rag-packager

Structuring documentation for RAG ingestion involves splitting canonical texts into domain-specific chunks with stable IDs, cross-references, and metadata annotation. This creates a structured format optimized for efficient retrieval and indexing.

Incremental updates for RAG indexing are handled by packaging only changed artifacts since the last package generation. This ensures your retrieval system stays current without reprocessing the entire documentation workspace every time.

Metadata annotation improves RAG retrieval by attaching stable IDs and cross-references to document chunks. This structured packaging allows retrieval systems to accurately map and index content, resulting in highly relevant and contextually accurate model responses.

Yes, you can generate embeddings automatically when chunking documents for RAG. The packaging process offers optional embedding generation alongside an index.md file for human-readable chunk mapping, streamlining the transition from raw text to indexed vectors.

Yes, canonical documentation is required to effectively structure a RAG retrieval system. The packaging process relies on structured source texts to perform domain-specific splitting and generate the cross-referenced chunks required for high-quality retrieval.