如何拆分HTML

将HTML文档分割成可管理的块对于各种文本处理任务（如自然语言处理、搜索索引等）至关重要。在本指南中，我们将探讨LangChain提供的三种不同的文本分割器，您可以使用它们来有效地分割HTML内容：

HTMLHeaderTextSplitter
HTMLSectionSplitter
HTML语义保留分割器

这些分割器中的每一个都有独特的功能和用例。本指南将帮助您理解它们之间的差异，为什么您可能会选择其中一个而不是其他，以及如何有效地使用它们。

%pip install -qU langchain-text-splitters

分割器概述

HTMLHeaderTextSplitter

info

当您希望根据文档的标题保留其层次结构时非常有用。

描述: 根据标题标签（例如，

, , 等）拆分HTML文本，并为每个标题添加与任何给定块相关的元数据。

功能:

在HTML元素级别拆分文本。
保留文档结构中编码的丰富上下文信息。
可以逐个元素返回块，或者将具有相同元数据的元素组合起来。

HTMLSectionSplitter

info

当您想要将HTML文档分割成更大的部分时，例如

、或自定义部分时，这很有用。

描述: 类似于 HTMLHeaderTextSplitter，但专注于根据指定的标签将 HTML 分割成部分。

功能:

使用XSLT转换来检测和分割部分。
内部使用 RecursiveCharacterTextSplitter 处理大段内容。
考虑字体大小以确定部分。

HTMLSemanticPreservingSplitter

info

当您需要确保结构化元素不会跨块分割，保持上下文相关性时，这是理想的选择。

描述: 将HTML内容分割成可管理的块，同时保留表格、列表和其他HTML组件的重要元素的语义结构。

功能:

保留表格、列表和其他指定的HTML元素。
允许为特定的HTML标签自定义处理程序。
确保文档的语义含义得以保留。
内置的标准化和停用词移除

选择合适的分割器

使用 HTMLHeaderTextSplitter 的情况：当你需要根据HTML文档的标题层次结构进行分割，并保留有关标题的元数据时。
使用 HTMLSectionSplitter 的情况：当您需要将文档分割成更大、更通用的部分时，可能是基于自定义标签或字体大小。
使用 HTMLSemanticPreservingSplitter 的情况：当您需要将文档分割成块，同时保留表格和列表等语义元素，确保它们不会被分割并且它们的上下文得以保持。

功能	HTMLHeaderTextSplitter	HTMLSectionSplitter	HTMLSemanticPreservingSplitter
基于标题的分割	是	是	是
保留语义元素（表格、列表）	否	否	是
为头部添加元数据	是	是	是
HTML标签的自定义处理程序	否	否	是
保留媒体（图片、视频）	否	否	是
考虑字体大小	否	是	否
使用XSLT转换	否	是	否

示例HTML文档

让我们使用以下HTML文档作为示例：

html_string = """
<!DOCTYPE html>
  <html lang='en'>
  <head>
    <meta charset='UTF-8'>
    <meta name='viewport' content='width=device-width, initial-scale=1.0'>
    <title>Fancy Example HTML Page</title>
  </head>
  <body>
    <h1>Main Title</h1>
    <p>This is an introductory paragraph with some basic content.</p>
    
    <h2>Section 1: Introduction</h2>
    <p>This section introduces the topic. Below is a list:</p>
    <ul>
      <li>First item</li>
      <li>Second item</li>
      <li>Third item with <strong>bold text</strong> and <a href='#'>a link</a></li>
    </ul>
    
    <h3>Subsection 1.1: Details</h3>
    <p>This subsection provides additional details. Here's a table:</p>
    <table border='1'>
      <thead>
        <tr>
          <th>Header 1</th>
          <th>Header 2</th>
          <th>Header 3</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td>Row 1, Cell 1</td>
          <td>Row 1, Cell 2</td>
          <td>Row 1, Cell 3</td>
        </tr>
        <tr>
          <td>Row 2, Cell 1</td>
          <td>Row 2, Cell 2</td>
          <td>Row 2, Cell 3</td>
        </tr>
      </tbody>
    </table>
    
    <h2>Section 2: Media Content</h2>
    <p>This section contains an image and a video:</p>
      <img src='example_image_link.mp4' alt='Example Image'>
      <video controls width='250' src='example_video_link.mp4' type='video/mp4'>
      Your browser does not support the video tag.
    </video>

