ZeroxPDFLoader#

class langchain_community.document_loaders.pdf.ZeroxPDFLoader(file_path: str | Path, model: str = 'gpt-4o-mini', **zerox_kwargs: Any)[source]#

Document loader utilizing Zerox library: getomni-ai/zerox

Zerox converts PDF document to serties of images (page-wise) and uses vision-capable LLM model to generate Markdown representation.

Zerox utilizes anyc operations. Therefore when using this loader inside Jupyter Notebook (or any environment running async) you will need to: ```python

import nest_asyncio nest_asyncio.apply()

```

Initialize with a file path.

Parameters:

file_path (str | Path) – Either a local, S3 or web path to a PDF file.
headers – Headers to use for GET request to download a file from a web path.
model (str)
zerox_kwargs (Any)

Attributes

source

Methods

`__init__`(file_path[, model])	Initialize with a file path.
`alazy_load`()	A lazy loader for Documents.
`aload`()	Load data into Document objects.
`lazy_load`()	Loads documnts from pdf utilizing zerox library: getomni-ai/zerox
`load`()	Load data into Document objects.
`load_and_split`([text_splitter])	Load Documents and split into chunks.

__init__(file_path: str | Path, model: str = 'gpt-4o-mini', **zerox_kwargs: Any) → None[source]#

Initialize with a file path.

Parameters:

file_path (str | Path) – Either a local, S3 or web path to a PDF file.
headers – Headers to use for GET request to download a file from a web path.
model (str)
zerox_kwargs (Any)

Return type:

None

async alazy_load() → AsyncIterator[Document]#

A lazy loader for Documents.

Return type:: AsyncIterator[Document]

async aload() → list[Document]#

Load data into Document objects.

Return type:: list[Document]

lazy_load() → Iterator[Document][source]#

Loads documnts from pdf utilizing zerox library: getomni-ai/zerox

Returns:: An iterator over parsed Document instances.
Return type:: Iterator[Document]

load() → list[Document]#

Load data into Document objects.

Return type:: list[Document]

load_and_split(text_splitter: TextSplitter | None = None) → list[Document]#

Load Documents and split into chunks. Chunks are returned as Documents.

Do not override this method. It should be considered to be deprecated!

Parameters:: text_splitter (Optional[TextSplitter]) – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.
Returns:: List of Documents.
Return type:: list[Document]