Vector Database

Overview

The Vector Database repository is part of the HereFamni project and provides a system for storing and querying vector embeddings. It is optimized for handling high-dimensional data and is used for the retrieval-augmented generation (RAG) system to retrieve relevant content based on vector embeddings.

Features

• Stores vector embeddings for fast similarity search.
• Supports integration with the RAG system.
• Can handle large datasets with efficient storage and querying.

Setup Instructions

Prerequisites

• Docker and Docker Compose installed.
• A running PostgreSQL database container (configured separately).
• The vector database container requires access to the same network as the RAG system for seamless integration.

Steps

1. Clone the repository:

   git clone https://github.com/HeReFanMi/vector-database.git
   cd vector-database

2. Build and Run the Docker Container: Build the Docker image and start the containers:

   docker build -t vector-database .
   docker-compose up

3. Access the Application: Once the container is running, access the database via the configured port. The default PostgreSQL port is mapped to 5433:

   psql -h localhost -p 5433 -U postgres -d vector_database

Usage

• The vector database stores embeddings and allows for efficient similarity searches.
• You can connect this database to your RAG system to perform retrieval-augmented generation.