Merge branch 'main' into feature-foundry-agents

dotnet/src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj

@@ -4,11 +4,15 @@
     <TargetFrameworks>$(ProjectsTargetFrameworks)</TargetFrameworks>
     <TargetFrameworks Condition="'$(Configuration)' == 'Debug'">$(ProjectsDebugTargetFrameworks)</TargetFrameworks>
     <VersionSuffix>preview</VersionSuffix>
-    <IsPackable>false</IsPackable>
   </PropertyGroup>
 
   <Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
 
+  <PropertyGroup>
+    <!-- Disable packing until we are ready to release this as a nuget -->
+    <IsPackable>false</IsPackable>
+  </PropertyGroup>
+
   <PropertyGroup>
     <InjectSharedThrow>true</InjectSharedThrow>
   </PropertyGroup>

dotnet/src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj

@@ -6,15 +6,14 @@
     <Nullable>enable</Nullable>
     <RootNamespace>Microsoft.Agents.AI.DevUI</RootNamespace>
     <OutputType>Library</OutputType>
-    <Title>Microsoft Agent Framework Developer UI</Title>
-    <Description>Provides Microsoft Agent Framework support for developer UI.</Description>
     <EnableRequestDelegateGenerator>true</EnableRequestDelegateGenerator>
+    <VersionSuffix>preview</VersionSuffix>
     <!-- Suppress warnings for internal DevUI implementation -->
     <NoWarn>$(NoWarn);CS1591;CA1852;CA1050;RCS1037;RCS1036;RCS1124;RCS1021;RCS1146;RCS1211;CA2007;CA1308;IL2026;IL3050;CA1812</NoWarn>
   </PropertyGroup>
 
   <!-- Import nuget packaging properties -->
-  <Import Project="..\..\nuget\nuget-package.props" />
+  <Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
 
   <!-- Import frontend web assets build targets -->
   <Import Project="Microsoft.Agents.AI.DevUI.Frontend.targets" />
@@ -28,4 +27,10 @@
     <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
   </ItemGroup>
 
+  <PropertyGroup>
+    <!-- NuGet Package Settings -->
+    <Title>Microsoft Agent Framework Developer UI</Title>
+    <Description>Provides Microsoft Agent Framework support for developer UI.</Description>
+  </PropertyGroup>
+
 </Project>

dotnet/src/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj

@@ -6,13 +6,17 @@
     <RootNamespace>Microsoft.Agents.AI.Hosting.AGUI.AspNetCore</RootNamespace>
     <VersionSuffix>preview</VersionSuffix>
     <DefineConstants>$(DefineConstants);ASPNETCORE</DefineConstants>
-    <IsPackable>false</IsPackable>
     <InterceptorsNamespaces>$(InterceptorsNamespaces);Microsoft.AspNetCore.Http.Generated</InterceptorsNamespaces>
     <EnableRequestDelegateGenerator>true</EnableRequestDelegateGenerator>
   </PropertyGroup>
 
   <Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
 
+  <PropertyGroup>
+    <!-- Disable packing until we are ready to release this as a nuget -->
+    <IsPackable>false</IsPackable>
+  </PropertyGroup>
+
   <PropertyGroup>
     <!-- NuGet Package Settings -->
     <Title>Microsoft Agent Framework Hosting AG-UI ASP.NET Core</Title>

dotnet/src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj

@@ -4,7 +4,6 @@
     <TargetFrameworks>$(ProjectsTargetFrameworks)</TargetFrameworks>
     <TargetFrameworks Condition="'$(Configuration)' == 'Debug'">$(ProjectsDebugTargetFrameworks)</TargetFrameworks>
     <VersionSuffix>preview</VersionSuffix>
-    <!-- Disable packing until we are ready to release this as a nuget -->
   </PropertyGroup>
 
