Enhancing a Log-analyzer with GraphRAG
Sifting through complex software logs for the root cause of errors can be a daunting and time-consuming task. This thesis explores a novel approach using knowledge graphs and GraphRAG to empower Large Language Models (LLMs) for more efficient and accurate analysis. The methodology involves utilizing log template mining and a CMake-generated file dependency tree to build the knowledge graph, which
