Retrieval Augmented Generation
Showing 9 of 9 projects
A comprehensive open-source guide covering prompt engineering techniques, papers, notebooks, and resources for LLMs, RAG, and AI agents.
A high-performance, cloud-native vector database built for scalable approximate nearest neighbor (ANN) search.
Open-source vector database and embedding store for building AI applications with semantic search.
A customizable AI chatbot agent that ingests PDF documents, stores embeddings in a vector database, and answers user queries using LangChain and LangGraph.
An open-source, cloud-native vector database that combines semantic search with structured filtering for AI applications.
An all-in-one AI framework for semantic search, LLM orchestration, and language model workflows built around an embeddings database.
An end-to-end AI agent engineering platform with an open-source TypeScript framework and a production-ready observability console.
A Ruby gem for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A high-performance GraphRAG framework in Rust that transforms documents into knowledge graphs for superior retrieval and generation.
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