rag-pipeline

A multimodal RAG dashboard and interactive 3D Knowledge Graph. Process documents locally with Ollama or via Cloud APIs, powered by LightRAG, RAG-Anything and Neo4j.

Experimental RAG playground for exploring retrieval quality, corpus construction, and filter-chain design. Features configurable ranking and filtering pipelines, visual document grounding, chat interfaces, web search, Open WebUI integration, and rich debugging insights. Ollama and vLLM, running in Dev Containers or natively on Linux and Windows.

A PDF Question-Answering App built with RAG (Retrieval-Augmented Generation), allowing users to upload PDFs and ask context-based questions. Powered by Streamlit, LangChain, Ollama, and Chroma for efficient and accurate answers.

A clean, modular implementation of an Agentic RAG (Retrieval-Augmented Generation) system built with a production-ready architecture.

API/MCP wrapper for RagAnything

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

Never repeat yourself across AI :)

The open-source, self-hosted alternative to NotebookLM.

Production-ready Chainlit RAG application with Pinecone pipeline offering all Groq and OpenAI Models, to chat with your documents.