This notebook shows how to load email (.eml
) or Microsoft Outlook
(.msg
) files.
Using Unstructured
%pip install --upgrade --quiet unstructured
from langchain_community.document_loaders import UnstructuredEmailLoader
API Reference:
loader = UnstructuredEmailLoader("example_data/fake-email.eml")
data = loader.load()
data
[Document(page_content='This is a test email to use for unit tests.\n\nImportant points:\n\nRoses are red\n\nViolets are blue', metadata={'source': 'example_data/fake-email.eml'})]
Retain Elements
Under the hood, Unstructured creates different "elements" for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying mode="elements"
.
loader = UnstructuredEmailLoader("example_data/fake-email.eml", mode="elements")
data = loader.load()
data[0]
Document(page_content='This is a test email to use for unit tests.', metadata={'source': 'example_data/fake-email.eml', 'filename': 'fake-email.eml', 'file_directory': 'example_data', 'date': '2022-12-16T17:04:16-05:00', 'filetype': 'message/rfc822', 'sent_from': ['Matthew Robinson <mrobinson@unstructured.io>'], 'sent_to': ['Matthew Robinson <mrobinson@unstructured.io>'], 'subject': 'Test Email', 'category': 'NarrativeText'})
Processing Attachments
You can process attachments with UnstructuredEmailLoader
by setting process_attachments=True
in the constructor. By default, attachments will be partitioned using the partition
function from unstructured
. You can use a different partitioning function by passing the function to the attachment_partitioner
kwarg.
loader = UnstructuredEmailLoader(
"example_data/fake-email.eml",
mode="elements",
process_attachments=True,
)
data = loader.load()
data[0]
Document(page_content='This is a test email to use for unit tests.', metadata={'source': 'example_data/fake-email.eml', 'filename': 'fake-email.eml', 'file_directory': 'example_data', 'date': '2022-12-16T17:04:16-05:00', 'filetype': 'message/rfc822', 'sent_from': ['Matthew Robinson <mrobinson@unstructured.io>'], 'sent_to': ['Matthew Robinson <mrobinson@unstructured.io>'], 'subject': 'Test Email', 'category': 'NarrativeText'})
Using OutlookMessageLoader
%pip install --upgrade --quiet extract_msg
from langchain_community.document_loaders import OutlookMessageLoader
API Reference:
loader = OutlookMessageLoader("example_data/fake-email.msg")
data = loader.load()
data[0]
Document(page_content='This is a test email to experiment with the MS Outlook MSG Extractor\r\n\r\n\r\n-- \r\n\r\n\r\nKind regards\r\n\r\n\r\n\r\n\r\nBrian Zhou\r\n\r\n', metadata={'subject': 'Test for TIF files', 'sender': 'Brian Zhou <brizhou@gmail.com>', 'date': 'Mon, 18 Nov 2013 16:26:24 +0800'})