Rename Responsive -> Conversable

flaml/autogen/agentchat/__init__.py

@@ -1,12 +1,12 @@
 from .agent import Agent
-from .responsive_agent import ResponsiveAgent
+from .conversable_agent import ConversableAgent
 from .assistant_agent import AssistantAgent
 from .user_proxy_agent import UserProxyAgent
 from .groupchat import GroupChat, GroupChatManager
 
 __all__ = [
     "Agent",
-    "ResponsiveAgent",
+    "ConversableAgent",
     "AssistantAgent",
     "UserProxyAgent",
     "GroupChat",

flaml/autogen/agentchat/assistant_agent.py

@@ -1,11 +1,11 @@
-from .responsive_agent import ResponsiveAgent
+from .conversable_agent import ConversableAgent
 from typing import Callable, Dict, Optional, Union
 
 
-class AssistantAgent(ResponsiveAgent):
+class AssistantAgent(ConversableAgent):
     """(In preview) Assistant agent, designed to solve a task with LLM.
 
-    AssistantAgent is a subclass of ResponsiveAgent configured with a default system message.
+    AssistantAgent is a subclass of ConversableAgent configured with a default system message.
     The default system message is designed to solve a task with LLM,
     including suggesting python code blocks and debugging.
     `human_input_mode` is default to "NEVER"
@@ -52,7 +52,7 @@ def __init__(
                 default to None (no limit provided, class attribute MAX_CONSECUTIVE_AUTO_REPLY will be used as the limit in this case).
                 The limit only plays a role when human_input_mode is not "ALWAYS".
             **kwargs (dict): Please refer to other kwargs in
-                [ResponsiveAgent](responsive_agent#__init__).
+                [ConversableAgent](conversable_agent#__init__).
         """
         super().__init__(
             name,

flaml/autogen/agentchat/contrib/math_user_proxy_agent.py

@@ -165,7 +165,7 @@ def __init__(
             default_auto_reply=default_auto_reply,
             **kwargs,
         )
-        self.register_auto_reply([Agent, None], MathUserProxyAgent._generate_math_reply, 1)
+        self.register_reply([Agent, None], MathUserProxyAgent._generate_math_reply, 1)
         # fixed var
         self._max_invalid_q_per_step = max_invalid_q_per_step
 

flaml/autogen/agentchat/contrib/retrieve_assistant_agent.py

@@ -16,7 +16,7 @@ class RetrieveAssistantAgent(AssistantAgent):
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.register_auto_reply(Agent, RetrieveAssistantAgent._generate_retrieve_assistant_reply)
+        self.register_reply(Agent, RetrieveAssistantAgent._generate_retrieve_assistant_reply)
 
     def _generate_retrieve_assistant_reply(
         self,

flaml/autogen/agentchat/contrib/retrieve_user_proxy_agent.py

@@ -148,7 +148,7 @@ def __init__(
         self._ipython = get_ipython()
         self._doc_idx = -1  # the index of the current used doc
         self._results = {}  # the results of the current query
-        self.register_auto_reply(Agent, RetrieveUserProxyAgent._generate_retrieve_user_reply)
+        self.register_reply(Agent, RetrieveUserProxyAgent._generate_retrieve_user_reply)
 
     @staticmethod
     def get_max_tokens(model="gpt-3.5-turbo"):

flaml/autogen/agentchat/responsive_agent.py → flaml/autogen/agentchat/conversable_agent.py

@@ -21,11 +21,11 @@ def colored(x, *args, **kwargs):
         return x
 
 
-class ResponsiveAgent(Agent):
-    """(Experimental) A class for generic responsive agents which can be configured as assistant or user proxy.
+class ConversableAgent(Agent):
+    """(In preview) A class for generic conversable agents which can be configured as assistant or user proxy.
 
     After receiving each message, the agent will send a reply to the sender unless the msg is a termination msg.
-    For example, AssistantAgent and UserProxyAgent are subclasses of ResponsiveAgent,
+    For example, AssistantAgent and UserProxyAgent are subclasses of this class,
     configured with different default settings.
 
     To modify auto reply, override `generate_reply` method.
@@ -119,12 +119,12 @@ def __init__(
         self._default_auto_reply = default_auto_reply
         self._reply_func_list = []
         self.reply_at_receive = defaultdict(bool)
-        self.register_auto_reply([Agent, None], ResponsiveAgent.generate_oai_reply)
-        self.register_auto_reply([Agent, None], ResponsiveAgent.generate_code_execution_reply)
-        self.register_auto_reply([Agent, None], ResponsiveAgent.generate_function_call_reply)
-        self.register_auto_reply([Agent, None], ResponsiveAgent.check_termination_and_human_reply)
+        self.register_reply([Agent, None], ConversableAgent.generate_oai_reply)
+        self.register_reply([Agent, None], ConversableAgent.generate_code_execution_reply)
+        self.register_reply([Agent, None], ConversableAgent.generate_function_call_reply)
+        self.register_reply([Agent, None], ConversableAgent.check_termination_and_human_reply)
 
