Late Chunking has been introduced in Chonkie, a lean chunking library. This update is crucial for integrating late chunking into retrieval pipelines, as it addresses the issue of preserving long-distance context in large documents. Chonkie makes embedding chunks based on the entire document's context, significantly improving retrieval performance. The article explains the concept of late chunking, its benefits, and how to implement it using Chonkie and KDB.AI as the vector store.
Table of contents
Easy Late-Chunking With ChonkieWhat is Late Chunking?The Lost Context ProblemLate Chunking SolutionNaive vs Late Chunking ComparisonImplementation with Chonkie and KDB.AI1. Install Dependencies and Set Up LateChunker2. Set Up the Vector Database3. Chunk and Embed4. Query the Vector Store5. Clean UpConclusionSort: