Merge branch 'main' into remove_deprecation

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

@@ -11,7 +11,6 @@
     List,
     Mapping,
     Sequence,
-    Tuple,
 )
 
 from autogen_core import CancellationToken, FunctionCall
@@ -72,40 +71,47 @@ class AssistantAgent(BaseChatAgent):
     the inner messages as they are created, and the :class:`~autogen_agentchat.base.Response`
     object as the last item before closing the generator.
 
-
     .. note::
 
         The caller must only pass the new messages to the agent on each call
         to the :meth:`on_messages` or :meth:`on_messages_stream` method.
         The agent maintains its state between calls to these methods.
         Do not pass the entire conversation history to the agent on each call.
 
+    .. note::
+        The assistant agent is not thread-safe or coroutine-safe.
+        It should not be shared between multiple tasks or coroutines, and it should
+        not call its methods concurrently.
+
     Tool call behavior:
 
     * 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.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`.
 
+    .. note::
+        By default, the tool call results are returned as response when tool calls are made.
+        So it is recommended to pay attention to the formatting of the tools return values,
+        especially if another agent is expecting them in a specific format.
+        Use `tool_call_summary_format` to customize the tool call summary, if needed.
+
     Hand off behavior:
 
     * If a handoff is triggered, a :class:`~autogen_agentchat.messages.HandoffMessage` will be returned in :attr:`~autogen_agentchat.base.Response.chat_message`.
     * If there are tool calls, they will also be executed right away before returning the handoff.
 
 
     .. note::
-        The assistant agent is not thread-safe or coroutine-safe.
-        It should not be shared between multiple tasks or coroutines, and it should
-        not call its methods concurrently.
+        If multiple handoffs are detected, only the first handoff is executed.
 
-    .. note::
-        By default, the tool call results are returned as response when tool calls are made.
-        So it is recommended to pay attention to the formatting of the tools return values,
-        especially if another agent is expecting them in a specific format.
-        Use `tool_call_summary_format` to customize the tool call summary, if needed.
 
-    .. note::
-        If multiple handoffs are detected, only the first handoff is executed.
+    Limit context size sent to the model:
+
+    You can limit the number of messages sent to the model by setting
+    the `model_context` parameter to a :class:`~autogen_core.model_context.BufferedChatCompletionContext`.
+    This will limit the number of recent messages sent to the model and can be useful
+    when the model has a limit on the number of tokens it can process.
 
 
     Args:
@@ -305,7 +311,7 @@ def __init__(
         self._is_running = False
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         """The types of messages that the assistant agent produces."""
         message_types: List[type[ChatMessage]] = [TextMessage]
         if self._handoffs:

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

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any, AsyncGenerator, List, Mapping, Sequence, Tuple
+from typing import Any, AsyncGenerator, List, Mapping, Sequence
 
 from autogen_core import CancellationToken
 
@@ -56,7 +56,7 @@ def description(self) -> str:
 
     @property
     @abstractmethod
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         """The types of messages that the agent produces in the
         :attr:`Response.chat_message` field. They must be :class:`ChatMessage` types."""
         ...

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

@@ -1,5 +1,5 @@
 import re
-from typing import List, Sequence, Tuple
+from typing import List, Sequence
 
 from autogen_core import CancellationToken
 from autogen_core.code_executor import CodeBlock, CodeExecutor
@@ -80,7 +80,7 @@ def __init__(
         self._code_executor = code_executor
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         """The types of messages that the code executor agent produces."""
         return (TextMessage,)
 

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

@@ -1,4 +1,4 @@
-from typing import Any, AsyncGenerator, List, Mapping, Sequence, Tuple
+from typing import Any, AsyncGenerator, List, Mapping, Sequence
 
 from autogen_core import CancellationToken
 from autogen_core.models import ChatCompletionClient, LLMMessage, SystemMessage, UserMessage
@@ -103,7 +103,7 @@ def __init__(
         self._response_prompt = response_prompt
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         return (TextMessage,)
 
     async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:

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

@@ -1,6 +1,6 @@
 import asyncio
 from inspect import iscoroutinefunction
-from typing import Awaitable, Callable, Optional, Sequence, Tuple, Union, cast
+from typing import Awaitable, Callable, Optional, Sequence, Union, cast
 
 from aioconsole import ainput  # type: ignore
 from autogen_core import CancellationToken
@@ -122,7 +122,7 @@ def __init__(
         self._is_async = iscoroutinefunction(self.input_func)
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         """Message types this agent can produce."""
         return (TextMessage, HandoffMessage)
 

python/packages/autogen-agentchat/src/autogen_agentchat/base/_chat_agent.py

@@ -1,5 +1,5 @@
 from dataclasses import dataclass
-from typing import Any, AsyncGenerator, Mapping, Protocol, Sequence, Tuple, runtime_checkable
+from typing import Any, AsyncGenerator, Mapping, Protocol, Sequence, runtime_checkable
 
 from autogen_core import CancellationToken
 
@@ -37,7 +37,7 @@ def description(self) -> str:
         ...
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         """The types of messages that the agent produces in the
         :attr:`Response.chat_message` field. They must be :class:`ChatMessage` types."""
         ...

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

@@ -2,7 +2,7 @@
 import json
 import logging
 import tempfile
-from typing import Any, AsyncGenerator, List, Sequence, Tuple
+from typing import Any, AsyncGenerator, List, Sequence
 
 import pytest
 from autogen_agentchat import EVENT_LOGGER_NAME
@@ -75,7 +75,7 @@ def __init__(self, name: str, description: str) -> None:
         self._total_messages = 0
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         return (TextMessage,)
 
     @property
@@ -104,7 +104,7 @@ def __init__(self, name: str, description: str, *, stop_at: int = 1) -> None:
         self._stop_at = stop_at
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         return (TextMessage, StopMessage)
 
     async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
@@ -797,7 +797,7 @@ def __init__(self, name: str, description: str, next_agent: str) -> None:
         self._next_agent = next_agent
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         return (HandoffMessage,)
 
     async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:

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

@@ -1,7 +1,7 @@
 import asyncio
 import json
 import logging
-from typing import Sequence, Tuple
+from typing import Sequence
 
 import pytest
 from autogen_agentchat import EVENT_LOGGER_NAME
@@ -33,7 +33,7 @@ def __init__(self, name: str, description: str) -> None:
         self._total_messages = 0
 
     @property
-    def produced_message_types(self) -> Tuple[type[ChatMessage], ...]:
+    def produced_message_types(self) -> Sequence[type[ChatMessage]]:
         return (TextMessage,)
 
     @property