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Sitemap

Extends from the WebBaseLoader, SitemapLoader loads a sitemap from a given URL, and then scrapes and loads all pages in the sitemap, returning each page as a Document.

The scraping is done concurrently. There are reasonable limits to concurrent requests, defaulting to 2 per second. If you aren't concerned about being a good citizen, or you control the scrapped server, or don't care about load you can increase this limit. Note, while this will speed up the scraping process, it may cause the server to block you. Be careful!

Overviewโ€‹

Integration detailsโ€‹

ClassPackageLocalSerializableJS support
SiteMapLoaderlangchain_communityโœ…โŒโœ…

Loader featuresโ€‹

SourceDocument Lazy LoadingNative Async Support
SiteMapLoaderโœ…โŒ

Setupโ€‹

To access SiteMap document loader you'll need to install the langchain-community integration package.

Credentialsโ€‹

No credentials are needed to run this.

If you want to get automated best in-class tracing of your model calls you can also set your LangSmith API key by uncommenting below:

# os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
# os.environ["LANGSMITH_TRACING"] = "true"

Installationโ€‹

Install langchain_community.

%pip install -qU langchain-community

Fix notebook asyncio bugโ€‹

import nest_asyncio

nest_asyncio.apply()

Initializationโ€‹

Now we can instantiate our model object and load documents:

from langchain_community.document_loaders.sitemap import SitemapLoader
API Reference:SitemapLoader
sitemap_loader = SitemapLoader(web_path="https://api.python.langchain.com/sitemap.xml")

Loadโ€‹

docs = sitemap_loader.load()
docs[0]
Fetching pages: 100%|##########| 28/28 [00:04<00:00,  6.83it/s]
Document(metadata={'source': 'https://api.python.langchain.com/en/stable/', 'loc': 'https://api.python.langchain.com/en/stable/', 'lastmod': '2024-05-15T00:29:42.163001+00:00', 'changefreq': 'weekly', 'priority': '1'}, page_content='\n\n\n\n\n\n\n\n\n\nLangChain Python API Reference Documentation.\n\n\nYou will be automatically redirected to the new location of this page.\n\n')
print(docs[0].metadata)
{'source': 'https://api.python.langchain.com/en/stable/', 'loc': 'https://api.python.langchain.com/en/stable/', 'lastmod': '2024-05-15T00:29:42.163001+00:00', 'changefreq': 'weekly', 'priority': '1'}

You can change the requests_per_second parameter to increase the max concurrent requests. and use requests_kwargs to pass kwargs when send requests.

sitemap_loader.requests_per_second = 2
# Optional: avoid `[SSL: CERTIFICATE_VERIFY_FAILED]` issue
sitemap_loader.requests_kwargs = {"verify": False}

Lazy Loadโ€‹

You can also load the pages lazily in order to minimize the memory load.

page = []
for doc in sitemap_loader.lazy_load():
page.append(doc)
if len(page) >= 10:
# do some paged operation, e.g.
# index.upsert(page)

page = []
Fetching pages: 100%|##########| 28/28 [00:01<00:00, 19.06it/s]

Filtering sitemap URLsโ€‹

Sitemaps can be massive files, with thousands of URLs. Often you don't need every single one of them. You can filter the URLs by passing a list of strings or regex patterns to the filter_urls parameter. Only URLs that match one of the patterns will be loaded.

loader = SitemapLoader(
web_path="https://api.python.langchain.com/sitemap.xml",
filter_urls=["https://api.python.langchain.com/en/latest"],
)
documents = loader.load()
documents[0]
Document(page_content='\n\n\n\n\n\n\n\n\n\nLangChain Python API Reference Documentation.\n\n\nYou will be automatically redirected to the new location of this page.\n\n', metadata={'source': 'https://api.python.langchain.com/en/latest/', 'loc': 'https://api.python.langchain.com/en/latest/', 'lastmod': '2024-02-12T05:26:10.971077+00:00', 'changefreq': 'daily', 'priority': '0.9'})

Add custom scraping rulesโ€‹

The SitemapLoader uses beautifulsoup4 for the scraping process, and it scrapes every element on the page by default. The SitemapLoader constructor accepts a custom scraping function. This feature can be helpful to tailor the scraping process to your specific needs; for example, you might want to avoid scraping headers or navigation elements.

The following example shows how to develop and use a custom function to avoid navigation and header elements.

Import the beautifulsoup4 library and define the custom function.

pip install beautifulsoup4
from bs4 import BeautifulSoup


def remove_nav_and_header_elements(content: BeautifulSoup) -> str:
# Find all 'nav' and 'header' elements in the BeautifulSoup object
nav_elements = content.find_all("nav")
header_elements = content.find_all("header")

# Remove each 'nav' and 'header' element from the BeautifulSoup object
for element in nav_elements + header_elements:
element.decompose()

return str(content.get_text())

Add your custom function to the SitemapLoader object.

loader = SitemapLoader(
"https://api.python.langchain.com/sitemap.xml",
filter_urls=["https://api.python.langchain.com/en/latest/"],
parsing_function=remove_nav_and_header_elements,
)

Local Sitemapโ€‹

The sitemap loader can also be used to load local files.

sitemap_loader = SitemapLoader(web_path="example_data/sitemap.xml", is_local=True)

docs = sitemap_loader.load()

API referenceโ€‹

For detailed documentation of all SiteMapLoader features and configurations head to the API reference: https://api.python.langchain.com/en/latest/document_loaders/langchain_community.document_loaders.sitemap.SitemapLoader.html#langchain_community.document_loaders.sitemap.SitemapLoader


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