Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKGet startedIntroductionInstallationQuickstartLangChain Expression LanguageInterfaceHow toCookbookLangChain Expression Language (LCEL)Why use LCEL?ModulesModel I/‚ÄãORetrievalDocument loadersCSVFile DirectoryHTMLJSONMarkdownPDFDocument transformersText embedding modelsVector storesRetrieversIndexingChainsMemoryAgentsCallbacksModulesSecurityGuidesMoreModulesRetrievalDocument loadersMarkdownOn this pageMarkdownMarkdown is a lightweight markup language for creating formatted text using a plain-text editor.This covers how to load Markdown documents into a document format that we can use downstream.# !pip install unstructured > /dev/nullfrom langchain.document_loaders import UnstructuredMarkdownLoadermarkdown_path = "../../../../../README.md"loader = UnstructuredMarkdownLoader(markdown_path)data = loader.load()data    [Document(page_content="√∞\x9f¬¶\x9c√Ø¬∏\x8f√∞\x9f‚Äù\x97 LangChain\n\n√¢\x9a¬° Building applications with LLMs through composability √¢\x9a¬°\n\nLooking for the JS/TS version? Check out LangChain.js.\n\nProduction Support: As you move your LangChains into production, we'd love to offer more comprehensive support.\nPlease fill out this form and we'll set up a dedicated support Slack channel.\n\nQuick Install\n\npip install langchain\nor\nconda install langchain -c conda-forge\n\n√∞\x9f¬§‚Äù What is this?\n\nLarge language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. However, using these LLMs in isolation is often insufficient for creating a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge.\n\nThis library aims to assist in the development of those types of applications. Common examples of these applications include:\n\n√¢\x9d‚Äú Question Answering over specific
Markdown is a lightweight markup language for creating formatted text using a plain-text editor.
Markdown is a lightweight markup language for creating formatted text using a plain-text editor. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKGet startedIntroductionInstallationQuickstartLangChain Expression LanguageInterfaceHow toCookbookLangChain Expression Language (LCEL)Why use LCEL?ModulesModel I/‚ÄãORetrievalDocument loadersCSVFile DirectoryHTMLJSONMarkdownPDFDocument transformersText embedding modelsVector storesRetrieversIndexingChainsMemoryAgentsCallbacksModulesSecurityGuidesMoreModulesRetrievalDocument loadersMarkdownOn this pageMarkdownMarkdown is a lightweight markup language for creating formatted text using a plain-text editor.This covers how to load Markdown documents into a document format that we can use downstream.# !pip install unstructured > /dev/nullfrom langchain.document_loaders import UnstructuredMarkdownLoadermarkdown_path = "../../../../../README.md"loader = UnstructuredMarkdownLoader(markdown_path)data = loader.load()data    [Document(page_content="√∞\x9f¬¶\x9c√Ø¬∏\x8f√∞\x9f‚Äù\x97 LangChain\n\n√¢\x9a¬° Building applications with LLMs through composability √¢\x9a¬°\n\nLooking for the JS/TS version? Check out LangChain.js.\n\nProduction Support: As you move your LangChains into production, we'd love to offer more comprehensive support.\nPlease fill out this form and we'll set up a dedicated support Slack channel.\n\nQuick Install\n\npip install langchain\nor\nconda install langchain -c conda-forge\n\n√∞\x9f¬§‚Äù What is this?\n\nLarge language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. However, using these LLMs in isolation is often insufficient for creating a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge.\n\nThis library aims to assist in the development of those types of applications. Common examples of these applications include:\n\n√¢\x9d‚Äú Question Answering over specific