-    def register_auto_reply(
+    def register_reply(
         self,
         trigger: Union[Type[Agent], str, Agent, Callable[[Agent], bool], List],
         reply_func: Callable,
@@ -151,7 +151,7 @@ def register_auto_reply(
                 The function takes a recipient agent, a list of messages, a sender agent and a config as input and returns a reply message.
         ```python
         def reply_func(
-            recipient: ResponsiveAgent,
+            recipient: ConversableAgent,
             messages: Optional[List[Dict]] = None,
             sender: Optional[Agent] = None,
             config: Optional[Any] = None,
@@ -499,7 +499,7 @@ def _prepare_chat(self, recipient, clear_history):
 
     def initiate_chat(
         self,
-        recipient: "ResponsiveAgent",
+        recipient: "ConversableAgent",
         clear_history: Optional[bool] = True,
         silent: Optional[bool] = False,
         **context,
@@ -522,7 +522,7 @@ def initiate_chat(
 
     async def a_initiate_chat(
         self,
-        recipient: "ResponsiveAgent",
+        recipient: "ConversableAgent",
         clear_history: Optional[bool] = True,
         silent: Optional[bool] = False,
         **context,
@@ -610,8 +610,8 @@ def generate_code_execution_reply(
             return False, None
         if messages is None:
             messages = self._oai_messages[sender]
-        last_n_messages = min(len(messages), code_execution_config.pop("last_n_messages", 1))
-        for i in range(last_n_messages):
+        last_n_messages = code_execution_config.pop("last_n_messages", 1)
+        for i in range(min(len(messages), last_n_messages)):
             message = messages[-(i + 1)]
             code_blocks = extract_code(message["content"])
             if len(code_blocks) == 1 and code_blocks[0][0] == UNKNOWN:

flaml/autogen/agentchat/groupchat.py

@@ -2,7 +2,7 @@
 import sys
 from typing import Dict, List, Optional, Union
 from .agent import Agent
-from .responsive_agent import ResponsiveAgent
+from .conversable_agent import ConversableAgent
 
 
 @dataclass
@@ -39,7 +39,7 @@ def select_speaker_msg(self):
 Read the following conversation.
 Then select the next role from {self.agent_names} to play. Only return the role."""
 
-    def select_speaker(self, last_speaker: Agent, selector: ResponsiveAgent):
+    def select_speaker(self, last_speaker: Agent, selector: ConversableAgent):
         """Select the next speaker."""
         selector.update_system_message(self.select_speaker_msg())
         final, name = selector.generate_oai_reply(
@@ -63,7 +63,7 @@ def _participant_roles(self):
         return "\n".join([f"{agent.name}: {agent.system_message}" for agent in self.agents])
 
 
-class GroupChatManager(ResponsiveAgent):
+class GroupChatManager(ConversableAgent):
     """(In preview) A chat manager agent that can manage a group chat of multiple agents."""
 
     def __init__(
@@ -84,7 +84,7 @@ def __init__(
             system_message=system_message,
             **kwargs,
         )
-        self.register_auto_reply(Agent, GroupChatManager.run_chat, config=groupchat, reset_config=GroupChat.reset)
+        self.register_reply(Agent, GroupChatManager.run_chat, config=groupchat, reset_config=GroupChat.reset)
         # self._random = random.Random(seed)
 
     def run_chat(

flaml/autogen/agentchat/user_proxy_agent.py

@@ -1,14 +1,14 @@
-from .responsive_agent import ResponsiveAgent
+from .conversable_agent import ConversableAgent
 from typing import Callable, Dict, Optional, Union
 
 
-class UserProxyAgent(ResponsiveAgent):
+class UserProxyAgent(ConversableAgent):
     """(In preview) A proxy agent for the user, that can execute code and provide feedback to the other agents.
 
-    UserProxyAgent is a subclass of ResponsiveAgent configured with `human_input_mode` to ALWAYS
+    UserProxyAgent is a subclass of ConversableAgent configured with `human_input_mode` to ALWAYS
     and `llm_config` to False. By default, the agent will prompt for human input every time a message is received.
     Code execution is enabled by default. LLM-based auto reply is disabled by default.
-    To modify auto reply, register a method with (`register_auto_reply`)[responsive_agent#register_auto_reply].
+    To modify auto reply, register a method with (`register_reply`)[conversable_agent#register_reply].
     To modify the way to get human input, override `get_human_input` method.
     To modify the way to execute code blocks, single code block, or function call, override `execute_code_blocks`,
     `run_code`, and `execute_function` methods respectively.

