of memory implementations, and examples of chains/agents that use memory.\n\n√∞\x9f¬ß\x90 Evaluation:\n\n[BETA] Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this.\n\nFor more information on these concepts, please see our full documentation.\n\n√∞\x9f‚Äô\x81 Contributing\n\nAs an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.\n\nFor detailed information on how to contribute, see here.", metadata={'source': '../../../../../README.md'})]Retain Elements‚ÄãUnder the hood, Unstructured creates different "elements" for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying mode="elements".loader = UnstructuredMarkdownLoader(markdown_path, mode="elements")data = loader.load()data[0]    Document(page_content='√∞\x9f¬¶\x9c√Ø¬∏\x8f√∞\x9f‚Äù\x97 LangChain', metadata={'source': '../../../../../README.md', 'page_number': 1, 'category': 'Title'})PreviousJSONNextPDFRetain ElementsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
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. ->: of memory implementations, and examples of chains/agents that use memory.\n\n√∞\x9f¬ß\x90 Evaluation:\n\n[BETA] Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this.\n\nFor more information on these concepts, please see our full documentation.\n\n√∞\x9f‚Äô\x81 Contributing\n\nAs an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.\n\nFor detailed information on how to contribute, see here.", metadata={'source': '../../../../../README.md'})]Retain Elements‚ÄãUnder the hood, Unstructured creates different "elements" for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying mode="elements".loader = UnstructuredMarkdownLoader(markdown_path, mode="elements")data = loader.load()data[0]    Document(page_content='√∞\x9f¬¶\x9c√Ø¬∏\x8f√∞\x9f‚Äù\x97 LangChain', metadata={'source': '../../../../../README.md', 'page_number': 1, 'category': 'Title'})PreviousJSONNextPDFRetain ElementsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.