{"repo":"gibram-io/gibram","free":true,"listed":false,"github":"https://github.com/gibram-io/gibram","clone":"git clone https://github.com/gibram-io/gibram.git","description":"GibRAM is an in-memory knowledge graph server designed for retrieval augmented generation (RAG / GraphRAG) workflows.","language":"Go","stars":105,"topics":["graph","graph-database","graphrag","llm","llms","rag","vector-database"],"license":"MIT","category":"ai-agents","readme_excerpt":"GibRAM Graph in-Buffer Retrieval & Associative Memory - Graph in-Buffer : Graph structure (entities + relationships) stored in RAM - Retrieval : Query mechanism for retrieving relevant context in RAG workflows - Associative Memory : Traverse between associated nodes via relationships, all accessed from memory GibRAM is an in-memory knowledge graph server designed for retrieval augmented generation (RAG) workflows. It combines a lightweight graph store with vector search so that related pieces of information remain connected in memory. This makes it easier to retrieve related regulations, articles or other text when a query mentions specific subjects. Why GibRAM? - In memory and Ephemeral: Data lives in RAM with a configurable time to live. It is meant for short lived analysis and exploration rather than persistent storage. - Graph and Vectors Together: Stores named entities, relationships and document chunks alongside their embeddings in the same structure. - Graph aware Retrieval: Supports traversal over entities and relations as well as semantic search, helping you pull in context that would be missed by vector similarity alone. - Python SDK: Provides a GraphRAG style workflow for indexing documents and running queries with minimal code. Components such as chunker, extractor and embedder can be swapped out. Quick Start Install via Binary Server runs on port 6161 by default. Install via Docker Python SDK Basic Usage: Custom Components: License MIT","default_branch":null,"files":null,"tree":[],"storefront":"/r/gibram-io","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/gibram-io/gibram/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}