Adding an option to isolate views in Group Chat

autogen/agentchat/conversable_agent.py

@@ -4287,6 +4287,9 @@ def normilize_message_to_oai(
 
     if oai_message.get("function_call", False) or oai_message.get("tool_calls", False):
         oai_message["role"] = "assistant"  # only messages with role 'assistant' can have a function call.
+        # Also set the name for tool_calls messages so we can track the originating agent
+        if "name" not in oai_message:
+            oai_message["name"] = name
     elif "name" not in oai_message:
         # If we don't have a name field, append it
         oai_message["name"] = name

autogen/agentchat/group/group_tool_executor.py

@@ -324,5 +324,41 @@ def _generate_group_tool_reply(
             tool_message["tool_responses"] = tool_responses_inner
             tool_message["content"] = "\n".join(contents)
 
+            # When agent views are isolated, the tool executor's response never reaches
+            # the originating agent's history via the group manager broadcast. Copy the
+            # tool response into the originator's thread with the manager so subsequent
+            # LLM calls have the required tool messages.
+            if self._group_manager and self._group_manager.groupchat.isolate_agent_views:
+                originator = self._group_manager.groupchat.agent_by_name(agent_name)
+                if isinstance(originator, ConversableAgent):
+                    existing_ids: set[str] = set()
+                    history = originator._oai_messages.get(self._group_manager, [])
+
+                    for hist_msg in history:
+                        # Collect tool_call_ids from prior tool responses
+                        for resp in hist_msg.get("tool_responses", []):
+                            if resp.get("tool_call_id"):
+                                existing_ids.add(resp["tool_call_id"])
+                        # Some tool messages may store tool_call_id directly
+                        if hist_msg.get("tool_call_id"):
+                            existing_ids.add(hist_msg["tool_call_id"])
+
+                    new_tool_responses = [
+                        resp for resp in tool_message["tool_responses"] if resp.get("tool_call_id") not in existing_ids
+                    ]
+
+                    if new_tool_responses:
+                        deduped_tool_message = deepcopy(tool_message)
+                        deduped_tool_message["tool_responses"] = new_tool_responses
+                        deduped_tool_message["content"] = "\n".join(
+                            resp.get("content", "") for resp in new_tool_responses
+                        )
+                        originator._append_oai_message(
+                            deduped_tool_message,
+                            self._group_manager,
+                            role="user",
+                            name=self._group_manager.name,
+                        )
+
             return True, tool_message
         return False, None

autogen/agentchat/group/multi_agent_chat.py

@@ -36,6 +36,7 @@ def initiate_group_chat(
     safeguard_policy: dict[str, Any] | str | None = None,
     safeguard_llm_config: LLMConfig | None = None,
     mask_llm_config: LLMConfig | None = None,
+    isolate_agent_views: bool = False,
 ) -> tuple[ChatResult, ContextVariables, "Agent"]:
     """Initialize and run a group chat using a pattern for configuration.
 
@@ -46,6 +47,10 @@ def initiate_group_chat(
         safeguard_policy: Optional safeguard policy dict or path to JSON file.
         safeguard_llm_config: Optional LLM configuration for safeguard checks.
         mask_llm_config: Optional LLM configuration for masking.
+        isolate_agent_views: If True, agents will only maintain their own message history
+            and will not receive messages from other agents. When False (default), all agents
+            receive all messages. When True, messages are still stored in groupchat.messages
+            for the GroupChatManager's view, but are not broadcast to other agents.
 
     Returns:
         ChatResult:         Conversations chat history.
@@ -71,6 +76,7 @@ def initiate_group_chat(
     ) = pattern.prepare_group_chat(
         max_rounds=max_rounds,
         messages=messages,
+        isolate_agent_views=isolate_agent_views,
     )
 
     # Apply safeguards if provided
@@ -115,6 +121,7 @@ async def a_initiate_group_chat(
     safeguard_policy: dict[str, Any] | str | None = None,
     safeguard_llm_config: LLMConfig | None = None,
     mask_llm_config: LLMConfig | None = None,
+    isolate_agent_views: bool = False,
 ) -> tuple[ChatResult, ContextVariables, "Agent"]:
     """Initialize and run a group chat using a pattern for configuration, asynchronously.
 
