text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKUse casesQA and Chat over DocumentsAnalyzing structured dataExtractionInteracting with APIsChatbotsSummarizationCode UnderstandingAgent simulationsAgentsBabyAGI User GuideBabyAGI with ToolsCAMEL Role-Playing Autonomous Cooperative AgentsCustom Agent with PlugIn RetrievalPlug-and-Plaimulti_modal_output_agentSalesGPT - Your Context-Aware AI Sales Assistant With Knowledge BaseWikibase AgentAutonomous (long-running) agentsMulti-modalUse casesAgentsOn this pageAgentsAgents can be used for a variety of tasks.
  Agents combine the decision making ability of a language model with tools in order to create a system
  that can execute and implement solutions on your behalf. Before reading any more, it is highly
  recommended that you read the documentation in the agent module to understand the concepts associated with agents more.
  Specifically, you should be familiar with what the agent, tool, and agent executor abstractions are before reading more.Agent documentation (for interacting with the outside world)Create Your Own Agentâ€‹Once you have read that documentation, you should be prepared to create your own agent.
  What exactly does that involve?
  Here's how we recommend getting started with creating your own agent:Step 1: Create Toolsâ€‹Agents are largely defined by the tools they can use.
  If you have a specific task you want the agent to accomplish, you have to give it access to the right tools.
  We have many tools natively in LangChain, so you should first look to see if any of them meet your needs.