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Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Game...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-27
Opening Day? Here's your guide to MLB's offseason chaosWait, Jacob deGrom is on the Rangers now? Xander Bogaerts and Trea Turner signed where? And what about Carlos Correa? Yeah, you're going to need to read up before Opening Day.12hESPNIllustration by ESPNEverything you missed in the MLB offseason3h2:33World Series od...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-28
Jackson the most7h2:00Would Lamar sit out? Will Ravens draft a QB? Jackson trade request insightsLamar Jackson has asked Baltimore to trade him, but Ravens coach John Harbaugh hopes the QB will be back.3hJamison HensleyBallard, Colts will consider trading for QB JacksonJackson to Indy? Washington? Barnwell ranks the QB...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-29
find comparisons.16hKevin PeltonWOMEN'S ELITE EIGHT SCOREBOARDMONDAY'S GAMESCheck your bracket!NBA DRAFTHow top prospects fared on the road to the Final FourThe 2023 NCAA tournament is down to four teams, and ESPN's Jonathan Givony recaps the players who saw their NBA draft stock change.11hJonathan GivonyAndy Lyons/Get...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-30
Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
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can follow throughout the Big Dance. Women's Tournament ChallengeIllustration by ESPNWomen's Tournament ChallengeCheck your bracket(s) in the 2023 Women's Tournament Challenge, which you can follow throughout the Big Dance. Best of ESPN+AP Photo/Lynne SladkyFantasy Baseball ESPN+ Cheat Sheet: Sleepers, busts, rookies a...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-32
predictionsMel Kiper Jr. makes his predictions for Round 1 of the NFL draft, including projecting a trade in the top five. Trending NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, milestonesThe B's are on pace for NHL records in wins and points, along with some individual superlatives as wel...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-33
on ESPN, ESPN+Here's everything you need to know about how to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN and ESPN+.Hailie Lynch/XFLHow to watch the XFL: 2023 schedule, teams, players, news, moreEvery XFL game will be streamed on ESPN+. Find out when and where else you can watch the eig...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-34
Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-35
ESPNCopyright: © ESPN Enterprises, Inc. All rights reserved.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", lookup_str='', metadata={'source': 'https://www.espn.com/'}, lookup_index=0),
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-36
Document(page_content='GoogleSearch Images Maps Play YouTube News Gmail Drive More »Web History | Settings | Sign in\xa0Advanced searchAdvertisingBusiness SolutionsAbout Google© 2023 - Privacy - Terms ', lookup_str='', metadata={'source': 'https://google.com'}, lookup_index=0)] Loading a xml file, or using a differen...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-37
[Document(page_content='\n\n10\nEnergy\n3\n2018-01-01\n2018-01-01\nfalse\nUniform test method for the measurement of energy efficiency of commercial packaged boilers.\n§ 431.86\nSection § 431.86\n\nEnergy\nDEPARTMENT OF ENERGY\nENERGY CONSERVATION\nENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIP...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-38
rated inputBtu/h\n\nStandards efficiency metric(§\u2009431.87)\n\nTest procedure(corresponding to\nstandards efficiency\nmetric required\nby §\u2009431.87)\n\n\n\nHot Water\nGas-fired\n≥300,000 and ≤2,500,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\nHot Water\nGas-fired\n>2,500,000\nCombustion Efficiency\nAppen...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
f52903517a5d-39
Efficiency\nAppendix A, Section 2.\n\n\nSteam\nOil-fired\n>2,500,000 and ≤5,000,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\n\u2003\n\n>5,000,000\nThermal Efficiency\nAppendix A, Section 2.OR\nAppendix A, Section 3. with Section 2.4.3.2.\n\n\n\n*\u2009Equipment classes for commercial packaged boilers as of July...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
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previous URL next WhatsApp Chat Contents Loading multiple webpages Load multiple urls concurrently Loading a xml file, or using a different BeautifulSoup parser By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/web_base.html
30f7d62912ee-0
.ipynb .pdf PDF Contents Using PyPDF Using MathPix Using Unstructured Retain Elements Fetching remote PDFs using Unstructured Using PDFMiner Using PDFMiner to generate HTML text Using PyMuPDF PyPDF Directory PDF# This covers how to load pdfs into a document format that we can use downstream. Using PyPDF# Load PDF usi...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-1
Document(page_content='LayoutParser : A Uni\x0ced Toolkit for Deep\nLearning Based Document Image Analysis\nZejiang Shen1( \x00), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain\nLee4, Jacob Carlson3, and Weining Li5\n1Allen Institute for AI\nshannons@allenai.org\n2Brown University\nruochen zhang@brown.edu\n3Ha...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-2
