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theorem for projective orbifolds ([11]). When p = d + 1 − s the proof relies on the Cayley trick, a trick which associates to X a quasi-smooth hypersurface Y in a projective vector bundle, and the Cayley Proposition (4.3) which gives an isomorphism of some primitive cohomologies (4.2) of X and Y . The Cayley trick, fol...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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N ⊗ Z R .\n\nif there exist k linearly independent primitive elements e\n\n, . . . , e k ∈ N such that σ = { µ\n\ne\n\n+ ⋯ + µ k e k } . • The generators e i are integral if for every i and any nonnegative rational number µ the product µe i is in N only if µ is an integer. • Given two rational simplicial cones σ , σ ′ ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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< σ and σ ∩ σ ′ < σ ′ ;\n\nN R = σ\n\n∪ ⋅ ⋅ ⋅ ∪ σ t .\n\nA rational simplicial complete d -dimensional fan Σ defines a d -dimensional toric variety P d Σ having only orbifold singularities which we assume to be projective. Moreover, T ∶ = N ⊗ Z C ∗ ≃ ( C ∗ ) d is the torus action on P d Σ . We denote by Σ ( i ) the i -d...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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locus Z ( Σ ) ∶ = V ( B Σ ) in the affine space A d ∶ = Spec ( S ) is the irrelevant locus.\n\nProposition 2.3 (Theorem 5.1.11 [5]) . The toric variety P d Σ is a categorical quotient A d ∖ Z ( Σ ) by the group Hom ( Cl ( Σ ) , C ∗ ) and the group action is induced by the Cl ( Σ ) - grading of S .\n\nNow we give a brief ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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A differential form on a complex orbifold Z is defined locally at z ∈ Z as a G -invariant differential form on C d where G ⊂ Gl ( d, C ) and Z is locally isomorphic to d\n\nRoughly speaking the local geometry of orbifolds reduces to local G -invariant geometry.\n\nWe have a complex of differential forms ( A ● ( Z ) , d ) a...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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. Quasi-smooth hypersurfaces or more generally quasi-smooth intersection sub-\n\nExample 3.2 . Quasi-smooth hypersurfaces or more generally quasi-smooth intersection sub- varieties are quasi-smooth subvarieties (see [2] or [7] for more details).\n\nRemark 3.3 . Quasi-smooth subvarieties are suborbifolds of P d Σ in the...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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/ H 2 ( X, O X ) ≃ Dolbeault H 2 ( X, C ) deRham ≃ H 2 dR ( X, C ) / / H 0 , 2 ¯ ∂ ( X )\n\nof the proof follows as the ( 1 , 1 ) -Lefschetz theorem in [6].\n\nRemark 3.5 . For k = 1 and P d Σ as the projective space, we recover the classical ( 1 , 1 ) - Lefschetz theorem.\n\nBy the Hard Lefschetz Theorem for projectiv...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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If the dimension of X is 1 , 2 or 3 . The Hodge conjecture holds on X\n\nProof. If the dim C X = 1 the result is clear by the Hard Lefschetz theorem for projective orbifolds. The dimension 2 and 3 cases are covered by Theorem 3.5 and the Hard Lefschetz.\n\nCayley trick and Cayley proposition\n\nThe Cayley trick is a wa...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Cox ring, without considering the grading, of P d Σ is C [ x 1 , . . . , x m ] then the Cox ring of P ( E ) is\n\nMoreover for X a quasi-smooth intersection subvariety cut off by f 1 , . . . , f s with deg ( f i ) = [ L i ] we relate the hypersurface Y cut off by F = y 1 f 1 + ⋅ ⋅ ⋅ + y s f s which turns out to be quasi-...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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y ) ∈ Y with y ≠ 0 has a preimage. Hence for any subvariety W = V ( I W ) ⊂ X ⊂ P d Σ there exists W ′ ⊂ Y ⊂ P d + s − 1 Σ ,X such that π ( W ′ ) = W , i.e., W ′ = { z = ( x, y ) ∣ x ∈ W } .\n\nFor X ⊂ P d Σ a quasi-smooth intersection variety the morphism in cohomology induced by the inclusion i ∗ ∶ H d − s ( P d Σ , ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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− s prim ( X, Q ) with rational coefficients.\n\nH d − s ( P d Σ , C ) and H d − s ( X, C ) have pure Hodge structures, and the morphism i ∗ is com- patible with them, so that H d − s prim ( X ) gets a pure Hodge structure.\n\nThe next Proposition is the Cayley proposition.\n\nProposition 4.3. [Proposition 2.3 in [3] ] L...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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C . See the beginning of Section 7.1 in [10] for more details.\n\nTheorem 5.1. Let Y = { F = y 1 f 1 + ⋯ + y k f k = 0 } ⊂ P 2 k + 1 Σ ,X be the quasi-smooth hypersurface associated to the quasi-smooth intersection surface X = X f 1 ∩ ⋅ ⋅ ⋅ ∩ X f k ⊂ P k + 2 Σ . Then on Y the Hodge conjecture holds.