PyPDFParser#

class langchain_community.document_loaders.parsers.pdf.PyPDFParser(password: str | bytes | None = None, extract_images: bool = False, *, mode: Literal['single', 'page'] = 'page', pages_delimiter: str = '\n\x0c', images_parser: BaseImageBlobParser | None = None, images_inner_format: Literal['text', 'markdown-img', 'html-img'] = 'text', extraction_mode: Literal['plain', 'layout'] = 'plain', extraction_kwargs: dict[str, Any] | None = None)[source]#

Parse a blob from a PDF using pypdf library.

This class provides methods to parse a blob from a PDF document, supporting various configurations such as handling password-protected PDFs, extracting images. It integrates the ‘pypdf’ library for PDF processing and offers synchronous blob parsing.

Examples:

Setup:

pip install -U langchain-community pypdf

Load a blob from a PDF file:

from langchain_core.documents.base import Blob

blob = Blob.from_path("./example_data/layout-parser-paper.pdf")

Instantiate the parser:

from langchain_community.document_loaders.parsers import PyPDFParser

parser = PyPDFParser(
    # password = None,
    mode = "single",
    pages_delimiter = "
“,

# images_parser = TesseractBlobParser(),

)

Lazily parse the blob:

docs = []
docs_lazy = parser.lazy_parse(blob)

for doc in docs_lazy:
    docs.append(doc)
print(docs[0].page_content[:100])
print(docs[0].metadata)

Initialize a parser based on PyPDF.

Parameters:

  • password (Optional[Union[str, bytes]]) – Optional password for opening encrypted PDFs.

  • extract_images (bool) – Whether to extract images from the PDF.

  • mode (Literal['single', 'page']) – The extraction mode, either “single” for the entire document or “page” for page-wise extraction.

  • pages_delimiter (str) – A string delimiter to separate pages in single-mode extraction.

  • images_parser (Optional[BaseImageBlobParser]) – Optional image blob parser.

  • images_inner_format (Literal['text', 'markdown-img', 'html-img']) – The format for the parsed output. - “text” = return the content as is - “markdown-img” = wrap the content into an image markdown link, w/ link pointing to (![body)(#)] - “html-img” = wrap the content as the alt text of an tag and link to (<img alt=”{body}” src=”#”/>)

  • extraction_mode (Literal['plain', 'layout']) – “plain” for legacy functionality, “layout” extract text in a fixed width format that closely adheres to the rendered layout in the source pdf.

  • extraction_kwargs (Optional[dict[str, Any]]) – Optional additional parameters for the extraction process.

Raises:

ValueError – If the mode is not “single” or “page”.

Methods

__init__([password, extract_images, mode, ...])

Initialize a parser based on PyPDF.

extract_images_from_page(page)

Extract images from a PDF page and get the text using images_to_text.

lazy_parse(blob)

Lazily parse the blob.

parse(blob)

Eagerly parse the blob into a document or documents.
__init__(password: str | bytes | None = None, extract_images: bool = False, *, mode: Literal['single', 'page'] = 'page', pages_delimiter: str = '\n\x0c', images_parser: BaseImageBlobParser | None = None, images_inner_format: Literal['text', 'markdown-img', 'html-img'] = 'text', extraction_mode: Literal['plain', 'layout'] = 'plain', extraction_kwargs: dict[str, Any] | None = None)[source]#

Initialize a parser based on PyPDF.

Parameters:

  • password (str | bytes | None) – Optional password for opening encrypted PDFs.

  • extract_images (bool) – Whether to extract images from the PDF.

  • mode (Literal['single', 'page']) – The extraction mode, either “single” for the entire document or “page” for page-wise extraction.

  • pages_delimiter (str) – A string delimiter to separate pages in single-mode extraction.

  • images_parser (BaseImageBlobParser | None) – Optional image blob parser.

  • images_inner_format (Literal['text', 'markdown-img', 'html-img']) – The format for the parsed output. - “text” = return the content as is - “markdown-img” = wrap the content into an image markdown link, w/ link pointing to (![body)(#)] - “html-img” = wrap the content as the alt text of an tag and link to (<img alt=”{body}” src=”#”/>)

  • extraction_mode (Literal['plain', 'layout']) – “plain” for legacy functionality, “layout” extract text in a fixed width format that closely adheres to the rendered layout in the source pdf.

  • extraction_kwargs (dict[str, Any] | None) – Optional additional parameters for the extraction process.

Raises:

ValueError – If the mode is not “single” or “page”.

extract_images_from_page(page: pypdf._page.PageObject) → str[source]#

Extract images from a PDF page and get the text using images_to_text.

Parameters:

page (pypdf._page.PageObject) – The page object from which to extract images.

Returns:

The extracted text from the images on the page.

Return type:

str

lazy_parse(blob: Blob) → Iterator[Document][source]#

Lazily parse the blob. Insert image, if possible, between two paragraphs. In this way, a paragraph can be continued on the next page.

Parameters:

blob (Blob) – The blob to parse.

Raises:

ImportError – If the pypdf package is not found.

Yields:

An iterator over the parsed documents.

Return type:

Iterator[Document]

parse(blob: Blob) → list[Document]#

Eagerly parse the blob into a document or documents.

This is a convenience method for interactive development environment.

Production applications should favor the lazy_parse method instead.

Subclasses should generally not over-ride this parse method.

Parameters:

blob (Blob) – Blob instance

Returns:

List of documents

Return type:

list[Document]