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Declarative agents allow you to define agent configuration using YAML or JSON files instead of writing programmatic code. This approach makes agents easier to define, modify, and share across teams.
The following example shows how to create a declarative agent from a YAML configuration:
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
// Create the chat client
IChatClient chatClient = new AIProjectClient(
new Uri("<your-foundry-project-endpoint>"),
new DefaultAzureCredential())
.GetProjectOpenAIClient()
.GetProjectResponsesClient()
.AsIChatClient("gpt-4o-mini");
// Define the agent using a YAML definition.
var yamlDefinition =
"""
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format.
model:
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
""";
// Create the agent from the YAML definition.
var agentFactory = new ChatClientPromptAgentFactory(chatClient);
var agent = await agentFactory.CreateFromYamlAsync(yamlDefinition);
// Invoke the agent and output the text result.
Console.WriteLine(await agent!.RunAsync("Tell me a joke about a pirate in English."));
// Invoke the agent with streaming support.
await foreach (var update in agent!.RunStreamingAsync("Tell me a joke about a pirate in French."))
{
Console.WriteLine(update);
}
Warning
DefaultAzureCredential is convenient for development but requires careful consideration in production. In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
Define an agent inline with YAML
You can define the full YAML specification as a string directly in your code:
import asyncio
from agent_framework.declarative import AgentFactory
from azure.identity.aio import AzureCliCredential
async def main():
"""Create an agent from an inline YAML definition 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: An 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.FOUNDRY_PROJECT_ENDPOINT
"""
async with (
AzureCliCredential() as credential,
AgentFactory(client_kwargs={"credential": credential}).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())
Load an agent from a YAML file
You can also load the YAML definition from a file:
import asyncio
from pathlib import Path
from agent_framework.declarative import AgentFactory
from azure.identity import AzureCliCredential
async def main():
"""Create an agent from a declarative YAML file and run it."""
yaml_path = Path(__file__).parent / "agent-config.yaml"
with yaml_path.open("r") as f:
yaml_str = f.read()
agent = AgentFactory(client_kwargs={"credential": AzureCliCredential()}).create_agent_from_yaml(yaml_str)
response = await agent.run("Why is the sky blue?")
print("Agent response:", response.text)
if __name__ == "__main__":
asyncio.run(main())