\n\nthe Hodge conjec...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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1 , . . . , λ C n with rational coefficients of H 1 , 1 prim ( X, Q ) , that is, there are n ∶ = h 1 , 1 prim ( X, Q ) algebraic curves C 1 , . . . , C n in X such that under the Poincar´e duality the class in homology [ C i ] goes to λ C i , [ C i ] ↦ λ C i . Recall that the Cox ring of P k + 2 is contained in the Cox r...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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degree. Moreover, by Remark 4.1 each C i is contained in Y = { F = y 1 f 1 + ⋯ + y k f k = 0 } and\n\nfurthermore it has codimension k .\n\nClaim: { C i } ni = 1 is a basis of prim ( ) . It is enough to prove that λ C i is different from zero in H k,k prim ( Y, Q ) or equivalently that the cohomology classes { λ C i } n...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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,X such that V ∩ Y = C j so they are equal as a homology class of P 2 k + 1 Σ ,X ,i.e., [ V ∩ Y ] = [ C j ] . It is easy to check that π ( V ) ∩ X = C j as a subvariety of P k + 2 Σ where π ∶ ( x, y ) ↦ x . Hence [ π ( V ) ∩ X ] = [ C j ] which is equivalent to say that λ C j comes from P k + 2 Σ which contradicts the ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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0 } ⊂ P 2 k + 1 Σ ,X be the quasi-smooth hypersurface associated to a quasi-smooth intersection subvariety X = X f 1 ∩ ⋅ ⋅ ⋅ ∩ X f s ⊂ P d Σ such that d + s = 2 ( k + 1 ) . If the Hodge conjecture holds on X then it holds as well on Y .\n\nCorollary 5.4. If the dimension of Y is 2 s − 1 , 2 s or 2 s + 1 then the Hodge ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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U., and Montoya, W. On the Hodge conjecture for quasi-smooth in- tersections in toric varieties. S˜ao Paulo J. Math. Sci. Special Section: Geometry in Algebra and Algebra in Geometry (\n\n). [\n\n] Caramello Jr, F. C. Introduction to orbifolds. a\n\niv:\n\nv\n\n(\n\n). [\n\n] Cox, D., Little, J., and Schenck, H. Toric ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Steenbrink, J. H. M. Intersection form for quasi-homogeneous singularities. Com- positio Mathematica\n\n,\n\n(\n\n),\n\n–\n\n[\n\n] Voisin, C. Hodge Theory and Complex Algebraic Geometry I, vol.\n\nof Cambridge Studies in Advanced Mathematics . Cambridge University Press,\n\n[\n\n] Wang, Z. Z., and Zaffran, D. A remark...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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U., and Montoya, W. On the Hodge conjecture for quasi-smooth in- tersections in toric varieties. S˜ao Paulo J. Math. Sci. Special Section: Geometry in Algebra and Algebra in Geometry (2021).\n\nA. R. Cohomology of complete intersections in toric varieties. Pub-', lookup_str='', metadata={'source': '/var/folders/ph/hhm7...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Using PDFMiner# from langchain.document_loaders import PDFMinerLoader loader = PDFMinerLoader("example_data/layout-parser-paper.pdf") data = loader.load() Using PyMuPDF# This is the fastest of the PDF parsing options, and contains detailed metadata about the PDF and its pages, as well as returns one document per page. ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Document(page_content='LayoutParser: A Unified Toolkit for Deep\nLearning Based Document Image Analysis\nZejiang Shen1 (�), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain\nLee4, Jacob Carlson3, and Weining Li5\n1 Allen Institute for AI\nshannons@allenai.org\n2 Brown University\nruochen zhang@brown.edu\n3 Harvar...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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processing and computer\nvision, none of them are optimized for challenges in the domain of DIA.\nThis represents a major gap in the existing toolkit, as DIA is central to\nacademic research across a wide range of disciplines in the social sciences\nand humanities. This paper introduces LayoutParser, an open-source\nli...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Learning(DL)-based approaches are the state-of-the-art for a wide range of\ndocument image analysis (DIA) tasks including document image classification [11,\narXiv:2103.15348v2 [cs.CV] 21 Jun 2021\n', lookup_str='', metadata={'file_path': 'example_data/layout-parser-paper.pdf', 'page_number': 1, 'total_pages': 16, 'fo...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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Additionally, you can pass along any of the options from the PyMuPDF documentation as keyword arguments in the load call, and it will be pass along to the get_text() call. previous Obsidian next PowerPoint Contents Using PyPDF Using Unstructured Retain Elements Fetching remote PDFs using Unstructured Using PDFMiner...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/pdf.html
