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agent-framework/python/samples/02-agents/declarative/inline_yaml.py
T
Dmytro Struk 57da1bcfeb Python: Fixed declarative samples (#4051)
* Updated declarative kind mapping

* Fixed required property handling

* Updated inline yaml sample

* Fixed remaining declarative samples

* Added lazy initialization for PowerFx engine

* Small fix
2026-02-18 23:08:31 +00:00

48 lines
1.6 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
from agent_framework.declarative import AgentFactory
from azure.identity.aio import AzureCliCredential
from dotenv import load_dotenv
load_dotenv()
"""
This sample shows how to create an agent using an inline YAML string rather than a file.
It uses a Azure AI Client so it needs the credential to be passed into the AgentFactory.
Prerequisites:
- `pip install agent-framework-azure-ai agent-framework-declarative --pre`
- Set the following environment variables in a .env file or your environment:
- AZURE_AI_PROJECT_ENDPOINT
- AZURE_OPENAI_MODEL
"""
async def main():
"""Create an agent from a declarative YAML specification and run it."""
yaml_definition = """kind: Prompt
name: DiagnosticAgent
displayName: Diagnostic Assistant
instructions: Specialized diagnostic and issue detection agent for systems with critical error protocol and automatic handoff capabilities
description: A agent that performs diagnostics on systems and can escalate issues when critical errors are detected.
model:
id: =Env.AZURE_OPENAI_MODEL
connection:
kind: remote
endpoint: =Env.AZURE_AI_PROJECT_ENDPOINT
"""
# create the agent from the yaml
async with (
AzureCliCredential() as credential,
AgentFactory(client_kwargs={"credential": credential}, safe_mode=False).create_agent_from_yaml(yaml_definition) as agent,
):
response = await agent.run("What can you do for me?")
print("Agent response:", response.text)
if __name__ == "__main__":
asyncio.run(main())