Fix: deserialize model_context in AssistantAgent and SocietyOfMindAgent and CodeExecutorAgent

python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py

@@ -1337,7 +1337,7 @@ def _from_config(cls, config: AssistantAgentConfig) -> Self:
             model_client=ChatCompletionClient.load_component(config.model_client),
             tools=[BaseTool.load_component(tool) for tool in config.tools] if config.tools else None,
             handoffs=config.handoffs,
-            model_context=None,
+            model_context=ChatCompletionContext.load_component(config.model_context) if config.model_context else None,
             memory=[Memory.load_component(memory) for memory in config.memory] if config.memory else None,
             description=config.description,
             system_message=config.system_message,

python/packages/autogen-agentchat/src/autogen_agentchat/agents/_code_executor_agent.py

@@ -369,6 +369,13 @@ def produced_message_types(self) -> Sequence[type[BaseChatMessage]]:
         """The types of messages that the code executor agent produces."""
         return (TextMessage,)
 
+    @property
+    def model_context(self) -> ChatCompletionContext:
+        """
+        The model context in use by the agent.
+        """
+        return self._model_context
+
     async def on_messages(self, messages: Sequence[BaseChatMessage], cancellation_token: CancellationToken) -> Response:
         async for message in self.on_messages_stream(messages, cancellation_token):
             if isinstance(message, Response):
@@ -566,7 +573,7 @@ def _from_config(cls, config: CodeExecutorAgentConfig) -> Self:
             sources=config.sources,
             system_message=config.system_message,
             model_client_stream=config.model_client_stream,
-            model_context=None,
+            model_context=ChatCompletionContext.load_component(config.model_context) if config.model_context else None,
         )
 
     @staticmethod

python/packages/autogen-agentchat/src/autogen_agentchat/agents/_society_of_mind_agent.py

@@ -286,6 +286,7 @@ def _to_config(self) -> SocietyOfMindAgentConfig:
             description=self.description,
             instruction=self._instruction,
             response_prompt=self._response_prompt,
+            model_context=self._model_context.dump_component(),
         )
 
     @classmethod
@@ -299,4 +300,5 @@ def _from_config(cls, config: SocietyOfMindAgentConfig) -> Self:
             description=config.description or cls.DEFAULT_DESCRIPTION,
             instruction=config.instruction or cls.DEFAULT_INSTRUCTION,
             response_prompt=config.response_prompt or cls.DEFAULT_RESPONSE_PROMPT,
+            model_context=ChatCompletionContext.load_component(config.model_context) if config.model_context else None,
         )

