Evan Mattson dae3caa719 Python: Fix IndexError when reasoning models produce reasoning-only messages in Magentic-One workflow (#4413)
* Fix IndexError when reasoning models return no text content (#4384)

In _prepare_message_for_openai(), the text_reasoning case unconditionally
accessed all_messages[-1] to attach reasoning_details. When a reasoning
model (e.g. gpt-5-mini) returns reasoning_details without text content,
all_messages is empty, causing an IndexError.

Guard the access by initializing all_messages with the current args dict
when it is empty, so reasoning_details can be safely attached.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address review: buffer reasoning details for valid message payloads (#4384)

- Buffer pending reasoning details and attach to the next message with
  content/tool_calls, avoiding standalone reasoning-only messages.
- When reasoning is the only content, emit a message with empty content
  to satisfy Chat Completions schema requirements.
- Strengthen test assertions to verify text+reasoning co-location and
  that all messages with reasoning_details also have content or tool_calls.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix text_reasoning handling: always buffer and tighten tests (#4384)

- Always buffer reasoning into pending_reasoning instead of conditionally
  attaching to the previous message via fragile all_messages emptiness check
- Attach buffered reasoning to last message at end-of-loop when no subsequent
  content consumed it
- Assert exact content values (content == '' not in ('', None))
- Assert exact list lengths (== 1 not >= 1) for stronger regression guards
- Add test for reasoning before FunctionCallContent

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Apply pre-commit auto-fixes

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
dae3caa719 · 2026-03-03 16:13:24 +00:00
1,594 Commits
2025-10-30 20:29:01 +00:00
2025-04-28 12:54:43 -07:00
2025-04-28 12:54:42 -07:00

Microsoft Agent Framework

Welcome to Microsoft Agent Framework!

Microsoft Azure AI Foundry Discord MS Learn Documentation PyPI NuGet

Welcome to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration.

Watch the full Agent Framework introduction (30 min)

Watch the full Agent Framework introduction (30 min)

📋 Getting Started

📦 Installation

Python

pip install agent-framework --pre
# 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

📚 Documentation

Still have questions? Join our weekly office hours or ask questions in our Discord channel to get help from the team and other users.

Highlights

  • Graph-based Workflows: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
  • AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
  • DevUI: Interactive developer UI for agent development, testing, and debugging workflows

See the DevUI in action

See the DevUI in action (1 min)

💬 We want your feedback!

Quickstart

Basic Agent - Python

Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework

# pip install agent-framework --pre
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential


async def main():
    # Initialize a chat agent with Azure OpenAI Responses
    # the endpoint, deployment name, and api version can be set via environment variables
    # or they can be passed in directly to the AzureOpenAIResponsesClient constructor
    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"],
        # api_key=os.environ["AZURE_OPENAI_API_KEY"],  # Optional if using AzureCliCredential
        credential=AzureCliCredential(), # Optional, if using api_key
    ).as_agent(
        name="HaikuBot",
        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())

Basic Agent - .NET

Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

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

// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

Create a simple Agent, using Azure OpenAI Responses with token based auth, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
// dotnet add package Azure.Identity
// Use `az login` to authenticate with Azure CLI
using System.ClientModel.Primitives;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;

// Replace <resource> and gpt-4o-mini with your Azure OpenAI resource name and deployment name.
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") })
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

More Examples & Samples

Python

.NET

Contributor Resources

Important Notes

If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for 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.

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