A tiny local RAG baseline using only SQLite search
JAS RAG is a small local tool for testing before adding heavier parts. It indexes Markdown files, splits them into documents and chunks, and stores everything in SQLite. It uses SQLite FTS5 for , searches at the chunk level, and formats the matched chunks as context for a .
It does not need embeddings, a , rerankers, s, or API keys. The workflow is to index a small folder, run a few questions, check whether the top 1 and top 3 results are right, and inspect the returned chunks directly. Vector search is added only if the test shows SQLite FTS5 is not good enough.
It is not a full RAG platform or production framework, but a simple local baseline for checking .
Key points
- Markdown files are stored locally in SQLite and searched with SQLite FTS5.
- The tool avoids embeddings, a , external services, and API keys.
- Retrieved chunks are formatted into context for a .
- Top 1 and top 3 search results are checked before adding more complex search.
- The goal is a simple RAG baseline, not a platform.