Update speaker selector in GroupChat and update some notebooks (#688)

* Add speaker selection methods

* Update groupchat RAG

* Update seed to cache_seed

* Update RetrieveChat notebook

* Update parameter name

* Add test

* Add more tests

* Add mock to test

* Add mock to test

* Fix typo speaking

* Add gracefully exit manual input

* Update round_robin docstring

* Add method checking

* Remove participant roles

* Fix versions in notebooks

* Minimize installation overhead

* Fix missing lower()

* Add comments for try_count 3

* Update warning for n_agents < 3

* Update warning for n_agents < 3

* Add test_n_agents_less_than_3

* Add a function for manual select

* Update version in notebooks

* Fixed bugs that allow speakers to go twice in a row even when allow_repeat_speaker = False

---------

Co-authored-by: Adam Fourney <adamfo@microsoft.com>

.github/workflows/build.yml

@@ -40,7 +40,7 @@ jobs:
           python -m pip install --upgrade pip wheel
           pip install -e .
           python -c "import autogen"
-          pip install -e. pytest
+          pip install -e. pytest mock
           pip uninstall -y openai
       - name: Install unstructured if not windows
         if: matrix.os != 'windows-2019'

autogen/agentchat/groupchat.py

@@ -1,5 +1,6 @@
 import logging
 import sys
+import random
 from dataclasses import dataclass
 from typing import Dict, List, Optional, Union
 import re
@@ -21,6 +22,13 @@ class GroupChat:
         When set to True and when a message is a function call suggestion,
         the next speaker will be chosen from an agent which contains the corresponding function name
         in its `function_map`.
+    - speaker_selection_method: the method for selecting the next speaker. Default is "auto".
+        Could be any of the following (case insensitive), will raise ValueError if not recognized:
+        - "auto": the next speaker is selected automatically by LLM.
+        - "manual": the next speaker is selected manually by user input.
+        - "random": the next speaker is selected randomly.
+        - "round_robin": the next speaker is selected in a round robin fashion, i.e., iterating in the same order as provided in `agents`.
+    - allow_repeat_speaker: whether to allow the same speaker to speak consecutively. Default is True.
     """
 
     agents: List[Agent]
@@ -28,6 +36,10 @@ class GroupChat:
     max_round: int = 10
     admin_name: str = "Admin"
     func_call_filter: bool = True
+    speaker_selection_method: str = "auto"
+    allow_repeat_speaker: bool = True
+
+    _VALID_SPEAKER_SELECTION_METHODS = ["auto", "manual", "random", "round_robin"]
 
     @property
     def agent_names(self) -> List[str]:
@@ -55,13 +67,61 @@ class GroupChat:
     def select_speaker_msg(self, agents: List[Agent]):
         """Return the message for selecting the next speaker."""
         return f"""You are in a role play game. The following roles are available:
-{self._participant_roles()}.
+{self._participant_roles(agents)}.
 
 Read the following conversation.
 Then select the next role from {[agent.name for agent in agents]} to play. Only return the role."""
 
