Merge remote-tracking branch 'upstream/main' into peterj/updateautogen0425

* upstream/main:
  Update website for v0.5.5 (microsoft#6401)
  Document custom message types in teams API docs (microsoft#6400)
  [doc] Clarify selector prompt for SelectorGroupChat (microsoft#6399)
  Add functional termination condition (microsoft#6398)
  Update: implement return_value_as_string for McpToolAdapter  (microsoft#6380)
  Update version to 0.5.5 (microsoft#6397)
  Add example using autogen-core and FastAPI for handoff multi-agent design pattern with streaming and UI (microsoft#6391)
  Update agent documentation  (microsoft#6394)
  AssistantAgent to support Workbench (microsoft#6393)
  TEST: skip when macos+uv and adding uv venv tests (microsoft#6387)
  Add guide for workbench and mcp & bug fixes for create_mcp_server_session (microsoft#6392)

Signed-off-by: Peter Jausovec <peter.jausovec@solo.io>

Author: peterj

.github/ISSUE_TEMPLATE/1-bug_report.yml

@@ -90,6 +90,7 @@ body:
       multiple: false
       options:
         - "Python dev (main branch)"
+        - "Python 0.5.5"
         - "Python 0.5.4"
         - "Python 0.5.3"
         - "Python 0.5.2"

.github/workflows/docs.yml

@@ -33,7 +33,7 @@ jobs:
           [
             # For main use the workflow target
             { ref: "${{github.ref}}", dest-dir: dev, uv-version: "0.5.13", sphinx-release-override: "dev" },
-            { ref: "python-v0.5.4", dest-dir: stable, uv-version: "0.5.13", sphinx-release-override: "stable" },
+            { ref: "python-v0.5.5", dest-dir: stable, uv-version: "0.5.13", sphinx-release-override: "stable" },
             { ref: "v0.4.0.post1", dest-dir: "0.4.0", uv-version: "0.5.13", sphinx-release-override: "" },
             { ref: "v0.4.1", dest-dir: "0.4.1", uv-version: "0.5.13", sphinx-release-override: "" },
             { ref: "v0.4.2", dest-dir: "0.4.2", uv-version: "0.5.13", sphinx-release-override: "" },
@@ -48,6 +48,7 @@ jobs:
             { ref: "python-v0.5.2", dest-dir: "0.5.2", uv-version: "0.5.13", sphinx-release-override: "" },
             { ref: "python-v0.5.3", dest-dir: "0.5.3", uv-version: "0.5.13", sphinx-release-override: "" },
             { ref: "python-v0.5.4", dest-dir: "0.5.4", uv-version: "0.5.13", sphinx-release-override: "" },
+            { ref: "python-v0.5.5", dest-dir: "0.5.5", uv-version: "0.5.13", sphinx-release-override: "" },
           ]
     steps:
       - name: Checkout

docs/switcher.json

@@ -5,11 +5,16 @@
         "url": "/autogen/dev/"
     },
     {
-        "name": "0.5.4 (stable)",
+        "name": "0.5.5 (stable)",
         "version": "stable",
         "url": "/autogen/stable/",
         "preferred": true
     },
+    {
+        "name": "0.5.4",
+        "version": "0.5.4",
+        "url": "/autogen/0.5.4/"
+    },
     {
         "name": "0.5.3",
         "version": "0.5.3",

python/packages/autogen-agentchat/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "autogen-agentchat"
-version = "0.5.4"
+version = "0.5.5"
 license = {file = "LICENSE-CODE"}
 description = "AutoGen agents and teams library"
 readme = "README.md"
@@ -15,7 +15,7 @@ classifiers = [
     "Operating System :: OS Independent",
 ]
 dependencies = [
-    "autogen-core==0.5.4",
+    "autogen-core==0.5.5",
 ]
 
 [tool.ruff]

