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Developer guide

You're a developer if you're building agents that participate in a Yutha-governed swarm. That includes:

  • Wrapping an existing LangGraph, CrewAI, OpenAI Agents, or Microsoft Agent Framework agent so it can join.
  • Reading and writing envelopes through the SDK.
  • Handling capabilities for tools that take consequential actions.
  • Writing a new framework adapter against the spec.

If you're standing up and running the swarm itself, you're an operator — see the operator guide instead.

Start here

  • Quickstart — the 15-minute joiner path. Bring an existing agent, get a passport, send and receive your first envelope, observe a capability check.
  • Python SDK — the canonical client surface. Async by default; handles passport mint, bearer auth, envelope encoding, subscription multiplexing.
  • Writing a new adapter — how to add support for a framework Yutha doesn't yet ship for.

Framework adapters

Four adapters ship today. Each has a full developer walkthrough and a paired worked example under Examples. Pick whichever framework matches what you already build agents in — the substrate is identical under all four.

  • LangGraph — wrap a LangGraph node as a Yutha agent. The richest hands-on walkthrough; deterministic state-graph handler, no LLM dependency at the dispatch level. Paired example: customer support with refund cap.
  • CrewAI — each Agent in a Crew becomes a Yutha agent with its own identity. LLM-driven dispatch via Crew.kickoff(). Paired example: AP & invoice processing.
  • OpenAI Agents — each agents.Agent becomes a Yutha agent. Handoff bridging via RunHooks so every inter-agent transition produces a signed audit envelope; cap-gating via @capability_required on function_tool bodies. Paired example: research crew with citation enforcement.
  • Microsoft Agent Framework — each agent_framework.Agent becomes a Yutha agent. Cap-gating on async-native tool callables (no sync/async bridge); honest documentation of v1 scope vs WorkflowBuilder / RequestInfoExecutor / FunctionMiddleware follow-ons. Paired example: DevOps incident-response.