Improve Vector Databases

Operation

Implement the requested coherent change at the owning source and update directly affected consumers. An earlier audit is optional when the user and repository already establish the target. Validate the changed behavior, then stop when the requested scope is complete.

Goal

Implement one selected, evidence-backed Vector Databases improvement at the authoritative owner. Complete the directly affected contract without broad cleanup or redesign.

Domain rules

• Centralize embedding/collection compatibility metadata and reject mismatched dimensions/model versions before write/query.
• Enforce tenant filters server-side in the repository's retrieval boundary and cover every query variant with isolation tests.
• Use stable source/chunk IDs and versioned idempotent upserts; reconcile deletes and failed partial batches.
• Tune ANN only against an evaluation dataset and explicit latency/resource budget; preserve a measurable quality floor.
• Perform reindex/migration through staged collection/alias cutover with completeness and quality comparison plus rollback.

Validation

• Run integration tests against the supported vector engine/version, including payload filters, aliases, snapshots, and consistency settings used in production.
• Evaluate retrieval quality and latency under representative filters, concurrency, write load, partial failure, and degraded index state.
• Verify tenant isolation, stale/delete convergence, migration completeness, snapshot restore, and fallback behavior.