flaml/version.py

@@ -1 +1 @@
-__version__ = "2.0.3"
+__version__ = "2.1.0"

notebook/autogen_agentchat_chess.ipynb

@@ -35,7 +35,7 @@
    "outputs": [],
    "source": [
     "%%capture --no-stderr\n",
-    "# %pip install flaml[autogen]~=2.0.0\n",
+    "# %pip install flaml[autogen]~=2.1.0\n",
     "%pip install chess -U"
    ]
   },
@@ -158,7 +158,7 @@
     "            llm_config={\"temperature\": 0.0, \"config_list\": config_list_gpt4},\n",
     "            max_consecutive_auto_reply=10,\n",
     "        )\n",
-    "        self.register_auto_reply(autogen.ResponsiveAgent, BoardAgent._generate_board_reply)\n",
+    "        self.register_reply(autogen.ConversableAgent, BoardAgent._generate_board_reply)\n",
     "        self.board = board\n",
     "        self.correct_move_messages = defaultdict(list)\n",
     "\n",
@@ -226,8 +226,8 @@
     "            max_consecutive_auto_reply=max_turns,\n",
     "            **kwargs,\n",
     "        )\n",
-    "        self.register_auto_reply(BoardAgent, ChessPlayerAgent._generate_reply_for_board, config=board_agent.board)\n",
-    "        self.register_auto_reply(ChessPlayerAgent, ChessPlayerAgent._generate_reply_for_player, config=board_agent)\n",
+    "        self.register_reply(BoardAgent, ChessPlayerAgent._generate_reply_for_board, config=board_agent.board)\n",
+    "        self.register_reply(ChessPlayerAgent, ChessPlayerAgent._generate_reply_for_player, config=board_agent)\n",
     "        self.update_max_consecutive_auto_reply(board_agent.max_consecutive_auto_reply(), board_agent)\n",
     "\n",
     "    def _generate_reply_for_board(\n",
@@ -262,7 +262,7 @@
     "            return True, None\n",
     "        # converse with the board until a legal move is made or max allowed retries.\n",
     "        # change silent to False to see that conversation.\n",
-    "        self.initiate_chat(board_agent, clear_history=False, message=message, silent=True)\n",
+    "        self.initiate_chat(board_agent, clear_history=False, message=message, silent=self.human_input_mode == \"NEVER\")\n",
     "        # last message sent by the board agent\n",
     "        last_message = self._oai_messages[board_agent][-1]\n",
     "        if last_message[\"role\"] == \"assistant\":\n",

notebook/autogen_agentchat_stream.ipynb

@@ -45,7 +45,7 @@
    },
    "outputs": [],
    "source": [
-    "# %pip install flaml[autogen]~=2.0.0"
+    "# %pip install flaml[autogen]~=2.1.0"
    ]
   },
   {
@@ -258,7 +258,7 @@
     "            )\n",
     "        return False, None\n",
     "\n",
-    "user_proxy.register_auto_reply(autogen.AssistantAgent, add_data_reply, 1, config={\"news_stream\": data})"
+    "user_proxy.register_reply(autogen.AssistantAgent, add_data_reply, 1, config={\"news_stream\": data})"
    ]
   },
   {

test/autogen/agentchat/test_async.py

@@ -98,7 +98,7 @@ async def add_data_reply(recipient, messages, sender, config):
                 )
             return False, None
 
-    user_proxy.register_auto_reply(autogen.AssistantAgent, add_data_reply, 1, config={"news_stream": data})
+    user_proxy.register_reply(autogen.AssistantAgent, add_data_reply, 1, config={"news_stream": data})
 
     await user_proxy.a_initiate_chat(
         assistant,

test/autogen/agentchat/test_responsive_agent.py → test/autogen/agentchat/test_conversable_agent.py

@@ -1,48 +1,48 @@
 import pytest
-from flaml.autogen.agentchat import ResponsiveAgent
+from flaml.autogen.agentchat import ConversableAgent
 