@@ -125,6 +132,10 @@ async def a_initiate_group_chat(
         safeguard_policy: Optional safeguard policy dict or path to JSON file.
         safeguard_llm_config: Optional LLM configuration for safeguard checks.
         mask_llm_config: Optional LLM configuration for masking.
+        isolate_agent_views: If True, agents will only maintain their own message history
+            and will not receive messages from other agents. When False (default), all agents
+            receive all messages. When True, messages are still stored in groupchat.messages
+            for the GroupChatManager's view, but are not broadcast to other agents.
 
     Returns:
         ChatResult:         Conversations chat history.
@@ -150,6 +161,7 @@ async def a_initiate_group_chat(
     ) = pattern.prepare_group_chat(
         max_rounds=max_rounds,
         messages=messages,
+        isolate_agent_views=isolate_agent_views,
     )
 
     # Apply safeguards if provided
@@ -194,7 +206,25 @@ def run_group_chat(
     safeguard_policy: dict[str, Any] | str | None = None,
     safeguard_llm_config: LLMConfig | None = None,
     mask_llm_config: LLMConfig | None = None,
+    isolate_agent_views: bool = False,
 ) -> RunResponseProtocol:
+    """Run a group chat using a pattern for configuration in a separate thread.
+
+    Args:
+        pattern: Pattern object that encapsulates the chat configuration.
+        messages: Initial message(s).
+        max_rounds: Maximum number of conversation rounds.
+        safeguard_policy: Optional safeguard policy dict or path to JSON file.
+        safeguard_llm_config: Optional LLM configuration for safeguard checks.
+        mask_llm_config: Optional LLM configuration for masking.
+        isolate_agent_views: If True, agents will only maintain their own message history
+            and will not receive messages from other agents. When False (default), all agents
+            receive all messages. When True, messages are still stored in groupchat.messages
+            for the GroupChatManager's view, but are not broadcast to other agents.
+
+    Returns:
+        RunResponseProtocol: Response object for tracking the async execution.
+    """
     iostream = ThreadIOStream()
     all_agents = pattern.agents + ([pattern.user_agent] if pattern.user_agent else [])
     response = RunResponse(iostream, agents=all_agents)
@@ -206,6 +236,7 @@ def _initiate_group_chat(
         safeguard_policy: dict[str, Any] | str | None = safeguard_policy,
         safeguard_llm_config: LLMConfig | None = safeguard_llm_config,
         mask_llm_config: LLMConfig | None = mask_llm_config,
+        isolate_agent_views: bool = isolate_agent_views,
         iostream: ThreadIOStream = iostream,
         response: RunResponse = response,
     ) -> None:
@@ -218,6 +249,7 @@ def _initiate_group_chat(
                     safeguard_policy=safeguard_policy,
                     safeguard_llm_config=safeguard_llm_config,
                     mask_llm_config=mask_llm_config,
+                    isolate_agent_views=isolate_agent_views,
                 )
 