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.ipynb .pdf Telegram Telegram# This notebook covers how to load data from Telegram into a format that can be ingested into LangChain. from langchain.document_loaders import TelegramChatLoader loader = TelegramChatLoader("example_data/telegram.json") loader.load() [Document(page_content="Henry on 2020-01-01T00:00:02: It...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/telegram.html
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.ipynb .pdf Microsoft Word Contents Retain Elements Microsoft Word# This notebook shows how to load text from Microsoft word documents. from langchain.document_loaders import UnstructuredDocxLoader loader = UnstructuredDocxLoader('example_data/fake.docx') data = loader.load() data [Document(page_content='Lorem ipsum ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/microsoft_word.html
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.ipynb .pdf Obsidian Obsidian# This notebook covers how to load documents from an Obsidian database. Since Obsidian is just stored on disk as a folder of Markdown files, the loader just takes a path to this directory. from langchain.document_loaders import ObsidianLoader loader = ObsidianLoader("<path-to-obsidian>") do...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/obsidian.html
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.ipynb .pdf YouTube Contents Add video info YouTube loader from Google Cloud Prerequisites 🧑 Instructions for ingesting your Google Docs data YouTube# How to load documents from YouTube transcripts. from langchain.document_loaders import YoutubeLoader # !pip install youtube-transcript-api loader = YoutubeLoader.from...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/youtube.html
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# Use a Channel youtube_loader_channel = GoogleApiYoutubeLoader(google_api_client=google_api_client, channel_name="Reducible",captions_language="en") # Use Youtube Ids youtube_loader_ids = GoogleApiYoutubeLoader(google_api_client=google_api_client, video_ids=["TrdevFK_am4"], add_video_info=True) # returns a list of Doc...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/youtube.html
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.ipynb .pdf Notebook Notebook# This notebook covers how to load data from an .ipynb notebook into a format suitable by LangChain. from langchain.document_loaders import NotebookLoader loader = NotebookLoader("example_data/notebook.ipynb", include_outputs=True, max_output_length=20, remove_newline=True) NotebookLoader.l...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/notebook.html
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traceback (bool): whether to include full traceback (default is False). loader.load() [Document(page_content='\'markdown\' cell: \'[\'# Notebook\', \'\', \'This notebook covers how to load data from an .ipynb notebook into a format suitable by LangChain.\']\'\n\n \'code\' cell: \'[\'from langchain.document_loaders impo...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/notebook.html
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.ipynb .pdf ReadTheDocs Documentation ReadTheDocs Documentation# This notebook covers how to load content from html that was generated as part of a Read-The-Docs build. For an example of this in the wild, see here. This assumes that the html has already been scraped into a folder. This can be done by uncommenting and r...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/readthedocs_documentation.html
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.ipynb .pdf Blackboard Blackboard# This covers how to load data from a Blackboard Learn instance. from langchain.document_loaders import BlackboardLoader loader = BlackboardLoader( blackboard_course_url="https://blackboard.example.com/webapps/blackboard/execute/announcement?method=search&context=course_entry&course...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/blackboard.html
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.ipynb .pdf CoNLL-U CoNLL-U# This is an example of how to load a file in CoNLL-U format. The whole file is treated as one document. The example data (conllu.conllu) is based on one of the standard UD/CoNLL-U examples. from langchain.document_loaders import CoNLLULoader loader = CoNLLULoader("example_data/conllu.conllu"...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/CoNLL-U.html
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.ipynb .pdf s3 File s3 File# This covers how to load document objects from an s3 file object. from langchain.document_loaders import S3FileLoader #!pip install boto3 loader = S3FileLoader("testing-hwc", "fake.docx") loader.load() [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/s3_file.html
