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This quickstart is the fastest path to run an agent against Sudoiq and see a completed result. Use Python (asapi), the agentservice CLI, or (soon) Node.js.

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Before you begin

  • Python 3.10+ if you use the Python client or install the CLI via pip.
  • A virtual environment (recommended):
python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
Install the Python client (for the Python tab below): 
pip install asapi
The PyPI project may be published as asapi or agentserviceapi; the import is asapi unless your release notes say otherwise. The CLI wheel package name is agentservice.

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Run one agent

Use the dropdown to switch between Python, Node.js, and CLI. After start, the client waits for the run to finish using a long-lived streaming connection when the API supports it (server-sent events, SSE), so you do not write your own polling loop.
Python
import asyncio
from asapi import AsapiClient

async def main():
    client = AsapiClient()
    client.set_api_key("sk_...")  # from https://sudoiq.com/settings

    result = await client.run_agent(
        agent_id="YOUR_AGENT_UUID",
        string_inputs={"1": "Hello"},
        environment="playground",
    )
    print(result.status)
    print(result.result)

asyncio.run(main())

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After your first run

Add tools, validators, and tests so you can measure and improve behavior: For alternative delivery models (for example very long-running jobs), see Running agents.

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Next steps