Open-source tool to visualise your RAG 🔮
$ git clone https://github.com/gabrielchua/RAGxplorer.gitA Retrieval-Augmented Generation (RAG) application for querying legal documents. It uses PostgreSQL, Elasticsearch, and LLM to provide summaries and suggestions based on user queries. Features data ingestion with Airflow, real-time monitoring with Grafana, and a Streamlit interface.
AI-powered virtual executive team — a single coherent executive persona backed by 8 specialist agents (FastAPI + Next.js).
▲ +24 ★ this week
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
Everything you need to know to build your own RAG application
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Data from GitHub · snapshot Nov 13, 2026