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.ipynb .pdf Google Drive Contents Prerequisites 🧑 Instructions for ingesting your Google Docs data Google Drive# This notebook covers how to load documents from Google Drive. Currently, only Google Docs are supported. Prerequisites# Create a Google Cloud project or use an existing project Enable the Google Drive API...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/googledrive.html
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docs = loader.load() previous GitBook next Gutenberg Contents Prerequisites 🧑 Instructions for ingesting your Google Docs data By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/googledrive.html
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.ipynb .pdf Markdown Contents Retain Elements Markdown# This covers how to load markdown documents into a document format that we can use downstream. from langchain.document_loaders import UnstructuredMarkdownLoader loader = UnstructuredMarkdownLoader("../../../../README.md") data = loader.load() data
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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[Document(page_content="ð\x9f¦\x9cï¸\x8fð\x9f”\x97 LangChain\n\nâ\x9a¡ Building applications with LLMs through composability â\x9a¡\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 cha...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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Chatbots\n\nDocumentation\n\nEnd-to-end Example: Chat-LangChain\n\nð\x9f¤\x96 Agents\n\nDocumentation\n\nEnd-to-end Example: GPT+WolframAlpha\n\nð\x9f“\x96 Documentation\n\nPlease see here for full documentation on:\n\nGetting started (installation, setting up the environment, simple examples)\n\nHow-To examples (demos...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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chains for common applications.\n\nð\x9f“\x9a Data Augmented Generation:\n\nData Augmented Generation involves specific types of chains that first interact with an external datasource to fetch data to use in the generation step. Examples of this include summarization of long pieces of text and question/answering over s...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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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\nð\x9f’\x81 Contributing\n\nAs an open source project in a rapidly developing field, we are extremely open to contributi...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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Retain Elements# Under 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("../../../../README.md", mode="elements") data = loader.load() data[0]...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/markdown.html
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.ipynb .pdf Facebook Chat Facebook Chat# This notebook covers how to load data from the Facebook Chats into a format that can be ingested into LangChain. from langchain.document_loaders import FacebookChatLoader loader = FacebookChatLoader("example_data/facebook_chat.json") loader.load() [Document(page_content='User 2 ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/facebook_chat.html
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previous EverNote next GCS Directory By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/facebook_chat.html
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.ipynb .pdf GitBook Contents Load from single GitBook page Load from all paths in a given GitBook GitBook# How to pull page data from any GitBook. from langchain.document_loaders import GitbookLoader loader = GitbookLoader("https://docs.gitbook.com") Load from single GitBook page# page_data = loader.load() page_data ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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all_pages_data = loader.load() Fetching text from https://docs.gitbook.com/ Fetching text from https://docs.gitbook.com/getting-started/overview Fetching text from https://docs.gitbook.com/getting-started/import Fetching text from https://docs.gitbook.com/getting-started/git-sync Fetching text from https://docs.gitbook...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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Fetching text from https://docs.gitbook.com/troubleshooting/hard-refresh Fetching text from https://docs.gitbook.com/troubleshooting/report-bugs Fetching text from https://docs.gitbook.com/troubleshooting/connectivity-issues Fetching text from https://docs.gitbook.com/troubleshooting/support print(f"fetched {len(all_pa...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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Document(page_content="Import\nFind out how to easily migrate your existing documentation and which formats are supported.