Retrieval-Augmented-Generation

RAG Car Attribute Retrieval is a project aimed at retrieving car attributes using a Retrieval-Augmented Generation (RAG) approach. It leverages state-of-the-art language models and vector embeddings to facilitate accurate retrieval of car attributes based on user queries.

Features

• Utilizes advanced language models for natural language understanding.
• Employs vector embeddings for semantic similarity calculations.
• Supports retrieval of various car attributes such as brand, model, type, year, country, and rating.
• Provides a seamless interface for querying car attributes and retrieving relevant information.

Usage

1. Install the necessary dependencies.
2. Initialize the RAG model with appropriate settings.
3. Query the system with car-related questions or descriptions.
4. Retrieve relevant car attributes based on the input.

Installation

To install RAG Car Attribute Retrieval, follow these steps:

1. Clone the repository: git clone https://github.com/arjunanand13/RAG-Car-Attribute-Retrieval.git
2. Navigate to the project directory: cd RAG-Car-Attribute-Retrieval
3. Install dependencies: pip install -r requirements.txt