Measure whether the tenant pgvector index works

Translate the claim into assertions or a tiny eval harness. The metric to protect is: tenant isolation test (0 cross-tenant hits); version pin echoed in response. Always record the denominator (how many cases) beside any rate. A percentage without a denominator is marketing, not measurement.

hits_other_tenant=0
assert hits_other_tenant==0
print({'cross_tenant_hits':0,'index_version':'v3'})

Expected evidence: cross_tenant_hits 0. A passing assertion proves only the behavior it names; broader usefulness still needs the chapter’s full limits.

Be explicit: beating the baseline (in-memory cosine search on the same fixtures) on this fixture does not prove behavior under missing tenant filter in SQL, or querying a stale index version silently. Label observations separately from conclusions so the next page inherits honest evidence about the tenant pgvector index.

Compute tenant isolation test (0 cross-tenant hits); version pin echoed in response with the denominator written beside the rate every time. For this chapter, the evaluation set is intentionally tiny; that is allowed only if you say so in the evidence. Compare against in-memory cosine search on the same fixtures before celebrating.

Add one negative case aimed at missing tenant filter in SQL, or querying a stale index version silently. A suite with only happy cases cannot protect the tenant pgvector index when the characteristic failure appears in review.

If a check is expensive or flaky, shrink it until it is deterministic on two tenants with overlapping vocabulary FAQ chunks. Flaky green builds teach the team to ignore gates. Record what this page does not prove so security-ops and mastery-ship inherit honest limits.

At the evaluation stage for vector-db-lab, the job is narrower than finishing a product demo. You are creating one progressive evidence piece about two tenants with overlapping vocabulary FAQ chunks that later pages inherit without redefining success. Keep that fixture small enough to inspect by hand, keep outputs copy-pasteable as text, and refuse to narrate this baseline as if it were a production SLA: in-memory cosine search on the same fixtures.

For this page specifically, success looks like metrics with explicit denominators and a negative case while still centering the user decision to replace an in-memory list with a versioned vector index that cannot leak across tenants. If you cannot point to a file, command, or assertion that proves that for the tenant pgvector index, stay on this page instead of advancing.

Glossary: vector database · Glossary: vector index · Cheatsheet: RAG quality

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For vector-db-lab, write a transfer example that differs in one constraint from the chapter scenario. Keep the quality bar fixed. Explain which check still applies.

For vector-db-lab, write a transfer example that differs in one constraint from the chapter scenario. Keep the quality bar fixed. Explain which check still applies.