+    def manual_select_speaker(self, agents: List[Agent]) -> Agent:
+        """Manually select the next speaker."""
+
+        print("Please select the next speaker from the following list:")
+        _n_agents = len(agents)
+        for i in range(_n_agents):
+            print(f"{i+1}: {agents[i].name}")
+        try_count = 0
+        # Assume the user will enter a valid number within 3 tries, otherwise use auto selection to avoid blocking.
+        while try_count <= 3:
+            try_count += 1
+            if try_count >= 3:
+                print(f"You have tried {try_count} times. The next speaker will be selected automatically.")
+                break
+            try:
+                i = input("Enter the number of the next speaker (enter nothing or `q` to use auto selection): ")
+                if i == "" or i == "q":
+                    break
+                i = int(i)
+                if i > 0 and i <= _n_agents:
+                    return agents[i - 1]
+                else:
+                    raise ValueError
+            except ValueError:
+                print(f"Invalid input. Please enter a number between 1 and {_n_agents}.")
+        return None
+
     def select_speaker(self, last_speaker: Agent, selector: ConversableAgent):
         """Select the next speaker."""
+        if self.speaker_selection_method.lower() not in self._VALID_SPEAKER_SELECTION_METHODS:
+            raise ValueError(
+                f"GroupChat speaker_selection_method is set to '{self.speaker_selection_method}'. "
+                f"It should be one of {self._VALID_SPEAKER_SELECTION_METHODS} (case insensitive). "
+            )
+
+        agents = self.agents
+        n_agents = len(agents)
+        # Warn if GroupChat is underpopulated
+        if n_agents < 2:
+            raise ValueError(
+                f"GroupChat is underpopulated with {n_agents} agents. "
+                "Please add more agents to the GroupChat or use direct communication instead."
+            )
+        elif n_agents == 2 and self.speaker_selection_method.lower() != "round_robin" and self.allow_repeat_speaker:
+            logger.warning(
+                f"GroupChat is underpopulated with {n_agents} agents. "
+                "It is recommended to set speaker_selection_method to 'round_robin' or allow_repeat_speaker to False."
+                "Or, use direct communication instead."
+            )
+
         if self.func_call_filter and self.messages and "function_call" in self.messages[-1]:
             # find agents with the right function_map which contains the function name
             agents = [
@@ -80,14 +140,20 @@ Then select the next role from {[agent.name for agent in agents]} to play. Only
                         f"No agent can execute the function {self.messages[-1]['name']}. "
                         "Please check the function_map of the agents."
                     )
-        else:
-            agents = self.agents
-            # Warn if GroupChat is underpopulated
-            n_agents = len(agents)
-            if n_agents < 3:
-                logger.warning(
-                    f"GroupChat is underpopulated with {n_agents} agents. Direct communication would be more efficient."
-                )
+
+        # remove the last speaker from the list to avoid selecting the same speaker if allow_repeat_speaker is False
+        agents = agents if self.allow_repeat_speaker else [agent for agent in agents if agent != last_speaker]
+
+        if self.speaker_selection_method.lower() == "manual":
+            selected_agent = self.manual_select_speaker(agents)
+            if selected_agent:
+                return selected_agent
+        elif self.speaker_selection_method.lower() == "round_robin":
+            return self.next_agent(last_speaker, agents)
+        elif self.speaker_selection_method.lower() == "random":
+            return random.choice(agents)
+
+        # auto speaker selection
         selector.update_system_message(self.select_speaker_msg(agents))
         final, name = selector.generate_oai_reply(
             self.messages
@@ -99,26 +165,31 @@ Then select the next role from {[agent.name for agent in agents]} to play. Only
             ]
         )
         if not final:
-            # i = self._random.randint(0, len(self._agent_names) - 1)  # randomly pick an id
+            # the LLM client is None, thus no reply is generated. Use round robin instead.
             return self.next_agent(last_speaker, agents)
 
         # If exactly one agent is mentioned, use it. Otherwise, leave the OAI response unmodified
         mentions = self._mentioned_agents(name, agents)
         if len(mentions) == 1:
             name = next(iter(mentions))
+        else:
+            logger.warning(
+                f"GroupChat select_speaker failed to resolve the next speaker's name. This is because the speaker selection OAI call returned:\n{name}"
+            )
 
         # Return the result
         try:
             return self.agent_by_name(name)
         except ValueError:
-            logger.warning(
-                f"GroupChat select_speaker failed to resolve the next speaker's name. Speaker selection will default to the next speaker in the list. This is because the speaker selection OAI call returned:\n{name}"
-            )
             return self.next_agent(last_speaker, agents)
 
-    def _participant_roles(self):
+    def _participant_roles(self, agents: List[Agent] = None) -> str:
+        # Default to all agents registered
+        if agents is None:
+            agents = self.agents
+
         roles = []
-        for agent in self.agents:
+        for agent in agents:
             if agent.system_message.strip() == "":
                 logger.warning(
                     f"The agent '{agent.name}' has an empty system_message, and may not work well with GroupChat."

