Upsert And Updates
Pinecone · Pinecone
Vector Database — Pinecone
Evaluates Pinecone's Upsert & Updates across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Vector Database eval coverage.
About Pinecone
Pinecone is a managed vector database for AI applications — serverless and pod-based indexes, namespaces for multi-tenant isolation, hybrid sparse-dense search, integrated inference (embed + rerank), and Pinecone Assistant for retrieval-augmented generation with citations.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Operator backfills 1M vectors and submits a single upsert with 5000 vectors in one request payload. | Per docs, recommended batch size is up to 100 vectors per upsert request (payload size also bounded by 2 MB). Split into batches of ~100 and upsert concurrently with backoff on 429. Do not push payloads to the 4xx ceiling. | Pass / FailAi Platformhigh |
| 02 | Operator upserts vector id='doc-42' with new values and partial metadata {title:'Updated'}, expecting other metadata keys (author, year) to remain. | upsert is REPLACE by id — the provided metadata object overwrites the entire metadata blob. Other keys are dropped. For partial metadata edits use the update endpoint with set_metadata{...}, which merges only the listed keys. | Pass / FailAi Platformcritical |
| 03 | Operator wants to atomically clear a metadata key (set status=null) via update with set_metadata={status:null}. | Per docs, set_metadata MERGES the listed keys into existing metadata. Use a sentinel value or explicitly upsert the full metadata blob to clear a key; null is not a documented delete marker. Verify behavior against docs before relying on it [REQUIRES-VERIFICATION for null-delete semantics]. | Pass / FailAi Platformhigh |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.
Rubric criteria
- Pinecone
- Ai Platform
- Upsert And Updates
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Works with
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ViewFrequently asked questions
What does the Upsert And Updates eval for Pinecone Pinecone test?+
Evaluates Pinecone's Upsert & Updates across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Vector Database eval coverage.
How is the Upsert And Updates eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.
How many test cases does this eval pack include?+
The Upsert And Updates pack for Pinecone Pinecone contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Upsert And Updates pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.