RAG Knowledge Builder
Overview
Garbage in, garbage out. Clean sources beat clever chunkers.
Workflow
- Define the question types the RAG must answer.
- Ingest sources (docs,
web-extractoroutput, PDFs). - Chunk with structure awareness (headings > fixed blind windows).
- Embed/index with the project’s vector store (note model + dims).
- Evaluate with 10-20 gold questions; measure hit rate / faithfulness.
- Fix gaps (missing docs, bad chunking) before tuning prompts.
Rules
- Track provenance (source URL/path) on every chunk.
- Exclude secrets and credentials from the corpus.