   <PropertyGroup>
@@ -14,6 +13,7 @@
 
   <Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
   <PropertyGroup>
+    <!-- Disable packing until we are ready to release this as a nuget -->
     <IsPackable>false</IsPackable>
   </PropertyGroup>
 

python/CHANGELOG.md

@@ -7,6 +7,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [1.0.0b251106] - 2025-11-06
+
+### Changed
+
+- **agent-framework-ag-ui**: export sample ag-ui agents ([#1927](https://github.com/microsoft/agent-framework/pull/1927))
+
 ## [1.0.0b251105] - 2025-11-05
 
 ### Added

python/packages/ag-ui/README.md

@@ -36,7 +36,7 @@ add_agent_framework_fastapi_endpoint(app, agent, "/")
 ## Documentation
 
 - **[Getting Started Tutorial](getting_started/)** - Step-by-step guide to building your first AG-UI server and client
-- **[Examples](examples/)** - Complete examples for AG-UI features
+- **[Examples](agent_framework_ag_ui_examples/)** - Complete examples for AG-UI features
 
 ## Features
 
@@ -64,7 +64,7 @@ The package uses a clean, orchestrator-based architecture:
 ## Next Steps
 
 1. **New to AG-UI?** Start with the [Getting Started Tutorial](getting_started/)
-2. **Want to see examples?** Check out the [Examples](examples/) for AG-UI features
+2. **Want to see examples?** Check out the [Examples](agent_framework_ag_ui_examples/) for AG-UI features
 
 ## License
 

python/packages/ag-ui/getting_started/README.md

@@ -629,7 +629,7 @@ Now that you understand the basics of AG-UI, you can:
 
 ## Additional Resources
 
-- [AG-UI Examples](../examples/README.md): Complete working examples for all 7 features
+- [AG-UI Examples](../agent_framework_ag_ui_examples/README.md): Complete working examples for all 7 features
 - [Agent Framework Documentation](../../core/README.md): Learn more about creating agents
 - [AG-UI Protocol Spec](https://docs.ag-ui.com/): Official protocol documentation
 

python/packages/ag-ui/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "agent-framework-ag-ui"
-version = "1.0.0b251105"
+version = "1.0.0b251106.post1"
 description = "AG-UI protocol integration for Agent Framework"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -40,8 +40,7 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [tool.hatch.build.targets.wheel]
-packages = ["agent_framework_ag_ui"]
-force-include = { "examples" = "agent_framework_ag_ui_examples" }
+packages = ["agent_framework_ag_ui", "agent_framework_ag_ui_examples"]
 
 [tool.pytest.ini_options]
 asyncio_mode = "auto"

python/samples/getting_started/threads/README.md

@@ -7,5 +7,14 @@ This folder contains examples demonstrating different ways to manage conversatio
 | File | Description |
 |------|-------------|
 | [`custom_chat_message_store_thread.py`](custom_chat_message_store_thread.py) | Demonstrates how to implement a custom `ChatMessageStore` for persisting conversation history. Shows how to create a custom store with serialization/deserialization capabilities and integrate it with agents for thread management across multiple sessions. |
-| [`suspend_resume_thread.py`](suspend_resume_thread.py) | Shows how to suspend and resume conversation threads, allowing you to save the state of a conversation and continue it later. This is useful for long-running conversations or when you need to persist conversation state across application restarts. |
 | [`redis_chat_message_store_thread.py`](redis_chat_message_store_thread.py) | Comprehensive examples of using the Redis-backed `RedisChatMessageStore` for persistent conversation storage. Covers basic usage, user session management, conversation persistence across app restarts, thread serialization, and automatic message trimming. Requires Redis server and demonstrates production-ready patterns for scalable chat applications. |
+| [`suspend_resume_thread.py`](suspend_resume_thread.py) | Shows how to suspend and resume conversation threads, comparing service-managed threads (Azure AI) with in-memory threads (OpenAI). Demonstrates saving conversation state and continuing it later, useful for long-running conversations or persisting state across application restarts. |
+
+## Environment Variables
+
+Make sure to set the following environment variables before running the examples:
+
+- `OPENAI_API_KEY`: Your OpenAI API key (required for all samples)
+- `OPENAI_CHAT_MODEL_ID`: The OpenAI model to use (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`) (required for all samples)
+- `AZURE_AI_PROJECT_ENDPOINT`: Azure AI Project endpoint URL (required for service-managed thread examples)
+- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: The name of your model deployment (required for service-managed thread examples)

