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* Adds BlobParsers for images. These implementations can take an image and produce one or more documents per image. This interface can be used for exposing OCR capabilities. * Update PyMuPDFParser and Loader to standardize metadata, handle images, improve table extraction etc. - **Twitter handle:** pprados This is one part of a larger Pull Request (PR) that is too large to be submitted all at once. This specific part focuses to prepare the update of all parsers. For more details, see [PR 28970](https://github.com/langchain-ai/langchain/pull/28970). --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> |
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brandfetch-brandfetch-2.0.0-resolved.json | ||
building.jpg | ||
default-encoding.py | ||
docusaurus-sitemap.xml | ||
duplicate-chars.pdf | ||
example-utf8.html | ||
example.html | ||
example.json | ||
example.mht | ||
facebook_chat.json | ||
factbook.xml | ||
fake-email-attachment.eml | ||
fake.odt | ||
hello_world.js | ||
hello_world.py | ||
hello.msg | ||
hello.pdf | ||
layout-parser-paper-page-1.txt | ||
layout-parser-paper-password.pdf | ||
layout-parser-paper.pdf | ||
multi-page-forms-sample-2-page.pdf | ||
non-utf8-encoding.py | ||
page.png | ||
README.org | ||
README.rst | ||
sample_rss_feeds.opml | ||
sitemap.xml | ||
slack_export.zip | ||
stanley-cups.csv | ||
stanley-cups.tsv | ||
stanley-cups.xlsx | ||
text.png | ||
whatsapp_chat.txt |
Example Docs ------------ The sample docs directory contains the following files: - ``example-10k.html`` - A 10-K SEC filing in HTML format - ``layout-parser-paper.pdf`` - A PDF copy of the layout parser paper - ``factbook.xml``/``factbook.xsl`` - Example XML/XLS files that you can use to test stylesheets These documents can be used to test out the parsers in the library. In addition, here are instructions for pulling in some sample docs that are too big to store in the repo. XBRL 10-K ^^^^^^^^^ You can get an example 10-K in inline XBRL format using the following ``curl``. Note, you need to have the user agent set in the header or the SEC site will reject your request. .. code:: bash curl -O \ -A '${organization} ${email}' https://www.sec.gov/Archives/edgar/data/311094/000117184321001344/0001171843-21-001344.txt You can parse this document using the HTML parser.