retreival-augmented-generation

A 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.

Chat with PDF lets you ask questions to PDF documents. Built and deployed with NuxtHub, and powered by Cloudflare Workers AI and Vectorize.

My attempt at implementing retreival augmented generation on Ollama and other LLM services using chromadb and langchain while also providing an easy to understand, clean code for others since nobody else does

👨🏻‍💻 Meet Lumina – my personal AI assistant powered by hybrid RAG with Pinecone vector search and Neo4j graph traversal, Google AI, LangChain, and an MCP server with 30+ tools. Features real-time streaming, conversation branching, and a multi-agent agentic AI pipeline for intelligent, grounded responses with inline citations.