python/samples/getting_started/threads/custom_chat_message_store_thread.py

@@ -8,6 +8,14 @@ from agent_framework import ChatMessage, ChatMessageStoreProtocol
 from agent_framework._threads import ChatMessageStoreState
 from agent_framework.openai import OpenAIChatClient
 
+"""
+Custom Chat Message Store Thread Example
+
+This sample demonstrates how to implement and use a custom chat message store
+for thread management, allowing you to persist conversation history in your
+preferred storage solution (database, file system, etc.).
+"""
+
 
 class CustomChatMessageStore(ChatMessageStoreProtocol):
     """Implementation of custom chat message store.
@@ -24,13 +32,22 @@ class CustomChatMessageStore(ChatMessageStoreProtocol):
     async def list_messages(self) -> list[ChatMessage]:
         return self._messages
 
-    async def deserialize_state(self, serialized_store_state: Any, **kwargs: Any) -> None:
+    @classmethod
+    async def deserialize(cls, serialized_store_state: Any, **kwargs: Any) -> "CustomChatMessageStore":
+        """Create a new instance from serialized state."""
+        store = cls()
+        await store.update_from_state(serialized_store_state, **kwargs)
+        return store
+
+    async def update_from_state(self, serialized_store_state: Any, **kwargs: Any) -> None:
+        """Update this instance from serialized state."""
         if serialized_store_state:
             state = ChatMessageStoreState.from_dict(serialized_store_state, **kwargs)
             if state.messages:
                 self._messages.extend(state.messages)
 
-    async def serialize_state(self, **kwargs: Any) -> Any:
+    async def serialize(self, **kwargs: Any) -> Any:
+        """Serialize this store's state."""
         state = ChatMessageStoreState(messages=self._messages)
         return state.to_dict(**kwargs)
 
@@ -42,8 +59,8 @@ async def main() -> None:
     # OpenAI Chat Client is used as an example here,
     # other chat clients can be used as well.
     agent = OpenAIChatClient().create_agent(
-        name="Joker",
-        instructions="You are good at telling jokes.",
+        name="CustomBot",
+        instructions="You are a helpful assistant that remembers our conversation.",
         # Use custom chat message store.
         # If not provided, the default in-memory store will be used.
         chat_message_store_factory=CustomChatMessageStore,
@@ -53,7 +70,7 @@ async def main() -> None:
     thread = agent.get_new_thread()
 
     # Respond to user input.
-    query = "Tell me a joke about a pirate."
+    query = "Hello! My name is Alice and I love pizza."
     print(f"User: {query}")
     print(f"Agent: {await agent.run(query, thread=thread)}\n")
 
@@ -67,7 +84,7 @@ async def main() -> None:
     resumed_thread = await agent.deserialize_thread(serialized_thread)
 
     # Respond to user input.
-    query = "Now tell the same joke in the voice of a pirate, and add some emojis to the joke."
+    query = "What do you remember about me?"
     print(f"User: {query}")
     print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n")
 

python/samples/getting_started/threads/redis_chat_message_store_thread.py

@@ -8,6 +8,14 @@ from agent_framework import AgentThread
 from agent_framework.openai import OpenAIChatClient
 from agent_framework.redis import RedisChatMessageStore
 
+"""
+Redis Chat Message Store Thread Example
+
+This sample demonstrates how to use Redis as a chat message store for thread
+management, enabling persistent conversation history storage across sessions
+with Redis as the backend data store.
+"""
+
 
 async def example_manual_memory_store() -> None:
     """Basic example of using Redis chat message store."""

