rag_kit 0.3.0

Pure-Dart RAG (retrieval-augmented generation): chunking, embeddings, vector search, and context building. Zero dependencies, bring your own embedding model.

0.3.0

• Add a label callback to buildContext. Until now it joined only the raw chunk texts, so the model got the passages with no way to say which document each came from. Pass label to prefix every chunk with a source marker, for example label: (c) => '[${c.document.metadata['sourceId']}]'; it counts against maxChars like the rest of the chunk. Left off, the output is byte-for-byte what it was before.

0.2.2

• Shorten the screenshot description. pub.dev accepts up to 200 characters but scores only those under 160, so the previous release published cleanly and quietly gave up the documentation points it was meant to earn.

0.2.1

• Declare the diagram in pubspec.yaml so pub.dev renders it on the package page. It was already in the repository and the README, but pub.dev shows only what the screenshots: field points at, so the page opened with prose where the picture should have been.

0.2.0

• Add Retriever.retrieveDiverse, maximal marginal relevance over a larger candidate pool. Similarity alone returns near-duplicates when a source repeats itself, so the context window pays for one fact several times while the one that answers the question falls below the cut; this picks each next chunk for its relevance minus how much it repeats what is already picked. lambda runs from pure relevance (1.0, identical to retrieve) to pure diversity (0.0), fetchK sets the candidate pool, and results keep their query-similarity score. buildContext takes diverse: true to select the same way.

0.1.4

• Docs: sharpen the pub.dev description to lead with the value and the terms people search.

0.1.3

• Retriever.retrieve now takes a where predicate, and buildContext now takes both minScore and where, forwarded to the store. The metadata filter and score threshold were already implemented in the store but could not be reached through the retriever's public API.

0.1.2

• Docs: tightened the README wording and visuals.

0.1.1

• Expand the package description to name what the package does in the words people search for. No code changes.

Changelog

0.1.0

Initial release.

• Chunker.fixed, Chunker.paragraphs, and Chunker.sentences, all reporting exact source offsets.
• VectorStore interface and InMemoryVectorStore: cosine similarity over float32 vectors with precomputed norms, top-k via a bounded min-heap, minScore and metadata where filters.
• Binary serialization (toBytes/fromBytes) and, on the VM, file persistence via package:rag_kit/io.dart.
• Retriever: chunk, batch-embed, upsert, retrieve, and buildContext for assembling LLM prompt context.