Published
KNN Multi-Round Router
KNN-based agentic router for complex, multi-step agent tasks requiring task decomposition.
Overview
The KNN Multi-Round Router extends the KNN routing approach to handle complex, multi-step agentic tasks by decomposing them into subtasks and routing each to the appropriate model.
How It Works
Complex tasks are broken down into subtasks, each represented as an embedding. The KNN algorithm finds similar subtasks from historical data and routes them to models that performed best on those subtask types.
Strategy
Extends KNN routing for complex, multi-step agentic tasks.
API Endpoint
autoroute:knnmultiroundrouter
Use Cases
- Agent workflows requiring multiple LLM calls
- Complex task decomposition and routing
- Multi-step reasoning pipelines
Best Practices
Task Granularity
The granularity of task decomposition significantly impacts routing quality. Too coarse, and you lose the benefit of specialized model selection. Too fine, and routing overhead dominates.
Related Models
- LLM Multi-Round Router — For LLM-based agentic routing
- KNN Router — The single-round foundation