arjbingly/grag
GRAG is a simple python package that provides an easy end-to-end solution for implementing Retrieval Augmented Generation (RAG). The package offers an easy way for running various LLMs locally, Thanks to LlamaCpp and also supports vector stores like Chroma and DeepLake.
This is a tool for developers looking to quickly build and deploy a Retrieval Augmented Generation (RAG) system. It takes your documents and a large language model (LLM) as input, then allows the LLM to provide more informed and accurate answers by retrieving relevant information from your documents. Developers building AI applications, chatbots, or Q&A systems would find this useful.
No commits in the last 6 months. Available on PyPI.
Use this if you are a developer and want an easy, end-to-end solution to integrate RAG into your AI applications, especially if you plan to run LLMs locally.
Not ideal if you are an end-user without programming experience, as this is a developer tool requiring Python knowledge.
Stars
15
Forks
1
Language
Python
License
AGPL-3.0
Category
Last pushed
May 11, 2024
Commits (30d)
0
Dependencies
19
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