langchain/docs/extras/integrations/document_loaders/email.ipynb

Email

This notebook shows how to load email (.eml) or Microsoft Outlook (.msg) files.

Using Unstructured

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#!pip install unstructured

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from langchain.document_loaders import UnstructuredEmailLoader

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loader = UnstructuredEmailLoader("example_data/fake-email.eml")

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data = loader.load()

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data

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[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".

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loader = UnstructuredEmailLoader("example_data/fake-email.eml", mode="elements")

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data = loader.load()

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data[0]

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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.

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loader = UnstructuredEmailLoader(
    "example_data/fake-email.eml",
    mode="elements",
    process_attachments=True,
)

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data = loader.load()

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data[0]

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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

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#!pip install extract_msg

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from langchain.document_loaders import OutlookMessageLoader

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loader = OutlookMessageLoader("example_data/fake-email.msg")

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data = loader.load()

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data[0]

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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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