\nThe import function allows you to migrate and unify existing documentation in GitBook. You can choose to import single or multiple pages although limits apply. \nPermissions\nAll members with edit...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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in the page action menu, found in the table of contents:\nImport from the page action menu\nWhen you choose your input source, instructions will explain how to proceed.\nAlthough GitBook supports importing content from different kinds of sources, the end result might be different from your source due to differences in ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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previous GCS File Storage next Google Drive Contents Load from single GitBook page Load from all paths in a given GitBook By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gitbook.html
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.ipynb .pdf s3 Directory Contents Specifying a prefix s3 Directory# This covers how to load document objects from an s3 directory object. from langchain.document_loaders import S3DirectoryLoader #!pip install boto3 loader = S3DirectoryLoader("testing-hwc") loader.load() [Document(page_content='Lorem ipsum dolor sit a...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/s3_directory.html
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.ipynb .pdf Unstructured File Loader Contents Retain Elements Define a Partitioning Strategy PDF Example Unstructured File Loader# This notebook covers how to use Unstructured to load files of many types. Unstructured currently supports loading of text files, powerpoints, html, pdfs, images, and more. # # Install pac...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/unstructured_file.html
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loader = UnstructuredFileLoader("../../state_of_the_union.txt", mode="elements") docs = loader.load() docs[:5] [Document(page_content='Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans.', lookup_str='', metad...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/unstructured_file.html
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from langchain.document_loaders import UnstructuredFileLoader loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf", strategy="fast", mode="elements") docs = loader.load() docs[:5] [Document(page_content='1', lookup_str='', metadata={'source': 'layout-parser-paper-fast.pdf', 'filename': 'layout-parser-paper-fa...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/unstructured_file.html
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docs = loader.load() docs[:5] [Document(page_content='LayoutParser : A Unified Toolkit for Deep Learning Based Document Image Analysis', lookup_str='', metadata={'source': '../../layout-parser-paper.pdf'}, lookup_index=0), Document(page_content='Zejiang Shen 1 ( (ea)\n ), Ruochen Zhang 2 , Melissa Dell 3 , Benjamin Cha...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/unstructured_file.html
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.ipynb .pdf College Confidential College Confidential# This covers how to load College Confidential webpages into a document format that we can use downstream. from langchain.document_loaders import CollegeConfidentialLoader loader = CollegeConfidentialLoader("https://www.collegeconfidential.com/colleges/brown-universi...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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[Document(page_content='\n\n\n\n\n\n\n\nA68FEB02-9D19-447C-B8BC-818149FD6EAF\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n Media (2)\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nE45B8B13-33D4-450E-B7DB-F66EFE8F2097\n\n\n\n\n\n\n\n\n\nE45B8B13-33D4-450E-B7DB-F66EFE8F2097\n\n\n\n\n\n\n\n\n\n\n\n\n\...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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students to get involved at Brown! \nLove music or performing? Join a campus band, sing in a chorus, or perform with one of the school\'s theater groups.\nInterested in journalism or communications? Brown students can write for the campus newspaper, host a radio show or be a producer for the student-run television chan...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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"good" school. Some factors that can help you determine what a good school for you might be include admissions criteria, acceptance rate, tuition costs, and more.\nLet\'s take a look at these factors to get a clearer sense of what Brown offers and if it could be the right college for you.\nBrown Acceptance Rate 2022\nI...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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six-year graduation rate for U.S. colleges and universities is 61% for public schools, and 67% for private, non-profit schools.