knowledge-base

A structured knowledge base for large language model technologies, covering LLMs, Agents, RAG, model training, evaluation methodologies, and AI engineering practices.

Advanced RAG (Retrieval-Augmented Generation) system for private document intelligence. Uses OpenAI GPT-4o and Vector Databases to provide zero-hallucination chat insights.

Production-ready Retrieval Augmented Generation (RAG) system with hybrid retrieval, advanced evaluation metrics, and monitoring. Build enterprise LLM applications with reduced hallucinations, better context management, and comprehensive observability.

A self-hosted omni-modal agentic retrieval platform that understands, searches, and explores documents, images, audio, and video through semantic routing, hybrid retrieval, adaptive agents, and traceable citations.

An AI-powered search engine to interact with documentation using RAG and local LLMs. Privately deployable with vector search and a modern frontend.

Enterprise multi-source RAG platform with multimodal embedding, hybrid vector/BM25 retrieval, MCP & RBAC support

A full-modal personal knowledge base built on the Karpathy LLM Wiki concept.

OpenViking knowledge base integration for nanobot — RAG augmentation, semantic search, vector embeddings, document indexing. Free models on SiliconFlow.

A local personal memory lab with programmable fractal search and evidence governance.