Add support for Deferred Functions

.gitignore

@@ -18,7 +18,7 @@ venv.bak/
 .dmypy.json
 dmypy.json
 
-.copilot-instructions.md
+private/
 
 # other
 .DS_STORE
@@ -30,6 +30,7 @@ ref/
 py.typed
 CLAUDE.md
 
+.copilot-instructions.md
 .env.claude/
 .claude/
 

examples/a2a-test/src/main.py

@@ -180,7 +180,11 @@ async def location_handler(params: LocationParams) -> str:
             parts=[Part(root=TextPart(kind="text", text="Please provide a location"))],
         )
     else:
-        return result.response.content if result.response.content else "No weather information available."
+        return (
+            result.response.content
+            if result.response and result.response.content
+            else "No weather information available."
+        )
 
 
 # A2A Server Message Event Handler
@@ -206,7 +210,7 @@ async def handle_a2a_message(message: A2AMessageEvent) -> None:
         await respond(result)
 
 
-async def handler(message: str) -> ModelMessage:
+async def handler(message: str) -> ModelMessage | None:
     # Now we can send the message to the prompt and it will decide if
     # the a2a agent should be used or not and also manages contacting the agent
     result = await prompt.send(message)
@@ -219,7 +223,7 @@ async def handle_message(ctx: ActivityContext[MessageActivity]):
     await ctx.reply(TypingActivityInput())
 
     result = await handler(ctx.activity.text)
-    if result.content:
+    if result and result.content:
         await ctx.send(result.content)
 
 

examples/ai-test/src/handlers/function_calling.py

@@ -68,7 +68,7 @@ async def handle_pokemon_search(model: AIModel, ctx: ActivityContext[MessageActi
         input=ctx.activity.text, instructions="You are a helpful assistant that can look up Pokemon for the user."
     )
 
-    if chat_result.response.content:
+    if chat_result.response and chat_result.response.content:
         message = MessageActivityInput(text=chat_result.response.content).add_ai_generated()
         await ctx.send(message)
     else:
@@ -129,7 +129,7 @@ async def handle_multiple_functions(model: AIModel, ctx: ActivityContext[Message
         ),
     )
 
-    if chat_result.response.content:
+    if chat_result.response and chat_result.response.content:
         message = MessageActivityInput(text=chat_result.response.content).add_ai_generated()
         await ctx.send(message)
     else:

examples/ai-test/src/handlers/memory_management.py

@@ -39,7 +39,7 @@ async def handle_stateful_conversation(model: AIModel, ctx: ActivityContext[Mess
         input=ctx.activity.text, instructions="You are a helpful assistant that remembers our previous conversation."
     )
 
-    if chat_result.response.content:
+    if chat_result.response and chat_result.response.content:
         message = MessageActivityInput(text=chat_result.response.content).add_ai_generated()
         await ctx.send(message)
     else:

examples/ai-test/src/main.py

@@ -68,7 +68,7 @@ async def handle_simple_chat(ctx: ActivityContext[MessageActivity]):
         input=ctx.activity.text, instructions="You are a friendly assistant who talks like a pirate"
     )
 
-    if chat_result.response.content:
+    if chat_result.response and chat_result.response.content:
         message = MessageActivityInput(text=chat_result.response.content).add_ai_generated()
         await ctx.send(message)
 
@@ -107,7 +107,7 @@ async def handle_streaming(ctx: ActivityContext[MessageActivity]):
 
         if hasattr(ctx.activity.conversation, "is_group") and ctx.activity.conversation.is_group:
             # Group chat - send final response
-            if chat_result.response.content:
+            if chat_result.response and chat_result.response.content:
                 message = MessageActivityInput(text=chat_result.response.content).add_ai_generated()
                 await ctx.send(message)
         else:
@@ -167,7 +167,7 @@ async def handle_feedback_demo(ctx: ActivityContext[MessageActivity]):
         input="Tell me a short joke", instructions="You are a comedian. Keep responses brief and funny."
     )
 
-    if chat_result.response.content:
+    if chat_result.response and chat_result.response.content:
         # Create message with feedback enabled and initialize storage
         message = MessageActivityInput(text=chat_result.response.content).add_ai_generated().add_feedback()
         sent_message = await ctx.send(message)

examples/mcp-client/src/main.py

@@ -88,7 +88,7 @@ async def handle_agent_chat(ctx: ActivityContext[MessageActivity]):
 
         # Use ChatPrompt with MCP tools (stateful conversation)
         result = await responses_prompt.send(query)
-        if result.response.content:
+        if result.response and result.response.content:
             message = MessageActivityInput(text=result.response.content).add_ai_generated()
             await ctx.send(message)
 
@@ -111,7 +111,7 @@ async def handle_prompt_chat(ctx: ActivityContext[MessageActivity]):
             ),
         )
 
-        if result.response.content:
+        if result.response and result.response.content:
             message = MessageActivityInput(text=result.response.content).add_ai_generated()
             await ctx.send(message)
 
@@ -157,7 +157,7 @@ async def handle_fallback_message(ctx: ActivityContext[MessageActivity]):
 