\nJob Outcomes for Brown Grads\nJob placement stats are a good resource for understanding the value of a degree from Brown by providing a look on how job placement has gone for other grads. \nC...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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Financial Aid at Brown\nTuition is another important factor when choose a college. Some colleges may have high tuition, but do a better job at meeting students\' financial need.\nBrown meets 100% of the demonstrated financial need for undergraduates. The average financial aid package for a full-time, first-year studen...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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so be very wary of anyone asking you for money.\nLearn more about Tuition and Financial Aid at Brown.\nBased on this information, does Brown seem like a good fit? Remember, a school that is perfect for one person may be a terrible fit for someone else! So ask yourself: Is Brown a good school for you?\nIf Brown Universi...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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best way to reach campus is to take Interstate 95 to Providence, or book a flight to the nearest airport, T.F. Green.\nYou can also take a virtual campus tour to get a sense of what Brown and Providence are like without leaving home.\nConsidering Going to School in Rhode Island?\nSee a full list of colleges in Rhode Is...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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\n\n Virtual Tour\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBrown Application Deadline\n\n\n\nFirst-Year Applications are Due\n\nJan 5\n\nTransfer Applications are Due\n\nMar 1\n\n\n\n \n The deadline for Fall first-year applications to Brown is \n ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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for more information about deadlines for specific programs or special admissions programs\n \n \n\n\n\n\n\n\nBrown ACT Scores\n\n\n\n\nic_reflect\n\n\n\n\n\n\n\n\nACT Range\n\n\n \n 33 - 35\n \n \n\n\n\nEstimated Chance of Acceptanc...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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720 - 770\n \n \n\n\n\nic_reflect\n\n\n\n\n\n\n\n\nMath SAT Range\n\n\n \n Not available\n \n \n\n\n\nic_reflect\n\n\n\n\n\n\n\n\nReading SAT Range\n\n\n \n 740 - 800\n...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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$82,286\n \nOut-of-State\n\n\n\n\n\n\n\nCost Breakdown\n\n\nIn State\n\n\nOut-of-State\n\n\n\n\nState Tuition\n\n\n\n $62,680\n \n\n\n\n $62,680\n \n\n\n\n\nFees\n\n\n\n $2,4...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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\n\n\n\n $15,840\n \n\n\n\n\nBooks\n\n\n\n $1,300\n \n\n\n\n $1,300\n \n\n\n\n\n\n Total (Before Financial Aid):\n \n\n\...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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\n\n\n\n\n\n\n\n\n\n\n\nStudent Life\n\n Wondering what life at Brown is like? There are approximately \n 10,696 students enrolled at \n Brown, \n including 7,349 undergraduate students and \n 3,347 graduate students.\n 96% percent of students attend school \n full-time...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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4%\n \nPart Time\n\n\n\n\n\n\n\n 94%\n \n\n\n\n\nResidency\n\n\n\n 6%\n \nIn State\n\n\n\n\n 94%\n \nOut-of-State\n\n\n\n\n\n\n\n Data Source: IPEDs and Peterso...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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previous Blackboard next Copy Paste By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/college_confidential.html
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.ipynb .pdf CSV Loader Contents CSV Loader Customizing the csv parsing and loading Specify a column to be used identify the document source CSV Loader# Load csv files with a single row per document. from langchain.document_loaders.csv_loader import CSVLoader loader = CSVLoader(file_path='./example_data/mlb_teams_2012...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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[Document(page_content='Team: Nationals\n"Payroll (millions)": 81.34\n"Wins": 98', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 0}, lookup_index=0), Document(page_content='Team: Reds\n"Payroll (millions)": 82.20\n"Wins": 97', lookup_str='', metadata={'source': './example_data/mlb_teams...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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lookup_index=0), Document(page_content='Team: Rangers\n"Payroll (millions)": 120.51\n"Wins": 93', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 6}, lookup_index=0), Document(page_content='Team: Orioles\n"Payroll (millions)": 81.43\n"Wins": 93', lookup_str='', metadata={'source': './exam...