notebook/agentchat_qdrant_RetrieveChat.ipynb

@@ -29,10 +29,19 @@
     "\n",
     "AutoGen requires `Python>=3.8`. To run this notebook example, please install the [retrievechat] option.\n",
     "```bash\n",
-    "pip install \"pyautogen[retrievechat] flaml[automl] qdrant_client[fastembed]\"\n",
+    "pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\" \"qdrant_client[fastembed]\"\n",
     "```"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\" \"qdrant_client[fastembed]\""
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -165,7 +174,7 @@
     "    system_message=\"You are a helpful assistant.\",\n",
     "    llm_config={\n",
     "        \"timeout\": 600,\n",
-    "        \"seed\": 42,\n",
+    "        \"cache_seed\": 42,\n",
     "        \"config_list\": config_list,\n",
     "    },\n",
     ")\n",
@@ -1224,7 +1233,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

notebook/agentchat_teaching.ipynb

@@ -24,7 +24,7 @@
     "\n",
     "AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n",
     "```bash\n",
-    "pip install pyautogen\n",
+    "pip install \"pyautogen~=0.2.0b5\"\n",
     "```"
    ]
   },
@@ -34,7 +34,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# %pip install --quiet pyautogen~=0.1.0"
+    "# %pip install --quiet \"pyautogen~=0.2.0b5\""
    ]
   },
   {
@@ -85,7 +85,7 @@
     "\n",
     "llm_config={\n",
     "    \"timeout\": 600,\n",
-    "    \"seed\": 44,  # change the seed for different trials\n",
+    "    \"cache_seed\": 44,  # change the seed for different trials\n",
     "    \"config_list\": autogen.config_list_from_json(\n",
     "        \"OAI_CONFIG_LIST\",\n",
     "        filter_dict={\"model\": [\"gpt-4-32k\"]},\n",

setup.py

@@ -46,6 +46,7 @@ setuptools.setup(
             "pre-commit",
             "pytest-asyncio",
             "pytest>=6.1.1",
+            "mock",
         ],
         "blendsearch": ["flaml[blendsearch]"],
         "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"],

test/agentchat/test_groupchat.py

@@ -1,4 +1,6 @@
 import pytest
+import mock
+import builtins
 import autogen
 import json
 
@@ -8,7 +10,7 @@ def test_func_call_groupchat():
         "alice",
         human_input_mode="NEVER",
         llm_config=False,
-        default_auto_reply="This is alice sepaking.",
+        default_auto_reply="This is alice speaking.",
     )
     agent2 = autogen.ConversableAgent(
         "bob",
@@ -56,7 +58,7 @@ def test_chat_manager():
         max_consecutive_auto_reply=2,
         human_input_mode="NEVER",
         llm_config=False,
-        default_auto_reply="This is alice sepaking.",
+        default_auto_reply="This is alice speaking.",
     )
     agent2 = autogen.ConversableAgent(
         "bob",
@@ -83,6 +85,150 @@ def test_chat_manager():
         agent2.initiate_chat(group_chat_manager, message={"function_call": {"name": "func", "arguments": '{"x": 1}'}})
 
