Matthias Howell
8e1998ddcb
* Adds Valkey to chat message history * Address review: switch to Valkey.Glide, add options class, remove context provider - Switch from StackExchange.Redis to Valkey.Glide 1.1.0 (official Valkey .NET client) - Extract optional params into ValkeyChatHistoryProviderOptions - Add JsonSerializerOptions support, remove [RequiresUnreferencedCode] - Make MaxMessages/MaxMessagesToRetrieve readonly via options - Remove ValkeyContextProvider (overlaps with ChatHistoryMemoryProvider + MEVD) - Remove ValkeyProviderScope (only used by context provider) - Remove connection string constructors (caller manages IConnectionMultiplexer) - Update samples to use new API and gpt-5.4-mini * Use type-safe JsonSerializer overloads, remove suppress attributes Use JsonSerializerOptions.GetTypeInfo() for Serialize/Deserialize calls to enable NativeAOT/trimming compatibility without suppress attributes. Default to AgentAbstractionsJsonUtilities.DefaultOptions when no options provided. Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Update READMEs: remove context provider references Remove ValkeyContextProvider and long-term memory references from sample READMEs since the context provider was removed from this PR. Simplify Valkey server requirements (no search module needed for chat history). Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Apply suggestion from @westey-m * Fix formatting (dotnet format) Signed-off-by: Matthias Howell <matthias.howell@improving.com> * Update dotnet/src/Microsoft.Agents.AI.Valkey/Microsoft.Agents.AI.Valkey.csproj Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com> --------- Signed-off-by: Matthias Howell <matthias.howell@improving.com> Co-authored-by: Matthias Howell <matthias.howell@yoppworks.com> Co-authored-by: westey <164392973+westey-m@users.noreply.github.com> Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
Agent Framework Samples
The agent framework samples are designed to help you get started with building AI-powered agents from various providers.
The Agent Framework supports building agents using various inference and inference-style services.
All these are supported using the single ChatClientAgent class.
The Agent Framework also supports creating proxy agents, that allow accessing remote agents as if they
were local agents. These are supported using various AIAgent subclasses.
Sample Structure
| Folder | Description |
|---|---|
01-get-started/ |
Progressive tutorial: hello agent → hosting |
02-agents/ |
Deep-dive by concept: tools, middleware, providers, orchestrations |
03-workflows/ |
Workflow patterns: sequential, concurrent, state, declarative |
04-hosting/ |
Deployment: Azure Functions, Durable Tasks |
05-end-to-end/ |
Full applications, evaluation, demos |
Getting Started
Start with 01-get-started/ and work through the numbered files:
- 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
Additional Samples
Some additional samples of note include:
- Agents: Basic steps to get started with the agent framework.
These samples demonstrate the fundamental concepts and functionalities of the agent framework when using the
AIAgentand can be used with any underlying service that provides anAIAgentimplementation. - Agent Providers: Shows how to create an AIAgent instance for a selection of providers.
- Agent Telemetry: Demo which showcases the integration of OpenTelemetry with the Microsoft Agent Framework using Azure OpenAI and .NET Aspire Dashboard for telemetry visualization.
- Durable Agents - Azure Functions: Samples for using the Microsoft Agent Framework with Azure Functions via the durable task extension.
- Durable Agents - Console Apps: Samples demonstrating durable agents in console applications.
Migration from Semantic Kernel
If you are migrating from Semantic Kernel to the Microsoft Agent Framework, the following resources provide guidance and side-by-side examples to help you transition your existing agents, tools, and orchestration patterns.
The migration samples map Semantic Kernel primitives (such as ChatCompletionAgent and Team orchestrations) to their Agent Framework equivalents (such as ChatClientAgent and workflow builders).
For an in-depth migration guide, see the official migration documentation.
Prerequisites
For prerequisites see each set of samples for their specific requirements.