initate chats enhancement (#2404)

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

autogen/agentchat/chat.py

@@ -171,6 +171,9 @@ def initiate_chats(chat_queue: List[Dict[str, Any]]) -> List[ChatResult]:
             - `"carryover"` - It can be used to specify the carryover information to be passed
                to this chat. If provided, we will combine this carryover with the "message" content when
                generating the initial chat message in `generate_init_message`.
+            - `"finished_chat_indexes_to_exclude_from_carryover"` - It can be used by specifying a list of indexes of the finished_chats list,
+               from which to exclude the summaries for carryover. If 'finished_chat_indexes_to_exclude_from_carryover' is not provided or an empty list,
+               then summary from all the finished chats will be taken.
     Returns:
         (list): a list of ChatResult objects corresponding to the finished chats in the chat_queue.
     """
@@ -182,9 +185,16 @@ def initiate_chats(chat_queue: List[Dict[str, Any]]) -> List[ChatResult]:
     while current_chat_queue:
         chat_info = current_chat_queue.pop(0)
         _chat_carryover = chat_info.get("carryover", [])
+        finished_chat_indexes_to_exclude_from_carryover = chat_info.get(
+            "finished_chat_indexes_to_exclude_from_carryover", []
+        )
+
         if isinstance(_chat_carryover, str):
             _chat_carryover = [_chat_carryover]
-        chat_info["carryover"] = _chat_carryover + [r.summary for r in finished_chats]
+        chat_info["carryover"] = _chat_carryover + [
+            r.summary for i, r in enumerate(finished_chats) if i not in finished_chat_indexes_to_exclude_from_carryover
+        ]
+
         __post_carryover_processing(chat_info)
         sender = chat_info["sender"]
         chat_res = sender.initiate_chat(**chat_info)

autogen/agentchat/conversable_agent.py

@@ -1180,6 +1180,23 @@ class ConversableAgent(LLMAgent):
         response = self._generate_oai_reply_from_client(llm_client=llm_client, messages=messages, cache=cache)
         return response
 
+    def _check_chat_queue_for_sender(self, chat_queue: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """
+        Check the chat queue and add the "sender" key if it's missing.
+
+        Args:
+            chat_queue (List[Dict[str, Any]]): A list of dictionaries containing chat information.
+
+        Returns:
+            List[Dict[str, Any]]: A new list of dictionaries with the "sender" key added if it was missing.
+        """
+        chat_queue_with_sender = []
+        for chat_info in chat_queue:
+            if chat_info.get("sender") is None:
+                chat_info["sender"] = self
+            chat_queue_with_sender.append(chat_info)
+        return chat_queue_with_sender
+
     def initiate_chats(self, chat_queue: List[Dict[str, Any]]) -> List[ChatResult]:
         """(Experimental) Initiate chats with multiple agents.
 
@@ -1189,16 +1206,13 @@ class ConversableAgent(LLMAgent):
 
         Returns: a list of ChatResult objects corresponding to the finished chats in the chat_queue.
         """
-        _chat_queue = chat_queue.copy()
-        for chat_info in _chat_queue:
-            chat_info["sender"] = self
+        _chat_queue = self._check_chat_queue_for_sender(chat_queue)
         self._finished_chats = initiate_chats(_chat_queue)
         return self._finished_chats
 
     async def a_initiate_chats(self, chat_queue: List[Dict[str, Any]]) -> Dict[int, ChatResult]:
-        _chat_queue = chat_queue.copy()
-        for chat_info in _chat_queue:
-            chat_info["sender"] = self
+
+        _chat_queue = self._check_chat_queue_for_sender(chat_queue)
         self._finished_chats = await a_initiate_chats(_chat_queue)
         return self._finished_chats