 
 def test_trigger():
-    agent = ResponsiveAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER")
-    agent1 = ResponsiveAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
-    agent.register_auto_reply(agent1, lambda recipient, messages, sender, config: (True, "hello"))
+    agent = ConversableAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER")
+    agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
+    agent.register_reply(agent1, lambda recipient, messages, sender, config: (True, "hello"))
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello"
-    agent.register_auto_reply("a1", lambda recipient, messages, sender, config: (True, "hello a1"))
+    agent.register_reply("a1", lambda recipient, messages, sender, config: (True, "hello a1"))
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello a1"
-    agent.register_auto_reply(
-        ResponsiveAgent, lambda recipient, messages, sender, config: (True, "hello responsive agent")
+    agent.register_reply(
+        ConversableAgent, lambda recipient, messages, sender, config: (True, "hello conversable agent")
     )
     agent1.initiate_chat(agent, message="hi")
-    assert agent1.last_message(agent)["content"] == "hello responsive agent"
-    agent.register_auto_reply(
+    assert agent1.last_message(agent)["content"] == "hello conversable agent"
+    agent.register_reply(
         lambda sender: sender.name.startswith("a"), lambda recipient, messages, sender, config: (True, "hello a")
     )
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello a"
-    agent.register_auto_reply(
+    agent.register_reply(
         lambda sender: sender.name.startswith("b"), lambda recipient, messages, sender, config: (True, "hello b")
     )
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello a"
-    agent.register_auto_reply(
+    agent.register_reply(
         ["agent2", agent1], lambda recipient, messages, sender, config: (True, "hello agent2 or agent1")
     )
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello agent2 or agent1"
-    agent.register_auto_reply(
+    agent.register_reply(
         ["agent2", "agent3"], lambda recipient, messages, sender, config: (True, "hello agent2 or agent3")
     )
     agent1.initiate_chat(agent, message="hi")
     assert agent1.last_message(agent)["content"] == "hello agent2 or agent1"
-    pytest.raises(ValueError, agent.register_auto_reply, 1, lambda recipient, messages, sender, config: (True, "hi"))
+    pytest.raises(ValueError, agent.register_reply, 1, lambda recipient, messages, sender, config: (True, "hi"))
     pytest.raises(ValueError, agent._match_trigger, 1, agent1)
 
 
 def test_context():
-    agent = ResponsiveAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER")
-    agent1 = ResponsiveAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
+    agent = ConversableAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER")
+    agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
     agent1.send(
         {
             "content": "hello {name}",
@@ -77,8 +77,8 @@ def test_context():
 
 
 def test_max_consecutive_auto_reply():
-    agent = ResponsiveAgent("a0", max_consecutive_auto_reply=2, llm_config=False, human_input_mode="NEVER")
-    agent1 = ResponsiveAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
+    agent = ConversableAgent("a0", max_consecutive_auto_reply=2, llm_config=False, human_input_mode="NEVER")
+    agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER")
     assert agent.max_consecutive_auto_reply() == agent.max_consecutive_auto_reply(agent1) == 2
     agent.update_max_consecutive_auto_reply(1)
     assert agent.max_consecutive_auto_reply() == agent.max_consecutive_auto_reply(agent1) == 1
@@ -105,9 +105,9 @@ def test_max_consecutive_auto_reply():
     assert agent1.reply_at_receive[agent] is False and agent.reply_at_receive[agent1] is True
 
 
-def test_responsive_agent():
-    dummy_agent_1 = ResponsiveAgent(name="dummy_agent_1", human_input_mode="ALWAYS")
-    dummy_agent_2 = ResponsiveAgent(name="dummy_agent_2", human_input_mode="TERMINATE")
+def test_conversable_agent():
+    dummy_agent_1 = ConversableAgent(name="dummy_agent_1", human_input_mode="ALWAYS")
+    dummy_agent_2 = ConversableAgent(name="dummy_agent_2", human_input_mode="TERMINATE")
 
     # monkeypatch.setattr(sys, "stdin", StringIO("exit"))
     dummy_agent_1.receive("hello", dummy_agent_2)  # receive a str
@@ -159,7 +159,7 @@ def add_num(num_to_be_added):
         given_num = 10
         return num_to_be_added + given_num
 
-    dummy_agent_2 = ResponsiveAgent(name="user_proxy", human_input_mode="TERMINATE", function_map={"add_num": add_num})
+    dummy_agent_2 = ConversableAgent(name="user_proxy", human_input_mode="TERMINATE", function_map={"add_num": add_num})
     messsages = [{"function_call": {"name": "add_num", "arguments": '{ "num_to_be_added": 5 }'}, "role": "assistant"}]
 
     # when sender is None, messages is provided
@@ -168,7 +168,7 @@ def add_num(num_to_be_added):
     ), "generate_reply not working when sender is None"
 
     # when sender is provided, messages is None
-    dummy_agent_1 = ResponsiveAgent(name="dummy_agent_1", human_input_mode="ALWAYS")
+    dummy_agent_1 = ConversableAgent(name="dummy_agent_1", human_input_mode="ALWAYS")
     dummy_agent_2._oai_messages[dummy_agent_1] = messsages
     assert (
         dummy_agent_2.generate_reply(messages=None, sender=dummy_agent_1)["content"] == "15"
@@ -179,4 +179,4 @@ def add_num(num_to_be_added):
     test_trigger()
     # test_context()
     # test_max_consecutive_auto_reply()
-    # test_responsive_agent(pytest.monkeypatch)
+    # test_conversable_agent(pytest.monkeypatch)