python/packages/autogen-agentchat/tests/test_agent.py

@@ -0,0 +1,126 @@
+import pytest
+from autogen_agentchat.agents import (
+    AssistantAgent,
+    CodeExecutorAgent,
+    SocietyOfMindAgent,
+)
+from autogen_agentchat.teams import RoundRobinGroupChat
+from autogen_core.model_context import (
+    BufferedChatCompletionContext,
+    ChatCompletionContext,
+    HeadAndTailChatCompletionContext,
+    TokenLimitedChatCompletionContext,
+    UnboundedChatCompletionContext,
+)
+from autogen_ext.code_executors.local import LocalCommandLineCodeExecutor
+from autogen_ext.models.replay import ReplayChatCompletionClient
+
+
+@pytest.mark.parametrize(
+    "model_context_class",
+    [
+        UnboundedChatCompletionContext(),
+        BufferedChatCompletionContext(buffer_size=5),
+        TokenLimitedChatCompletionContext(model_client=ReplayChatCompletionClient([]), token_limit=5),
+        HeadAndTailChatCompletionContext(head_size=3, tail_size=2),
+    ],
+)
+def test_serialize_and_deserialize_model_context_on_assistant_agent(model_context_class: ChatCompletionContext) -> None:
+    """Test the serialization and deserialization of the message context on the AssistantAgent."""
+    agent = AssistantAgent(
+        name="assistant",
+        model_client=ReplayChatCompletionClient([]),
+        description="An assistant agent.",
+        model_context=model_context_class,
+    )
+
+    # Serialize the agent
+    serialized_agent = agent.dump_component()
+    # Deserialize the agent
+    deserialized_agent = AssistantAgent.load_component(serialized_agent)
+
+    # Check that the deserialized agent has the same model context as the original agent
+    original_model_context = agent.model_context
+    deserialized_model_context = deserialized_agent.model_context
+
+    assert isinstance(original_model_context, type(deserialized_model_context))
+    assert isinstance(deserialized_model_context, type(original_model_context))
+    assert original_model_context.dump_component() == deserialized_model_context.dump_component()
+
+
+@pytest.mark.parametrize(
+    "model_context_class",
+    [
+        UnboundedChatCompletionContext(),
+        BufferedChatCompletionContext(buffer_size=5),
+        TokenLimitedChatCompletionContext(model_client=ReplayChatCompletionClient([]), token_limit=5),
+        HeadAndTailChatCompletionContext(head_size=3, tail_size=2),
+    ],
+)
+def test_serialize_and_deserialize_model_context_on_society_of_mind_agent(
+    model_context_class: ChatCompletionContext,
+) -> None:
+    """Test the serialization and deserialization of the message context on the AssistantAgent."""
+    agent1 = AssistantAgent(
+        name="assistant1", model_client=ReplayChatCompletionClient([]), description="An assistant agent."
+    )
+    agent2 = AssistantAgent(
+        name="assistant2", model_client=ReplayChatCompletionClient([]), description="An assistant agent."
+    )
+    team = RoundRobinGroupChat(
+        participants=[agent1, agent2],
+    )
+    agent = SocietyOfMindAgent(
+        name="assistant",
+        model_client=ReplayChatCompletionClient([]),
+        description="An assistant agent.",
+        team=team,
+        model_context=model_context_class,
+    )
+
+    # Serialize the agent
+    serialized_agent = agent.dump_component()
+    # Deserialize the agent
+    deserialized_agent = SocietyOfMindAgent.load_component(serialized_agent)
+
+    # Check that the deserialized agent has the same model context as the original agent
+    original_model_context = agent.model_context
+    deserialized_model_context = deserialized_agent.model_context
+
+    assert isinstance(original_model_context, type(deserialized_model_context))
+    assert isinstance(deserialized_model_context, type(original_model_context))
+    assert original_model_context.dump_component() == deserialized_model_context.dump_component()
+
+
+@pytest.mark.parametrize(
+    "model_context_class",
+    [
+        UnboundedChatCompletionContext(),
+        BufferedChatCompletionContext(buffer_size=5),
+        TokenLimitedChatCompletionContext(model_client=ReplayChatCompletionClient([]), token_limit=5),
+        HeadAndTailChatCompletionContext(head_size=3, tail_size=2),
+    ],
+)
+def test_serialize_and_deserialize_model_context_on_code_executor_agent(
+    model_context_class: ChatCompletionContext,
+) -> None:
+    """Test the serialization and deserialization of the message context on the AssistantAgent."""
+    agent = CodeExecutorAgent(
+        name="assistant",
+        code_executor=LocalCommandLineCodeExecutor(),
+        description="An assistant agent.",
+        model_context=model_context_class,
+    )
+
+    # Serialize the agent
+    serialized_agent = agent.dump_component()
+    # Deserialize the agent
+    deserialized_agent = CodeExecutorAgent.load_component(serialized_agent)
+
+    # Check that the deserialized agent has the same model context as the original agent
+    original_model_context = agent.model_context
+    deserialized_model_context = deserialized_agent.model_context
+
+    assert isinstance(original_model_context, type(deserialized_model_context))
+    assert isinstance(deserialized_model_context, type(original_model_context))
+    assert original_model_context.dump_component() == deserialized_model_context.dump_component()