GraphMemory
Embedded graph database with vector search and GraphRAG
All Skills in This Repository (1)
Pure Emerald Level IndicatorsFrequently Asked Questions
FAQPage SchemaHow to install GraphMemory?▼
Run `npx skills add bradAGI/GraphMemory --all -g -y` in your terminal to install this skill globally.
What is GraphMemory used for?▼
It is an embedded graph database for building knowledge graphs and running GraphRAG retrieval, combining vector search, full-text search, and graph traversal in one Python package.
Does GraphMemory need a separate database server?▼
No. It runs embedded on DuckDB, so it works in-memory or from a single local file with no Neo4j, Postgres, or external services required.
Can GraphMemory extract knowledge graphs from text?▼
Yes. With the optional DSPy extra, it extracts entities and relationships from unstructured text and merges them into the graph with automatic deduplication.
Does GraphMemory support semantic and keyword search together?▼
Yes. Its hybrid search combines HNSW vector similarity with BM25 full-text scoring using configurable weights for better retrieval accuracy.
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