.0"
   resolved "https://registry.yarnpkg.com/abort-controller/-/abort-controller-3.0.0.tgz#eaf54d53b62bae4138e809ca225c8439a6efb392"
@@ -1240,11 +1357,49 @@ axobject-query@^3.2.1:
   dependencies:
     dequal "^2.0.3"
 
+b4a@^1.6.4:
+  version "1.6.7"
+  resolved "https://registry.yarnpkg.com/b4a/-/b4a-1.6.7.tgz#a99587d4ebbfbd5a6e3b21bdb5d5fa385767abe4"
+  integrity sha512-OnAYlL5b7LEkALw87fUVafQw5rVR9RjwGd4KUwNQ6DrrNmaVaUCgLipfVlzrPQ4tWOR9P0IXGNOx50jYCCdSJg==
+
 balanced-match@^1.0.0:
   version "1.0.2"
   resolved "https://registry.yarnpkg.com/balanced-match/-/balanced-match-1.0.2.tgz#e83e3a7e3f300b34cb9d87f615fa0cbf357690ee"
   integrity sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==
 
+bare-events@^2.0.0, bare-events@^2.2.0:
+  version "2.5.4"
+  resolved "https://registry.yarnpkg.com/bare-events/-/bare-events-2.5.4.tgz#16143d435e1ed9eafd1ab85f12b89b3357a41745"
+  integrity sha512-+gFfDkR8pj4/TrWCGUGWmJIkBwuxPS5F+a5yWjOHQt2hHvNZd5YLzadjmDUtFmMM4y429bnKLa8bYBMHcYdnQA==
+
+bare-fs@^4.0.1:
+  version "4.0.1"
+  resolved "https://registry.yarnpkg.com/bare-fs/-/bare-fs-4.0.1.tgz#85844f34da819c76754d545323a8b23ed3617c76"
+  integrity sha512-ilQs4fm/l9eMfWY2dY0WCIUplSUp7U0CT1vrqMg1MUdeZl4fypu5UP0XcDBK5WBQPJAKP1b7XEodISmekH/CEg==
+  dependencies:
+    bare-events "^2.0.0"
+    bare-path "^3.0.0"
+    bare-stream "^2.0.0"
+
+bare-os@^3.0.1:
+  version "3.6.0"
+  resolved "https://registry.yarnpkg.com/bare-os/-/bare-os-3.6.0.tgz#1465dd7e1bebe0dec230097a23ad00f7db51f957"
+  integrity sha512-BUrFS5TqSBdA0LwHop4OjPJwisqxGy6JsWVqV6qaFoe965qqtaKfDzHY5T2YA1gUL0ZeeQeA+4BBc1FJTcHiPw==
+
+bare-path@^3.0.0:
+  version "3.0.0"
+  resolved "https://registry.yarnpkg.com/bare-path/-/bare-path-3.0.0.tgz#b59d18130ba52a6af9276db3e96a2e3d3ea52178"
+  integrity sha512-tyfW2cQcB5NN8Saijrhqn0Zh7AnFNsnczRcuWODH0eYAXBsJ5gVxAUuNr7tsHSC6IZ77cA0SitzT+s47kot8Mw==
+  dependencies:
+    bare-os "^3.0.1"
+
+bare-stream@^2.0.0:
+  version "2.6.5"
+  resolved "https://registry.yarnpkg.com/bare-stream/-/bare-stream-2.6.5.tgz#bba8e879674c4c27f7e27805df005c15d7a2ca07"
+  integrity sha512-jSmxKJNJmHySi6hC42zlZnq00rga4jjxcgNZjY9N5WlOe/iOoGRtdwGsHzQv2RlH2KOYMwGUXhf2zXd32BA9RA==
+  dependencies:
+    streamx "^2.21.0"
+
 base-64@^0.1.0:
   version "0.1.0"
   resolved "https://registry.yarnpkg.com/base-64/-/base-64-0.1.0.tgz#780a99c84e7d600260361511c4877613bf24f6bb"
@@ -1661,7 +1816,7 @@ dequal@^2.0.3:
   resolved "https://registry.yarnpkg.com/dequal/-/dequal-2.0.3.tgz#2644214f1997d39ed0ee0ece72335490a7ac67be"
   integrity sha512-0je+qPKHEMohvfRTCEo3CrPG6cAzAYgmzKyxRiYSSDkS6eGJdyVJm7WaYA5ECaAD9wLB2T4EEeymA5aFVcYXCA==
 
