Tool call result summary message

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

@@ -28,6 +28,7 @@
     TextMessage,
     ToolCallExecutionEvent,
     ToolCallRequestEvent,
+    ToolCallSummaryMessage,
 )
 from ..state import AssistantAgentState
 from ._base_chat_agent import BaseChatAgent
@@ -62,7 +63,7 @@ class AssistantAgent(BaseChatAgent):
 
     * If the model returns no tool call, then the response is immediately returned as a :class:`~autogen_agentchat.messages.TextMessage` in :attr:`~autogen_agentchat.base.Response.chat_message`.
     * When the model returns tool calls, they will be executed right away:
-        - When `reflect_on_tool_use` is False (default), the tool call results are returned as a :class:`~autogen_agentchat.messages.TextMessage` in :attr:`~autogen_agentchat.base.Response.chat_message`. `tool_call_summary_format` can be used to customize the tool call summary.
+        - When `reflect_on_tool_use` is False (default), the tool call results are returned as a :class:`~autogen_agentchat.messages.ToolCallSummaryMessage` in :attr:`~autogen_agentchat.base.Response.chat_message`. `tool_call_summary_format` can be used to customize the tool call summary.
         - When `reflect_on_tool_use` is True, the another model inference is made using the tool calls and results, and the text response is returned as a :class:`~autogen_agentchat.messages.TextMessage` in :attr:`~autogen_agentchat.base.Response.chat_message`.
 
     Hand off behavior:
@@ -280,9 +281,12 @@ def __init__(
     @property
     def produced_message_types(self) -> List[type[ChatMessage]]:
         """The types of messages that the assistant agent produces."""
+        message_types: List[type[ChatMessage]] = [TextMessage]
         if self._handoffs:
-            return [TextMessage, HandoffMessage]
-        return [TextMessage]
+            message_types.append(HandoffMessage)
+        if self._tools:
+            message_types.append(ToolCallSummaryMessage)
+        return message_types
 
     async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
         async for message in self.on_messages_stream(messages, cancellation_token):
@@ -379,7 +383,7 @@ async def on_messages_stream(
                 )
             tool_call_summary = "\n".join(tool_call_summaries)
             yield Response(
-                chat_message=TextMessage(content=tool_call_summary, source=self.name),
+                chat_message=ToolCallSummaryMessage(content=tool_call_summary, source=self.name),
                 inner_messages=inner_messages,
             )
 

python/packages/autogen-agentchat/src/autogen_agentchat/messages.py

@@ -101,7 +101,18 @@ class ToolCallExecutionEvent(BaseMessage):
     type: Literal["ToolCallExecutionEvent"] = "ToolCallExecutionEvent"
 
 
-ChatMessage = Annotated[TextMessage | MultiModalMessage | StopMessage | HandoffMessage, Field(discriminator="type")]
+class ToolCallSummaryMessage(BaseMessage):
+    """A message signaling the summary of tool call results."""
+
+    content: str
+    """Summary of the the tool call results."""
+
+    type: Literal["ToolCallSummaryMessage"] = "ToolCallSummaryMessage"
+
+
+ChatMessage = Annotated[
+    TextMessage | MultiModalMessage | StopMessage | ToolCallSummaryMessage | HandoffMessage, Field(discriminator="type")
+]
 """Messages for agent-to-agent communication only."""
 
 
@@ -110,7 +121,13 @@ class ToolCallExecutionEvent(BaseMessage):
 
 
 AgentMessage = Annotated[
-    TextMessage | MultiModalMessage | StopMessage | HandoffMessage | ToolCallRequestEvent | ToolCallExecutionEvent,
+    TextMessage
+    | MultiModalMessage
+    | StopMessage
+    | HandoffMessage
+    | ToolCallRequestEvent
+    | ToolCallExecutionEvent
+    | ToolCallSummaryMessage,
     Field(discriminator="type"),
 ]
 """(Deprecated, will be removed in 0.4.0) All message and event types."""
@@ -126,6 +143,7 @@ class ToolCallExecutionEvent(BaseMessage):
     "ToolCallExecutionEvent",
     "ToolCallMessage",
     "ToolCallResultMessage",
+    "ToolCallSummaryMessage",
     "ChatMessage",
     "AgentEvent",
     "AgentMessage",

python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_magentic_one/_magentic_one_orchestrator.py

