> ## Documentation Index
> Fetch the complete documentation index at: https://cndoc-langchain.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 电子邮件集成

> 使用 LangChain Python 与电子邮件文档加载器集成。

本笔记本展示了如何加载电子邮件（`.eml`）或 `Microsoft Outlook`（`.msg`）文件。

请参阅 [Unstructured](/oss/python/integrations/providers/unstructured/) 以获取有关在本地设置 Unstructured 的更多说明，包括设置所需的系统依赖项。

## 使用 unstructured

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pip install -qU unstructured
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_community.document_loaders import UnstructuredEmailLoader

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

data = loader.load()

data
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[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'})]
```

### 保留元素

在底层，Unstructured 为不同的文本块创建不同的“元素”。默认情况下，我们将它们组合在一起，但你可以通过指定 `mode="elements"` 轻松地保持这种分离。

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
loader = UnstructuredEmailLoader("example_data/fake-email.eml", mode="elements")

data = loader.load()

data[0]
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
Document(page_content='This is a test email to use for unit tests.', metadata={'source': 'example_data/fake-email.eml', 'file_directory': 'example_data', 'filename': 'fake-email.eml', 'last_modified': '2022-12-16T17:04:16-05:00', 'sent_from': ['Matthew Robinson [mrobinson@unstructured.io](mailto:mrobinson@unstructured.io)'], 'sent_to': ['Matthew Robinson [mrobinson@unstructured.io](mailto:mrobinson@unstructured.io)'], 'subject': 'Test Email', 'languages': ['eng'], 'filetype': 'message/rfc822', 'category': 'NarrativeText'})
```

### 处理附件

你可以通过在构造函数中设置 `process_attachments=True` 来使用 `UnstructuredEmailLoader` 处理附件。默认情况下，附件将使用 `unstructured` 中的 `partition` 函数进行分区。你可以通过将函数传递给 `attachment_partitioner` 关键字参数来使用不同的分区函数。

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
loader = UnstructuredEmailLoader(
    "example_data/fake-email.eml",
    mode="elements",
    process_attachments=True,
)

data = loader.load()

data[0]
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
Document(page_content='This is a test email to use for unit tests.', metadata={'source': 'example_data/fake-email.eml', 'file_directory': 'example_data', 'filename': 'fake-email.eml', 'last_modified': '2022-12-16T17:04:16-05:00', 'sent_from': ['Matthew Robinson [mrobinson@unstructured.io](mailto:mrobinson@unstructured.io)'], 'sent_to': ['Matthew Robinson [mrobinson@unstructured.io](mailto:mrobinson@unstructured.io)'], 'subject': 'Test Email', 'languages': ['eng'], 'filetype': 'message/rfc822', 'category': 'NarrativeText'})
```

## 使用 OutlookMessageLoader

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pip install -qU extract_msg
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_community.document_loaders import OutlookMessageLoader

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

data = loader.load()

data[0]
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
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={'source': 'example_data/fake-email.msg', 'subject': 'Test for TIF files', 'sender': 'Brian Zhou [brizhou@gmail.com](mailto:brizhou@gmail.com)', 'date': datetime.datetime(2013, 11, 18, 0, 26, 24, tzinfo=zoneinfo.ZoneInfo(key='America/Los_Angeles'))})
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
```

***

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    [在 GitHub 上编辑此页面](https://github.com/langchain-ai/docs/edit/main/src/oss/python/integrations/document_loaders/email.mdx) 或 [提交问题](https://github.com/langchain-ai/docs/issues/new/choose)。
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