This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
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Updated
Sep 9, 2024 - Jupyter Notebook
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
All-in-One: Text Embedding, Retrieval, Reranking and RAG
Multiple Coder assistants: This project leverages Language Model (LLM) agents to generate code snippets for users, providing assistance in various programming tasks. Additionally, it constructs a knowledge bank that can be referenced to aid in code creation for individual references.
This is a an Advanced RAG system, where I tried to make it functioning in regular PC with a CPU using all free resources, using APIs and tools to make it happen.
Building a multi-agent RAG system with advanced RAG methods
RAG still needs to evolve. So evolution is all you need.
Discussing advanced RAG methodologies and summarizing a relevant research paper.
"RAG is all you need"
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