@@ -21,6 +21,7 @@
     TextMessage,
     ToolCallExecutionEvent,
     ToolCallRequestEvent,
+    ToolCallSummaryMessage,
 )
 from ....state import MagenticOneOrchestratorState
 from .._base_group_chat_manager import BaseGroupChatManager
@@ -433,7 +434,7 @@ def _thread_to_context(self) -> List[LLMMessage]:
             elif isinstance(m, StopMessage | HandoffMessage):
                 context.append(UserMessage(content=m.content, source=m.source))
             elif m.source == self._name:
-                assert isinstance(m, TextMessage)
+                assert isinstance(m, TextMessage | ToolCallSummaryMessage)
                 context.append(AssistantMessage(content=m.content, source=m.source))
             else:
                 assert isinstance(m, TextMessage) or isinstance(m, MultiModalMessage)

python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_selector_group_chat.py

@@ -15,6 +15,7 @@
     TextMessage,
     ToolCallExecutionEvent,
     ToolCallRequestEvent,
+    ToolCallSummaryMessage,
 )
 from ...state import SelectorManagerState
 from ._base_group_chat import BaseGroupChat
@@ -100,7 +101,7 @@ async def select_speaker(self, thread: List[AgentEvent | ChatMessage]) -> str:
                 continue
             # The agent type must be the same as the topic type, which we use as the agent name.
             message = f"{msg.source}:"
-            if isinstance(msg, TextMessage | StopMessage | HandoffMessage):
+            if isinstance(msg, TextMessage | StopMessage | HandoffMessage | ToolCallSummaryMessage):
                 message += f" {msg.content}"
             elif isinstance(msg, MultiModalMessage):
                 for item in msg.content:

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

@@ -14,6 +14,7 @@
     TextMessage,
     ToolCallExecutionEvent,
     ToolCallRequestEvent,
+    ToolCallSummaryMessage,
 )
 from autogen_core import Image
 from autogen_core.tools import FunctionTool
@@ -142,7 +143,7 @@ async def test_run_with_tools(monkeypatch: pytest.MonkeyPatch) -> None:
     assert result.messages[1].models_usage.prompt_tokens == 10
     assert isinstance(result.messages[2], ToolCallExecutionEvent)
     assert result.messages[2].models_usage is None
-    assert isinstance(result.messages[3], TextMessage)
+    assert isinstance(result.messages[3], ToolCallSummaryMessage)
     assert result.messages[3].content == "pass"
     assert result.messages[3].models_usage is None
 

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

@@ -22,6 +22,7 @@
     TextMessage,
     ToolCallExecutionEvent,
     ToolCallRequestEvent,
+    ToolCallSummaryMessage,
 )
 from autogen_agentchat.teams import (
     RoundRobinGroupChat,
@@ -325,7 +326,8 @@ async def test_round_robin_group_chat_with_tools(monkeypatch: pytest.MonkeyPatch
     assert isinstance(result.messages[0], TextMessage)  # task
     assert isinstance(result.messages[1], ToolCallRequestEvent)  # tool call
     assert isinstance(result.messages[2], ToolCallExecutionEvent)  # tool call result
-    assert isinstance(result.messages[3], TextMessage)  # tool use agent response
+    assert isinstance(result.messages[3], ToolCallSummaryMessage)  # tool use agent response
+    assert result.messages[3].content == "pass"  #  ensure the tool call was executed
     assert isinstance(result.messages[4], TextMessage)  # echo agent response
     assert isinstance(result.messages[5], TextMessage)  # tool use agent response
     assert isinstance(result.messages[6], TextMessage)  # echo agent response