如何按 HTML 标题分割
描述和动机
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,并为每个与给定块“相关”的标题添加元数据。它可以逐个元素返回块,也可以将具有相同元数据的元素组合在一起,其目标是 (a) 将相关文本(或多或少)在语义上分组,以及 (b) 保留文档结构中编码的富含上下文的信息。它可以与其他文本分割器一起用作分块管道的一部分。
它类似于用于 markdown 文件的 MarkdownHeaderTextSplitter。
要指定要分割的标题,请在实例化 HTMLHeaderTextSplitter
时指定 headers_to_split_on
,如下所示。
使用示例
1) 如何分割 HTML 字符串:
%pip install -qU langchain-text-splitters
from langchain_text_splitters import HTMLHeaderTextSplitter
html_string = """
<!DOCTYPE html>
<html>
<body>
<div>
<h1>Foo</h1>
<p>Some intro text about Foo.</p>
<div>
<h2>Bar main section</h2>
<p>Some intro text about Bar.</p>
<h3>Bar subsection 1</h3>
<p>Some text about the first subtopic of Bar.</p>
<h3>Bar subsection 2</h3>
<p>Some text about the second subtopic of Bar.</p>
</div>
<div>
<h2>Baz</h2>
<p>Some text about Baz</p>
</div>
<br>
<p>Some concluding text about Foo</p>
</div>
</body>
</html>
"""
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
[Document(page_content='Foo'),
Document(page_content='Some intro text about Foo. \nBar main section Bar subsection 1 Bar subsection 2', metadata={'Header 1': 'Foo'}),
Document(page_content='Some intro text about Bar.', metadata={'Header 1': 'Foo', 'Header 2': 'Bar main section'}),
Document(page_content='Some text about the first subtopic of Bar.', metadata={'Header 1': 'Foo', 'Header 2': 'Bar main section', 'Header 3': 'Bar subsection 1'}),
Document(page_content='Some text about the second subtopic of Bar.', metadata={'Header 1': 'Foo', 'Header 2': 'Bar main section', 'Header 3': 'Bar subsection 2'}),
Document(page_content='Baz', metadata={'Header 1': 'Foo'}),
Document(page_content='Some text about Baz', metadata={'Header 1': 'Foo', 'Header 2': 'Baz'}),
Document(page_content='Some concluding text about Foo', metadata={'Header 1': 'Foo'})]
要返回每个元素及其关联的标题,请在实例化 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)
与上述将元素按标题聚合的情况进行比较
for element in html_header_splits[:2]:
print(element)
page_content='Foo'
page_content='Some intro text about Foo. \nBar main section Bar subsection 1 Bar subsection 2' metadata={'Header 1': 'Foo'}
现在,每个元素都作为不同的 Document
返回
for element in html_header_splits_elements[:3]:
print(element)
page_content='Foo'
page_content='Some intro text about Foo.' metadata={'Header 1': 'Foo'}
page_content='Bar main section Bar subsection 1 Bar subsection 2' metadata={'Header 1': 'Foo'}
2) 如何从 URL 或 HTML 文件分割:
要直接从 URL 读取,请将 URL 字符串传递到 split_text_from_url
方法中。
类似地,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)
2) 如何约束块大小:
HTMLHeaderTextSplitter
基于 HTML 标题进行分割,它可以与另一个基于字符长度约束分割的分割器(例如 RecursiveCharacterTextSplitter
)组合使用。
这可以使用第二个分割器的 .split_documents
方法完成
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]
[Document(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', 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'}),
Document(page_content='means that arithmetic truth and arithmetic provability are not co-extensive — whence the First Incompleteness Theorem.', 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'}),
Document(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', 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'}),
Document(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.', 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'}),
Document(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.', 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'})]
局限性
HTML 文档的结构可能存在相当大的差异,虽然 HTMLHeaderTextSplitter
会尝试将所有“相关”的标题附加到任何给定的块,但有时可能会遗漏某些标题。例如,该算法假设一个信息层次结构,其中标题始终位于相关文本“上方”的节点,即之前的兄弟节点、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”)与我们期望它“上方”的文本元素位于不同的子树中——因此我们可以观察到,“h1”元素及其关联的文本没有显示在块元数据中(但是,如果适用,我们确实看到了“h2”及其关联的文本)
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