-detect-libc@^2.0.0, detect-libc@^2.0.3:
+detect-libc@^2.0.0, detect-libc@^2.0.2, detect-libc@^2.0.3:
   version "2.0.3"
   resolved "https://registry.yarnpkg.com/detect-libc/-/detect-libc-2.0.3.tgz#f0cd503b40f9939b894697d19ad50895e30cf700"
   integrity sha512-bwy0MGW55bG41VqxxypOsdSdGqLwXPI/focwgTYCFMbdUiBAxLg9CFzG08sz2aqzknwiX7Hkl0bQENjg8iLByw==
@@ -2224,6 +2379,11 @@ fast-deep-equal@^3.1.1, fast-deep-equal@^3.1.3:
   resolved "https://registry.yarnpkg.com/fast-deep-equal/-/fast-deep-equal-3.1.3.tgz#3a7d56b559d6cbc3eb512325244e619a65c6c525"
   integrity sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q==
 
+fast-fifo@^1.2.0, fast-fifo@^1.3.2:
+  version "1.3.2"
+  resolved "https://registry.yarnpkg.com/fast-fifo/-/fast-fifo-1.3.2.tgz#286e31de96eb96d38a97899815740ba2a4f3640c"
+  integrity sha512-/d9sfos4yxzpwkDkuN7k2SqFKtYNmCTzgfEpz82x34IM9/zc8KGxQoXg1liNC/izpRM/MBdt44Nmx41ZWqk+FQ==
+
 fast-glob@^3.2.9, fast-glob@^3.3.0, fast-glob@^3.3.1:
   version "3.3.2"
   resolved "https://registry.yarnpkg.com/fast-glob/-/fast-glob-3.3.2.tgz#a904501e57cfdd2ffcded45e99a54fef55e46129"
@@ -2245,6 +2405,13 @@ fast-levenshtein@^2.0.6:
   resolved "https://registry.yarnpkg.com/fast-levenshtein/-/fast-levenshtein-2.0.6.tgz#3d8a5c66883a16a30ca8643e851f19baa7797917"
   integrity sha512-DCXu6Ifhqcks7TZKY3Hxp3y6qphY5SJZmrWMDrKcERSOXWQdMhU9Ig/PYrzyw/ul9jOIyh0N4M0tbC5hodg8dw==
 
+fast-xml-parser@^4.4.1:
+  version "4.5.3"
+  resolved "https://registry.yarnpkg.com/fast-xml-parser/-/fast-xml-parser-4.5.3.tgz#c54d6b35aa0f23dc1ea60b6c884340c006dc6efb"
+  integrity sha512-RKihhV+SHsIUGXObeVy9AXiBbFwkVk7Syp8XgwN5U3JV416+Gwp/GO9i0JYKmikykgz/UHRrrV4ROuZEo/T0ig==
+  dependencies:
+    strnum "^1.1.1"
+
 fastq@^1.6.0:
   version "1.17.1"
   resolved "https://registry.yarnpkg.com/fastq/-/fastq-1.17.1.tgz#2a523f07a4e7b1e81a42b91b8bf2254107753b47"
@@ -2298,6 +2465,11 @@ flat@^5.0.2:
   resolved "https://registry.yarnpkg.com/flat/-/flat-5.0.2.tgz#8ca6fe332069ffa9d324c327198c598259ceb241"
   integrity sha512-b6suED+5/3rTpUBdG1gupIl8MPFCAMA0QXwmljLhvCUKcUvdE4gWky9zpuGCcXHOsz4J9wPGNWq6OKpmIzz3hQ==
 
+flatbuffers@^1.12.0:
+  version "1.12.0"
+  resolved "https://registry.yarnpkg.com/flatbuffers/-/flatbuffers-1.12.0.tgz#72e87d1726cb1b216e839ef02658aa87dcef68aa"
+  integrity sha512-c7CZADjRcl6j0PlvFy0ZqXQ67qSEZfrVPynmnL+2zPc+NtMvrF8Y0QceMo7QqnSPc7+uWjUIAbvCQ5WIKlMVdQ==
+
 flatted@^3.2.9:
   version "3.3.1"
   resolved "https://registry.yarnpkg.com/flatted/-/flatted-3.3.1.tgz#21db470729a6734d4997002f439cb308987f567a"
@@ -2532,6 +2704,11 @@ graphemer@^1.4.0:
   resolved "https://registry.yarnpkg.com/graphemer/-/graphemer-1.4.0.tgz#fb2f1d55e0e3a1849aeffc90c4fa0dd53a0e66c6"
   integrity sha512-EtKwoO6kxCL9WO5xipiHTZlSzBm7WLT627TqC/uVRd0HKmq8NXyebnNYxDoBi7wt8eTWrUrKXCOVaFq9x1kgag==
 
