* Python: Re-read env vars in configure_otel_providers and enable_instrumentation (#4119) Fix ENABLE_SENSITIVE_DATA and VS_CODE_EXTENSION_PORT env vars being ignored when load_dotenv() runs after module import. The module-level OBSERVABILITY_SETTINGS singleton cached env state at import time, and configure_otel_providers() / enable_instrumentation() never re-read from os.environ when parameters were None. Both functions now construct a fresh ObservabilitySettings() to pick up current env vars when explicit parameters are not provided, matching the existing behavior of the env_file_path branch. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback for #4119: avoid throwaway ObservabilitySettings - Add _read_bool_env/_read_int_env helpers to read env vars without constructing a full ObservabilitySettings (which calls create_resource()) - Replace ObservabilitySettings() in enable_instrumentation() and configure_otel_providers() else-branch with direct env reads - Add enable_console_exporters parameter to configure_otel_providers() for override parity with enable_sensitive_data and vs_code_extension_port - Propagate _resource and _executed_setup in the non-env_file_path branch - Make existing tests hermetic (clear VS_CODE_EXTENSION_PORT and ENABLE_CONSOLE_EXPORTERS env vars) - Add tests: enable_console_exporters env refresh, explicit param overrides for both enable_instrumentation() and configure_otel_providers() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address remaining review feedback for #4119 - Refresh enable_console_exporters in enable_instrumentation() for consistency with configure_otel_providers(), so env var changes after import are picked up by both public API functions - Make test_configure_otel_providers_reads_env_vs_code_port hermetic by clearing ENABLE_CONSOLE_EXPORTERS from the environment - Add test_enable_instrumentation_reads_env_console_exporters to cover the new refresh behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove unconditional enable_console_exporters overwrite from enable_instrumentation() (#4119) enable_instrumentation() is documented as not configuring exporters, so managing enable_console_exporters there was a leaky abstraction. The unconditional _read_bool_env call silently reset the value to False when ENABLE_CONSOLE_EXPORTERS was absent from env, clobbering any value previously set by configure_otel_providers(enable_console_exporters=True). - Remove the unconditional overwrite line from enable_instrumentation() - Replace test_enable_instrumentation_reads_env_console_exporters with test_enable_instrumentation_does_not_touch_console_exporters - Add regression test: enable_instrumentation() does not clobber a previously configured enable_console_exporters value - Add test: explicit enable_sensitive_data param still leaves enable_console_exporters untouched Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Welcome to Microsoft Agent Framework!
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)
📋 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
- Overview - High level overview of the framework
- Quick Start - Get started with a simple agent
- Tutorials - Step by step tutorials
- User Guide - In-depth user guide for building agents and workflows
- Migration from Semantic Kernel - Guide to migrate from Semantic Kernel
- Migration from AutoGen - Guide to migrate from AutoGen
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 (1 min)
- Python and C#/.NET Support: Full framework support for both Python and C#/.NET implementations with consistent APIs
- Observability: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- Multiple Agent Provider Support: Support for various LLM providers with more being added continuously
- Middleware: Flexible middleware system for request/response processing, exception handling, and custom pipelines
💬 We want your feedback!
- For bugs, please file a GitHub issue.
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
- Getting Started with Agents: progressive tutorial from hello-world to hosting
- Agent Concepts: deep-dive samples by topic (tools, middleware, providers, etc.)
- Getting Started with Workflows: workflow creation and integration with agents
.NET
- Getting Started with Agents: basic agent creation and tool usage
- Agent Provider Samples: samples showing different agent providers
- Workflow Samples: advanced multi-agent patterns and workflow orchestration
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.
