Microsoft Word
Microsoft Word is a word processor developed by Microsoft.
This covers how to load Word
documents into a document format that we can use downstream.
Using Docx2txt
Load .docx using Docx2txt
into a document.
%pip install --upgrade --quiet docx2txt
from langchain_community.document_loaders import Docx2txtLoader
API Reference:
loader = Docx2txtLoader("example_data/fake.docx")
data = loader.load()
data
[Document(page_content='Lorem ipsum dolor sit amet.', metadata={'source': 'example_data/fake.docx'})]
Using Unstructured
from langchain_community.document_loaders import UnstructuredWordDocumentLoader
API Reference:
loader = UnstructuredWordDocumentLoader("example_data/fake.docx")
data = loader.load()
data
[Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': 'fake.docx'}, lookup_index=0)]
Retain Elements
Under the hood, Unstructured creates different "elements" for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying mode="elements"
.
loader = UnstructuredWordDocumentLoader("example_data/fake.docx", mode="elements")
data = loader.load()
data[0]
Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': 'fake.docx', 'filename': 'fake.docx', 'category': 'Title'}, lookup_index=0)
Using Azure AI Document Intelligence
Azure AI Document Intelligence (formerly known as
Azure Form Recognizer
) is machine-learning based service that extracts texts (including handwriting), tables, document structures (e.g., titles, section headings, etc.) and key-value-pairs from digital or scanned PDFs, images, Office and HTML files.Document Intelligence supports
JPEG/JPG
,PNG
,BMP
,TIFF
,HEIF
,DOCX
,XLSX
,PPTX
andHTML
.
This current implementation of a loader using Document Intelligence
can incorporate content page-wise and turn it into LangChain documents. The default output format is markdown, which can be easily chained with MarkdownHeaderTextSplitter
for semantic document chunking. You can also use mode="single"
or mode="page"
to return pure texts in a single page or document split by page.
Prerequisite
An Azure AI Document Intelligence resource in one of the 3 preview regions: East US, West US2, West Europe - follow this document to create one if you don't have. You will be passing <endpoint>
and <key>
as parameters to the loader.
%pip install --upgrade --quiet langchain langchain-community azure-ai-documentintelligence
from langchain_community.document_loaders import AzureAIDocumentIntelligenceLoader
file_path = "<filepath>"
endpoint = "<endpoint>"
key = "<key>"
loader = AzureAIDocumentIntelligenceLoader(
api_endpoint=endpoint, api_key=key, file_path=file_path, api_model="prebuilt-layout"
)
documents = loader.load()