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.NET: Nuget update (#987)
* Update README with enhanced highlights and streamlined getting started - Added banner image for professional branding - Updated highlights section to focus on key features: multi-agent orchestration, workflows, AF Labs, DevUI, Python/C# support, observability, multiple providers, and middleware - Streamlined getting started section with direct links to comprehensive guides - Fixed file paths in samples section and removed outdated Azure integration reference - Improved overall structure and readability * Update NuGet package documentation and add framework icon - Added comprehensive high-level summary for Microsoft Agent Framework - Included key features highlighting multi-agent orchestration, workflows, observability, and cross-platform support - Added agent-framework-icon.png for NuGet package branding * Update README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update dotnet/nuget/NUGET.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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# Microsoft Agent Framework
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## Welcome to the Private Preview of Agent Framework!
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# Welcome to Microsoft Agent Framework!
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[](https://discord.gg/b5zjErwbQM)
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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.
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### 📋 Important Setup Information
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**Package Availability:** Public PyPI and NuGet packages are not yet available. You have two options:
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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.
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**Option 1: Run samples directly from this repository (no package installation needed)**
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- Clone this repository
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- For .NET: Run samples with `dotnet run` from any sample directory (e.g., `dotnet/samples/GettingStarted/Agents/Agent_Step01_Running`)
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- For Python: Run samples from any sample directory (e.g., [`python/samples/getting_started/minimal_sample.py`](python/samples/getting_started/minimal_sample.py)) after setting up the local dev environment following this [guide](python/DEV_SETUP.md).
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### 📋 Getting Started
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**Option 2: Install packages in your own project**
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- **[.NET Getting Started Guide](./user-documentation-dotnet/getting-started/README.md)** - Instructions for using nightly packages
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- **[Python Package Installation Guide](./user-documentation-python/getting-started/package_installation.md)** - Install packages directly from GitHub
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**Quick Installation:**
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- **Python**: `pip install agent-framework`
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- **.NET**: `dotnet add package Microsoft.Agents.AI`
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**Stay Updated:** This is an active project - sync your local repository regularly to get the latest updates.
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**Complete Getting Started Guides:**
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- **[.NET Getting Started Guide](./user-documentation-dotnet/getting-started/README.md)** - Complete setup and usage instructions
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- **[Python Getting Started Guide](./user-documentation-python/getting-started/package_installation.md)** - Installation and first steps
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### ✨ **Highlights**
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- **Multi-Agent Orchestration**: Coordinate multiple agents with sequential, concurrent, group chat, and handoff patterns
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- [Python samples](./python/samples/getting_started/workflow/orchestration/) | [.NET samples](./dotnet/samples/GettingStarted/AgentOrchestration/)
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- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
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- [Python workflows](./python/samples/getting_started/workflow/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/)
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- **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
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- [Labs directory](./python/packages/lab/)
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- **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
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- [DevUI package](./python/packages/devui/)
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- **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
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- [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
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- **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
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- [Python observability](./python/samples/getting_started/workflow/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/)
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- **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
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- [Python examples](./python/samples/getting_started/agents/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/)
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- **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
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- [Python middleware](./python/samples/getting_started/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/)
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### 💬 **We want your feedback!**
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- For bugs, please file a [GitHub issue](https://github.com/microsoft/agent-framework/issues).
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- For feedback and suggestions for the team, please fill out [this survey](https://forms.office.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR9huAe5pW55CqgnnimXONJJUMlVMUzdCN1ZGOURXODlBSVJOSkxERVNCNS4u).
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### ✨ **Highlights**
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- Flexible Agent Framework: build, orchestrate, and deploy AI agents and workflows
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- Multi-Agent Orchestration: group chat, sequential, concurrent, and handoff patterns
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- Graph-based Workflows: connect agents and deterministic functions using data flows with streaming, checkpointing, time-travel, and Human-in-the-loop.
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- Plugin Ecosystem: extend with native functions, OpenAPI, Model Context Protocol (MCP), and more
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- LLM Support: OpenAI, Azure OpenAI, Azure AI Foundry, and more
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- Runtime Support: in-process and distributed agent execution
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- Multimodal: text, vision, and function calling
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- Cross-Platform: .NET and Python implementations
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Below are the basics for each language implementation. For more details on python see [here](./python/README.md) and for .NET see [here](./dotnet/README.md).
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## More Examples & Samples
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### Python
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- [Getting Started with Agents](./python/samples/getting_started/agents): basic agent creation and tool usage
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- [Chat Client Examples](./python/samples/getting_started/chat_client): direct chat client usage patterns
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- [Azure Integration](./python/packages/azure): Azure OpenAI and AI Foundry integration
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- [Getting Started with Workflows](./python/samples/getting_started/workflow): basic workflow creation and integration with agents
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### .NET
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- [Getting Started with Agents](./dotnet/samples/GettingStarted/Agents): basic agent creation and tool usage
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- [Agent Provider Samples](./dotnet/samples/GettingStarted/AgentProviders): samples showing different agent providers
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- [Orchestration Samples](./dotnet/samples/GettingStarted/AgentOrchestration): advanced multi-agent patterns
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- [Workflow Samples](./dotnet/samples/GettingStarted/Workflows): advanced multi-agent patterns and workflow orchestration
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## Agent Framework Documentation
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- [Agent Framework Repository](https://github.com/microsoft/agent-framework)
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- [Design Documents](./docs/design)
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- [Architectural Decision Records](./docs/decisions)
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- Learn docs are coming soon.
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- [MSFT Learn Docs](https://learn.microsoft.com/agent-framework/overview/agent-framework-overview)
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# About Microsoft Agent Framework
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To be filled in.
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Microsoft Agent Framework is a comprehensive .NET library for building, orchestrating, and deploying AI agents and multi-agent workflows. The framework provides everything from simple chat agents to complex multi-agent systems with graph-based orchestration capabilities.
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## Key Features
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- **Multi-Agent Orchestration**: Coordinate multiple agents using sequential, concurrent, group chat, and handoff patterns
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- **Graph-based Workflows**: Connect agents and deterministic functions with streaming, checkpointing, and human-in-the-loop capabilities
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- **Multiple Provider Support**: Seamlessly integrate with various LLM providers with more being added continuously
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- **Extensible Middleware**: Flexible request/response processing with custom pipelines and exception handling
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- **Built-in Observability**: OpenTelemetry integration for distributed tracing, monitoring, and debugging
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- **Cross-Platform**: Compatible with .NET 8.0, .NET Standard 2.0, and .NET Framework for broad deployment options
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Whether you're building simple AI assistants or complex multi-agent systems, Microsoft Agent Framework provides the tools and abstractions needed to create robust, scalable AI applications in .NET.
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# Getting Started ⚡
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- Learn more at the [documentation site](https://aka.ms/TBD).
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- Join the [Discord community](https://aka.ms/TBD).
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- Follow the team on [Semantic Kernel blog](https://aka.ms/TBD).
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- Learn more at the [documentation site](https://learn.microsoft.com/agent-framework/overview/agent-framework-overview).
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- Join the [Discord community](https://discord.gg/b5zjErwbQM).
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- Follow the team on [Semantic Kernel blog](https://devblogs.microsoft.com/semantic-kernel/).
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- Check out the [GitHub repository](https://github.com/microsoft/agent-framework) for the latest updates.
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