mickymultani/nvidia-NIM-RAG
Project demonstrates the power and simplicity of NVIDIA NIM (NVIDIA Inference Model), a suite of optimized cloud-native microservices, by setting up and running a Retrieval-Augmented Generation (RAG) pipeline.
This project helps developers quickly integrate a Retrieval-Augmented Generation (RAG) pipeline into their applications. It takes your text data and a user's question, then provides a relevant, AI-generated answer based on your data. This is ideal for developers building AI-powered chatbots or Q&A systems who want to leverage NVIDIA's optimized AI models.
No commits in the last 6 months.
Use this if you are a developer looking to build or enhance a generative AI application by integrating a RAG pipeline with NVIDIA Inference Models for efficient deployment.
Not ideal if you are an end-user without programming experience, as this tool requires coding knowledge and an understanding of AI development workflows.
Stars
15
Forks
5
Language
Python
License
MIT
Category
Last pushed
Mar 21, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/mickymultani/nvidia-NIM-RAG"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
bragai/bRAG-langchain
Everything you need to know to build your own RAG application
guyernest/advanced-rag
Jupyter Notebooks for Mastering LLM with Advanced RAG Course
liu673/rag-all-techniques
Implementation of all RAG techniques in a simpler way(以简单的方式实现所有 RAG 技术)
FareedKhan-dev/rag-ecosystem
Understand and code every important component of RAG architecture
FareedKhan-dev/14-rag-failures
Encountering 14 different Naive RAG fails and using KG to solve it