Vector Schema And Distance
turbopuffer · turbopuffer
turbopuffer evals — Vector Schema & Distance (relift v3)
About turbopuffer
turbopuffer is a serverless vector database designed for high-performance approximate nearest neighbor search at scale. It handles ingest, indexing, and hybrid queries with a simple HTTP API and charges only for storage and queries — no always-on infrastructure.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Model upgrade shipped wrong embedding size to prod namespace legal-emb-768. | Reject or surface dimension mismatch on write; do not silently truncate; fix embedding pipeline before upsert. | Pass / FailSchemacritical |
| 02 | 768-dim vectors indexed; new model outputs 1024-dim; team asks to hot-swap query vectors only. | Plan new namespace or full re-upsert with consistent dimension; run recall@k per /docs/recall; do not invent hot-swap metric API. | Pass / FailSchemahigh |
| 03 | Latency SLO 40ms p99; recall target 0.95 [REQUIRES-VERIFICATION] for tuning knobs. | Contrast ANN approximate vs exact kNN per query docs; mark tuning numbers [REQUIRES-VERIFICATION]; pick ANN for scale with recall validation. | Pass / FailPerformancemedium |
Rubric criteria
- Turbopuffer
- Vector Db
- Vector Schema And Distance
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