To help you get started quickly, we’ve created a ready-to-use starter repository. You can clone it and start coding right away—no setup headaches or boilerplate required. This guide walks you through running your first “Hello World” agent and then customizing it to make it your own.Documentation Index
Fetch the complete documentation index at: https://ibm-8c0b5b62-gpt-researcher-integration.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
Prerequisites
- Agent Stack installed (Quickstart)
- uv package manager (should be already installed if you followed the quickstart)
Start From Template
You should see: “Ciao Alice!” 🎉
With your first agent running, you can now modify it to do anything you want.
Implement Your Agent Logic
Navigate to src/agentstack_agents/agent.py and replace the example with your agent logic. The starter example is minimal and intended for demonstration purposes only:Start a server
An agent is essentially an HTTP server. Create a
Server instance and run it using run().Mark your agent function
Add the
@server.agent decorator to your function so the platform recognizes it as an agent.Describe your agent
Write a docstring for the function; it will be extracted and shown as the agent’s description in the platform.
Understand the function arguments
- First argument: an A2A
Message. - Second argument: a
RunContextobject with run details (e.g.,task_id,context_id).
Extract text from Message
Use
get_message_text() to quickly extract the text content from a Message.Make it an async generator
The agent function should be asynchronous and yield results as they’re ready.
Starting from Scratch
If you prefer not to use the starter repo:- Create an empty Python project
- Install
agentstack-sdk - Copy the example code above
Next Steps
After building your agent, you can enhance it and learn more:Agent Details
Customize your agent’s name, description, and how it appears in the UI
Working with Messages
Learn how agents and clients communicate through structured messaging
Multi-Turn Conversations
Understand how to handle multi-turn conversations and maintain context
Working with Files
Work with files to provide inputs or store outputs for your agent