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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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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 PDFMiner to generate HTML text# This can be helpful for chunking texts semantically into sections as the output html content can be parsed via BeautifulSoup to...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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from langchain.docstore.document import Document cur_idx = -1 semantic_snippets = [] # Assumption: headings have higher font size than their respective content for s in snippets: # if current snippet's font size > previous section's heading => it is a new heading if not semantic_snippets or s[1] > semantic_snip...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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Document(page_content='Recently, various DL models and datasets have been developed for layout analysis\ntasks. The dhSegment [22] utilizes fully convolutional networks [20] for segmen-\ntation tasks on historical documents. Object detection-based methods like Faster\nR-CNN [28] and Mask R-CNN [12] are used for identif...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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by Neudecker et al. [21], it is designed for\nanalyzing historical documents, and provides no supports for recent DL models.\nThe DocumentLayoutAnalysis project8 focuses on processing born-digital PDF\ndocuments via analyzing the stored PDF data. Repositories like DeepLayout9\nand Detectron2-PubLayNet10 are individual ...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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type as ‘code’.\n7 https://ocr-d.de/en/about\n8 https://github.com/BobLd/DocumentLayoutAnalysis\n9 https://github.com/leonlulu/DeepLayout\n10 https://github.com/hpanwar08/detectron2\n11 https://github.com/JaidedAI/EasyOCR\n12 https://github.com/PaddlePaddle/PaddleOCR\n4\nZ. Shen et al.\nFig. 1: The overall architecture...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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and deploying models for general computer\nvision and natural language processing problems. LayoutParser, on the other\nhand, specializes specifically in DIA tasks. LayoutParser is also equipped with a\ncommunity platform inspired by established model hubs such as Torch Hub [23]\nand TensorFlow Hub [1]. It enables the s...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
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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. from langchain.document_loaders import PyMuPDFLoader loader = PyMuPDFLoader("example_data/layout-parser-paper.pdf") data = loader.load() data[0]
https:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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. PyPDF Directory# Load PDFs from directory from langchain.document_loaders import PyPDFDirectoryLoader loader = PyPDFDirectoryLoader("example_data/")...
https:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/telegram.html
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.ipynb .pdf DuckDB Loader Contents Specifying Which Columns are Content vs Metadata Adding Source to Metadata DuckDB Loader# Load a DuckDB query with one document per row. from langchain.document_loaders import DuckDBLoader %%file example.csv Team,Payroll Nationals,81.34 Reds,82.20 Writing example.csv loader = DuckDB...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/duckdb.html
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Specifying Which Columns are Content vs Metadata Adding Source to Metadata By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/duckdb.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. Obsidian files also sometimes contain metadata which is a YAML block at the top of the file. These val...
https:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/blackboard.html
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.ipynb .pdf Notion DB Loader Contents Requirements Setup 1. Create a Notion Table Database 2. Create a Notion Integration 3. Connect the Integration to the Database 4. Get the Database ID Usage Notion DB Loader# NotionDBLoader is a Python class for loading content from a Notion database. It retrieves pages from the d...
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To connect your integration to the database, follow these steps: Open your database in Notion. Click on the three-dot menu icon in the top right corner of the database view. Click on the “+ New integration” button. Find your integration, you may need to start typing its name in the search box. Click on the “Connect” bu...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/notiondb.html
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Requirements Setup 1. Create a Notion Table Database 2. Create a Notion Integration 3. Connect the Integration to the Database 4. Get the Database ID Usage By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/notiondb.html
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.ipynb .pdf ChatGPT Data Loader ChatGPT Data Loader# This notebook covers how to load conversations.json from your ChatGPT data export folder. You can get your data export by email by going to: https://chat.openai.com/ -> (Profile) - Settings -> Export data -> Confirm export. from langchain.document_loaders.chatgpt imp...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/chatgpt_loader.html
