text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKUse casesQA and Chat over DocumentsAnalyzing structured dataExtractionInteracting with APIsChatbotsSummarizationCode UnderstandingAgent simulationsCAMEL Role-Playing Autonomous Cooperative AgentsGenerative Agents in LangChainSimulated Environment: GymnasiumMulti-Player Dungeons & DragonsMulti-agent authoritarian speaker selectionMulti-agent decentralized speaker selectionMulti-Agent Simulated Environment: Petting ZooAgent Debates with ToolsTwo-Player Dungeons & DragonsAgentsAutonomous (long-running) agentsMulti-modalUse casesAgent simulationsAgent Debates with ToolsOn this pageAgent Debates with ToolsThis example shows how to simulate multi-agent dialogues where agents have access to tools.Import LangChain related modulesâ€‹from typing import List, Dict, Callablefrom langchain.chains import ConversationChainfrom langchain.chat_models import ChatOpenAIfrom langchain.llms import OpenAIfrom langchain.memory import ConversationBufferMemoryfrom langchain.prompts.prompt import PromptTemplatefrom langchain.schema import (    AIMessage,    HumanMessage,    SystemMessage,    BaseMessage,)Import modules related to toolsâ€‹from langchain.agents import Toolfrom langchain.agents import initialize_agentfrom langchain.agents import AgentTypefrom langchain.agents import load_toolsDialogueAgent and DialogueSimulator classesâ€‹We will use the same DialogueAgent and DialogueSimulator classes defined in Multi-Player Authoritarian Speaker Selection.class DialogueAgent:    def __init__(        self,        name: str,        system_message: SystemMessage,        model: ChatOpenAI,    ) -> None:        self.name = name