Using Kernel Memory to Chunk Documents into Azure AI Search
I've recently been working on building retrieval augmented generation (RAG) experiences into applications; building systems where large language models (LLMs) can query documents. To achieve this, we first need a strategy to chunk those documents and make them LLM-friendly. Kernel Memory, a sister project of Semantic Kernel supports this.