How to Connect Your First AI Agent

Prerequisites

• A running AI agent (any framework)
• A FuseIQ account with an active workspace
• Python 3.9+ (for the SDK) — or just use the REST API directly

1. Install the FuseIQ SDK

Open your terminal and install the SDK:

bash
pip install fuseiq-sdk

2. Get Your API Key

Navigate to Settings → API Keysin your dashboard. Generate a new key. Keys are prefixed fk_live_... — copy it immediately as it is shown only once.

3. Add the Agent Wrapper

Wrap any agent function with the FuseIQ heartbeat. Here's a minimal example using the current API:

python
from fuseiq import FuseIQAgent
import os

agent = FuseIQAgent(
    api_key=os.getenv("FUSEIQ_API_KEY"),
    agent_name="My First Agent",
    agent_type="llm",
    description="A helpful assistant for customer queries",
    heartbeat_url="https://fuseiq.vercel.app/api/external/heartbeat",
)

@agent.on_heartbeat
def report_status():
    return {
        "status": "online",
        "load": 0.45,
        "tasks_completed": 128,
        "uptime_seconds": 3600,
    }

@agent.on_message
def handle_request(payload):
    # Your agent logic here
    response = your_agent_fn(payload["message"])
    return {"response": response}

agent.start()

4. Verify in Staff Directory

Within 30 seconds, your agent will appear in the Staff Directorywith a green online indicator. You can now:

• Assign tasks directly from Operations
• Monitor cost and performance in Analytics
• Add the agent to a Swarm workflow

Supported Providers

FuseIQ supports the following LLM providers for agent execution:

• OpenAI (GPT-4o, GPT-4o-mini, o-series)
• Anthropic (Claude Sonnet 4, Opus)
• Google (Gemini Pro 2.5, Gemini Flash)
• Grok (xAI)
• Kimi (Moonshot AI)
• Perplexity (Sonar, Sonar Pro)
• Manus
• Custom / Self-hosted models