Azure-Samples /
Agentic-AI-Investment-Analysis-Sample
Sample App using Agent Framework for analysis of investment opportunities.
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A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
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Microsoft Agent Framework (MAF) is an open, multi-language framework for building production-grade AI agents and multi-agent workflows in .NET and Python.
Microsoft Agent Framework is built for teams taking agents from prototype to production. It provides a consistent foundation for building, orchestrating, and operating agent systems across Python and .NET, while keeping architecture choices open as requirements evolve, and supports a broad ecosystem including Microsoft Foundry, Azure OpenAI, OpenAI, and the GitHub Copilot SDK, with samples and hosting patterns for both local development and cloud deployment.
MAF is a strong fit if you:
Explore new MAF capabilities and real implementation patterns on the official blog.
Python
pip install agent-framework
# This will install all sub-packages, see `python/packages` for individual packages.
# It may take a minute on first install on Windows.
.NET
dotnet add package Microsoft.Agents.AI
# For Foundry integration (used in the .NET quickstart below):
dotnet add package Microsoft.Agents.AI.Foundry
dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity
Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework
# pip install agent-framework
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from azure.identity import AzureCliCredential
async def main():
# Initialize a chat agent with Microsoft Foundry
# the endpoint, deployment name, and api version can be set via environment variables
# or they can be passed in directly to the FoundryChatClient constructor
agent = Agent(
client=FoundryChatClient(
credential=AzureCliCredential(),
# project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
# model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
),
name="HaikuAgent",
instructions="You are an upbeat assistant that writes beautifully.",
)
print(await agent.run("Write a haiku about Microsoft Agent Framework."))
if __name__ == "__main__":
asyncio.run(main())
Create a simple Agent, using Microsoft Foundry that writes a haiku about the Microsoft Agent Framework
// This sample shows how to create and run a basic agent with AIProjectClient.AsAIAgent(...).
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
AIAgent agent =
new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: deploymentName, instructions: "You are an upbeat assistant that writes beautifully.", name: "HaikuAgent");
// Once you have the agent, you can invoke it like any other AIAgent.
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
| Problem | Cause | Fix |
|---|---|---|
| Authentication errors when using Azure credentials | Not signed in to Azure CLI | Run az login before starting your app |
| API key errors | Wrong or missing API key | Verify the key and ensure it's for the correct resource/provider |
Tip:
DefaultAzureCredentialis convenient for development but in production, consider using a specific credential (e.g.,ManagedIdentityCredential) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
For environment variable configuration specific to each sample, refer to the README in the sample directory (Python samples | .NET samples).
[!IMPORTANT] If you use Microsoft Agent Framework to build applications that operate with any third-party servers, agents, code, or non-Azure Direct models (“Third-Party Systems”), you do so at your own risk. Third-Party Systems are Non-Microsoft Products under the Microsoft Product Terms and are governed by their own third-party license terms. You are responsible for any usage and associated costs.
We recommend reviewing all data being shared with and received from Third-Party Systems and being cognizant of third-party practices for handling, sharing, retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization’s Azure compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries and approvals are provisioned.
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