Amit Mukherjee fae36b36f2 Python: Add OpenTelemetry instrumentation to ClaudeAgent (#4278) (#4326)
* Python: Add OpenTelemetry instrumentation to ClaudeAgent (#4278)

Add inline telemetry to ClaudeAgent.run() so that enable_instrumentation()
emits invoke_agent spans and metrics. Covers both streaming and
non-streaming paths using the same observability helpers as
AgentTelemetryLayer. Adds 5 unit tests for telemetry behavior.

Co-Authored-By: amitmukh <amimukherjee@microsoft.com>

* Address PR review feedback for ClaudeAgent telemetry

- Add justification comment for private observability API imports
- Pass system_instructions to capture_messages for system prompt capture
- Use monkeypatch instead of try/finally for test global state isolation

Co-Authored-By: amitmukh <amitmukh@users.noreply.github.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Adopt AgentTelemetryLayer instead of inline telemetry

Restructure ClaudeAgent to inherit from AgentTelemetryLayer via a
_ClaudeAgentRunImpl mixin, eliminating duplicated telemetry code and
private API imports.

MRO: ClaudeAgent → AgentTelemetryLayer → _ClaudeAgentRunImpl → BaseAgent

- Remove inline _run_with_telemetry / _run_with_telemetry_stream methods
- Remove private observability helper imports (_capture_messages, etc.)
- Add default_options property mapping system_prompt → instructions
- Net -105 lines by reusing core telemetry layer

Co-Authored-By: amitmukh <amitmukh@users.noreply.github.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Fix mypy: align _ClaudeAgentRunImpl.run() signature with AgentTelemetryLayer.run()

Remove explicit `options` parameter from mixin's run() signature and
extract it from **kwargs to match AgentTelemetryLayer's signature.
Also align overload return types (ResponseStream, Awaitable) to match.

Co-Authored-By: Claude <noreply@anthropic.com>

* Introduce RawClaudeAgent following framework's RawAgent/Agent pattern

Replace private _ClaudeAgentRunImpl mixin with public RawClaudeAgent
class that contains all core logic (init, run, lifecycle, tools).
ClaudeAgent becomes a thin wrapper that adds AgentTelemetryLayer.

- RawClaudeAgent(BaseAgent): full implementation without telemetry
- ClaudeAgent(AgentTelemetryLayer, RawClaudeAgent): adds OTel tracing
- Export RawClaudeAgent from package __init__.py

Users who want to skip telemetry or provide their own can use
RawClaudeAgent directly.

Co-Authored-By: Claude <noreply@anthropic.com>

* Address review nits: trim RawClaudeAgent docstring, fix import paths

- Simplify RawClaudeAgent docstring to a single basic example (not the
  primary entry point for most users)
- Use agent_framework.anthropic import path in docstrings instead of
  direct agent_framework_claude path
- Add RawClaudeAgent to agent_framework.anthropic lazy re-exports

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Amit Mukherjee <amimukherjee@microsoft.com>
Co-authored-by: amitmukh <amitmukh@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
fae36b36f2 · 2026-03-03 20:12:21 +00:00
1,598 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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