pyagent-router 0.1.0

Difficulty-aware routing and model selection for multi-agent LLM workflows

pyagent-router

Difficulty-aware routing and model selection for multi-agent LLM workflows. Route easy tasks to cheap models, hard tasks to expensive ones.

Install

pip install pyagent-router

Components

• DifficultyScorer — Score task difficulty 1-10 based on heuristics
• CostEstimator — Estimate LLM call costs with built-in model pricing
• ModelSelector — Auto-select the cheapest viable model
• RouterMiddleware — Inject routing into agent calls

Quick Example

from pyagent_router import ModelSelector

result = ModelSelector().select("What is 2+2?")
print(f"{result.model}: ${result.cost_estimate.total_cost:.6f}")
# gpt-4.1-nano: $0.000002 (instead of $0.003 with gpt-4o)

Typical Savings: 40-60%

For workloads where 70% of queries are easy, routing to cheap models saves 40-60% vs always using the most expensive model.