ReferenceSDKs
Python SDK
Build agents with the AgentField Python SDK
Build AI agents as production microservices with Python.
The Python SDK turns registered reasoners and skills into callable agent endpoints with routing, coordination, memory, async execution, and optional DID-backed governance. Identity and verifiable-credential features are available when you enable them.
Install
pip install agentfieldRequires Python 3.8+. The package version is currently 0.1.63-rc.1.
Python SDK roadmap
Track open Python SDK work on GitHub, including upcoming features, parity work, and contributor-friendly tasks. If an API you need is missing, open a feature request and tell us what you expected to build.
Quick Start
from agentfield import Agent, AIConfig
from pydantic import BaseModel
app = Agent(
node_id="my-agent",
ai_config=AIConfig(model="anthropic/claude-sonnet-4-20250514"),
)
class Summary(BaseModel):
title: str
key_points: list[str]
@app.reasoner()
async def summarize(text: str) -> dict:
result = await app.ai(
system="You are a concise summarizer.",
user=text,
schema=Summary,
)
return result.model_dump()
app.run()Start the control plane and your agent:
af server # Terminal 1 — Dashboard at http://localhost:8080
python app.py # Terminal 2 — Agent auto-registersCall your agent:
curl -X POST http://localhost:8080/api/v1/execute/my-agent.summarize \
-H "Content-Type: application/json" \
-d '{"input": {"text": "AgentField is an open-source control plane..."}}'