Agent Creation

Agent Creation with Microsoft Agent Framework

This skill helps you create AI agents using Microsoft Agent Framework, supporting both Python and .NET implementations.

When to Use This Skill

• Creating a new AI agent or chatbot
• Setting up agent providers (Azure OpenAI, OpenAI, etc.)
• Implementing agents with custom tools/functions
• Building agents with specific instructions or personas

Installation

Python

pip install agent-framework --pre

.NET

dotnet add package Microsoft.Agents.AI --prerelease

Quick Start Examples

Python - Azure OpenAI Agent

import os
import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential

async def main():
    agent = AzureOpenAIResponsesClient(
        endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
        deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
        api_version=os.environ["AZURE_OPENAI_API_VERSION"],
        credential=AzureCliCredential(),
    ).as_agent(
        name="MyAgent",
        instructions="You are a helpful assistant.",
    )
    
    response = await agent.run("Hello, how can you help me?")
    print(response)

if __name__ == "__main__":
    asyncio.run(main())

Python - OpenAI Agent

import asyncio
from agent_framework.openai import OpenAIResponsesClient

async def main():
    agent = OpenAIResponsesClient(
        api_key="your-api-key",  # Or use OPENAI_API_KEY env var
    ).as_agent(
        name="MyAgent",
        instructions="You are a helpful coding assistant.",
    )
    
    response = await agent.run("Explain async/await in Python")
    print(response)

if __name__ == "__main__":
    asyncio.run(main())

.NET - Azure OpenAI Agent

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
// dotnet add package Azure.Identity
using System;
using OpenAI;

var agent = new OpenAIClient(
    new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"),
    new OpenAIClientOptions() { Endpoint = new Uri("https://<resource>.openai.azure.com/openai/v1") })
    .GetOpenAIResponseClient("gpt-4o-mini")
    .AsAIAgent(name: "MyAgent", instructions: "You are a helpful assistant.");

Console.WriteLine(await agent.RunAsync("Hello, how can you help me?"));

.NET - OpenAI Agent

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
using System;
using OpenAI;

var agent = new OpenAIClient("<your-api-key>")
    .GetOpenAIResponseClient("gpt-4o-mini")
    .AsAIAgent(name: "MyAgent", instructions: "You are a helpful assistant.");

Console.WriteLine(await agent.RunAsync("Write a haiku about coding."));

Adding Tools to Agents

Python - Agent with Tools

import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework.tools import tool
from azure.identity import AzureCliCredential

@tool
def get_weather(location: str) -> str:
    """Get the current weather for a location."""
    return f"The weather in {location} is sunny and 72°F"

@tool
def calculate(expression: str) -> float:
    """Evaluate a mathematical expression."""
    return eval(expression)

async def main():
    agent = AzureOpenAIResponsesClient(
        credential=AzureCliCredential(),
    ).as_agent(
        name="ToolAgent",
        instructions="You are a helpful assistant with access to weather and calculation tools.",
        tools=[get_weather, calculate],
    )
    
    response = await agent.run("What's the weather in Seattle and what is 15 * 7?")
    print(response)

if __name__ == "__main__":
    asyncio.run(main())

.NET - Agent with Tools

using Microsoft.Agents.AI;

public class WeatherTools
{
    [AIFunction("Get the current weather for a location")]
    public string GetWeather(string location)
    {
        return $"The weather in {location} is sunny and 72°F";
    }
    
    [AIFunction("Evaluate a mathematical expression")]
    public double Calculate(string expression)
    {
        // Use a proper expression evaluator in production
        return 0.0;
    }
}

var tools = new WeatherTools();
var agent = client.GetOpenAIResponseClient("gpt-4o-mini")
    .AsAIAgent(
        name: "ToolAgent", 
        instructions: "You are a helpful assistant.",
        tools: [tools.GetWeather, tools.Calculate]);

Best Practices

1. Use environment variables for API keys and endpoints
2. Reuse client instances - Don't create new clients for each request
3. Use async APIs for better throughput
4. Handle rate limiting - Implement retry logic for 429 errors
5. Set clear instructions - Be specific about agent behavior and constraints
6. Use Azure CLI authentication (AzureCliCredential) for local development

Environment Variables

Python/Azure OpenAI

• AZURE_OPENAI_ENDPOINT - Your Azure OpenAI endpoint
• AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME - Deployment name
• AZURE_OPENAI_API_VERSION - API version (e.g., "2024-02-15-preview")
• AZURE_OPENAI_API_KEY - API key (optional if using credential)

Python/OpenAI

• OPENAI_API_KEY - Your OpenAI API key

References

• Getting Started with Agents (Python)
• Getting Started with Agents (.NET)
• MS Learn Documentation

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