[Add] Function calling support for Autobuild

OAI_CONFIG_LIST_sample

@@ -21,4 +21,4 @@
         "api_type": "azure",
         "api_version": "2024-02-15-preview"
     }
-]
+]

autogen/agentchat/contrib/agent_builder.py

@@ -113,6 +113,19 @@ class AgentBuilder:
     # Only return the list of agent names.
     """
 
+    AGENT_FUNCTION_MAP_PROMPT = """Consider the following function.
+    Function Name: {function_name}
+    Function Description: {function_description}
+
+    The agent details are given in the format: {format_agent_details}
+
+    Which one of the following agents should be able to execute this function?
+    {agent_details}
+
+    Hint:
+    # Only respond with the name of the agent that is most suited to execute the function and nothing else.
+    """
+
     def __init__(
         self,
         config_file_or_env: Optional[str] = "OAI_CONFIG_LIST",
@@ -338,6 +351,7 @@ def build(
         self,
         building_task: str,
         default_llm_config: Dict,
+        list_of_functions: Optional[List[Dict]] = None,
         coding: Optional[bool] = None,
         code_execution_config: Optional[Dict] = None,
         use_oai_assistant: Optional[bool] = False,
@@ -461,7 +475,7 @@ def build(
             }
         )
 
-        return self._build_agents(use_oai_assistant, **kwargs)
+        return self._build_agents(use_oai_assistant, list_of_functions, **kwargs)
 
     def build_from_library(
         self,
@@ -631,7 +645,7 @@ def build_from_library(
         return self._build_agents(use_oai_assistant, **kwargs)
 
     def _build_agents(
-        self, use_oai_assistant: Optional[bool] = False, **kwargs
+        self, use_oai_assistant: Optional[bool] = False, list_of_functions: Optional[List[Dict]] = None, **kwargs
     ) -> Tuple[List[autogen.ConversableAgent], Dict]:
         """
         Build agents with generated configs.
@@ -680,6 +694,48 @@ def _build_agents(
                 + agent_list
             )
 
+            agent_details = []
+
+            for agent in agent_list[1:]:
+                agent_details.append({"name": agent.name, "description": agent.description})
+
+            config_list = autogen.config_list_from_json(
+                self.config_file_or_env,
+                file_location=self.config_file_location,
+                filter_dict={"model": [self.builder_model]},
+            )
+
+            build_manager = autogen.OpenAIWrapper(config_list=config_list)
+
+            for func in list_of_functions:
+                resp = (
+                    build_manager.create(
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": self.AGENT_FUNCTION_MAP_PROMPT.format(
+                                    function_name=func["name"],
+                                    function_description=func["description"],
+                                    format_agent_details='[{"name": "agent_name", "description": "agent description"}, ...]',
+                                    agent_details=str(json.dumps(agent_details)),
+                                ),
+                            }
+                        ]
+                    )
+                    .choices[0]
+                    .message.content
+                )
+
+                autogen.agentchat.register_function(
+                    func["function"],
+                    caller=self.agent_procs_assign[resp][0],
+                    executor=agent_list[0],
+                    name=func["name"],
+                    description=func["description"],
+                )
+
+                print(f"Function {func['name']} is registered to agent {resp}.")
+
         return agent_list, self.cached_configs.copy()
 
     def save(self, filepath: Optional[str] = None) -> str:

notebook/autobuild_function_calling.ipynb

@@ -0,0 +1,120 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'autogen.agentchat.contrib.agent_builder'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mautogen\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mautogen\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39magentchat\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mcontrib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39magent_builder\u001b[39;00m \u001b[39mimport\u001b[39;00m AgentBuilder\n\u001b[1;32m      4\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mIPython\u001b[39;00m \u001b[39mimport\u001b[39;00m get_ipython\n\u001b[1;32m      5\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtyping_extensions\u001b[39;00m \u001b[39mimport\u001b[39;00m Annotated\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'autogen.agentchat.contrib.agent_builder'"
+     ]
+    }
+   ],
+   "source": [
+    "import autogen\n",
+    "from autogen.agentchat.contrib.agent_builder import AgentBuilder\n",
+    "\n",
+    "from IPython import get_ipython\n",
+    "from typing_extensions import Annotated\n",
+    "\n",
+    "\n",
+    "config_file_or_env = \"/workspaces/autogen/OAI_CONFIG_LIST.json\"\n",
+    "\n",
+    "\n",
+    "def exec_python(cell: Annotated[str, \"Valid Python cell to execute.\"]) -> str:\n",
+    "    ipython = get_ipython()\n",
+    "    result = ipython.run_cell(cell)\n",
+    "    log = str(result.result)\n",
+    "    if result.error_before_exec is not None:\n",
+    "        log += f\"\\n{result.error_before_exec}\"\n",
+    "    if result.error_in_exec is not None:\n",
+    "        log += f\"\\n{result.error_in_exec}\"\n",
+    "    return log\n",
+    "\n",
+    "\n",
+    "config_list = autogen.config_list_from_json(config_file_or_env, filter_dict={\"model\": [\"gpt-4-1106-preview\", \"gpt-4\"]})\n",
+    "\n",
+    "\n",
+    "llm_config = {\n",
+    "    \"config_list\": config_list,\n",
+    "    \"timeout\": 120,\n",
+    "}\n",
+    "\n",
+    "def start_task(execution_task: str, agent_list: list):\n",
+    "    group_chat = autogen.GroupChat(agents=agent_list, messages=[], max_round=12)\n",
+    "    manager = autogen.GroupChatManager(groupchat=group_chat, llm_config={\"config_list\": config_list})\n",
+    "    agent_list[0].initiate_chat(manager, message=execution_task)\n",
+    "\n",
+    "\n",
+    "builder = AgentBuilder(\n",
+    "    config_file_or_env=config_file_or_env, builder_model=\"gpt-4-1106-preview\", agent_model=\"gpt-4-1106-preview\"\n",
+    ")\n",
+    "\n",
+    "building_task = \"Draw two agents chatting with each other with an example dialog using matplotlib. Don't add plt.show().\"\n",
+    "\n",
+    "list_of_functions = [\n",
+    "    {\"name\": \"exec_python\", \"description\": \"run cell in ipython and return the execution result.\", \"function\": exec_python}\n",
+    "]\n",
+    "\n",
+    "agent_list, agent_configs = builder.build(building_task, llm_config, list_of_functions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_task(\n",
+    "    execution_task=building_task,\n",
+    "    agent_list=agent_list\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "builder.clear_all_agents(recycle_endpoint=True)\n",
+    "\n",
+    "saved_path = builder.save()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}