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chore: import upstream snapshot with attribution
2026-07-13 13:39:25 +08:00

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# Samples Structure & Design Choices — .NET
> This file documents the structure and conventions of the .NET samples so that
> agents (AI or human) can maintain them without rediscovering decisions.
## Directory layout
```
dotnet/samples/
├── 01-get-started/ # Progressive tutorial (steps 0106)
│ ├── 01_hello_agent/ # Create and run your first agent
│ ├── 02_add_tools/ # Add function tools
│ ├── 03_multi_turn/ # Multi-turn conversations with AgentSession
│ ├── 04_memory/ # Agent memory with AIContextProvider
│ ├── 05_first_workflow/ # Build a workflow with executors and edges
│ └── 06_host_your_agent/ # Host your agent via Azure Functions
├── 02-agents/ # Deep-dive concept samples
│ ├── Agents/ # Core agent patterns (tools, structured output,
│ │ # conversations, middleware, plugins, MCP, etc.)
│ ├── AgentProviders/ # Provider-grouped samples
│ │ ├── a2a/ # A2A provider sample
│ │ ├── anthropic/ # Anthropic provider samples
│ │ ├── azure/ # Azure/OpenAI/Foundry model provider samples
│ │ ├── custom/ # Custom agent implementation sample
│ │ ├── foundry/ # Microsoft Foundry agent samples
│ │ ├── github-copilot/ # GitHub Copilot provider sample
│ │ ├── google-gemini/ # Google Gemini provider sample
│ │ ├── ollama/ # Ollama provider sample
│ │ ├── onnx/ # ONNX Runtime provider sample
│ │ └── openai/ # OpenAI provider samples
│ ├── AgentOpenTelemetry/ # OpenTelemetry integration
│ ├── AgentSkills/ # Agent skills patterns
│ ├── AgentWithMemory/ # Memory providers (chat history, Mem0, Foundry)
│ ├── AgentWithRAG/ # RAG patterns (text, vector store, Foundry)
│ ├── AGUI/ # AG-UI protocol samples
│ ├── DeclarativeAgents/ # Declarative agent definitions
│ ├── DevUI/ # DevUI samples
│ └── ModelContextProtocol/ # MCP server/client patterns
├── 03-workflows/ # Workflow patterns
│ ├── _StartHere/ # Introductory workflow samples
│ ├── Agents/ # Agents in workflows
│ ├── Checkpoint/ # Checkpointing & resume
│ ├── Concurrent/ # Concurrent execution
│ ├── ConditionalEdges/ # Conditional routing
│ ├── Declarative/ # YAML-based workflows
│ ├── HumanInTheLoop/ # HITL patterns
│ ├── Loop/ # Loop patterns
│ ├── Observability/ # Workflow telemetry
│ ├── SharedStates/ # State isolation
│ └── Visualization/ # Workflow visualization
├── 04-hosting/ # Deployment & hosting
│ ├── A2A/ # Agent-to-Agent protocol
│ └── DurableAgents/ # Durable task framework
│ ├── AzureFunctions/ # Azure Functions hosting
│ └── ConsoleApps/ # Console app hosting
├── 05-end-to-end/ # Complete applications
│ ├── A2AClientServer/ # A2A client/server demo
│ ├── AgentWebChat/ # Aspire-based web chat
│ ├── AgentWithPurview/ # Purview integration
│ ├── AGUIClientServer/ # AG-UI client/server demo
│ ├── AGUIWebChat/ # AG-UI web chat
│ ├── HostedAgents/ # Hosted agent scenarios
│ └── M365Agent/ # Microsoft 365 agent
```
## Design principles
1. **Progressive complexity**: Sections 01→05 build from "hello world" to
production. Within 01-get-started, projects are numbered 0106 and each step
adds exactly one concept.
2. **One concept per project** in 01-get-started. Each step is a standalone
C# project with a single `Program.cs` file.
3. **Workflows preserved**: 03-workflows/ keeps the upstream folder names
intact. Do not rename or restructure workflow samples.
4. **Per-project structure**: Each sample is a separate .csproj. Shared build
configuration is inherited from `Directory.Build.props`.
## Default provider
All canonical samples (01-get-started) use **Microsoft Foundry** via `AIProjectClient.AsAIAgent()` with `DefaultAzureCredential`:
```csharp
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT")
?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var model = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
AIAgent agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: model, instructions: "...", name: "...");
```
Environment variables:
- `FOUNDRY_PROJECT_ENDPOINT` — Your Foundry project endpoint
- `FOUNDRY_MODEL` — Model name (defaults to `gpt-5.4-mini`)
For authentication, run `az login` before running samples.
**Note:** Use `FoundryAgent` only when demonstrating Foundry-managed (prompt) agents specifically — see `02-agents/AgentsWithFoundry/`. For all other samples, use `AIProjectClient.AsAIAgent()`.
**Note:** For samples demonstrating other providers (Azure OpenAI, OpenAI, Anthropic, etc.), see `02-agents/AgentProviders/`.
## Snippet tags for docs integration
Samples embed named snippet regions for future `:::code` integration:
```csharp
// <snippet_name>
code here
// </snippet_name>
```
## Building and running
All samples use project references to the framework source. To build and run:
```bash
cd dotnet/samples/01-get-started/01_hello_agent
dotnet run
```
## Current API notes
- `AIAgent` is the primary agent abstraction (created via `ChatClient.AsAIAgent(...)`)
- `AgentSession` manages multi-turn conversation state
- `AIContextProvider` injects memory and context
- Prefer `AIProjectClient.AsAIAgent(...)` for Foundry-backed canonical samples
- Azure Functions hosting uses `ConfigureDurableAgents(options => options.AddAIAgent(agent))`
- Workflows use `WorkflowBuilder` with `Executor<TIn, TOut>` and edge connections