     # Use ChatPrompt with MCP tools for general conversation
     result = await responses_prompt.send(ctx.activity.text)
-    if result.response.content:
+    if result.response and result.response.content:
         message = MessageActivityInput(text=result.response.content).add_ai_generated()
         await ctx.send(message)
 

packages/ai/src/microsoft/teams/ai/__init__.py

@@ -3,11 +3,21 @@
 Licensed under the MIT License.
 """
 
+from . import plugins, utils
 from .ai_model import AIModel
 from .chat_prompt import ChatPrompt, ChatSendResult
-from .function import Function, FunctionCall, FunctionHandler, FunctionHandlers, FunctionHandlerWithNoParams
+from .function import (
+    DeferredResult,
+    Function,
+    FunctionCall,
+    FunctionHandler,
+    FunctionHandlers,
+    FunctionHandlerWithNoParams,
+)
 from .memory import ListMemory, Memory
-from .message import FunctionMessage, Message, ModelMessage, SystemMessage, UserMessage
+from .message import DeferredMessage, FunctionMessage, Message, ModelMessage, SystemMessage, UserMessage
+from .plugin import AIPluginProtocol, BaseAIPlugin
+from .utils import *  # noqa: F401, F403
 
 __all__ = [
     "ChatSendResult",
@@ -17,12 +27,18 @@
     "ModelMessage",
     "SystemMessage",
     "FunctionMessage",
+    "DeferredMessage",
     "Function",
     "FunctionCall",
+    "DeferredResult",
     "Memory",
     "ListMemory",
     "AIModel",
+    "AIPluginProtocol",
+    "BaseAIPlugin",
     "FunctionHandler",
     "FunctionHandlerWithNoParams",
     "FunctionHandlers",
 ]
+__all__.extend(utils.__all__)
+__all__.extend(plugins.__all__)

packages/ai/src/microsoft/teams/ai/agent.py

@@ -0,0 +1,70 @@
+"""
+Copyright (c) Microsoft Corporation. All rights reserved.
+Licensed under the MIT License.
+"""
+
+from typing import Any, Awaitable, Callable
+
+from microsoft.teams.ai.plugin import AIPluginProtocol
+
+from .ai_model import AIModel
+from .chat_prompt import ChatPrompt, ChatSendResult
+from .function import Function
+from .memory import ListMemory, Memory
+from .message import Message, SystemMessage
+
+
+class Agent(ChatPrompt):
+    """
+    A stateful implementation of ChatPrompt with persistent memory.
+
+    Agent extends ChatPrompt by providing default memory management,
+    making it easier to maintain conversation context across multiple
+    interactions without manually passing memory each time.
+    """
+
+    def __init__(
+        self,
+        model: AIModel,
+        *,
+        memory: Memory | None = None,
+        functions: list[Function[Any]] | None = None,
+        plugins: list[AIPluginProtocol] | None = None,
+    ):
+        """
+        Initialize Agent with model and persistent memory.
+
+        Args:
+            model: AI model implementation for text generation
+            memory: Memory for conversation persistence. Defaults to InMemory ListMemory
+            functions: Optional list of functions the model can call
+            plugins: Optional list of plugins for extending functionality
+        """
+        super().__init__(model, functions=functions, plugins=plugins)
+        self.memory = memory or ListMemory()
+
+    async def send(
+        self,
+        input: str | Message | None,
+        *,
+        instructions: str | SystemMessage | None = None,
+        memory: Memory | None = None,
+        on_chunk: Callable[[str], Awaitable[None]] | Callable[[str], None] | None = None,
+    ) -> ChatSendResult:
+        """
+        Send a message using the agent's persistent memory.
+
+        Args:
+            input: Message to send (string will be converted to UserMessage)
+            instructions: Optional system message to guide model behavior
+            memory: Optional memory override. Defaults to agent's persistent memory
+            on_chunk: Optional callback for streaming response chunks
+
+        Returns:
+            ChatSendResult containing the final model response
+
+        Note:
+            If no memory is provided, uses the agent's default memory,
+            making conversation state persistent across calls.
+        """
+        return await super().send(input, memory=memory or self.memory, instructions=instructions, on_chunk=on_chunk)

packages/ai/src/microsoft/teams/ai/ai_model.py

@@ -9,7 +9,7 @@
 
 from .function import Function
 from .memory import Memory
-from .message import Message, ModelMessage, SystemMessage
+from .message import DeferredMessage, Message, ModelMessage, SystemMessage
 
 
 class AIModel(Protocol):
@@ -23,13 +23,13 @@ class AIModel(Protocol):
 
     async def generate_text(
         self,
-        input: Message,
+        input: Message | None,
         *,
         system: SystemMessage | None = None,
         memory: Memory | None = None,
         functions: dict[str, Function[BaseModel]] | None = None,
         on_chunk: Callable[[str], Awaitable[None]] | None = None,
-    ) -> ModelMessage:
+    ) -> ModelMessage | list[DeferredMessage]:
         """
         Generate a text response from the AI model.