+guid-typescript@^1.0.9:
+  version "1.0.9"
+  resolved "https://registry.yarnpkg.com/guid-typescript/-/guid-typescript-1.0.9.tgz#e35f77003535b0297ea08548f5ace6adb1480ddc"
+  integrity sha512-Y8T4vYhEfwJOTbouREvG+3XDsjr8E3kIr7uf+JZ0BYloFsttiHU0WfvANVsR7TxNUJa/WpCnw/Ino/p+DeBhBQ==
+
 has-bigints@^1.0.1, has-bigints@^1.0.2:
   version "1.0.2"
   resolved "https://registry.yarnpkg.com/has-bigints/-/has-bigints-1.0.2.tgz#0871bd3e3d51626f6ca0966668ba35d5602d6eaa"
@@ -3112,6 +3289,11 @@ logform@^2.7.0:
     safe-stable-stringify "^2.3.1"
     triple-beam "^1.3.0"
 
+long@^4.0.0:
+  version "4.0.0"
+  resolved "https://registry.yarnpkg.com/long/-/long-4.0.0.tgz#9a7b71cfb7d361a194ea555241c92f7468d5bf28"
+  integrity sha512-XsP+KhQif4bjX1kbuSiySJFNAehNxgLb6hPRGJ9QsUr8ajHkuXGdrHmFUTUUXhDwVX2R5bY4JNZEwbUiMhV+MA==
+
 loose-envify@^1.1.0, loose-envify@^1.4.0:
   version "1.4.0"
   resolved "https://registry.yarnpkg.com/loose-envify/-/loose-envify-1.4.0.tgz#71ee51fa7be4caec1a63839f7e682d8132d30caf"
@@ -3331,6 +3513,11 @@ node-abi@^3.3.0:
   dependencies:
     semver "^7.3.5"
 
+node-addon-api@^6.1.0:
+  version "6.1.0"
+  resolved "https://registry.yarnpkg.com/node-addon-api/-/node-addon-api-6.1.0.tgz#ac8470034e58e67d0c6f1204a18ae6995d9c0d76"
+  integrity sha512-+eawOlIgy680F0kBzPUNFhMZGtJ1YmqM6l4+Crf4IkImjYrO/mqPwRMh352g23uIaQKFItcQ64I7KMaJxHgAVA==
+
 node-domexception@1.0.0:
   version "1.0.0"
   resolved "https://registry.yarnpkg.com/node-domexception/-/node-domexception-1.0.0.tgz#6888db46a1f71c0b76b3f7555016b63fe64766e5"
@@ -3458,6 +3645,37 @@ one-time@^1.0.0:
   dependencies:
     fn.name "1.x.x"
 