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.ipynb .pdf HuggingFace dataset loader Contents Example HuggingFace dataset loader# This notebook shows how to load Hugging Face Hub datasets to LangChain. The Hugging Face Hub hosts a large number of community-curated datasets for a diverse range of tasks such as translation, automatic speech recognition, and image ...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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data = loader.load() data[:15] [Document(page_content='I rented I AM CURIOUS-YELLOW from my video store because of all the controversy that surrounded it when it was first released in 1967. I also heard that at first it was seized by U.S. customs if it ever tried to enter this country, therefore being a fan of films co...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='"I Am Curious: Yellow" is a risible and pretentious steaming pile. It doesn\'t matter what one\'s political views are because this film can hardly be taken seriously on any level. As for the claim that frontal male nudity is an automatic NC-17, that isn\'t true. I\'ve seen R-rated films with male...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content="If only to avoid making this type of film in the future. This film is interesting as an experiment but tells no cogent story.<br /><br />One might feel virtuous for sitting thru it because it touches on so many IMPORTANT issues but it does so without any discernable motive. The viewer comes away ...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='Oh, brother...after hearing about this ridiculous film for umpteen years all I can think of is that old Peggy Lee song..<br /><br />"Is that all there is??" ...I was just an early teen when this smoked fish hit the U.S. I was too young to get in the theater (although I did manage to sneak into "G...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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pretension...and feeble who-cares simulated sex scenes with saggy, pale actors.<br /><br />Cultural icon, holy grail, historic artifact..whatever this thing was, shred it, burn it, then stuff the ashes in a lead box!<br /><br />Elite esthetes still scrape to find value in its boring pseudo revolutionary political spewi...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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it - rent the video and fast forward to the "dirty" parts, just to get it over with.<br /><br />', metadata={'label': 0}),
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content="I would put this at the top of my list of films in the category of unwatchable trash! There are films that are bad, but the worst kind are the ones that are unwatchable but you are suppose to like them because they are supposed to be good for you! The sex sequences, so shocking in its day, couldn...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='When I first saw a glimpse of this movie, I quickly noticed the actress who was playing the role of Lucille Ball. Rachel York\'s portrayal of Lucy is absolutely awful. Lucille Ball was an astounding comedian with incredible talent. To think about a legend like Lucille Ball being portrayed the way...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='Who are these "They"- the actors? the filmmakers? Certainly couldn\'t be the audience- this is among the most air-puffed productions in existence. It\'s the kind of movie that looks like it was a lot of fun to shoot\x97 TOO much fun, nobody is getting any actual work done, and that almost always ...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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respective children (nepotism alert: Bogdanovich\'s daughters) spew cute and pick up some fairly disturbing pointers on \'love\' while observing their parents. (Ms. Hepburn, drawing on her dignity, manages to rise above the proceedings- but she has the monumental challenge of playing herself, ostensibly.) Everybody loo...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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but at least they were long on charm. "They All Laughed" tries to coast on its good intentions, but nobody- least of all Peter Bogdanovich - has the good sense to put on the brakes.<br /><br />Due in no small part to the tragic death of Dorothy Stratten, this movie has a special place in the heart of Mr. Bogdanovich- h...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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in all, though, the movie is harmless, only a waste of rental. I want to watch people having a good time, I\'ll go to the park on a sunny day. For filmic expressions of joy and love, I\'ll stick to Ernest Lubitsch and Jaques Demy...', metadata={'label': 0}),
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content="This is said to be a personal film for Peter Bogdonavitch. He based it on his life but changed things around to fit the characters, who are detectives. These detectives date beautiful models and have no problem getting them. Sounds more like a millionaire playboy filmmaker than a detective, doesn...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='It was great to see some of my favorite stars of 30 years ago including John Ritter, Ben Gazarra and Audrey Hepburn. They looked quite wonderful. But that was it. They were not given any characters or good lines to work with. I neither understood or cared what the characters were doing.<br /><br ...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content="I can't believe that those praising this movie herein aren't thinking of some other film. I was prepared for the possibility that this would be awful, but the script (or lack thereof) makes for a film that's also pointless. On the plus side, the general level of craft on the part of the actors an...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content="Its not the cast. A finer group of actors, you could not find. Its not the setting. The director is in love with New York City, and by the end of the film, so are we all! Woody Allen could not improve upon what Bogdonovich has done here. If you are going to fall in love, or find love, Manhattan i...