rag_kit 0.1.4

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

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.