+onnx-proto@^4.0.4:
+  version "4.0.4"
+  resolved "https://registry.yarnpkg.com/onnx-proto/-/onnx-proto-4.0.4.tgz#2431a25bee25148e915906dda0687aafe3b9e044"
+  integrity sha512-aldMOB3HRoo6q/phyB6QRQxSt895HNNw82BNyZ2CMh4bjeKv7g/c+VpAFtJuEMVfYLMbRx61hbuqnKceLeDcDA==
+  dependencies:
+    protobufjs "^6.8.8"
+
+onnxruntime-common@~1.14.0:
+  version "1.14.0"
+  resolved "https://registry.yarnpkg.com/onnxruntime-common/-/onnxruntime-common-1.14.0.tgz#2bb5dac5261269779aa5fb6536ca379657de8bf6"
+  integrity sha512-3LJpegM2iMNRX2wUmtYfeX/ytfOzNwAWKSq1HbRrKc9+uqG/FsEA0bbKZl1btQeZaXhC26l44NWpNUeXPII7Ew==
+
+onnxruntime-node@1.14.0:
+  version "1.14.0"
+  resolved "https://registry.yarnpkg.com/onnxruntime-node/-/onnxruntime-node-1.14.0.tgz#c4ae6c355cfae7d83abaf36dd39a905c4a010217"
+  integrity sha512-5ba7TWomIV/9b6NH/1x/8QEeowsb+jBEvFzU6z0T4mNsFwdPqXeFUM7uxC6QeSRkEbWu3qEB0VMjrvzN/0S9+w==
+  dependencies:
+    onnxruntime-common "~1.14.0"
+
+onnxruntime-web@1.14.0:
+  version "1.14.0"
+  resolved "https://registry.yarnpkg.com/onnxruntime-web/-/onnxruntime-web-1.14.0.tgz#c8cee538781b1d4c1c6b043934f4a3e6ddf1466e"
+  integrity sha512-Kcqf43UMfW8mCydVGcX9OMXI2VN17c0p6XvR7IPSZzBf/6lteBzXHvcEVWDPmCKuGombl997HgLqj91F11DzXw==
+  dependencies:
+    flatbuffers "^1.12.0"
+    guid-typescript "^1.0.9"
+    long "^4.0.0"
+    onnx-proto "^4.0.4"
+    onnxruntime-common "~1.14.0"
+    platform "^1.3.6"
+
 openai@^4.26.0, openai@^4.32.1:
   version "4.33.0"
   resolved "https://registry.yarnpkg.com/openai/-/openai-4.33.0.tgz#8c33da687d4a7f3dd7576179318341615394c79d"
@@ -3625,6 +3843,11 @@ pirates@^4.0.1:
   resolved "https://registry.yarnpkg.com/pirates/-/pirates-4.0.6.tgz#3018ae32ecfcff6c29ba2267cbf21166ac1f36b9"
   integrity sha512-saLsH7WeYYPiD25LDuLRRY/i+6HaPYr6G1OUlN39otzkSTxKnubR9RTxS3/Kk50s1g2JTgFwWQDQyplC5/SHZg==
 
+platform@^1.3.6:
+  version "1.3.6"
+  resolved "https://registry.yarnpkg.com/platform/-/platform-1.3.6.tgz#48b4ce983164b209c2d45a107adb31f473a6e7a7"
+  integrity sha512-fnWVljUchTro6RiCFvCXBbNhJc2NijN7oIQxbwsyL0buWJPG85v81ehlHI9fXrJsMNgTofEoWIQeClKpgxFLrg==
+
 possible-typed-array-names@^1.0.0:
   version "1.0.0"
   resolved "https://registry.yarnpkg.com/possible-typed-array-names/-/possible-typed-array-names-1.0.0.tgz#89bb63c6fada2c3e90adc4a647beeeb39cc7bf8f"
@@ -3737,6 +3960,25 @@ prop-types@^15.8.1:
     object-assign "^4.1.1"
     react-is "^16.13.1"
 
+protobufjs@^6.8.8:
+  version "6.11.4"
+  resolved "https://registry.yarnpkg.com/protobufjs/-/protobufjs-6.11.4.tgz#29a412c38bf70d89e537b6d02d904a6f448173aa"
+  integrity sha512-5kQWPaJHi1WoCpjTGszzQ32PG2F4+wRY6BmAT4Vfw56Q2FZ4YZzK20xUYQH4YkfehY1e6QSICrJquM6xXZNcrw==
+  dependencies:
+    "@protobufjs/aspromise" "^1.1.2"
+    "@protobufjs/base64" "^1.1.2"
+    "@protobufjs/codegen" "^2.0.4"
+    "@protobufjs/eventemitter" "^1.1.0"
+    "@protobufjs/fetch" "^1.1.0"
+    "@protobufjs/float" "^1.0.2"
+    "@protobufjs/inquire" "^1.1.0"
+    "@protobufjs/path" "^1.1.2"
+    "@protobufjs/pool" "^1.1.0"
+    "@protobufjs/utf8" "^1.1.0"
+    "@types/long" "^4.0.1"
+    "@types/node" ">=13.7.0"
+    long "^4.0.0"
+
 proxy-from-env@^1.1.0:
   version "1.1.0"
   resolved "https://registry.yarnpkg.com/proxy-from-env/-/proxy-from-env-1.1.0.tgz#e102f16ca355424865755d2c9e8ea4f24d58c3e2"
@@ -3989,6 +4231,20 @@ set-function-name@^2.0.1, set-function-name@^2.0.2:
     functions-have-names "^1.2.3"
     has-property-descriptors "^1.0.2"
 
+sharp@^0.32.0:
+  version "0.32.6"
+  resolved "https://registry.yarnpkg.com/sharp/-/sharp-0.32.6.tgz#6ad30c0b7cd910df65d5f355f774aa4fce45732a"
+  integrity sha512-KyLTWwgcR9Oe4d9HwCwNM2l7+J0dUQwn/yf7S0EnTtb0eVS4RxO0eUSvxPtzT4F3SY+C4K6fqdv/DO27sJ/v/w==
+  dependencies:
+    color "^4.2.3"
+    detect-libc "^2.0.2"
+    node-addon-api "^6.1.0"
+    prebuild-install "^7.1.1"
+    semver "^7.5.4"
+    simple-get "^4.0.1"
+    tar-fs "^3.0.4"
+    tunnel-agent "^0.6.0"
+
 sharp@^0.33.5:
   version "0.33.5"
   resolved "https://registry.yarnpkg.com/sharp/-/sharp-0.33.5.tgz#13e0e4130cc309d6a9497596715240b2ec0c594e"
@@ -4055,7 +4311,7 @@ simple-concat@^1.0.0:
   resolved "https://registry.yarnpkg.com/simple-concat/-/simple-concat-1.0.1.tgz#f46976082ba35c2263f1c8ab5edfe26c41c9552f"
   integrity sha512-cSFtAPtRhljv69IK0hTVZQ+OfE9nePi/rtJmw5UjHeVyVroEqJXP1sFztKUy1qU+xvz3u/sfYJLa947b7nAN2Q==
 
-simple-get@^4.0.0:
+simple-get@^4.0.0, simple-get@^4.0.1:
   version "4.0.1"
   resolved "https://registry.yarnpkg.com/simple-get/-/simple-get-4.0.1.tgz#4a39db549287c979d352112fa03fd99fd6bc3543"
   integrity sha512-brv7p5WgH0jmQJr1ZDDfKDOSeWWg+OVypG99A/5vYGPqJ6pxiaHLy8nxtFjBA7oMa01ebA9gfh1uMCFqOuXxvA==
@@ -4119,6 +4375,16 @@ streamsearch@^1.1.0:
   resolved "https://registry.yarnpkg.com/streamsearch/-/streamsearch-1.1.0.tgz#404dd1e2247ca94af554e841a8ef0eaa238da764"
   integrity sha512-Mcc5wHehp9aXz1ax6bZUyY5afg9u2rv5cqQI3mRrYkGC8rW2hM02jWuwjtL++LS5qinSyhj2QfLyNsuc+VsExg==
 
+streamx@^2.15.0, streamx@^2.21.0:
+  version "2.22.0"
+  resolved "https://registry.yarnpkg.com/streamx/-/streamx-2.22.0.tgz#cd7b5e57c95aaef0ff9b2aef7905afa62ec6e4a7"
+  integrity sha512-sLh1evHOzBy/iWRiR6d1zRcLao4gGZr3C1kzNz4fopCOKJb6xD9ub8Mpi9Mr1R6id5o43S+d93fI48UC5uM9aw==
+  dependencies:
+    fast-fifo "^1.3.2"
+    text-decoder "^1.1.0"
+  optionalDependencies:
+    bare-events "^2.2.0"
+
 "string-width-cjs@npm:string-width@^4.2.0":
   version "4.2.3"
   resolved "https://registry.yarnpkg.com/string-width/-/string-width-4.2.3.tgz#269c7117d27b05ad2e536830a8ec895ef9c6d010"
@@ -4235,6 +4501,11 @@ strip-json-comments@~2.0.1:
   resolved "https://registry.yarnpkg.com/strip-json-comments/-/strip-json-comments-2.0.1.tgz#3c531942e908c2697c0ec344858c286c7ca0a60a"
   integrity sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ==
 
+strnum@^1.1.1:
+  version "1.1.2"
+  resolved "https://registry.yarnpkg.com/strnum/-/strnum-1.1.2.tgz#57bca4fbaa6f271081715dbc9ed7cee5493e28e4"
+  integrity sha512-vrN+B7DBIoTTZjnPNewwhx6cBA/H+IS7rfW68n7XxC1y7uoiGQBxaKzqucGUgavX15dJgiGztLJ8vxuEzwqBdA==
+
 styled-jsx@5.1.6:
   version "5.1.6"
   resolved "https://registry.yarnpkg.com/styled-jsx/-/styled-jsx-5.1.6.tgz#83b90c077e6c6a80f7f5e8781d0f311b2fe41499"
@@ -4322,6 +4593,17 @@ tar-fs@^2.0.0:
     pump "^3.0.0"
     tar-stream "^2.1.4"
 
+tar-fs@^3.0.4:
+  version "3.0.8"
+  resolved "https://registry.yarnpkg.com/tar-fs/-/tar-fs-3.0.8.tgz#8f62012537d5ff89252d01e48690dc4ebed33ab7"
+  integrity sha512-ZoROL70jptorGAlgAYiLoBLItEKw/fUxg9BSYK/dF/GAGYFJOJJJMvjPAKDJraCXFwadD456FCuvLWgfhMsPwg==
+  dependencies:
+    pump "^3.0.0"
+    tar-stream "^3.1.5"
+  optionalDependencies:
+    bare-fs "^4.0.1"
+    bare-path "^3.0.0"
+
 tar-stream@^2.1.4:
   version "2.2.0"
   resolved "https://registry.yarnpkg.com/tar-stream/-/tar-stream-2.2.0.tgz#acad84c284136b060dc3faa64474aa9aebd77287"
@@ -4333,6 +4615,22 @@ tar-stream@^2.1.4:
     inherits "^2.0.3"
     readable-stream "^3.1.1"
 
+tar-stream@^3.1.5:
+  version "3.1.7"
+  resolved "https://registry.yarnpkg.com/tar-stream/-/tar-stream-3.1.7.tgz#24b3fb5eabada19fe7338ed6d26e5f7c482e792b"
+  integrity sha512-qJj60CXt7IU1Ffyc3NJMjh6EkuCFej46zUqJ4J7pqYlThyd9bO0XBTmcOIhSzZJVWfsLks0+nle/j538YAW9RQ==
+  dependencies:
+    b4a "^1.6.4"
+    fast-fifo "^1.2.0"
+    streamx "^2.15.0"
+
+text-decoder@^1.1.0:
+  version "1.2.3"
+  resolved "https://registry.yarnpkg.com/text-decoder/-/text-decoder-1.2.3.tgz#b19da364d981b2326d5f43099c310cc80d770c65"
+  integrity sha512-3/o9z3X0X0fTupwsYvR03pJ/DjWuqqrfwBgTQzdWDiQSm9KitAyz/9WqsT2JQW7KV2m+bC2ol/zqpW37NHxLaA==
+  dependencies:
+    b4a "^1.6.4"
+
 text-hex@1.0.x:
   version "1.0.0"
   resolved "https://registry.yarnpkg.com/text-hex/-/text-hex-1.0.0.tgz#69dc9c1b17446ee79a92bf5b884bb4b9127506f5"
@@ -4482,6 +4780,11 @@ undici-types@~5.26.4:
   resolved "https://registry.yarnpkg.com/undici-types/-/undici-types-5.26.5.tgz#bcd539893d00b56e964fd2657a4866b221a65617"
   integrity sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==
 
+undici-types@~6.20.0:
+  version "6.20.0"
+  resolved "https://registry.yarnpkg.com/undici-types/-/undici-types-6.20.0.tgz#8171bf22c1f588d1554d55bf204bc624af388433"
+  integrity sha512-Ny6QZ2Nju20vw1SRHe3d9jVu6gJ+4e3+MMpqu7pqE5HT6WsTSlce++GQmK5UXS8mzV8DSYHrQH+Xrf2jVcuKNg==
+
 update-browserslist-db@^1.0.13:
   version "1.0.13"
   resolved "https://registry.yarnpkg.com/update-browserslist-db/-/update-browserslist-db-1.0.13.tgz#3c5e4f5c083661bd38ef64b6328c26ed6c8248c4"
@@ -4700,6 +5003,11 @@ zod-to-json-schema@^3.22.3, zod-to-json-schema@^3.22.5:
   resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.22.5.tgz#3646e81cfc318dbad2a22519e5ce661615418673"
   integrity sha512-+akaPo6a0zpVCCseDed504KBJUQpEW5QZw7RMneNmKw+fGaML1Z9tUNLnHHAC8x6dzVRO1eB2oEMyZRnuBZg7Q==
 
+zod-to-json-schema@^3.22.4:
+  version "3.24.5"
+  resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.24.5.tgz#d1095440b147fb7c2093812a53c54df8d5df50a3"
+  integrity sha512-/AuWwMP+YqiPbsJx5D6TfgRTc4kTLjsh5SOcd4bLsfUg2RcEXrFMJl1DGgdHy2aCfsIA/cr/1JM0xcB2GZji8g==
+
 zod@^3.22.3, zod@^3.22.4:
   version "3.22.4"
   resolved "https://registry.yarnpkg.com/zod/-/zod-3.22.4.tgz#f31c3a9386f61b1f228af56faa9255e845cf3fff"