redis-developer/agentic-rag
Complete example of how to build an Agentic RAG architecture with Redis, Amazon Bedrock, and LlamaIndex.
This project helps customer support teams quickly build an AI chatbot to answer specific product questions. You provide it with information about your products, and it creates a smart chatbot capable of understanding complex queries and providing accurate answers. This is ideal for customer service managers or business owners looking to automate support for specialized products.
101 stars. No commits in the last 6 months.
Use this if you need to deploy an intelligent chatbot that can provide accurate, up-to-date information about your products to customers.
Not ideal if you are looking for a general-purpose conversational AI that doesn't focus on specific product knowledge or if you don't have existing product documentation.
Stars
101
Forks
11
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 05, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/redis-developer/agentic-rag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepsense-ai/ragbits
Building blocks for rapid development of GenAI applications
infiniflow/ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses...
GiovanniPasq/agentic-rag-for-dummies
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
truefoundry/cognita
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications...
vectara/py-vectara-agentic
A python library for creating AI assistants with Vectara, using Agentic RAG