 
+def _test_selection_method(method: str):
+    agent1 = autogen.ConversableAgent(
+        "alice",
+        max_consecutive_auto_reply=10,
+        human_input_mode="NEVER",
+        llm_config=False,
+        default_auto_reply="This is alice speaking.",
+    )
+    agent2 = autogen.ConversableAgent(
+        "bob",
+        max_consecutive_auto_reply=10,
+        human_input_mode="NEVER",
+        llm_config=False,
+        default_auto_reply="This is bob speaking.",
+    )
+    agent3 = autogen.ConversableAgent(
+        "charlie",
+        max_consecutive_auto_reply=10,
+        human_input_mode="NEVER",
+        llm_config=False,
+        default_auto_reply="This is charlie speaking.",
+    )
+
+    groupchat = autogen.GroupChat(
+        agents=[agent1, agent2, agent3],
+        messages=[],
+        max_round=6,
+        speaker_selection_method=method,
+        allow_repeat_speaker=False if method == "manual" else True,
+    )
+    group_chat_manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=False)
+
+    if method == "round_robin":
+        agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+        assert len(agent1.chat_messages[group_chat_manager]) == 6
+        assert len(groupchat.messages) == 6
+        assert [msg["content"] for msg in agent1.chat_messages[group_chat_manager]] == [
+            "This is alice speaking.",
+            "This is bob speaking.",
+            "This is charlie speaking.",
+        ] * 2
+    elif method == "auto":
+        agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+        assert len(agent1.chat_messages[group_chat_manager]) == 6
+        assert len(groupchat.messages) == 6
+    elif method == "random":
+        agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+        assert len(agent1.chat_messages[group_chat_manager]) == 6
+        assert len(groupchat.messages) == 6
+    elif method == "manual":
+        for user_input in ["", "q", "x", "1", "10"]:
+            with mock.patch.object(builtins, "input", lambda _: user_input):
+                group_chat_manager.reset()
+                agent1.reset()
+                agent2.reset()
+                agent3.reset()
+                agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+                if user_input == "1":
+                    assert len(agent1.chat_messages[group_chat_manager]) == 6
+                    assert len(groupchat.messages) == 6
+                    assert [msg["content"] for msg in agent1.chat_messages[group_chat_manager]] == [
+                        "This is alice speaking.",
+                        "This is bob speaking.",
+                        "This is alice speaking.",
+                        "This is bob speaking.",
+                        "This is alice speaking.",
+                        "This is bob speaking.",
+                    ]
+                else:
+                    assert len(agent1.chat_messages[group_chat_manager]) == 6
+                    assert len(groupchat.messages) == 6
+    elif method == "wrong":
+        with pytest.raises(ValueError):
+            agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+
+
+def test_speaker_selection_method():
+    for method in ["auto", "round_robin", "random", "manual", "wrong", "RounD_roBin"]:
+        _test_selection_method(method)
+
+
+def _test_n_agents_less_than_3(method):
+    agent1 = autogen.ConversableAgent(
+        "alice",
+        max_consecutive_auto_reply=10,
+        human_input_mode="NEVER",
+        llm_config=False,
+        default_auto_reply="This is alice speaking.",
+    )
+    agent2 = autogen.ConversableAgent(
+        "bob",
+        max_consecutive_auto_reply=10,
+        human_input_mode="NEVER",
+        llm_config=False,
+        default_auto_reply="This is bob speaking.",
+    )
+    # test two agents
+    groupchat = autogen.GroupChat(
+        agents=[agent1, agent2],
+        messages=[],
+        max_round=6,
+        speaker_selection_method=method,
+        allow_repeat_speaker=True if method == "random" else False,
+    )
+    group_chat_manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=False)
+    agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+    assert len(agent1.chat_messages[group_chat_manager]) == 6
+    assert len(groupchat.messages) == 6
+    if method != "random" or method.lower() == "round_robin":
+        assert [msg["content"] for msg in agent1.chat_messages[group_chat_manager]] == [
+            "This is alice speaking.",
+            "This is bob speaking.",
+        ] * 3
+
+    # test one agent
+    groupchat = autogen.GroupChat(
+        agents=[agent1],
+        messages=[],
+        max_round=6,
+        speaker_selection_method="round_robin",
+        allow_repeat_speaker=False,
+    )
+    with pytest.raises(ValueError):
+        group_chat_manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=False)
+        agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+
+    # test zero agent
+    groupchat = autogen.GroupChat(
+        agents=[],
+        messages=[],
+        max_round=6,
+        speaker_selection_method="round_robin",
+        allow_repeat_speaker=False,
+    )
+    with pytest.raises(ValueError):
+        group_chat_manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=False)
+        agent1.initiate_chat(group_chat_manager, message="This is alice speaking.")
+
+
+def test_n_agents_less_than_3():
+    for method in ["auto", "round_robin", "random", "RounD_roBin"]:
+        _test_n_agents_less_than_3(method)
+
+
 def test_plugin():
     # Give another Agent class ability to manage group chat
     agent1 = autogen.ConversableAgent(
@@ -90,7 +236,7 @@ def test_plugin():
         max_consecutive_auto_reply=2,
         human_input_mode="NEVER",
         llm_config=False,
-        default_auto_reply="This is alice sepaking.",
+        default_auto_reply="This is alice speaking.",
     )
     agent2 = autogen.ConversableAgent(
         "bob",
@@ -185,8 +331,10 @@ def test_agent_mentions():
 
 
 if __name__ == "__main__":
-    test_func_call_groupchat()
+    # test_func_call_groupchat()
     # test_broadcast()
-    test_chat_manager()
+    # test_chat_manager()
     # test_plugin()
+    test_speaker_selection_method()
+    test_n_agents_less_than_3()
     # test_agent_mentions()