graphrag-patterns

What problem does it solve?

This Skill addresses the challenge of performing complex reasoning over interconnected data by integrating knowledge graphs with retrieval-augmented generation (RAG). It enables more sophisticated querying and understanding of relationships within data.

Core Features & Use Cases

• GraphRAG Architecture: Implements hybrid retrieval combining vector embeddings and knowledge graphs.
• Entity & Relationship Extraction: Tools to build knowledge graphs from text.
• Retrieval Strategies: Offers entity-centric, path-based, and community-based retrieval methods.
• Use Case: When analyzing a large corpus of research papers, use this skill to identify how different concepts or researchers are related, enabling multi-hop reasoning and discovery of indirect connections.

Quick Start

Use the graphrag-patterns skill to retrieve information about entities and their relationships from a knowledge graph.