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Document(page_content='Today I found "They All Laughed" on VHS on sale in a rental. It was a really old and very used VHS, I had no information about this movie, but I liked the references listed on its cover: the names of Peter Bogdanovich, Audrey Hepburn, John Ritter and specially Dorothy Stratten attracted me, the p...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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eyes who fall in love for the women they are chasing), but I have not laughed along the whole story. The coincidences, in a huge city like New York, are ridiculous. Ben Gazarra as an attractive and very seductive man, with the women falling for him as if her were a Brad Pitt, Antonio Banderas or George Clooney, is quit...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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most popular Brazilian singer since the end of the 60\'s and is called by his fans as "The King". I will keep this movie in my collection only because of these attractions (manly Dorothy Stratten). My vote is four.<br /><br />Title (Brazil): "Muito Riso e Muita Alegria" ("Many Laughs and Lots of Happiness")', metadata=...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.html
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Example# In this example, we use data from a dataset to answer a question from langchain.indexes import VectorstoreIndexCreator from langchain.document_loaders.hugging_face_dataset import HuggingFaceDatasetLoader dataset_name="tweet_eval" page_content_column="text" name="stance_climate" loader=HuggingFaceDatasetLoader(...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hugging_face_dataset.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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/CoNLL-U.html
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.ipynb .pdf Image captions Contents Prepare a list of image urls from Wikimedia Create the loader Create the index Query Image captions# This notebook shows how to use the ImageCaptionLoader tutorial to generate a query-able index of image captions from langchain.document_loaders import ImageCaptionLoader Prepare a l...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image_captions.html
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'https://upload.wikimedia.org/wikipedia/commons/thumb/b/b6/2022-01-22_Men%27s_World_Cup_at_2021-22_St._Moritz%E2%80%93Celerina_Luge_World_Cup_and_European_Championships_by_Sandro_Halank%E2%80%93257.jpg/288px-2022-01-22_Men%27s_World_Cup_at_2021-22_St._Moritz%E2%80%93Celerina_Luge_World_Cup_and_European_Championships_by...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image_captions.html
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Document(page_content='an image of a shark swimming in the ocean [SEP]', metadata={'image_path': 'https://upload.wikimedia.org/wikipedia/commons/thumb/7/71/Tibur%C3%B3n_azul_%28Prionace_glauca%29%2C_canal_Fayal-Pico%2C_islas_Azores%2C_Portugal%2C_2020-07-27%2C_DD_14.jpg/270px-Tibur%C3%B3n_azul_%28Prionace_glauca%29%2C_...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image_captions.html
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Document(page_content='an image of a man on skis in the snow [SEP]', metadata={'image_path': 'https://upload.wikimedia.org/wikipedia/commons/thumb/b/b6/2022-01-22_Men%27s_World_Cup_at_2021-22_St._Moritz%E2%80%93Celerina_Luge_World_Cup_and_European_Championships_by_Sandro_Halank%E2%80%93257.jpg/288px-2022-01-22_Men%27s_...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image_captions.html
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from .autonotebook import tqdm as notebook_tqdm /Users/saitosean/dev/langchain/.venv/lib/python3.10/site-packages/transformers/generation/utils.py:1313: UserWarning: Using `max_length`'s default (20) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image_captions.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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/googledrive.html
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# Optional: configure whether to recursively fetch files from subfolders. Defaults to False. recursive=False ) docs = loader.load() previous GitBook next Gutenberg Contents Prerequisites 🧑 Instructions for ingesting your Google Docs data By Harrison Chase © Copyright 2023, Harrison Chase. L...
https:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/markdown.html
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.ipynb .pdf Apify Dataset Contents Prerequisites An example with question answering Apify Dataset# This notebook shows how to load Apify datasets to LangChain. Apify Dataset is a scaleable append-only storage with sequential access built for storing structured web scraping results, such as a list of products or Googl...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/apify_dataset.html
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from langchain.docstore.document import Document from langchain.document_loaders import ApifyDatasetLoader from langchain.indexes import VectorstoreIndexCreator loader = ApifyDatasetLoader( dataset_id="your-dataset-id", dataset_mapping_function=lambda item: Document( page_content=item["text"] or "", met...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/apify_dataset.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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/facebook_chat.html
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previous EverNote next Figma By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/gitbook.html
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previous Git 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 May 02, 2023.