    <h2>Section 3: Code Example</h2>
    <p>This section contains a code block:</p>
    <pre><code data-lang="html">
    &lt;div&gt;
      &lt;p&gt;This is a paragraph inside a div.&lt;/p&gt;
    &lt;/div&gt;
    </code></pre>

    <h2>Conclusion</h2>
    <p>This is the conclusion of the document.</p>
  </body>
  </html>
"""

使用 HTMLHeaderTextSplitter

HTMLHeaderTextSplitter 是一个“结构感知”的文本分割器，它在 HTML 元素级别分割文本，并为每个与任何给定块“相关”的标题添加元数据。它可以逐个元素返回块，或者将具有相同元数据的元素组合在一起，目的是 (a) 保持相关文本在语义上（或多或少）分组，以及 (b) 保留文档结构中编码的上下文丰富信息。它可以与其他文本分割器一起使用，作为分块管道的一部分。

它类似于用于markdown文件的MarkdownHeaderTextSplitter。

要指定要拆分的标题，请在实例化HTMLHeaderTextSplitter时指定headers_to_split_on，如下所示。

from langchain_text_splitters import HTMLHeaderTextSplitter

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
    ("h3", "Header 3"),
]

html_splitter = HTMLHeaderTextSplitter(headers_to_split_on)
html_header_splits = html_splitter.split_text(html_string)
html_header_splits

API Reference:HTMLHeaderTextSplitter

[Document(metadata={'Header 1': 'Main Title'}, page_content='This is an introductory paragraph with some basic content.'),
 Document(metadata={'Header 1': 'Main Title', 'Header 2': 'Section 1: Introduction'}, page_content='This section introduces the topic. Below is a list:  \nFirst item Second item Third item with bold text and a link'),
 Document(metadata={'Header 1': 'Main Title', 'Header 2': 'Section 1: Introduction', 'Header 3': 'Subsection 1.1: Details'}, page_content="This subsection provides additional details. Here's a table:"),
 Document(metadata={'Header 1': 'Main Title', 'Header 2': 'Section 2: Media Content'}, page_content='This section contains an image and a video:'),
 Document(metadata={'Header 1': 'Main Title', 'Header 2': 'Section 3: Code Example'}, page_content='This section contains a code block:'),
 Document(metadata={'Header 1': 'Main Title', 'Header 2': 'Conclusion'}, page_content='This is the conclusion of the document.')]

要返回每个元素及其相关的标题，在实例化HTMLHeaderTextSplitter时指定return_each_element=True：

html_splitter = HTMLHeaderTextSplitter(
    headers_to_split_on,
    return_each_element=True,
)
html_header_splits_elements = html_splitter.split_text(html_string)

与上述情况相比，其中元素按其标题进行聚合：

for element in html_header_splits[:2]:
    print(element)

page_content='This is an introductory paragraph with some basic content.' metadata={'Header 1': 'Main Title'}
page_content='This section introduces the topic. Below is a list:  
First item Second item Third item with bold text and a link' metadata={'Header 1': 'Main Title', 'Header 2': 'Section 1: Introduction'}

现在每个元素都作为一个独立的 Document 返回：

for element in html_header_splits_elements[:3]:
    print(element)

page_content='This is an introductory paragraph with some basic content.' metadata={'Header 1': 'Main Title'}
page_content='This section introduces the topic. Below is a list:' metadata={'Header 1': 'Main Title', 'Header 2': 'Section 1: Introduction'}
page_content='First item Second item Third item with bold text and a link' metadata={'Header 1': 'Main Title', 'Header 2': 'Section 1: Introduction'}

如何从URL或HTML文件分割：

要从URL直接读取，将URL字符串传递给split_text_from_url方法。

同样，可以将本地HTML文件传递给split_text_from_file方法。

url = "https://plato.stanford.edu/entries/goedel/"

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
    ("h3", "Header 3"),
    ("h4", "Header 4"),
]

html_splitter = HTMLHeaderTextSplitter(headers_to_split_on)

# for local file use html_splitter.split_text_from_file(<path_to_file>)
html_header_splits = html_splitter.split_text_from_url(url)

如何限制块大小:

HTMLHeaderTextSplitter，它基于HTML标题进行分割，可以与另一个根据字符长度限制分割的分割器组合使用，例如RecursiveCharacterTextSplitter。

