# Using cURL
curl -X POST https://api.quantidium.ai/v1/agents \
  -H "Authorization: Bearer qai_live_xxxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{"name": "SensorMonitor", "type": "observability"}'

import { QuantidiumClient } from '@quantidium/sdk';

// Initialize client
const client = new QuantidiumClient({ apiKey: process.env.Q_API_KEY });

// Deploy an Agent
const myAgent = await client.agents.create({
    name: "GridOptimizer",
    model: "q-reasoning-v2",
    tools: ["quantum_router", "slack_alerts"],
    systemPrompt: "Monitor load sensors and reroute power to prevent overloads."
});

// Publish a sensor reading
await client.sensors.publish({
    topic: "facility/hvac/temp",
    payload: { temp_celsius: 86.4, status: "critical" }
});

from quantidium import Client, QuantumTask

client = Client(api_key="qai_live_...")

def optimize_delivery_fleet(fleet_data, constraints):
    # The agent will automatically construct the QUBO matrix
    task = QuantumTask(
        objective="minimize_fuel_and_time",
        dataset=fleet_data,
        hard_constraints=constraints
    )
    
    # Offload to QPU Alpha
    result = client.quantum.execute(task)
    
    return result.optimized_routes

# Pass this function to your agent as a custom tool
agent.equip_tool(optimize_delivery_fleet)