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

@@ -5,6 +5,7 @@
 
 from ._terminations import (
     ExternalTermination,
+    FunctionalTermination,
     FunctionCallTermination,
     HandoffTermination,
     MaxMessageTermination,
@@ -27,4 +28,5 @@
     "SourceMatchTermination",
     "TextMessageTermination",
     "FunctionCallTermination",
+    "FunctionalTermination",
 ]

python/packages/autogen-agentchat/src/autogen_agentchat/conditions/__init__.py

@@ -1,5 +1,6 @@
+import asyncio
 import time
-from typing import List, Sequence
+from typing import Awaitable, Callable, List, Sequence
 
 from autogen_core import Component
 from pydantic import BaseModel
@@ -154,6 +155,77 @@ def _from_config(cls, config: TextMentionTerminationConfig) -> Self:
         return cls(text=config.text)
 
 
+class FunctionalTermination(TerminationCondition):
+    """Terminate the conversation if an functional expression is met.
+
+    Args:
+        func (Callable[[Sequence[BaseAgentEvent | BaseChatMessage]], bool] | Callable[[Sequence[BaseAgentEvent | BaseChatMessage]], Awaitable[bool]]): A function that takes a sequence of messages
+            and returns True if the termination condition is met, False otherwise.
+            The function can be a callable or an async callable.
+
+    Example:
+
+        .. code-block:: python
+
+            import asyncio
+            from typing import Sequence
+
+            from autogen_agentchat.conditions import FunctionalTermination
+            from autogen_agentchat.messages import BaseAgentEvent, BaseChatMessage, StopMessage
+
+
+            def expression(messages: Sequence[BaseAgentEvent | BaseChatMessage]) -> bool:
+                # Check if the last message is a stop message
+                return isinstance(messages[-1], StopMessage)
+
+
+            termination = FunctionalTermination(expression)
+
+
+            async def run() -> None:
+                messages = [
+                    StopMessage(source="agent1", content="Stop"),
+                ]
+                result = await termination(messages)
+                print(result)
+
+
+            asyncio.run(run())
+
+        .. code-block:: text
+
+            StopMessage(source="FunctionalTermination", content="Functional termination condition met")
+
+    """
+
+    def __init__(
+        self,
+        func: Callable[[Sequence[BaseAgentEvent | BaseChatMessage]], bool]
+        | Callable[[Sequence[BaseAgentEvent | BaseChatMessage]], Awaitable[bool]],
+    ) -> None:
+        self._func = func
+        self._terminated = False
+
+    @property
+    def terminated(self) -> bool:
+        return self._terminated
+
+    async def __call__(self, messages: Sequence[BaseAgentEvent | BaseChatMessage]) -> StopMessage | None:
+        if self._terminated:
+            raise TerminatedException("Termination condition has already been reached")
+        if asyncio.iscoroutinefunction(self._func):
+            result = await self._func(messages)
+        else:
+            result = self._func(messages)
+        if result is True:
+            self._terminated = True
+            return StopMessage(content="Functional termination condition met", source="FunctionalTermination")
+        return None
+
+    async def reset(self) -> None:
+        self._terminated = False
+
+
 class TokenUsageTerminationConfig(BaseModel):
     max_total_token: int | None
     max_prompt_token: int | None

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

@@ -47,6 +47,9 @@ class MagenticOneGroupChat(BaseGroupChat, Component[MagenticOneGroupChatConfig])
         max_turns (int, optional): The maximum number of turns in the group chat before stopping. Defaults to 20.
         max_stalls (int, optional): The maximum number of stalls allowed before re-planning. Defaults to 3.
         final_answer_prompt (str, optional): The LLM prompt used to generate the final answer or response from the team's transcript. A default (sensible for GPT-4o class models) is provided.
+        custom_message_types (List[type[BaseAgentEvent | BaseChatMessage]], optional): A list of custom message types that will be used in the group chat.
+            If you are using custom message types or your agents produces custom message types, you need to specify them here.
+            Make sure your custom message types are subclasses of :class:`~autogen_agentchat.messages.BaseAgentEvent` or :class:`~autogen_agentchat.messages.BaseChatMessage`.
         emit_team_events (bool, optional): Whether to emit team events through :meth:`BaseGroupChat.run_stream`. Defaults to False.
 
