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This guide provides a quick overview for getting started with UnstructuredXMLLoader document loader. The UnstructuredXMLLoader is used to load XML files. The loader works with .xml files. The page content will be the text extracted from the XML tags.

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Overview

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Integration details

ClassPackageLocalSerializableJS support
UnstructuredXMLLoaderlangchain_community✅❌✅

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Loader features

SourceDocument Lazy LoadingNative Async Support
UnstructuredXMLLoader✅❌

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Setup

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

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Credentials

No credentials are needed to use the UnstructuredXMLLoader To enable automated tracing of your model calls, set your LangSmith API key: 
os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
os.environ["LANGSMITH_TRACING"] = "true"

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Installation

Install langchain_community. 
pip install -qU langchain_community

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Initialization

Now we can instantiate our model object and load documents: 
from langchain_community.document_loaders import UnstructuredXMLLoader

loader = UnstructuredXMLLoader(
    "./example_data/factbook.xml",
)

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Load

docs = loader.load()
docs[0]

Document(metadata={'source': './example_data/factbook.xml'}, page_content='United States\n\nWashington, DC\n\nJoe Biden\n\nBaseball\n\nCanada\n\nOttawa\n\nJustin Trudeau\n\nHockey\n\nFrance\n\nParis\n\nEmmanuel Macron\n\nSoccer\n\nTrinidad & Tobado\n\nPort of Spain\n\nKeith Rowley\n\nTrack & Field')

print(docs[0].metadata)

{'source': './example_data/factbook.xml'}

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Lazy load

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

        page = []

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API reference

For detailed documentation of all UnstructuredXMLLoader features and configurations head to the API reference
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