Load email files using Unstructured.
Works with both .eml and .msg files. You can process attachments in addition to the e-mail message itself by passing process_attachments=True into the constructor for the loader. By default, attachments will be processed with the unstructured partition function. If you already know the document types of the attachments, you can specify another partitioning function with the attachment partitioner kwarg.
from langchain_community.document_loaders import UnstructuredEmailLoader
loader = UnstructuredEmailLoader("example_data/fake-email.eml", mode="elements") loader.load()
from langchain_community.document_loaders import UnstructuredEmailLoader
loader = UnstructuredEmailLoader( "example_data/fake-email-attachment.eml", mode="elements", process_attachments=True, ) loader.load()
Loads Outlook Message files using extract_msg.
Load files using Unstructured.
The file loader uses the unstructured partition function and will automatically detect the file type. You can run the loader in different modes: "single", "elements", and "paged". The default "single" mode will return a single langchain Document object. If you use "elements" mode, the unstructured library will split the document into elements such as Title and NarrativeText and return those as individual langchain Document objects. In addition to these post-processing modes (which are specific to the LangChain Loaders), Unstructured has its own "chunking" parameters for post-processing elements into more useful chunks for uses cases such as Retrieval Augmented Generation (RAG). You can pass in additional unstructured kwargs to configure different unstructured settings.
from langchain_community.document_loaders import UnstructuredFileLoader
loader = UnstructuredFileLoader( "example.pdf", mode="elements", strategy="fast", ) docs = loader.load()
https://docs.unstructured.io/open-source/core-functionality/partitioning https://docs.unstructured.io/open-source/core-functionality/chunking
