Getting Started With Azure Document AI Document Intelligence API In Python (Source Code In Desc)

This paragraph introduces a tutorial on utilizing Azure's Document Intelligence API with Python. It's aimed at beginners but assumes some knowledge of Python and Azure. The agenda includes an overview of pricing, use cases, free tier limitations, setting up the Azure resource, exploring pre-built models, and developing scripts for the API client. The tutorial will cover various examples, starting with basic API calls, examining responses, loading documents, and extracting data from forms like W-2, invoices, and tables from documents.

The paragraph discusses the pricing model of Azure's Document Intelligence API, highlighting a free tier offering 500 pages per month. Beyond the free tier, pricing ranges from $3 to $50 per 1000 pages, depending on document type, with a special note on custom-trained models. It also outlines limitations of the free tier, such as processing only the first two pages of a document, compared to up to 2000 pages for paid subscriptions. File size limitations and supported formats are also detailed, including PDF, image files, and Microsoft Office files, with the latter only supporting read and layout models.

The speaker guides viewers through setting up an Azure Document Intelligence resource, starting from creating an Azure account and subscription to navigating the Azure console for resource group creation. The process includes naming the resource, selecting a region, and creating the document intelligence service instance with a globally unique name. After deployment, the tutorial covers accessing the instance dashboard, monitoring usage, and obtaining API keys and endpoint URLs for API access.

This section explains how to configure the Azure Document Intelligence client in Python. It involves creating a configuration file for API keys and endpoints, and writing a script to instantiate the client with these credentials. The script includes helper functions to check document sources and handle file paths, culminating in a test run to ensure the client object is created correctly.

The paragraph delves into the process of analyzing documents using pre-built models available in the Document Intelligence API. It explains the use of the 'analyze document request' to prepare documents for analysis and the initiation of the analysis process using the client instance. The focus is on extracting information from text forms like W2, with a mention of challenges in navigating the documentation and locating model IDs.

The speaker describes how to navigate the results of document analysis, explaining the structure of the output and the significance of keys such as 'content', 'pages', and 'styles'. The summary covers how to reference specific pages, extract text, and understand the document hierarchy. It also touches on using the results with generative APIs or iterating through documents to extract specific field values.

This section details the process of extracting data from text forms like W2 and invoices using the Document Intelligence API. It discusses identifying field IDs and navigating through the nested dictionary structure to retrieve values. The tutorial also covers handling special cases like box 12 on a W2 form, which requires accessing an array of values, and the process of extracting and iterating through line items on an invoice.

The paragraph explains how to extract tables from documents using the pre-built layout model of the Document Intelligence API. It covers the process of analyzing a document to identify tables and compiling the data into a data frame object. The summary includes steps for iterating through rows and columns, handling empty cells, and preparing the data for further use, with an emphasis on cleaning up the data to remove empty rows.

The final paragraph wraps up the tutorial by summarizing the process of extracting data from documents using Azure's Document Intelligence API. It invites viewers to ask questions or provide feedback in the comments and encourages them to like and subscribe for more content. The speaker also hints at continuing the topic in a follow-up video.