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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'row': 11}, lookup_index=0), Document(page_content='Team: Dodgers\n"Payroll (millions)": 95.14\n"Wins": 86', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 12}, lookup_index=0), Document(page_content='Team: White Sox\n"Payroll (millions)": 96.92\n"Wins": 85', lookup_str='', metadata={'so...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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'row': 17}, lookup_index=0), Document(page_content='Team: Padres\n"Payroll (millions)": 55.24\n"Wins": 76', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 18}, lookup_index=0), Document(page_content='Team: Mariners\n"Payroll (millions)": 81.97\n"Wins": 75', lookup_str='', metadata={'sour...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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'row': 23}, lookup_index=0), Document(page_content='Team: Red Sox\n"Payroll (millions)": 173.18\n"Wins": 69', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 24}, lookup_index=0), Document(page_content='Team: Indians\n"Payroll (millions)": 78.43\n"Wins": 68', lookup_str='', metadata={'sou...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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Customizing the csv parsing and loading# See the csv module documentation for more information of what csv args are supported. loader = CSVLoader(file_path='./example_data/mlb_teams_2012.csv', csv_args={ 'delimiter': ',', 'quotechar': '"', 'fieldnames': ['MLB Team', 'Payroll in millions', 'Wins'] }) data = ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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[Document(page_content='MLB Team: Team\nPayroll in millions: "Payroll (millions)"\nWins: "Wins"', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 0}, lookup_index=0), Document(page_content='MLB Team: Nationals\nPayroll in millions: 81.34\nWins: 98', lookup_str='', metadata={'source': './e...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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'./example_data/mlb_teams_2012.csv', 'row': 5}, lookup_index=0), Document(page_content='MLB Team: Athletics\nPayroll in millions: 55.37\nWins: 94', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 6}, lookup_index=0), Document(page_content='MLB Team: Rangers\nPayroll in millions: 120.51\nW...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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in millions: 132.30\nWins: 88', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 11}, lookup_index=0), Document(page_content='MLB Team: Cardinals\nPayroll in millions: 110.30\nWins: 88', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 12}, lookup_index=0), Do...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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16}, lookup_index=0), Document(page_content='MLB Team: Diamondbacks\nPayroll in millions: 74.28\nWins: 81', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 17}, lookup_index=0), Document(page_content='MLB Team: Pirates\nPayroll in millions: 63.43\nWins: 79', lookup_str='', metadata={'sour...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 22}, lookup_index=0), Document(page_content='MLB Team: Royals\nPayroll in millions: 60.91\nWins: 72', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 23}, lookup_index=0), Document(page_content='MLB Team: Marlins\nPayroll in ...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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in millions: 78.06\nWins: 64', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 28}, lookup_index=0), Document(page_content='MLB Team: Cubs\nPayroll in millions: 88.19\nWins: 61', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 29}, lookup_index=0), Document(...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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Specify a column to be used identify the document source# Use the source_column argument to specify a column to be set as the source for the document created from each row. Otherwise file_path will be used as the source for all documents created from the csv file. This is useful when using documents loaded from CSV fil...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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[Document(page_content='Team: Nationals\n"Payroll (millions)": 81.34\n"Wins": 98', lookup_str='', metadata={'source': 'Nationals', 'row': 0}, lookup_index=0), Document(page_content='Team: Reds\n"Payroll (millions)": 82.20\n"Wins": 97', lookup_str='', metadata={'source': 'Reds', 'row': 1}, lookup_index=0), Document(page...