这可以通过第二个分割器的.split_documents方法来完成：

from langchain_text_splitters import RecursiveCharacterTextSplitter

chunk_size = 500
chunk_overlap = 30
text_splitter = RecursiveCharacterTextSplitter(
    chunk_size=chunk_size, chunk_overlap=chunk_overlap
)

# Split
splits = text_splitter.split_documents(html_header_splits)
splits[80:85]

API Reference:RecursiveCharacterTextSplitter

[Document(metadata={'Header 1': 'Kurt Gödel', 'Header 2': '2. Gödel’s Mathematical Work', 'Header 3': '2.2 The Incompleteness Theorems', 'Header 4': '2.2.1 The First Incompleteness Theorem'}, page_content='We see that Gödel first tried to reduce the consistency problem for analysis to that of arithmetic. This seemed to require a truth definition for arithmetic, which in turn led to paradoxes, such as the Liar paradox (“This sentence is false”) and Berry’s paradox (“The least number not defined by an expression consisting of just fourteen English words”). Gödel then noticed that such paradoxes would not necessarily arise if truth were replaced by provability. But this means that arithmetic truth'),
 Document(metadata={'Header 1': 'Kurt Gödel', 'Header 2': '2. Gödel’s Mathematical Work', 'Header 3': '2.2 The Incompleteness Theorems', 'Header 4': '2.2.1 The First Incompleteness Theorem'}, page_content='means that arithmetic truth and arithmetic provability are not co-extensive — whence the First Incompleteness Theorem.'),
 Document(metadata={'Header 1': 'Kurt Gödel', 'Header 2': '2. Gödel’s Mathematical Work', 'Header 3': '2.2 The Incompleteness Theorems', 'Header 4': '2.2.1 The First Incompleteness Theorem'}, page_content='This account of Gödel’s discovery was told to Hao Wang very much after the fact; but in Gödel’s contemporary correspondence with Bernays and Zermelo, essentially the same description of his path to the theorems is given. (See Gödel 2003a and Gödel 2003b respectively.) From those accounts we see that the undefinability of truth in arithmetic, a result credited to Tarski, was likely obtained in some form by Gödel by 1931. But he neither publicized nor published the result; the biases logicians'),
 Document(metadata={'Header 1': 'Kurt Gödel', 'Header 2': '2. Gödel’s Mathematical Work', 'Header 3': '2.2 The Incompleteness Theorems', 'Header 4': '2.2.1 The First Incompleteness Theorem'}, page_content='result; the biases logicians had expressed at the time concerning the notion of truth, biases which came vehemently to the fore when Tarski announced his results on the undefinability of truth in formal systems 1935, may have served as a deterrent to Gödel’s publication of that theorem.'),
 Document(metadata={'Header 1': 'Kurt Gödel', 'Header 2': '2. Gödel’s Mathematical Work', 'Header 3': '2.2 The Incompleteness Theorems', 'Header 4': '2.2.2 The proof of the First Incompleteness Theorem'}, page_content='We now describe the proof of the two theorems, formulating Gödel’s results in Peano arithmetic. Gödel himself used a system related to that defined in Principia Mathematica, but containing Peano arithmetic. In our presentation of the First and Second Incompleteness Theorems we refer to Peano arithmetic as P, following Gödel’s notation.')]

限制

不同的HTML文档之间可能存在相当大的结构差异，虽然HTMLHeaderTextSplitter会尝试将所有“相关”的标题附加到任何给定的块中，但有时可能会遗漏某些标题。例如，该算法假设信息层次结构中标题始终位于相关文本的“上方”节点，即前兄弟节点、祖先节点及其组合。在以下新闻文章中（截至撰写本文时），文档的结构使得顶级标题的文本虽然标记为“h1”，但与我们所期望的“上方”文本元素位于不同的子树中——因此我们可以观察到“h1”元素及其相关文本不会出现在块元数据中（但在适用的情况下，我们确实会看到“h2”及其相关文本）：

url = "https://www.cnn.com/2023/09/25/weather/el-nino-winter-us-climate/index.html"

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
]

html_splitter = HTMLHeaderTextSplitter(headers_to_split_on)
html_header_splits = html_splitter.split_text_from_url(url)
print(html_header_splits[1].page_content[:500])

No two El Niño winters are the same, but many have temperature and precipitation trends in common.  
Average conditions during an El Niño winter across the continental US.  
One of the major reasons is the position of the jet stream, which often shifts south during an El Niño winter. This shift typically brings wetter and cooler weather to the South while the North becomes drier and warmer, according to NOAA.  
Because the jet stream is essentially a river of air that storms flow through, they c

