BeeAI

uv add agentstack-sdk import os from a2a.types import Message from a2a.utils.message import get_message_text from agentstack_sdk.server import Server from agentstack_sdk.server.context import RunContext from agentstack_sdk.a2a.types import AgentMessage server = Server() @server.agent () async def example_agent ( input : Message, context : RunContext): """Polite agent that greets the user""" hello_template: str = os.getenv( "HELLO_TEMPLATE" , "Ciao %s !" ) yield AgentMessage( text = hello_template % get_message_text( input )) def run (): server.run( host = os.getenv( "HOST" , "127.0.0.1" ), port = int (os.getenv( "PORT" , 8000 ))) if __name__ == "__main__" : run() uv run example_agent.py Your agent can be: A LangGraph workflow A custom reasoning loop A thin wrapper around an LLM call Agent Stack doesn’t care—as long as it can be executed. ​ 2. Deploy the agent as service Run the agent locally or on infrastructure you control. uv run example_agent "Emily" Your agent is now running as a backend service. ​ 3. Call the agent from your application Integrate the agent into your app using the Client SDK , HTTP API, or our out of the box UI extensions. Agent Stack takes care of running and deploying agents so you can wire them into your application like any other backend service. ​ What Agent Stack is (and isn’t) Agent Stack is: A bundled runtime for deploying agent services Optimized for experimentation and fast iteration Flexible enough to grow with you from local testing to a sandboxed deployment platform Agent Stack isn’t: An agent building framework A hosted AI service A replacement for enterprise AI platforms ​ Getting help, contributing, and staying up to date Agent Stack is an open-source project maintained as part of the Linux Foundation community. Documentation : Start here for guides and examples Issues : Use GitHub Issues to report bugs or request features Discussions : Use Github Discussions to ask questions, share ideas, and compare approaches Contributing : Contributions are welcome— see the contributing guide for details Agent Stack is being actively developed and intended to evolve alongside the agent ecosystem. Defaults may change, components may improve, but the goal remains the same: make agents easy to run, easy to deploy, and easy to integrate. Quickstart Get up and running in one command Wrap Existing Agents Deploy your existing agents to Agent Stack Build New Agents Build your first agent with the SDK Deploy to Production Deploy Agent Stack to Kubernetes for your team Quickstart Get Agent Stack up and running in minutes. Then explore running pre-built agents. Next ⌘ I github discord bluesky On this page Get running in one command Getting from “agent” to “running service” is harder than it should be How does it work? Getting started 1. Wrap an existing agent 2. Deploy the agent as service 3. Call the agent from your application What Agent Stack is (and isn’t) Getting help, contributing, and staying up to date