                 IOStream.get_default().send(
@@ -247,7 +279,25 @@ async def a_run_group_chat(
     safeguard_policy: dict[str, Any] | str | None = None,
     safeguard_llm_config: LLMConfig | None = None,
     mask_llm_config: LLMConfig | None = None,
+    isolate_agent_views: bool = False,
 ) -> AsyncRunResponseProtocol:
+    """Run a group chat using a pattern for configuration asynchronously.
+
+    Args:
+        pattern: Pattern object that encapsulates the chat configuration.
+        messages: Initial message(s).
+        max_rounds: Maximum number of conversation rounds.
+        safeguard_policy: Optional safeguard policy dict or path to JSON file.
+        safeguard_llm_config: Optional LLM configuration for safeguard checks.
+        mask_llm_config: Optional LLM configuration for masking.
+        isolate_agent_views: If True, agents will only maintain their own message history
+            and will not receive messages from other agents. When False (default), all agents
+            receive all messages. When True, messages are still stored in groupchat.messages
+            for the GroupChatManager's view, but are not broadcast to other agents.
+
+    Returns:
+        AsyncRunResponseProtocol: Response object for tracking the async execution.
+    """
     iostream = AsyncThreadIOStream()
     all_agents = pattern.agents + ([pattern.user_agent] if pattern.user_agent else [])
     response = AsyncRunResponse(iostream, agents=all_agents)
@@ -259,6 +309,7 @@ async def _initiate_group_chat(
         safeguard_policy: dict[str, Any] | str | None = safeguard_policy,
         safeguard_llm_config: LLMConfig | None = safeguard_llm_config,
         mask_llm_config: LLMConfig | None = mask_llm_config,
+        isolate_agent_views: bool = isolate_agent_views,
         iostream: AsyncThreadIOStream = iostream,
         response: AsyncRunResponse = response,
     ) -> None:
@@ -271,6 +322,7 @@ async def _initiate_group_chat(
                     safeguard_policy=safeguard_policy,
                     safeguard_llm_config=safeguard_llm_config,
                     mask_llm_config=mask_llm_config,
+                    isolate_agent_views=isolate_agent_views,
                 )
 
                 IOStream.get_default().send(

autogen/agentchat/group/patterns/auto.py

@@ -72,6 +72,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -96,6 +97,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing all necessary components for the group chat.
@@ -120,6 +125,7 @@ def prepare_group_chat(
         components = super().prepare_group_chat(
             max_rounds=max_rounds,
             messages=messages,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Extract the group_after_work and the rest of the components

autogen/agentchat/group/patterns/manual.py

@@ -59,6 +59,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -83,6 +84,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing all necessary components for the group chat.
@@ -91,6 +96,7 @@ def prepare_group_chat(
         components = super().prepare_group_chat(
             max_rounds=max_rounds,
             messages=messages,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Extract the group_after_work and the rest of the components

autogen/agentchat/group/patterns/pattern.py

@@ -76,6 +76,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -99,6 +100,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing:
@@ -147,6 +152,7 @@ def prepare_group_chat(
             messages=[],
             max_round=max_rounds,
             speaker_selection_method=group_transition,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Create the group manager
@@ -230,6 +236,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -253,6 +260,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing all necessary components for the group chat.
@@ -275,6 +286,7 @@ def prepare_group_chat(
         ) = super().prepare_group_chat(
             max_rounds=max_rounds,
             messages=messages,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Return all components with our group_after_work

autogen/agentchat/group/patterns/random.py

@@ -37,6 +37,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -61,6 +62,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing all necessary components for the group chat.
@@ -83,6 +88,7 @@ def prepare_group_chat(
         ) = super().prepare_group_chat(
             max_rounds=max_rounds,
             messages=messages,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Create the random handoffs between agents

autogen/agentchat/group/patterns/round_robin.py

@@ -48,6 +48,7 @@ def prepare_group_chat(
         self,
         max_rounds: int,
         messages: list[dict[str, Any]] | str,
+        isolate_agent_views: bool = False,
     ) -> tuple[
         list["ConversableAgent"],
         list["ConversableAgent"],
@@ -72,6 +73,10 @@ def prepare_group_chat(
         Args:
             max_rounds: Maximum number of conversation rounds.
             messages: Initial message(s) to start the conversation.
+            isolate_agent_views: If True, agents will only maintain their own message history
+                and will not receive messages from other agents. When False (default), all agents
+                receive all messages. When True, messages are still stored in groupchat.messages
+                for the GroupChatManager's view, but are not broadcast to other agents.
 
         Returns:
             Tuple containing all necessary components for the group chat.
@@ -94,6 +99,7 @@ def prepare_group_chat(
         ) = super().prepare_group_chat(
             max_rounds=max_rounds,
             messages=messages,
+            isolate_agent_views=isolate_agent_views,
         )
 
         # Create the handoffs between agents