HTML Document Loaders in LangChain

https://python.langchain.com.cn/docs/modules/data_connection/document_loaders/how_to/html

HTML Document Loaders in LangChain

This content is based on LangChain's official documentation (langchain.com.cn) and explains two HTML loaders ---tools to extract text and metadata from HTML files into LangChain Document objects---in simplified terms. It strictly preserves original source codes, examples, and knowledge points without arbitrary additions or modifications.

Key Note: HTML (HyperText Markup Language) is the standard language for web documents. LangChain's HTML loaders strip away HTML tags to extract usable text, with optional metadata (e.g., page title).

1. What Are HTML Loaders?

HTML loaders convert raw HTML files into structured Document objects for LangChain workflows.

  • Core function: Extract text content from HTML (removing tags like <h1>, <p>) and attach metadata (e.g., file source).
  • Two supported loaders:
    • UnstructuredHTMLLoader: Simple loader for basic text extraction.
    • BSHTMLLoader: Uses the BeautifulSoup4 library to extract text + page title (stored in metadata).

2. Prerequisites

  • For BSHTMLLoader, install the BeautifulSoup4 library first (required for HTML parsing):

    bash 复制代码
    pip install beautifulsoup4

3. Loader 1: UnstructuredHTMLLoader (Basic Text Extraction)

This loader extracts plain text from HTML, ignoring complex metadata (e.g., page title).

Step 3.1: Import the Loader

python 复制代码
from langchain.document_loaders import UnstructuredHTMLLoader

Step 3.2: Initialize and Load the HTML File

python 复制代码
# Initialize loader with the path to your HTML file
loader = UnstructuredHTMLLoader("example_data/fake-content.html")

# Load the HTML into a Document object
data = loader.load()

Step 3.3: View the Result

python 复制代码
data

Output (Exact as Original):

python 复制代码
[Document(page_content='My First Heading\n\nMy first paragraph.', lookup_str='', metadata={'source': 'example_data/fake-content.html'}, lookup_index=0)]

4. Loader 2: BSHTMLLoader (Text + Title Extraction)

This loader uses BeautifulSoup4 to extract both text content and the HTML page's title (stored in the title field of metadata).

Step 4.1: Import the Loader

python 复制代码
from langchain.document_loaders import BSHTMLLoader

Step 4.2: Initialize and Load the HTML File

python 复制代码
# Initialize loader with the path to your HTML file
loader = BSHTMLLoader("example_data/fake-content.html")

# Load the HTML into a Document object
data = loader.load()

Step 4.3: View the Result

python 复制代码
data

Output (Exact as Original):

python 复制代码
[Document(page_content='\n\nTest Title\n\n\nMy First Heading\nMy first paragraph.\n\n\n', metadata={'source': 'example_data/fake-content.html', 'title': 'Test Title'})]

Key Takeaways

  • UnstructuredHTMLLoader: Extracts basic text from HTML (no title metadata).
  • BSHTMLLoader: Requires BeautifulSoup4, extracts text + page title (stored in metadata["title"]).
  • Both loaders return Document objects with page_content (extracted text) and metadata["source"] (file path).
相关推荐
大模型真好玩10 小时前
LangChain DeepAgents 速通指南(九)—— 生产级智能体框架 DeepAgents Code 源码导读
人工智能·langchain·agent
牛奶2 天前
如何自己写一个浏览器插件?
前端·chrome·浏览器
ZhengEnCi2 天前
Q02-Vue-React-index.html完全指南
vue.js·react.js·html
牧艺2 天前
HTML-in-Canvas 深度解析:让 Canvas 真正「吃上」HTML 这碗饭
前端·html·canvas
早点睡啊3 天前
精读 LangChain 官方文档(二)Model 篇:把模型调用升级成工程化推理接口
人工智能·langchain
爱勇宝3 天前
我给自己做了一个新标签页:不登录、不打扰、打开就能用
前端·html·浏览器
越努力越幸运663 天前
多模态代码调试实战:Gemini3.5 精准捕获 HTML 隐性语法
html
星始流年4 天前
从 Tool 到 Skill——基于 LangChain 的服务端Skill实现
前端·langchain·agent
codedx5 天前
LangChain 和 LangGraph 构建的 Agent 项目模版
后端·langchain·agent
颜酱5 天前
LangGraph 入门指南
langchain