     Raises:
@@ -105,6 +108,7 @@ def __init__(
         runtime: AgentRuntime | None = None,
         max_stalls: int = 3,
         final_answer_prompt: str = ORCHESTRATOR_FINAL_ANSWER_PROMPT,
+        custom_message_types: List[type[BaseAgentEvent | BaseChatMessage]] | None = None,
         emit_team_events: bool = False,
     ):
         super().__init__(
@@ -114,6 +118,7 @@ def __init__(
             termination_condition=termination_condition,
             max_turns=max_turns,
             runtime=runtime,
+            custom_message_types=custom_message_types,
             emit_team_events=emit_team_events,
         )
 

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

@@ -97,6 +97,9 @@ class RoundRobinGroupChat(BaseGroupChat, Component[RoundRobinGroupChatConfig]):
         termination_condition (TerminationCondition, optional): The termination condition for the group chat. Defaults to None.
             Without a termination condition, the group chat will run indefinitely.
         max_turns (int, optional): The maximum number of turns in the group chat before stopping. Defaults to None, meaning no limit.
+        custom_message_types (List[type[BaseAgentEvent | BaseChatMessage]], optional): A list of custom message types that will be used in the group chat.
+            If you are using custom message types or your agents produces custom message types, you need to specify them here.
+            Make sure your custom message types are subclasses of :class:`~autogen_agentchat.messages.BaseAgentEvent` or :class:`~autogen_agentchat.messages.BaseChatMessage`.
         emit_team_events (bool, optional): Whether to emit team events through :meth:`BaseGroupChat.run_stream`. Defaults to False.
 
     Raises:

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

@@ -328,6 +328,9 @@ class SelectorGroupChat(BaseGroupChat, Component[SelectorGroupChatConfig]):
         max_turns (int, optional): The maximum number of turns in the group chat before stopping. Defaults to None, meaning no limit.
         selector_prompt (str, optional): The prompt template to use for selecting the next speaker.
             Available fields: '{roles}', '{participants}', and '{history}'.
+            `{participants}` is the names of candidates for selection. The format is `["<name1>", "<name2>", ...]`.
+            `{roles}` is a newline-separated list of names and descriptions of the candidate agents. The format for each line is: `"<name> : <description>"`.
+            `{history}` is the conversation history formatted as a double newline separated of names and message content. The format for each message is: `"<name> : <message content>"`.
         allow_repeated_speaker (bool, optional): Whether to include the previous speaker in the list of candidates to be selected for the next turn.
             Defaults to False. The model may still select the previous speaker -- a warning will be logged if this happens.
         max_selector_attempts (int, optional): The maximum number of attempts to select a speaker using the model. Defaults to 3.
@@ -341,6 +344,9 @@ class SelectorGroupChat(BaseGroupChat, Component[SelectorGroupChatConfig]):
             A custom function that takes the conversation history and returns a filtered list of candidates for the next speaker
             selection using model. If the function returns an empty list or `None`, `SelectorGroupChat` will raise a `ValueError`.
             This function is only used if `selector_func` is not set. The `allow_repeated_speaker` will be ignored if set.
+        custom_message_types (List[type[BaseAgentEvent | BaseChatMessage]], optional): A list of custom message types that will be used in the group chat.
+            If you are using custom message types or your agents produces custom message types, you need to specify them here.
+            Make sure your custom message types are subclasses of :class:`~autogen_agentchat.messages.BaseAgentEvent` or :class:`~autogen_agentchat.messages.BaseChatMessage`.
         emit_team_events (bool, optional): Whether to emit team events through :meth:`BaseGroupChat.run_stream`. Defaults to False.
         model_client_streaming (bool, optional): Whether to use streaming for the model client. (This is useful for reasoning models like QwQ). Defaults to False.