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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'row': 6}, lookup_index=0), Document(page_content='Team: Orioles\n"Payroll (millions)": 81.43\n"Wins": 93', lookup_str='', metadata={'source': 'Orioles', 'row': 7}, lookup_index=0), Document(page_content='Team: Rays\n"Payroll (millions)": 64.17\n"Wins": 90', lookup_str='', metadata={'source': 'Rays', 'row': 8}, lookup_...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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lookup_str='', metadata={'source': 'White Sox', 'row': 13}, lookup_index=0), Document(page_content='Team: Brewers\n"Payroll (millions)": 97.65\n"Wins": 83', lookup_str='', metadata={'source': 'Brewers', 'row': 14}, lookup_index=0), Document(page_content='Team: Phillies\n"Payroll (millions)": 174.54\n"Wins": 81', lookup...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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(millions)": 93.35\n"Wins": 74', lookup_str='', metadata={'source': 'Mets', 'row': 20}, lookup_index=0), Document(page_content='Team: Blue Jays\n"Payroll (millions)": 75.48\n"Wins": 73', lookup_str='', metadata={'source': 'Blue Jays', 'row': 21}, lookup_index=0), Document(page_content='Team: Royals\n"Payroll (millions)...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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lookup_index=0), Document(page_content='Team: Rockies\n"Payroll (millions)": 78.06\n"Wins": 64', lookup_str='', metadata={'source': 'Rockies', 'row': 27}, lookup_index=0), Document(page_content='Team: Cubs\n"Payroll (millions)": 88.19\n"Wins": 61', lookup_str='', metadata={'source': 'Cubs', 'row': 28}, lookup_index=0),...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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previous Copy Paste next Directory Loader Contents CSV Loader Customizing the csv parsing and loading Specify a column to be used identify the document source By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
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.ipynb .pdf Roam Contents 🧑 Instructions for ingesting your own dataset Roam# This notebook covers how to load documents from a Roam database. This takes a lot of inspiration from the example repo here. 🧑 Instructions for ingesting your own dataset# Export your dataset from Roam Research. You can do this by clickin...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/roam.html
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.ipynb .pdf GCS File Storage GCS File Storage# This covers how to load document objects from an Google Cloud Storage (GCS) file object. from langchain.document_loaders import GCSFileLoader # !pip install google-cloud-storage loader = GCSFileLoader(project_name="aist", bucket="testing-hwc", blob="fake.docx") loader.load...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/gcs_file.html
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.ipynb .pdf AZLyrics AZLyrics# This covers how to load AZLyrics webpages into a document format that we can use downstream. from langchain.document_loaders import AZLyricsLoader loader = AZLyricsLoader("https://www.azlyrics.com/lyrics/mileycyrus/flowers.html") data = loader.load() data
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/azlyrics.html
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[Document(page_content="Miley Cyrus - Flowers Lyrics | AZLyrics.com\n\r\nWe were good, we were gold\nKinda dream that can't be sold\nWe were right till we weren't\nBuilt a home and watched it burn\n\nI didn't wanna leave you\nI didn't wanna lie\nStarted to cry but then remembered I\n\nI can buy myself flowers\nWrite my...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/azlyrics.html
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to myself for hours, yeah\nSay things you don't understand\nI can take myself dancing\nAnd I can hold my own hand\nYeah, I can love me better than you can\n\nCan love me better\nI can love me better, baby\nCan love me better\nI can love me better, baby\nCan love me better\nI can love me better, baby\nCan love me better...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/azlyrics.html
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love me better\nI\n", lookup_str='', metadata={'source': 'https://www.azlyrics.com/lyrics/mileycyrus/flowers.html'}, lookup_index=0)]
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/azlyrics.html
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previous Airbyte JSON next Blackboard By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on Mar 22, 2023.
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/azlyrics.html
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.ipynb .pdf iFixit Contents Searching iFixit using /suggest iFixit# iFixit is the largest, open repair community on the web. The site contains nearly 100k repair manuals, 200k Questions & Answers on 42k devices, and all the data is licensed under CC-BY-NC-SA 3.0. This loader will allow you to download the text of a r...
https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/ifixit.html