使用 HTMLSectionSplitter

与HTMLHeaderTextSplitter的概念相似，HTMLSectionSplitter是一种“结构感知”的文本分割器，它在元素级别分割文本，并为每个与任何给定块“相关”的标题添加元数据。它允许你按部分分割HTML。

它可以逐个元素返回块，或者将具有相同元数据的元素组合在一起，目的是（a）保持相关文本在语义上（或多或少）分组，以及（b）保留文档结构中编码的上下文丰富信息。

使用xslt_path提供一个绝对路径来转换HTML，以便它可以根据提供的标签检测部分。默认情况下，使用data_connection/document_transformers目录中的converting_to_header.xslt文件。这是为了将HTML转换为更容易检测部分的格式/布局。例如，基于字体大小的span可以转换为标题标签，以便被检测为一个部分。

如何分割HTML字符串：

from langchain_text_splitters import HTMLSectionSplitter

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
]

html_splitter = HTMLSectionSplitter(headers_to_split_on)
html_header_splits = html_splitter.split_text(html_string)
html_header_splits

API Reference:HTMLSectionSplitter

[Document(metadata={'Header 1': 'Main Title'}, page_content='Main Title \n This is an introductory paragraph with some basic content.'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content="Section 1: Introduction \n This section introduces the topic. Below is a list: \n \n First item \n Second item \n Third item with  bold text  and  a link \n \n \n Subsection 1.1: Details \n This subsection provides additional details. Here's a table: \n \n \n \n Header 1 \n Header 2 \n Header 3 \n \n \n \n \n Row 1, Cell 1 \n Row 1, Cell 2 \n Row 1, Cell 3 \n \n \n Row 2, Cell 1 \n Row 2, Cell 2 \n Row 2, Cell 3"),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='Section 2: Media Content \n This section contains an image and a video: \n \n \n      Your browser does not support the video tag.'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='Section 3: Code Example \n This section contains a code block: \n \n    <div>\n      <p>This is a paragraph inside a div.</p>\n    </div>'),
 Document(metadata={'Header 2': 'Conclusion'}, page_content='Conclusion \n This is the conclusion of the document.')]

如何限制块大小：

HTMLSectionSplitter 可以与其他文本分割器一起使用，作为分块管道的一部分。在内部，当部分大小大于块大小时，它使用 RecursiveCharacterTextSplitter。它还考虑文本的字体大小，根据确定的字体大小阈值来判断它是否是一个部分。

from langchain_text_splitters import RecursiveCharacterTextSplitter

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
    ("h3", "Header 3"),
]

html_splitter = HTMLSectionSplitter(headers_to_split_on)

html_header_splits = html_splitter.split_text(html_string)

chunk_size = 50
chunk_overlap = 5
text_splitter = RecursiveCharacterTextSplitter(
    chunk_size=chunk_size, chunk_overlap=chunk_overlap
)

# Split
splits = text_splitter.split_documents(html_header_splits)
splits

API Reference:RecursiveCharacterTextSplitter

[Document(metadata={'Header 1': 'Main Title'}, page_content='Main Title'),
 Document(metadata={'Header 1': 'Main Title'}, page_content='This is an introductory paragraph with some'),
 Document(metadata={'Header 1': 'Main Title'}, page_content='some basic content.'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='Section 1: Introduction'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='This section introduces the topic. Below is a'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='is a list:'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='First item \n Second item'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='Third item with  bold text  and  a link'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='Subsection 1.1: Details'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='This subsection provides additional details.'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content="Here's a table:"),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='Header 1 \n Header 2 \n Header 3'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='Row 1, Cell 1 \n Row 1, Cell 2'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='Row 1, Cell 3 \n \n \n Row 2, Cell 1'),
 Document(metadata={'Header 3': 'Subsection 1.1: Details'}, page_content='Row 2, Cell 2 \n Row 2, Cell 3'),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='Section 2: Media Content'),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='This section contains an image and a video:'),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='Your browser does not support the video'),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='tag.'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='Section 3: Code Example'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='This section contains a code block: \n \n    <div>'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='<p>This is a paragraph inside a div.</p>'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='</div>'),
 Document(metadata={'Header 2': 'Conclusion'}, page_content='Conclusion'),
 Document(metadata={'Header 2': 'Conclusion'}, page_content='This is the conclusion of the document.')]

