text: Chatbots | ğŸ¦œï¸�ğŸ”— Langchain
  
  
  
  
  
  Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKUse casesQA and Chat over DocumentsAnalyzing structured dataExtractionInteracting with APIsChatbotsVoice AssistantSummarizationCode UnderstandingAgent simulationsAgentsAutonomous (long-running) agentsMulti-modalUse casesChatbotsChatbotsSince language models are good at producing text, that makes them ideal for creating chatbots.
  Aside from the base prompts/LLMs, an important concept to know for Chatbots is memory.
  Most chat based applications rely on remembering what happened in previous interactions, which memory is designed to help with.The following resources exist:ChatGPT Clone: A notebook walking through how to recreate a ChatGPT-like experience with LangChain.Conversation Agent: A notebook walking through how to create an agent optimized for conversation.Additional related resources include:Memory concepts and examples: Explanation of key concepts related to memory along with how-to's and examples.More end-to-end examples include:Voice Assistant: A notebook walking through how to create a voice assistant using LangChain.PreviousInteracting with APIsNextVoice AssistantCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.