VexaSearch

VexaSearch is a simple AI-powered search application designed to determine the actions to perform based on a function call.

Currently, the application is able to perform the following tasks:

• Generate images
• Search the internet
• Retrieve information about a specific URL

Models currently used:

• firefunction-v1 (for function calls)
• Mixtral for text generation
• stable-diffusion-xl-1024-v1-0 (for image generation)
• nomic-ai/nomic-embed-text-v1.5 (for RAG)

Prerequisites

• Supabase account
• Firework account
• Google Custom Search Engine API key and Search Engine ID
• Bing Search API key

Supabase

1. Create a new project on Supabase

2. Create a Search table with the following columns:

• id (Primary Key)
• response (Text)
• links (Text Array)
• query (Text)
• slug (Text)
• created_at (Timestamp)

CREATE TABLE Search (
  id SERIAL PRIMARY KEY,
  response TEXT,
  links TEXT[],
  query TEXT,
  slug TEXT,
  created_at TIMESTAMP DEFAULT now()
);

3. Create a Query table with the following columns:

• id (Primary Key)
• query (Text)
• slug (Text)

CREATE TABLE Query (
  id SERIAL PRIMARY KEY,
  query TEXT,
  slug TEXT
);

Installation

1. Clone the repository

git clone https://github.com/n4ze3m/vexasearch.git

2. Copy the .env.example file to .env and fill in the required information

cp .env.example .env

• Open the .env file and fill in the required information

3. Install the required packages

npm install

4. Start the application

npm run dev

This will start the application on http://localhost:3000

or you can start the application using Docker

docker-compose up

This will start the application on http://localhost:3000

Support

If you like the project and want to support it, you can buy me a coffee. It will help me to keep working on the project.