使用 HTMLSemanticPreservingSplitter

HTMLSemanticPreservingSplitter 旨在将HTML内容分割成可管理的块，同时保留重要元素（如表格、列表和其他HTML组件）的语义结构。这确保了这些元素不会在块之间分割，导致上下文相关性（如表头、列表头等）的丢失。

这个分割器的核心设计是为了创建上下文相关的块。使用HTMLHeaderTextSplitter进行一般递归分割可能会导致表格、列表和其他结构化元素在中间被分割，从而丢失重要的上下文并创建不良的块。

HTMLSemanticPreservingSplitter 对于拆分包含表格和列表等结构化元素的HTML内容至关重要，尤其是在需要保持这些元素完整的情况下。此外，它能够为特定的HTML标签定义自定义处理程序，使其成为处理复杂HTML文档的多功能工具。

重要: max_chunk_size 不是一个确定的块的最大大小，最大大小的计算发生在保留内容不属于块时，以确保它不会被分割。当我们把保留的数据重新添加到块中时，块的大小可能会超过 max_chunk_size。这对于确保我们保持原始文档的结构至关重要。

info

备注:

我们定义了一个自定义处理程序来重新格式化代码块的内容
我们为特定的html元素定义了一个拒绝列表，以便在预处理时分解它们及其内容
我们故意设置了一个小的块大小来演示元素的不分割

# BeautifulSoup is required to use the custom handlers
from bs4 import Tag
from langchain_text_splitters import HTMLSemanticPreservingSplitter

headers_to_split_on = [
    ("h1", "Header 1"),
    ("h2", "Header 2"),
]


def code_handler(element: Tag) -> str:
    data_lang = element.get("data-lang")
    code_format = f"<code:{data_lang}>{element.get_text()}</code>"

    return code_format


splitter = HTMLSemanticPreservingSplitter(
    headers_to_split_on=headers_to_split_on,
    separators=["\n\n", "\n", ". ", "! ", "? "],
    max_chunk_size=50,
    preserve_images=True,
    preserve_videos=True,
    elements_to_preserve=["table", "ul", "ol", "code"],
    denylist_tags=["script", "style", "head"],
    custom_handlers={"code": code_handler},
)

documents = splitter.split_text(html_string)
documents

API Reference:HTMLSemanticPreservingSplitter

[Document(metadata={'Header 1': 'Main Title'}, page_content='This is an introductory paragraph with some basic content.'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='This section introduces the topic'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content='. Below is a list: First item Second item Third item with bold text and a link Subsection 1.1: Details This subsection provides additional details'),
 Document(metadata={'Header 2': 'Section 1: Introduction'}, page_content=". Here's a table: Header 1 Header 2 Header 3 Row 1, Cell 1 Row 1, Cell 2 Row 1, Cell 3 Row 2, Cell 1 Row 2, Cell 2 Row 2, Cell 3"),
 Document(metadata={'Header 2': 'Section 2: Media Content'}, page_content='This section contains an image and a video: ![image:example_image_link.mp4](example_image_link.mp4) ![video:example_video_link.mp4](example_video_link.mp4)'),
 Document(metadata={'Header 2': 'Section 3: Code Example'}, page_content='This section contains a code block: <code:html> <div> <p>This is a paragraph inside a div.</p> </div> </code>'),
 Document(metadata={'Header 2': 'Conclusion'}, page_content='This is the conclusion of the document.')]

保留表格和列表

在这个例子中，我们将演示HTMLSemanticPreservingSplitter如何保留HTML文档中的表格和大列表。块大小将设置为50个字符，以说明分割器如何确保这些元素即使超过定义的最大块大小也不会被分割。

from langchain_text_splitters import HTMLSemanticPreservingSplitter

html_string = """
<!DOCTYPE html>
<html>
    <body>
        <div>
            <h1>Section 1</h1>
            <p>This section contains an important table and list that should not be split across chunks.</p>
            <table>
                <tr>
                    <th>Item</th>
                    <th>Quantity</th>
                    <th>Price</th>
                </tr>
                <tr>
                    <td>Apples</td>
                    <td>10</td>
                    <td>$1.00</td>
                </tr>
                <tr>
                    <td>Oranges</td>
                    <td>5</td>
                    <td>$0.50</td>
                </tr>
                <tr>
                    <td>Bananas</td>
                    <td>50</td>
                    <td>$1.50</td>
                </tr>
            </table>
            <h2>Subsection 1.1</h2>
            <p>Additional text in subsection 1.1 that is separated from the table and list.</p>
            <p>Here is a detailed list:</p>
            <ul>
                <li>Item 1: Description of item 1, which is quite detailed and important.</li>
                <li>Item 2: Description of item 2, which also contains significant information.</li>
                <li>Item 3: Description of item 3, another item that we don't want to split across chunks.</li>
            </ul>
        </div>
    </body>
</html>
"""

