AgentField Documentation
The AI backend. Build, deploy, and govern AI agents like APIs.
The AI backend. Build, deploy, and govern AI agents like APIs.
curl -sSf https://agentfield.ai/get | shfrom agentfield import Agent, AIConfig
from pydantic import BaseModel
app = Agent("demo", ai_config=AIConfig(model="anthropic/claude-sonnet-4-20250514"))
class Decision(BaseModel):
action: str
@app.reasoner()
async def route(text: str) -> dict:
out = await app.ai(
system="Pick one action: summarize | escalate | done.",
user=text,
schema=Decision,
)
return out.model_dump()
app.run()// Same idea in TS: Agent + reasoner + app.ai with a schema.
// See Quickstart for the full snippet.// Same idea in Go: agent package + reasoner + structured AI call.
// See Quickstart for the full snippet.- APIs — decorated functions become HTTP endpoints with discovery and tracing.
- Models — 100+ LLMs, structured output (Pydantic / Zod / structs), tool calling.
- Multi-agent —
app.call, shared memory, async, webhooks, governance (DIDs, policy, audit).