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

Use Azure AI Document Intelligence prebuilt-layout and Azure OpenAI GPT models to redact sensitive information from documents using natural language instruction to determine redaction areas.

Prebuilt - Analyze data from certain types of common documents using prebuilt models.

For example, to analyze fields from a sales receipt, use the prebuilt receipt model provided by passing model_id="prebuilt-receipt" into the begin_analyze_document method: from azure.core.credentials import AzureKeyCredential from ...

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

https://github.com/retkowsky/a... · Description: Focused example of OCR extraction, illustrating how to extract text content from scanned documents and images using Azure Document Intelligence....

The solution leverages Azure AI Document Intelligence to extract data from PDF forms and store the data in a Azure Cosmos DB.

Visit the Azure samples repository on GitHub and view the invoice model output. using Azure; using Azure.AI.DocumentIntelligence; //use your `key` and `endpoint` environment variables to create your `AzureKeyCredential` and `DocumentIntelligenceClient` instances string key = Environment.GetEnvironmentVariable("DI_KEY"); string endpoint = Environment.GetEnvironmentVariable("DI_ENDPOINT"); AzureKeyCredential credential = new AzureKeyCredential(key); DocumentIntelligenceClient client = new DocumentIntelligenceClient(new Uri(endpoint), credential); // sample document document Uri receiptUri = new

September 1, 2026 - AI Document Intelligence is an AI service that applies advanced machine learning to extract text, key-value pairs, tables, and structures from documents automatically and accurately - microsoft/AIDocIntelligence

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.

This sample demonstrates how to ... Layout model to convert documents, such as invoices, into Markdown, then use GPT-3.5 Turbo to extract structured JSON data using the Azure OpenAI Service....

DocumentIntelligence - processes the message in docqueue to Document Intelligence, then updates Blob metadata as "processed" and create new message in customfieldqueue This app employs scale limiting and Polly retries with back off for Document Intelligence (too many requests) replies to balance maximum throughput and overloading the API endpoint · CustomFieldExtraction - processes messages in the customfieldqueue to use Azure Open AI to extract custom fields based on the AzureUtilities/Prompts/ExtractCustomFields.yaml prompt description.

Automated Retrieval and GPT Understanding System by utilizing Azure Document Intelligence in combination with GPT models. - Azure-Samples/ARGUS

A small Python command-line project for comparing Azure AI Document Intelligence results across selected documents and models. It records service latency, extracted text, and optional checks against a human-reviewed ground truth and expected ...

Extract tables from PDF documents using Azure Document Intelligence (formerly Form Recognizer) prebuilt-layout model.

Extract tables from PDF documents using Azure Document Intelligence (formerly Form Recognizer) prebuilt-layout model.

For example, to analyze fields from a sales receipt, use the prebuilt receipt model provided by passing model_id="prebuilt-receipt" into the begin_analyze_document method: from azure.core.credentials import AzureKeyCredential from ...

First, you’ll complete some key parts of the application to enable using your Azure Document Intelligence resource. Examine the following invoice and note some of its fields and values. This is the invoice that your code will analyze. In Visual Studio Code, in the Explorer pane, browse to the Labfiles/01-prebuild-models folder and expand the CSharp or Python folder depending on your language preference. Each folder contains the language-specific files for an app into which you’re you’re going to integrate Azure Document Intelligence functionality.

Contribute to Azure-Samples/azure-doc-intelligence-dynamic-models-patient development by creating an account on GitHub.

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 ...