python/samples/getting_started/threads/suspend_resume_thread.py

@@ -2,38 +2,51 @@
 
 import asyncio
 
+from agent_framework.azure import AzureAIAgentClient
 from agent_framework.openai import OpenAIChatClient
+from azure.identity.aio import AzureCliCredential
+
+"""
+Thread Suspend and Resume Example
+
+This sample demonstrates how to suspend and resume conversation threads, comparing
+service-managed threads (Azure AI) with in-memory threads (OpenAI) for persistent
+conversation state across sessions.
+"""
 
 
 async def suspend_resume_service_managed_thread() -> None:
     """Demonstrates how to suspend and resume a service-managed thread."""
     print("=== Suspend-Resume Service-Managed Thread ===")
 
-    # OpenAI Chat Client is used as an example here,
-    # other chat clients can be used as well.
-    agent = OpenAIChatClient().create_agent(name="Joker", instructions="You are good at telling jokes.")
+    # AzureAIAgentClient supports service-managed threads.
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIAgentClient(async_credential=credential).create_agent(
+            name="MemoryBot", instructions="You are a helpful assistant that remembers our conversation."
+        ) as agent,
+    ):
+        # Start a new thread for the agent conversation.
+        thread = agent.get_new_thread()
 
-    # Start a new thread for the agent conversation.
-    thread = agent.get_new_thread()
+        # Respond to user input.
+        query = "Hello! My name is Alice and I love pizza."
+        print(f"User: {query}")
+        print(f"Agent: {await agent.run(query, thread=thread)}\n")
 
-    # Respond to user input.
-    query = "Tell me a joke about a pirate."
-    print(f"User: {query}")
-    print(f"Agent: {await agent.run(query, thread=thread)}\n")
+        # Serialize the thread state, so it can be stored for later use.
+        serialized_thread = await thread.serialize()
 
-    # Serialize the thread state, so it can be stored for later use.
-    serialized_thread = await thread.serialize()
+        # The thread can now be saved to a database, file, or any other storage mechanism and loaded again later.
+        print(f"Serialized thread: {serialized_thread}\n")
 
-    # The thread can now be saved to a database, file, or any other storage mechanism and loaded again later.
-    print(f"Serialized thread: {serialized_thread}\n")
+        # Deserialize the thread state after loading from storage.
+        resumed_thread = await agent.deserialize_thread(serialized_thread)
 
-    # Deserialize the thread state after loading from storage.
-    resumed_thread = await agent.deserialize_thread(serialized_thread)
-
-    # Respond to user input.
-    query = "Now tell the same joke in the voice of a pirate, and add some emojis to the joke."
-    print(f"User: {query}")
-    print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n")
+        # Respond to user input.
+        query = "What do you remember about me?"
+        print(f"User: {query}")
+        print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n")
 
 
 async def suspend_resume_in_memory_thread() -> None:
@@ -42,13 +55,15 @@ async def suspend_resume_in_memory_thread() -> None:
 
     # OpenAI Chat Client is used as an example here,
     # other chat clients can be used as well.
-    agent = OpenAIChatClient().create_agent(name="Joker", instructions="You are good at telling jokes.")
+    agent = OpenAIChatClient().create_agent(
+        name="MemoryBot", instructions="You are a helpful assistant that remembers our conversation."
+    )
 
     # Start a new thread for the agent conversation.
     thread = agent.get_new_thread()
 
     # Respond to user input.
-    query = "Tell me a joke about a pirate."
+    query = "Hello! My name is Alice and I love pizza."
     print(f"User: {query}")
     print(f"Agent: {await agent.run(query, thread=thread)}\n")
 
@@ -62,7 +77,7 @@ async def suspend_resume_in_memory_thread() -> None:
     resumed_thread = await agent.deserialize_thread(serialized_thread)
 
     # Respond to user input.
-    query = "Now tell the same joke in the voice of a pirate, and add some emojis to the joke."
+    query = "What do you remember about me?"
     print(f"User: {query}")
     print(f"Agent: {await agent.run(query, thread=resumed_thread)}\n")