{"repo":"Azure-Samples/data-extraction-using-azure-content-understanding","free":true,"listed":false,"github":"https://github.com/Azure-Samples/data-extraction-using-azure-content-understanding","clone":"git clone https://github.com/Azure-Samples/data-extraction-using-azure-content-understanding.git","description":"An intelligent document processing solution using Azure Content Understanding and OpenAI to extract data from documents and enable natural language querying with citations.","language":"Python","stars":28,"topics":["azure-content-understanding","citations","cosmosdb","llm","mongodb","openai"],"license":"MIT","category":"ai-agents","readme_excerpt":"Data Extraction using Azure Content Understanding This sample demonstrates how to build an intelligent document processing solution using Azure Content Understanding to extract structured data from documents and provide conversational querying capabilities. Note : This sample is for demonstration purposes and should be adapted for production use with appropriate security, monitoring, and error handling considerations. 🚀 Features - Document Ingestion : Automatically process documents using Azure Content Understanding to extract structured data - Configurable Extraction : Define custom field schemas and extraction rules via JSON configuration - Conversational Interface : Query processed documents using natural language powered by Azure OpenAI - Scalable Architecture : Built on Azure Functions for serverless, event-driven processing - Document Classification : Intelligent document type classification and routing - Data Storage : Persistent storage with Azure Cosmos DB for extracted data - Infrastructure as Code : Complete Terraform deployment for reproducible infrastructure 📋 Prerequisites - Azure subscription with access to: - Azure Content Understanding - Azure OpenAI Service - Azure Functions - Azure Cosmos DB - Azure Key Vault - Azure Storage Account - Python 3.12 or later - Terraform (for infrastructure deployment) - Azure CLI 🏗️ Architecture The solution implements three main workflows: 1. Document Enquiry : Natural language querying of processed documents using Azure O","default_branch":null,"files":null,"tree":[],"storefront":"/r/Azure-Samples","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Azure-Samples/data-extraction-using-azure-content-understanding/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}