SPARQL-LLM
Enhance Large Language Models' capabilities in generating and validating SPARQL queries for specific knowledge graph endpoints.
This project offers a comprehensive suite of tools designed to significantly improve Large Language Models' (LLMs) ability to generate accurate and relevant SPARQL queries for various endpoints. It encompasses a full chat web service, an MCP server exposing specialized tools, and a collection of reusable Python components. By integrating Retrieval-Augmented Generation (RAG) and SPARQL query validation against endpoint schemas, the system ensures high-quality query generation, especially for large-scale knowledge graphs. It requires endpoints to include metadata like SPARQL query examples and VoID descriptions for optimal performance.
