Evan Mattson dd3d085539 Python: Include reasoning messages in MESSAGES_SNAPSHOT events (#4844)
* Include reasoning messages in MESSAGES_SNAPSHOT (#4843)

FlowState now tracks reasoning messages emitted during a run.
_emit_text_reasoning() persists reasoning (including encrypted_value)
into flow.reasoning_messages, and _build_messages_snapshot() appends
them to the final MESSAGES_SNAPSHOT event.

Changes:
- Add reasoning_messages field to FlowState
- Update _emit_text_reasoning() to accept optional flow parameter
- Include reasoning_messages in _build_messages_snapshot()
- Add 'reasoning' to ALLOWED_AGUI_ROLES so normalize_agui_role()
  preserves the role through snapshot round-trips
- Skip reasoning messages in agui_messages_to_agent_framework() since
  they are UI-only state and should not be forwarded to LLM providers
- Add regression tests for snapshot emission, encrypted value
  preservation, and multi-turn round-trip with reasoning

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

* Python: Include reasoning messages in MESSAGES_SNAPSHOT events

Fixes #4843

* Fix PR review feedback for reasoning persistence (#4843)

- Accumulate reasoning text per message_id (append deltas) instead of
  storing only the current chunk, matching flow.accumulated_text pattern
- Use camelCase encryptedValue in snapshot JSON to match AG-UI protocol
  conventions (toolCallId, encryptedValue)
- Normalize snake_case encrypted_value to encryptedValue in
  agui_messages_to_snapshot_format for input compatibility
- Update normalize_agui_role docstring to include reasoning role
- Add tests for incremental reasoning accumulation and key normalization

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

* Address review feedback for #4843: Python: agent-framework-ag-ui: include reasoning messages in MESSAGES_SNAPSHOT

---------

Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
dd3d085539 · 2026-03-26 05:56:10 +00:00
1,749 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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