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\nl...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-3
Learning(DL)-based approaches are the state-of-the-art for a wide range of\ndocument image analysis (DIA) tasks including document image classi\x0ccation [ 11,arXiv:2103.15348v2 [cs.CV] 21 Jun 2021', lookup_str='', metadata={'source': 'example_data/layout-parser-paper.pdf', 'page': '0'}, lookup_index=0)
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-4
An advantage of this approach is that documents can be retrieved with page numbers. from langchain.vectorstores import FAISS from langchain.embeddings.openai import OpenAIEmbeddings faiss_index = FAISS.from_documents(pages, OpenAIEmbeddings()) docs = faiss_index.similarity_search("How will the community be engaged?", k...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-5
For each shared pipeline, it has a dedicated project page, with links to the source code, documentation, and an outline of the approaches. A discussion panel is provided for exchanging ideas. Combined with the core LayoutParser library, users can easily build reusable components based on the shared pipelines and apply ...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-6
vision and natural language processing problems. LayoutParser , on the other hand, specializes speci cally in DIA tasks. LayoutParser is also equipped with a community platform inspired by established model hubs such as Torch Hub [23] andTensorFlow Hub [1]. It enables the sharing of pretrained models as well as full do...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-7
data = loader.load() 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 = UnstructuredPDFLoader("example_data/layout-parser-paper.pdf", mode="elements...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-8
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
30f7d62912ee-9
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
30f7d62912ee-10
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
30f7d62912ee-11
Fetching remote PDFs using Unstructured# This covers how to load online pdfs into a document format that we can use downstream. This can be used for various online pdf sites such as https://open.umn.edu/opentextbooks/textbooks/ and https://arxiv.org/archive/ Note: all other pdf loaders can also be used to fetch remote ...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-12
[Document(page_content='A WEAK ( k, k ) -LEFSCHETZ THEOREM FOR PROJECTIVE TORIC ORBIFOLDS\n\nWilliam D. Montoya\n\nInstituto de Matem´atica, Estat´ıstica e Computa¸c˜ao Cient´ıfica,\n\nIn [3] we proved that, under suitable conditions, on a very general codimension s quasi- smooth intersection subvariety X in a projectiv...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-13
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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-14
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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-15
< 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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-16
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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-17
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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/pdf.html
30f7d62912ee-19
/ 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
30f7d62912ee-20
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
30f7d62912ee-21
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
30f7d62912ee-22
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
30f7d62912ee-23
− 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
30f7d62912ee-24
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
30f7d62912ee-25
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
30f7d62912ee-26
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
30f7d62912ee-27
,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
30f7d62912ee-28
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
30f7d62912ee-32
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
30f7d62912ee-33
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
30f7d62912ee-34
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
30f7d62912ee-35
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
30f7d62912ee-36
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
30f7d62912ee-37
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
30f7d62912ee-38
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
30f7d62912ee-40
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
30f7d62912ee-41
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 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 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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/unstructured_file.html
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loader = UnstructuredFileLoader("./example_data/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=...