headers_to_split_on = [("h1", "Header 1"), ("h2", "Header 2")]

splitter = HTMLSemanticPreservingSplitter(
    headers_to_split_on=headers_to_split_on,
    max_chunk_size=50,
    elements_to_preserve=["table", "ul"],
)

documents = splitter.split_text(html_string)
print(documents)

API Reference:HTMLSemanticPreservingSplitter

[Document(metadata={'Header 1': 'Section 1'}, page_content='This section contains an important table and list'), Document(metadata={'Header 1': 'Section 1'}, page_content='that should not be split across chunks.'), Document(metadata={'Header 1': 'Section 1'}, page_content='Item Quantity Price Apples 10 $1.00 Oranges 5 $0.50 Bananas 50 $1.50'), Document(metadata={'Header 2': 'Subsection 1.1'}, page_content='Additional text in subsection 1.1 that is'), Document(metadata={'Header 2': 'Subsection 1.1'}, page_content='separated from the table and list. Here is a'), Document(metadata={'Header 2': 'Subsection 1.1'}, page_content="detailed list: Item 1: Description of item 1, which is quite detailed and important. Item 2: Description of item 2, which also contains significant information. Item 3: Description of item 3, another item that we don't want to split across chunks.")]

解释

在这个例子中，HTMLSemanticPreservingSplitter 确保整个表格和无序列表（

）在各自的块中得以保留。即使块大小设置为50个字符，分割器也能识别出这些元素不应被分割，并保持它们的完整性。

在处理数据表或列表时，这一点尤为重要，因为拆分内容可能导致上下文丢失或混淆。生成的Document对象保留了这些元素的完整结构，确保信息的上下文相关性得以维持。

使用自定义处理程序

HTMLSemanticPreservingSplitter 允许您为特定的HTML元素定义自定义处理程序。某些平台具有自定义的HTML标签，这些标签无法被BeautifulSoup原生解析，当这种情况发生时，您可以利用自定义处理程序轻松添加格式化逻辑。

这对于需要特殊处理的元素特别有用，例如标签或特定的'data-'元素。在这个例子中，我们将为iframe标签创建一个自定义处理程序，将它们转换为类似Markdown的链接。

def custom_iframe_extractor(iframe_tag):
    iframe_src = iframe_tag.get("src", "")
    return f"[iframe:{iframe_src}]({iframe_src})"


splitter = HTMLSemanticPreservingSplitter(
    headers_to_split_on=headers_to_split_on,
    max_chunk_size=50,
    separators=["\n\n", "\n", ". "],
    elements_to_preserve=["table", "ul", "ol"],
    custom_handlers={"iframe": custom_iframe_extractor},
)

html_string = """
<!DOCTYPE html>
<html>
    <body>
        <div>
            <h1>Section with Iframe</h1>
            <iframe src="https://example.com/embed"></iframe>
            <p>Some text after the iframe.</p>
            <ul>
                <li>Item 1: Description of item 1, which is quite detailed and important.</li>
                <li>Item 2: Description of item 2, which also contains significant information.</li>
                <li>Item 3: Description of item 3, another item that we don't want to split across chunks.</li>
            </ul>
        </div>
    </body>
</html>
"""

documents = splitter.split_text(html_string)
print(documents)

[Document(metadata={'Header 1': 'Section with Iframe'}, page_content='[iframe:https://example.com/embed](https://example.com/embed) Some text after the iframe'), Document(metadata={'Header 1': 'Section with Iframe'}, page_content=". Item 1: Description of item 1, which is quite detailed and important. Item 2: Description of item 2, which also contains significant information. Item 3: Description of item 3, another item that we don't want to split across chunks.")]

