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https://github.com/microsoft/agent-framework.git
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Yuge Zhang
205cd700c8
* first commit to tau2-bench * tau2-bench agent * tau2 agent * add condition * checkpoint * bug fix * add tests * fix tests * add comments * add comments * minor fix * fix * batch test script * . * init.bak -> init.py * fix mypy * update readme * fix env * remove temp files * setup tests * fix gaia tasks * fix tau2 tests * fix coverage * fix default version * update cookiecutter template --------- Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
205cd700c8
·
2025-09-21 23:08:45 +00:00
370 Commits
Microsoft Agent Framework
Welcome to the Private Preview of Agent Framework!
You're getting early access 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.
📋 Important Setup Information
Package Availability: Public PyPI and NuGet packages are not yet available. You have two options:
Option 1: Run samples directly from this repository (no package installation needed)
- Clone this repository
- For .NET: Run samples with
dotnet runfrom any sample directory (e.g.,dotnet/samples/GettingStarted/Agents/Agent_Step01_Running) - For Python: Run samples from any sample directory (e.g.,
python/samples/getting_started/minimal_sample.py) after setting up the local dev environment following this guide.
Option 2: Install packages in your own project
- .NET Getting Started Guide - Instructions for using nightly packages
- Python Package Installation Guide - Install packages directly from GitHub
Stay Updated: This is an active project - sync your local repository regularly to get the latest updates.
💬 We want your feedback!
- For bugs, please file a GitHub issue.
- For feedback and suggestions for the team, please fill out this survey.
✨ Highlights
- Flexible Agent Framework: build, orchestrate, and deploy AI agents and workflows
- Multi-Agent Orchestration: group chat, sequential, concurrent, and handoff patterns
- Graph-based Workflows: connect agents and deterministic functions using data flows with streaming, checkpointing, time-travel, and Human-in-the-loop.
- Plugin Ecosystem: extend with native functions, OpenAPI, Model Context Protocol (MCP), and more
- LLM Support: OpenAI, Azure OpenAI, Azure AI Foundry, and more
- Runtime Support: in-process and distributed agent execution
- Multimodal: text, vision, and function calling
- Cross-Platform: .NET and Python implementations
Below are the basics for each language implementation. For more details on python see here and for .NET see here.
More Examples & Samples
Python
- Getting Started with Agents: basic agent creation and tool usage
- Chat Client Examples: direct chat client usage patterns
- Azure Integration: Azure OpenAI and AI Foundry integration
- Getting Started with Workflows: basic 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
- Orchestration Samples: advanced multi-agent patterns
Agent Framework Documentation
- Python documentation
- DotNet documentation
- Agent Framework Repository
- Design Documents
- Architectural Decision Records
- Learn docs are coming soon.