simplerag 0.0.4

This package will help you talk to your data using Retrieval Augmented Generation (RAG).

simplerag (Simple Retrieval Augmented Generation)

Simplerag: Retrieval Augmented Generation Library Simplerag is a Python library designed to assist users in working with custom data using Large Language Models (LLMs). It enables users to create a vector database, which is a one-time activity, and LLM models can then utilize the product outputs for retrieval augmented generation.

Table of Contents

1. Introduction
2. Installation
3. Usage
4. Creating a Vector DB
5. Retrieval Augmented Generation
6. Examples
7. Contributing
8. License

Introduction

Large Language Models (LLMs) have gained significant popularity in recent years due to their ability to generate human-like text. However, working with custom data using LLMs can be challenging, especially when dealing with large datasets or complex retrieval tasks. Simplerag aims to simplify this process by providing a convenient and efficient way to work with LLMs for retrieval augmented generation tasks.

Key features of simplerag include:

Vector Database Creation: simplerag allows users to create a vector database from their custom data. This database serves as an index for retrieval tasks and is generated as a one-time activity.

Retrieval Augmented Generation: With the vector database in place, Simplerag enables users to perform retrieval augmented generation using LLM models. This approach combines the power of retrieval and generation to produce high-quality outputs.

Installation To install simplerag, you can use pip:

pip install simplerag