Overview & Result
Sending simple formatting or deterministic questions to expensive frontier models wastes budget and increases latency. RouteKit uses Jev to grade task difficulty before calling any generative model, routing straightforward tasks to fast models and reserving deep reasoning models for complex challenges.
How Jev fits in the loop
- Analyze user query structure, required reasoning depth, and tool prerequisites.
- Jev Choice outputs the recommended tier: Tier 1 (Fast/Small), Tier 2 (General), Tier 3 (Reasoning/o1).
- The orchestrator dispatches the task to the selected model provider.
- If the lower tier signals uncertainty, RouteKit escalates seamlessly.
How to reproduce
- Clone rajdhakad9826/routeKit and define your model tier routing table.
- Submit varied benchmark prompts ranging from trivial formatting to complex code refactoring.
- Observe routing accuracy, downstream response quality, and total token savings.
Why this build matters
Delivers 60–80% cost reduction and significant speedups across enterprise agent platforms by eliminating model over-provisioning.
Limitations
- Routing accuracy depends on clear classification prompts distinguishing complexity tiers.
- Ambiguous queries may route to cheaper models, necessitating an automatic retry-escalation policy.
- Does not perform the underlying text generation.