解释

在这个例子中，我们为iframe标签定义了一个自定义处理程序，将其转换为类似Markdown的链接。当分割器处理HTML内容时，它使用这个自定义处理程序来转换iframe标签，同时保留其他元素如表格和列表。生成的Document对象展示了如何根据您提供的自定义逻辑处理iframe。

重要: 当保留诸如链接等项目时，您应注意不要在分隔符中包含.，或将分隔符留空。RecursiveCharacterTextSplitter会在句号处分割，这会将链接切成两半。确保您提供一个包含. 的分隔符列表。

使用自定义处理程序通过LLM分析图像

通过自定义处理程序，我们还可以覆盖任何元素的默认处理。一个很好的例子是，在文档中直接插入图像的语义分析，直接进入分块流程。

由于我们的函数在发现标签时被调用，我们可以覆盖标签并关闭preserve_images以插入我们想要嵌入到块中的任何内容。

"""This example assumes you have helper methods `load_image_from_url` and an LLM agent `llm` that can process image data."""

from langchain.agents import AgentExecutor

# This example needs to be replaced with your own agent
llm = AgentExecutor(...)


# This method is a placeholder for loading image data from a URL and is not implemented here
def load_image_from_url(image_url: str) -> bytes:
    # Assuming this method fetches the image data from the URL
    return b"image_data"


html_string = """
<!DOCTYPE html>
<html>
    <body>
        <div>
            <h1>Section with Image and Link</h1>
            <p>
                <img src="https://example.com/image.jpg" alt="An example image" />
                Some text after the image.
            </p>
            <ul>
                <li>Item 1: Description of item 1, which is quite detailed and important.</li>
                <li>Item 2: Description of item 2, which also contains significant information.</li>
                <li>Item 3: Description of item 3, another item that we don't want to split across chunks.</li>
            </ul>
        </div>
    </body>
</html>
"""


def custom_image_handler(img_tag) -> str:
    img_src = img_tag.get("src", "")
    img_alt = img_tag.get("alt", "No alt text provided")

    image_data = load_image_from_url(img_src)
    semantic_meaning = llm.invoke(image_data)

    markdown_text = f"[Image Alt Text: {img_alt} | Image Source: {img_src} | Image Semantic Meaning: {semantic_meaning}]"

    return markdown_text


splitter = HTMLSemanticPreservingSplitter(
    headers_to_split_on=headers_to_split_on,
    max_chunk_size=50,
    separators=["\n\n", "\n", ". "],
    elements_to_preserve=["ul"],
    preserve_images=False,
    custom_handlers={"img": custom_image_handler},
)

documents = splitter.split_text(html_string)

print(documents)

API Reference:AgentExecutor

[Document(metadata={'Header 1': 'Section with Image and Link'}, page_content='[Image Alt Text: An example image | Image Source: https://example.com/image.jpg | Image Semantic Meaning: semantic-meaning] Some text after the image'), 
Document(metadata={'Header 1': 'Section with Image and Link'}, page_content=". Item 1: Description of item 1, which is quite detailed and important. Item 2: Description of item 2, which also contains significant information. Item 3: Description of item 3, another item that we don't want to split across chunks.")]

解释:

通过我们编写的自定义处理程序来从HTML中的元素提取特定字段，我们可以进一步使用我们的代理处理数据，并将结果直接插入到我们的块中。重要的是要确保preserve_images设置为False，否则将进行字段的默认处理。

分割器概述​

HTMLHeaderTextSplitter​

HTMLSectionSplitter​

HTMLSemanticPreservingSplitter​

选择合适的分割器​

示例HTML文档​

使用 HTMLHeaderTextSplitter​

如何从URL或HTML文件分割：​

如何限制块大小:​

限制​

使用 HTMLSectionSplitter​

如何分割HTML字符串：​

如何限制块大小：​

使用 HTMLSemanticPreservingSplitter​

保留表格和列表​

解释​

使用自定义处理程序​

解释​

使用自定义处理程序通过LLM分析图像​

解释:​

这个页面有帮助吗？

分割器概述

HTMLHeaderTextSplitter

HTMLSectionSplitter

HTMLSemanticPreservingSplitter

选择合适的分割器

示例HTML文档

使用 HTMLHeaderTextSplitter

如何从URL或HTML文件分割：

如何限制块大小:

限制

使用 HTMLSectionSplitter

如何分割HTML字符串：

如何限制块大小：

使用 HTMLSemanticPreservingSplitter

保留表格和列表

解释

使用自定义处理程序

解释

使用自定义处理程序通过LLM分析图像

解释: