Agentchat move termination (microsoft#3992)

python/packages/autogen-agentchat/src/autogen_agentchat/task/_terminations.py

@@ -48,7 +48,7 @@ async def __call__(self, messages: Sequence[ChatMessage]) -> StopMessage | None:
         self._message_count += len(messages)
         if self._message_count >= self._max_messages:
             return StopMessage(
-                content=f"Maximal number of messages {self._max_messages} reached, current message count: {self._message_count}",
+                content=f"Maximum number of messages {self._max_messages} reached, current message count: {self._message_count}",
                 source="MaxMessageTermination",
             )
         return None

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

@@ -28,14 +28,20 @@ class BaseGroupChat(Team, ABC):
     create a subclass of :class:`BaseGroupChat` that uses the group chat manager.
     """
 
-    def __init__(self, participants: List[ChatAgent], group_chat_manager_class: type[BaseGroupChatManager]):
+    def __init__(
+        self,
+        participants: List[ChatAgent],
+        group_chat_manager_class: type[BaseGroupChatManager],
+        termination_condition: TerminationCondition | None = None,
+    ):
         if len(participants) == 0:
             raise ValueError("At least one participant is required.")
         if len(participants) != len(set(participant.name for participant in participants)):
             raise ValueError("The participant names must be unique.")
         self._participants = participants
         self._team_id = str(uuid.uuid4())
         self._base_group_chat_manager_class = group_chat_manager_class
+        self._termination_condition = termination_condition
 
     @abstractmethod
     def _create_group_chat_manager_factory(
@@ -109,7 +115,7 @@ async def run(
                 group_topic_type=group_topic_type,
                 participant_topic_types=participant_topic_types,
                 participant_descriptions=participant_descriptions,
-                termination_condition=termination_condition,
+                termination_condition=termination_condition or self._termination_condition,
             ),
         )
         # Add subscriptions for the group chat manager.

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

@@ -82,8 +82,12 @@ class RoundRobinGroupChat(BaseGroupChat):
 
     """
 
-    def __init__(self, participants: List[ChatAgent]):
-        super().__init__(participants, group_chat_manager_class=RoundRobinGroupChatManager)
+    def __init__(self, participants: List[ChatAgent], termination_condition: TerminationCondition | None = None):
+        super().__init__(
+            participants,
+            termination_condition=termination_condition,
+            group_chat_manager_class=RoundRobinGroupChatManager,
+        )
 
     def _create_group_chat_manager_factory(
         self,

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

@@ -140,7 +140,8 @@ def _mentioned_agents(self, message_content: str, agent_names: List[str]) -> Dic
                 + re.escape(name.replace("_", r"\_"))
                 + r")(?=\W)"
             )
-            count = len(re.findall(regex, f" {message_content} "))  # Pad the message to help with matching
+            # Pad the message to help with matching
+            count = len(re.findall(regex, f" {message_content} "))
             if count > 0:
                 mentions[name] = count
         return mentions
@@ -184,6 +185,7 @@ def __init__(
         participants: List[ChatAgent],
         model_client: ChatCompletionClient,
         *,
+        termination_condition: TerminationCondition | None = None,
         selector_prompt: str = """You are in a role play game. The following roles are available:
 {roles}.
 Read the following conversation. Then select the next role from {participants} to play. Only return the role.
@@ -194,7 +196,9 @@ def __init__(
 """,
         allow_repeated_speaker: bool = False,
     ):
-        super().__init__(participants, group_chat_manager_class=SelectorGroupChatManager)
+        super().__init__(
+            participants, termination_condition=termination_condition, group_chat_manager_class=SelectorGroupChatManager
+        )
         # Validate the participants.
         if len(participants) < 2:
             raise ValueError("At least two participants are required for SelectorGroupChat.")

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

@@ -82,8 +82,10 @@ class Swarm(BaseGroupChat):
             await team.run("What is bob's birthday?", termination_condition=MaxMessageTermination(3))
     """
 
-    def __init__(self, participants: List[ChatAgent]):
-        super().__init__(participants, group_chat_manager_class=SwarmGroupChatManager)
+    def __init__(self, participants: List[ChatAgent], termination_condition: TerminationCondition | None = None):
+        super().__init__(
+            participants, termination_condition=termination_condition, group_chat_manager_class=SwarmGroupChatManager
+        )
 
     def _create_group_chat_manager_factory(
         self,

python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/quickstart.ipynb

@@ -37,32 +37,32 @@
      "text": [
       "\n",
       "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-23T12:15:51.582079]:\u001b[0m\n",
+      "\u001b[91m[2024-10-29T15:48:06.329810]:\u001b[0m\n",
       "\n",
       "What is the weather in New York?\n",
       "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-23T12:15:52.745820], writing_agent:\u001b[0m\n",
+      "\u001b[91m[2024-10-29T15:48:08.085839], weather_agent:\u001b[0m\n",
       "\n",
-      "The weather in New York is currently 73 degrees and sunny. TERMINATE\n",
+      "The weather in New York is 73 degrees and sunny.\n",
       "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-23T12:15:52.746210], Termination:\u001b[0m\n",
+      "\u001b[91m[2024-10-29T15:48:08.086180], Termination:\u001b[0m\n",
       "\n",
-      "Maximal number of messages 1 reached, current message count: 1\n",
-      " TaskResult(messages=[TextMessage(source='user', content='What is the weather in New York?'), StopMessage(source='writing_agent', content='The weather in New York is currently 73 degrees and sunny. TERMINATE')])\n"
+      "Maximum number of messages 2 reached, current message count: 2\n",
+      " TaskResult(messages=[TextMessage(source='user', content='What is the weather in New York?'), TextMessage(source='weather_agent', content='The weather in New York is 73 degrees and sunny.')])\n"
      ]
     }
    ],
    "source": [
     "import logging\n",
     "\n",
     "from autogen_agentchat import EVENT_LOGGER_NAME\n",
-    "from autogen_agentchat.agents import ToolUseAssistantAgent\n",
+    "from autogen_agentchat.agents import AssistantAgent\n",
     "from autogen_agentchat.logging import ConsoleLogHandler\n",
     "from autogen_agentchat.task import MaxMessageTermination\n",
     "from autogen_agentchat.teams import RoundRobinGroupChat\n",
-    "from autogen_core.components.tools import FunctionTool\n",
     "from autogen_ext.models import OpenAIChatCompletionClient\n",
     "\n",
+    "# set up logging. You can define your own logger\n",
     "logger = logging.getLogger(EVENT_LOGGER_NAME)\n",
     "logger.addHandler(ConsoleLogHandler())\n",
     "logger.setLevel(logging.INFO)\n",
@@ -73,22 +73,18 @@
     "    return f\"The weather in {city} is 73 degrees and Sunny.\"\n",
     "\n",
     "\n",
-    "# wrap the tool for use with the agent\n",
-    "get_weather_tool = FunctionTool(get_weather, description=\"Get the weather for a city\")\n",
-    "\n",
     "# define an agent\n",
-    "weather_agent = ToolUseAssistantAgent(\n",
-    "    name=\"writing_agent\",\n",
+    "weather_agent = AssistantAgent(\n",
+    "    name=\"weather_agent\",\n",
     "    model_client=OpenAIChatCompletionClient(model=\"gpt-4o-2024-08-06\"),\n",
-    "    registered_tools=[get_weather_tool],\n",
+    "    tools=[get_weather],\n",
     ")\n",
     "\n",
     "# add the agent to a team\n",
-    "agent_team = RoundRobinGroupChat([weather_agent])\n",
+    "agent_team = RoundRobinGroupChat([weather_agent], termination_condition=MaxMessageTermination(max_messages=2))\n",
     "# Note: if running in a Python file directly you'll need to use asyncio.run(agent_team.run(...)) instead of await agent_team.run(...)\n",
     "result = await agent_team.run(\n",
     "    task=\"What is the weather in New York?\",\n",
-    "    termination_condition=MaxMessageTermination(max_messages=1),\n",
     ")\n",
     "print(\"\\n\", result)"
    ]
@@ -97,7 +93,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The code snippet above introduces two high level concepts in AgentChat: `Agent` and `Team`.  An Agent helps us define what actions are taken when a message is received. Specifically, we use the `ToolUseAssistantAgent` preset - an agent that can be given a function that it can then use to address tasks.  A Team helps us define the rules for how agents interact with each other.  In the  `RoundRobinGroupChat` team, agents receive messages in a sequential round-robin fashion.  "
+    "The code snippet above introduces two high level concepts in AgentChat: `Agent` and `Team`.  An Agent helps us define what actions are taken when a message is received. Specifically, we use the `AssistantAgent` preset - an agent that can be given tools (functions) that it can then use to address tasks.  A Team helps us define the rules for how agents interact with each other.  In the  `RoundRobinGroupChat` team, agents receive messages in a sequential round-robin fashion.  "
    ]
   },
   {
@@ -113,7 +109,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "agnext",
    "language": "python",
    "name": "python3"
   },
@@ -127,7 +123,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.6"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,