KPI-Weighted Routing

import cascadeflow

cascadeflow.init(mode="enforce")

with cascadeflow.run(
    kpi_weights={"quality": 0.6, "cost": 0.3, "latency": 0.1},
    kpi_targets={"quality": 0.9}
) as session:
    result = await agent.run("Analyze this legal document")

# Quality-first (premium workload)
kpi_weights = {"quality": 0.8, "cost": 0.1, "latency": 0.1}

# Cost-first (high-volume batch)
kpi_weights = {"quality": 0.2, "cost": 0.7, "latency": 0.1}

# Balanced
kpi_weights = {"quality": 0.4, "cost": 0.3, "latency": 0.2, "energy": 0.1}

kpi_targets = {
    "quality": 0.9,   # Require high quality
    "latency": 0.7,   # Require reasonable speed
}

score = quality_prior * w_quality + cost_utility * w_cost + latency_prior * w_latency + energy_utility * w_energy

@cascadeflow.agent(
    budget=0.50,
    kpi_weights={"quality": 0.8, "cost": 0.2}
)
async def quality_agent(query: str):
    return await llm.complete(query)

@cascadeflow.agent(
    budget=0.10,
    kpi_weights={"cost": 0.8, "quality": 0.2}
)
async def budget_agent(query: str):
    return await llm.complete(query)