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Microsoft Agent Framework
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
- Getting Started with Workflows: (Coming soon) basic workflow creation and integration with agents
Agent Framework Documentation
- Python documentation
- DotNet documentation
- Agent Framework Repository
- Design Documents
- Architectural Decision Records
- Learn docs are coming soon.