Sample site for Document Intelligence code samples and associated media. - Azure-Samples/document-intelligence-code-samples

Azure AI Document Intelligence is a cloud service that uses machine learning to analyze text and structured data from your documents.

Visit the Azure samples repository on GitHub and view the ID document model output. Client library |API reference | Package (NuGet) | Samples | Supported REST API versions · Client library | REST API reference | Package | Samples |Supported REST API versions · An Azure subscription - Create one for free. The Visual Studio IDE. A Foundry Tools or Document Intelligence resource.

These code samples show common scenario operations with the Azure Document Intelligence client library. All of these samples need the endpoint to your Document Intelligence resource (instructions on how to get endpoint), and your Document Intelligence API key (instructions on how to get key).

In this quickstart, learn to use the Document Intelligence REST API to analyze and extract data and values from documents: ... The cURL command line tool installed. PowerShell version 7.*+ (or a similar command-line application.): ... A Document Intelligence (single-service) or Foundry Tools (multi-service) resource. Once you have your Azure subscription, create a single-service or multi-service Document Intelligence resource, in the Azure portal, to get your key and endpoint.

Analyze the PDF file with the deployed Azure AI Document Intelligence API to convert the document to Markdown.

This repository contains a collection of Jupyter notebooks demonstrating how to use Azure AI Document Intelligence (formerly Form Recognizer) to extract text, structure, and insights from documents such as PDFs and images.

A collection of samples demonstrating techniques for processing documents with Azure AI including AI Foundry, OpenAI, Document Intelligence, etc. - Azure-Samples/azure-ai-document-processing-samples

To extract text from external images like labels, street signs, and posters, use the Azure Image Analysis v4.0 Read feature optimized for general (not document) images with a performance-enhanced synchronous API. This capability makes it easier to embed OCR in real-time user experience scenarios. Document Intelligence Read Optical Character Recognition (OCR) model runs at a higher resolution than Azure Vision Read and extracts print and handwritten text from PDF documents and scanned images.

A small ASP.NET Core Minimal API that turns a business PDF (for example an invoice) into clean, structured JSON. It uses Azure AI Document Intelligence to read the document and Azure OpenAI to normalize what was read.

October 22, 2024 - Code samples for the Azure.AI.DocumentIntelligence client library.

Document Intelligence returns extracted field values as strongly typed data. Each field in the extraction response carries a value type—such as string, number, integer, date, time, phoneNumber, currency, or address—that determines how the ...

Visit the Azure samples repository on GitHub and view the ID document model output. Client library |API reference | Package (NuGet) | Samples | Supported REST API versions · Client library | REST API reference | Package | Samples |Supported REST API versions · An Azure subscription - Create one for trial. The Visual Studio IDE. An Azure AI services or Document Intelligence resource.

May 8, 2026 - It exposes prebuilt models for invoices, receipts, IDs, business cards, tax forms and contracts, plus a layout/OCR Read model and a Custom-model framework for fine-tuned extraction.

To view the entire output, visit the Azure samples repository on GitHub to view the prebuilt invoice model output. Add the following code sample to the FormRecognizer.java file. Make sure you update the key and endpoint variables with values from your Azure portal Document Intelligence instance:

This sample demonstrates how to use Document Intelligence's Layout model to convert a PDF document, such as invoices, into Markdown, then use GPT-3.5 Turbo to extract structured JSON data using the Azure OpenAI Service.

A lightweight Python library for metadata-rich document chunking in Retrieval-Augmented Generation (RAG) workflows. It leverages Azure AI Document Intelligence to enhance chunking by retaining hierarchical structure, page numbers, and bounding ...

To view the entire output, visit the Azure samples repository on GitHub to view the prebuilt invoice model output. Add the following code sample to the FormRecognizer.java file. Make sure you update the key and endpoint variables with values from your Azure portal Document Intelligence instance:

Sends the location of the single page PDF file to Azure AI Document Intelligence for processing via a REST API (HTTPS POST)and receives response.

The following code block calls the Document Intelligence Analyze Layout API on the uploaded document.