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Email

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
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 β€œelements” 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'})

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