jev-router-playground GitHub avatar by hugo-alves

hugo-alves /

Routing & Cost Optimization

jev-router-playground

A model-routing playground where Jev picks a candidate and users compare the resulting answers.

License: MITLanguage: TypeScriptLast push: 9/18/2026#llm-routing-cost#evaluation-benchmarks

What Jev Does in this Architecture

Selects a model from the task and candidate profiles and records probabilities and runs.

Key Architecture Benefit

Exports observations for checking routing choices against user preferences.

Review & Benchmark Note: The default Jev connection passes through an author-provided CORS proxy. It should not be described as a private local-only execution path. No credentials were entered in this audit. README and integration source reviewed at a fixed commit; not independently run or benchmarked by this site.
Clone Repository
git clone https://github.com/hugo-alves/jev-router-playground.git

Inspect on GitHub

Check out the upstream repository README, issues, and commit log.

hugo-alves/jev-router-playground

Architecture Category

Routing & Cost Optimization

Complexity-based request routing to tier generative models and optimize token spend.

View all in this category →

Related Projects in Routing & Cost Optimization

53
Routing & Cost OptimizationMITPython

Uses Jev to classify each Codex turn, then applies local rules to choose the model, reasoning effort, and speed mode.

What Jev does here

Classifies task difficulty and reasoning needs before local policy selects a model configuration.

Keeps routing policy and decision logs local for inspection and tuning.

#llm-routing-cost#coding-agents
53 evidence links
Inspect details
jev-research repository icon by sherajdev

sherajdev

jev-research

1
Routing & Cost OptimizationMITTypeScript

A Jev and Herdr integration guide with a prototype for routing tasks to different Agents.

What Jev does here

Uses task and repository state to choose an executor and assess risk and dispatch readiness.

Provides a readable, editable example of multi-Agent task routing.

#llm-routing-cost#typed-decisions
2 evidence links
Inspect details
jev-demo repository icon by minghanminghan

minghanminghan

jev-demo

0
Routing & Cost OptimizationMITTypeScript

A customer-service routing demo that batches Jev questions before following the resulting route.

What Jev does here

Assesses classification levels, human-handoff intent and frustration, with low-confidence escalation.

Combines routing and human handoff while leaving response generation to the application.

#domain-workflows#classification-ranking
4 evidence links
Inspect details