Use this file to discover all available pages before exploring further.
Document loaders provide a standard interface for reading data from different sources (such as Slack, Notion, or Google Drive) into LangChain’s Document format.
This ensures that data can be handled consistently regardless of the source.All document loaders implement the BaseLoader interface.
Community document loaders are user-contributed and unverified. LangChain does not review or endorse these integrations; use them at your own risk.
Each document loader may define its own parameters, but they share a common API:
load() – Loads all documents at once.
lazy_load() – Streams documents lazily, useful for large datasets.
from langchain_docling.loader import DoclingLoaderFILE_PATH = "https://arxiv.org/pdf/2408.09869"loader = DoclingLoader(file_path=FILE_PATH)# Load all documentsdocuments = loader.load()# For large datasets, lazily load documentsfor document in loader.lazy_load(): print(document)