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/gitbook.html
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.ipynb .pdf Blockchain Contents Overview Load NFTs into Document Loader Option 1: Ethereum Mainnet (default BlockchainType) Option 2: Polygon Mainnet Blockchain# Overview# The intention of this notebook is to provide a means of testing functionality in the Langchain Document Loader for Blockchain. Initially this Load...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/blockchain.html
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nfts[:2] Option 2: Polygon Mainnet# contractAddress = "0x448676ffCd0aDf2D85C1f0565e8dde6924A9A7D9" # Polygon Mainnet contract address blockchainType = BlockchainType.POLYGON_MAINNET blockchainLoader = BlockchainDocumentLoader(contract_address=contractAddress, blockchainType...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/blockchain.html
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.ipynb .pdf Spreedly Spreedly# This notebook covers how to load data from the Spreedly REST API into a format that can be ingested into LangChain, along with example usage for vectorization. Note: this notebook assumes the following packages are installed: openai, chromadb, and tiktoken. import os from langchain.docume...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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# Test the retriever spreedly_doc_retriever.get_relevant_documents("CRC") [Document(page_content='installment_grace_period_duration\nreference_data_code\ninvoice_number\ntax_management_indicator\noriginal_amount\ninvoice_amount\nvat_tax_rate\nmobile_remote_payment_type\ngratuity_amount\nmdd_field_1\nmdd_field_2\nmdd_fi...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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Document(page_content='BG\nBH\nBI\nBJ\nBM\nBN\nBO\nBR\nBS\nBT\nBW\nBY\nBZ\nCA\nCC\nCF\nCH\nCK\nCL\nCM\nCN\nCO\nCR\nCV\nCX\nCY\nCZ\nDE\nDJ\nDK\nDO\nDZ\nEC\nEE\nEG\nEH\nES\nET\nFI\nFJ\nFK\nFM\nFO\nFR\nGA\nGB\nGD\nGE\nGF\nGG\nGH\nGI\nGL\nGM\nGN\nGP\nGQ\nGR\nGT\nGU\nGW\nGY\nHK\nHM\nHN\nHR\nHT\nHU\nID\nIE\nIL\nIM\nIN\nIO\nI...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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Z\nLA\nLC\nLI\nLK\nLS\nLT\nLU\nLV\nMA\nMC\nMD\nME\nMG\nMH\nMK\nML\nMN\nMO\nMP\nMQ\nMR\nMS\nMT\nMU\nMV\nMW\nMX\nMY\nMZ\nNA\nNC\nNE\nNF\nNG\nNI\nNL\nNO\nNP\nNR\nNU\nNZ\nOM\nPA\nPE\nPF\nPH\nPK\nPL\nPN\nPR\nPT\nPW\nPY\nQA\nRE\nRO\nRS\nRU\nRW\nSA\nSB\nSC\nSE\nSG\nSI\nSK\nSL\nSM\nSN\nST\nSV\nSZ\nTC\nTD\nTF\nTG\nTH\nTJ\nTK\nT...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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I\nVN\nVU\nWF\nWS\nYE\nYT\nZA\nZM\nsupported_cardtypes:
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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visa\nmaster\namerican_express\ndiscover\njcb\nmaestro\nelo\nnaranja\ncabal\nunionpay\nregions: asia_pacific\neurope\nmiddle_east\nnorth_america\nhomepage: http://worldpay.com\ndisplay_api_url: https://secure.worldpay.com/jsp/merchant/xml/paymentService.jsp\ncompany_name: WorldPay', metadata={'source': 'https://core.sp...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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Document(page_content='gateway_specific_fields: receipt_email\nradar_session_id\nskip_radar_rules\napplication_fee\nstripe_account\nmetadata\nidempotency_key\nreason\nrefund_application_fee\nrefund_fee_amount\nreverse_transfer\naccount_id\ncustomer_id\nvalidate\nmake_default\ncancellation_reason\ncapture_method\nconfir...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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Document(page_content='mdd_field_57\nmdd_field_58\nmdd_field_59\nmdd_field_60\nmdd_field_61\nmdd_field_62\nmdd_field_63\nmdd_field_64\nmdd_field_65\nmdd_field_66\nmdd_field_67\nmdd_field_68\nmdd_field_69\nmdd_field_70\nmdd_field_71\nmdd_field_72\nmdd_field_73\nmdd_field_74\nmdd_field_75\nmdd_field_76\nmdd_field_77\nmdd...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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ERROR: type should be string, got "https://api.cybersource.com\\ncompany_name: CyberSource REST', metadata={'source': 'https://core.spreedly.com/v1/gateways_options.json'})]"
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.html
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previous Slack (Local Exported Zipfile) next Subtitle Files By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/spreedly.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:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/s3_directory.html
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.ipynb .pdf Bilibili Bilibili# This loader utilizes the bilibili-api to fetch the text transcript from Bilibili, one of the most beloved long-form video sites in China. With this BiliBiliLoader, users can easily obtain the transcript of their desired video content on the platform. from langchain.document_loaders.bilibi...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/bilibili.html
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.ipynb .pdf Arxiv Contents Installation Examples Arxiv# arXiv is an open-access archive for 2 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. This notebook shows how t...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/arxiv.html
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'Authors': 'Caprice Stanley, Tobias Windisch', 'Summary': 'Graphs on lattice points are studied whose edges come from a finite set of\nallowed moves of arbitrary length. We show that the diameter of these graphs on\nfibers of a fixed integer matrix can be bounded from above by a constant. We\nthen study the mixing beh...
https:///python.langchain.com/en/latest/modules/indexes/document_loaders/examples/arxiv.html