https://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/unstructured_file.html
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.ipynb .pdf GCS Directory Contents Specifying a prefix GCS Directory# This covers how to load document objects from an Google Cloud Storage (GCS) directory. from langchain.document_loaders import GCSDirectoryLoader # !pip install google-cloud-storage loader = GCSDirectoryLoader(project_name="aist", bucket="testing-hw...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/gcs_directory.html
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Specifying a prefix# You can also specify a prefix for more finegrained control over what files to load. loader = GCSDirectoryLoader(project_name="aist", bucket="testing-hwc", prefix="fake") loader.load() /Users/harrisonchase/workplace/langchain/.venv/lib/python3.10/site-packages/google/auth/_default.py:83: UserWarning...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/gcs_directory.html
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By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/gcs_directory.html
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.ipynb .pdf Azure Blob Storage File Azure Blob Storage File# This covers how to load document objects from a Azure Blob Storage file. from langchain.document_loaders import AzureBlobStorageFileLoader #!pip install azure-storage-blob loader = AzureBlobStorageFileLoader(conn_str='<connection string>', container='<contain...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/azure_blob_storage_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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/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://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/college_confidential.html
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previous ChatGPT Data Loader next Confluence By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/college_confidential.html
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.ipynb .pdf Subtitle Files Subtitle Files# How to load data from subtitle (.srt) files from langchain.document_loaders import SRTLoader loader = SRTLoader("example_data/Star_Wars_The_Clone_Wars_S06E07_Crisis_at_the_Heart.srt") docs = loader.load() docs[0].page_content[:100] '<i>Corruption discovered\nat the core of the...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/srt.html
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.ipynb .pdf PowerPoint Contents Retain Elements PowerPoint# This covers how to load PowerPoint documents into a document format that we can use downstream. from langchain.document_loaders import UnstructuredPowerPointLoader loader = UnstructuredPowerPointLoader("example_data/fake-power-point.pptx") data = loader.load...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/powerpoint.html
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.ipynb .pdf Directory Loader Contents Show a progress bar Change loader class Directory Loader# This covers how to use the DirectoryLoader to load all documents in a directory. Under the hood, by default this uses the UnstructuredLoader from langchain.document_loaders import DirectoryLoader We can use the glob parame...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/directory_loader.html
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Diffbot next Discord Contents Show a progress bar Change loader class By Harrison Chase © Copyright 2023, Harrison Chase. Last updated on May 02, 2023.
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/directory_loader.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 Word Documents Contents Using Docx2txt Using Unstructured Retain Elements Word Documents# This covers how to load Word documents into a document format that we can use downstream. Using Docx2txt# Load .docx using Docx2txt into a document. from langchain.document_loaders import Docx2txtLoader loader = Docx...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/word_document.html
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.ipynb .pdf Discord Discord# You can follow the below steps to download your Discord data: Go to your User Settings Then go to Privacy and Safety Head over to the Request all of my Data and click on Request Data button It might take 30 days for you to receive your data. You’ll receive an email at the address which is r...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/discord_loader.html
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.ipynb .pdf Stripe Stripe# This notebook covers how to load data from the Stripe REST API into a format that can be ingested into LangChain, along with example usage for vectorization. import os from langchain.document_loaders import StripeLoader from langchain.indexes import VectorstoreIndexCreator The Stripe API requ...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/stripe.html
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.ipynb .pdf Hacker News Hacker News# How to pull page data and comments from Hacker News from langchain.document_loaders import HNLoader loader = HNLoader("https://news.ycombinator.com/item?id=34817881") data = loader.load() data [Document(page_content="delta_p_delta_x 18 hours ago \n | next [–] \n\nAstrop...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hn.html
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Document(page_content="andrewflnr 19 hours ago \n | prev | next [–] \n\nWhoa. I didn't know the accretion theory of Ia supernovae was dead, much less that it had been since 2011.\n \nreply", lookup_str='', metadata={'source': 'https://news.ycombinator.com/item?id=34817881', 'title': 'What Lights the Univer...
https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/hn.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
315ea59905fb-1
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