{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Stores and retrieves LangChain documents using a hybrid graph approach that combines vector similarity search with edge-based traversal between document chunks.","skillfed_tags":["rag-retrieval","graph-store","langchain-integration"],"use_cases":["Build a documentation system where hyperlinks between pages are traversed to surface related docs alongside vector matches.","Create a knowledge graph retriever that follows semantic edges between chunks to enrich context for generation.","Store and retrieve hierarchical or interconnected documents where edge depth controls retrieval scope.","Implement a hybrid search that combines vector similarity with relationship-based ranking for multi-hop context.","Populate and query a document store where metadata-driven links define how chunks should be connected."],"what_it_does":"RAGStack Graph Store is a LangChain-compatible document store that layers graph structure on top of vector search. Instead of retrieving documents by similarity alone, it lets you define edges between chunks\u2014via hyperlinks, semantic relationships, or custom metadata\u2014and then traverse those edges during retrieval to surface related context. You populate documents with metadata fields like `content_id` and `links`, add them to the store, and retrieve them with a configurable depth parameter that controls how many levels of edges to follow.\n\nThe package is built on top of cassio and designed to work with Cassandra as the underlying storage backend. It integrates with LangChain's embedding and retrieval ecosystems. The main use case is building retrieval systems where document relationships matter\u2014e.g., a knowledge base where pages link to each other, or chunks that should pull in related context when retrieved.","worth_installing":"Yes, if you need hybrid graph-based retrieval for LangChain and are comfortable with the BUSL-1.1 license terms. The package has low install friction, active maintenance, no known vulnerabilities, and clear integration with cassio. Verify the license is compatible with your use case before committing to production."},"id":"ragstack-ai-knowledge-store","links":{"html":"https://skillfed.io/packages/ragstack-ai-knowledge-store","md":"https://skillfed.io/packages/ragstack-ai-knowledge-store.md","pypi":"https://pypi.org/project/ragstack-ai-knowledge-store/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-07-30","license_spdx":null,"license_treatment":"unclear","name":"ragstack-ai-knowledge-store","python_support":"capped_below_current","summary":"DataStax RAGStack Graph Store"},"popularity":{"monthly_downloads":96854,"position":13192,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.1"}