oxibonsai-rag

Pure Rust Retrieval-Augmented Generation (RAG) pipeline for OxiBonsai.

Self-contained RAG stack: document chunking (character, sentence, paragraph, semantic, hierarchical, sliding window, markdown), pure Rust embedders (identity, TF-IDF), in-memory vector store with cosine similarity, top-k retrieval, and end-to-end prompt-building pipeline.

Part of the OxiBonsai project.

Status

Stable — version 0.2.2, 871 tests passing (cargo nextest run -p oxibonsai-rag). Uplifted from Alpha in 0.1.2.

Features

• RagPipeline — end-to-end index + query pipeline
• VectorStore — in-memory L2-normalized cosine similarity search
• Retriever — document indexing and top-k chunk retrieval
• Embedder trait — pluggable embedding backends
• IdentityEmbedder — hash-based embedder for testing
• TfIdfEmbedder — bag-of-words TF-IDF embedding
• Chunking strategies: character window, sentence, paragraph, recursive, sliding window, markdown, semantic (cosine boundary), hierarchical
• ChunkerRegistry — dynamic dispatch for pluggable chunking backends
• Zero external API calls — fully self-contained

Usage

[dependencies]
oxibonsai-rag = "0.2.2"

use oxibonsai_rag::RagPipeline;

let mut pipeline = RagPipeline::default();
pipeline.index_document("Rust is a systems programming language.")?;
let prompt = pipeline.build_prompt("What is Rust?")?;

License

Apache-2.0 — COOLJAPAN OU