RAGLight and nextwork-rag-api

RAGLight
68
Established
nextwork-rag-api
22
Experimental
Maintenance 20/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 10/25
Adoption 1/25
Maturity 11/25
Community 0/25
Stars: 655
Forks: 99
Downloads: —
Commits (30d): 33
Language: Python
License: MIT
Stars: 1
Forks: —
Downloads: —
Commits (30d): 0
Language: Python
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About RAGLight

Bessouat40/RAGLight

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

RAGLight helps you quickly build a chatbot that can answer questions using your own documents, like PDFs, Word files, or code. You feed it your collection of files, and it produces a chat interface where you can ask questions and get answers grounded in your specific information. This is ideal for anyone who needs to quickly create a custom AI assistant that understands their unique knowledge base.

knowledge-management custom-chatbot document-intelligence information-retrieval AI-assistant-creation

About nextwork-rag-api

ZAG23/nextwork-rag-api

A RAG (Retrieval-Augmented Generation) API built with FastAPI, ChromaDB, and Ollama. Supports environment configuration, document management, and advanced querying with relevance scores.

Related comparisons

RAGLight and ragctl RAGLight and super-rag RAGLight and rag_blueprint RAGLight and RAG-Boilerplate RAGLight and rag-doctor RAGLight and RAG-LLM-using-AI-Pipeline-with-streamlit-interface

Scores updated daily from GitHub, PyPI, and npm data. How scores work