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Signed-off-by: ChengZi <chen.zhang@zilliz.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Dan O'Donovan <dan.odonovan@gmail.com> Co-authored-by: Tom Daniel Grande <tomdgrande@gmail.com> Co-authored-by: Grande <Tom.Daniel.Grande@statsbygg.no> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: ccurme <chester.curme@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com> Co-authored-by: ZhangShenao <15201440436@163.com> Co-authored-by: Friso H. Kingma <fhkingma@gmail.com> Co-authored-by: ChengZi <chen.zhang@zilliz.com> Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: Morgante Pell <morgantep@google.com>
36 lines
2.3 KiB
Plaintext
36 lines
2.3 KiB
Plaintext
# How to load Microsoft Office files
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The [Microsoft Office](https://www.office.com/) suite of productivity software includes Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Microsoft Outlook, and Microsoft OneNote. It is available for Microsoft Windows and macOS operating systems. It is also available on Android and iOS.
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This covers how to load commonly used file formats including `DOCX`, `XLSX` and `PPTX` documents into a LangChain
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[Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html#langchain_core.documents.base.Document)
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object that we can use downstream.
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## Loading DOCX, XLSX, PPTX with AzureAIDocumentIntelligenceLoader
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[Azure AI Document Intelligence](https://aka.ms/doc-intelligence) (formerly known as `Azure Form Recognizer`) is machine-learning
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based service that extracts texts (including handwriting), tables, document structures (e.g., titles, section headings, etc.) and key-value-pairs from
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digital or scanned PDFs, images, Office and HTML files. Document Intelligence supports `PDF`, `JPEG/JPG`, `PNG`, `BMP`, `TIFF`, `HEIF`, `DOCX`, `XLSX`, `PPTX` and `HTML`.
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This [current implementation](https://aka.ms/di-langchain) 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.
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### Prerequisite
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An Azure AI Document Intelligence resource in one of the 3 preview regions: **East US**, **West US2**, **West Europe** - follow [this document](https://learn.microsoft.com/azure/ai-services/document-intelligence/create-document-intelligence-resource?view=doc-intel-4.0.0) to create one if you don't have. You will be passing `<endpoint>` and `<key>` as parameters to the loader.
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```python
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%pip install --upgrade --quiet langchain langchain-community azure-ai-documentintelligence
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from langchain_community.document_loaders import AzureAIDocumentIntelligenceLoader
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file_path = "<filepath>"
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endpoint = "<endpoint>"
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key = "<key>"
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loader = AzureAIDocumentIntelligenceLoader(
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api_endpoint=endpoint, api_key=key, file_path=file_path, api_model="prebuilt-layout"
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)
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documents = loader.load()
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```
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