Advanced45-75 minvector databasererankerevaluation set
Improve retrieval quality
Diagnose and improve weak search results before blaming the model.
Prerequisites
- A working retrieval pipeline
- Failed query examples
- Ability to inspect retrieved chunks
Step-by-step tutorial
Step 1
Classify failures
Separate parsing failures, chunking failures, embedding failures, metadata failures, and reranking failures.
- Collect failed queries
- Inspect parsed text
- Inspect top-k results
- Record cause
Step 2
Tune retrieval
Change one retrieval variable at a time and retest against the same questions.
- Try hybrid search
- Adjust chunk size
- Add metadata filters
- Compare rerankers
Step 3
Protect improvements
Turn successful fixes into regression tests so future changes do not undo them.
- Version test set
- Store expected sources
- Track recall
- Review drift
Next steps
- Add reranking
- Evaluate metadata filters
- Introduce observability traces