devwithjevNatural-Language Reranking with Jev
Pinecone’s demo uses Jev to rerank retrieval results according to natural-language criteria. Jev returns a reranked list in 830 to 1,300 ms across eight test queries.
View on X time830 to 1,300 ms across eight test queries
Use @typesafeai's Jev model with Pinecone to rerank results with natural language criteria!
Usually with rerankers, it's hard to cleanly specify what should and shouldn't be returned in results.
Jev resolves this by refactoring the problem into evaluating against distinct binary criteria, which pairs great with Pinecone retrieval!
In this demo, we compare using Jev and Claude to rerank 200 returned candidates from Pinecone. Jev returns a reranked list in about a second — 830 to 1,300 ms across eight test queries.
Claude Opus 5, doing the same job in one long-context call, takes 4.2 to 6.8
Jev evaluates distinct binary criteria to help specify what should and shouldn’t appear in results. The demo compares Jev with Claude on reranking 200 candidates returned from Pinecone.
Also filed under Tools & apps
- Swift Client for TypeSafe Jev Judgments
swift-jev is a Swift client for TypeSafe Jev that uses typed judgments instead of generated text.
- Go SDK and CLI for Jev Decisions
go-jev provides a Go SDK and CLI for TypeSafe Jev typed yes/no, Choice, and Score decisions.
- Open-Model Semantic-If Engine
SemIf-OpenJev is an open-model semantic-if engine for local Jev-style decisions.
- Open-Weight Jev Decision Model
JevK5 is an open-weight Jev alternative that returns typed decisions with probabilities in one forward pass.