Skill UI

This SDK enables developers to build robust document analysis applications using Azure AI Document Intelligence. It provides powerful capabilities to extract structured data from diverse document types, including receipts, invoices, ID cards, and general forms. Developers can analyze documents from local files or URLs to extract key-value pairs, tables, and specific fields automatically.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

This SDK provides Java developers with access to advanced image analysis features from Azure AI Vision. It allows applications to perform various visual tasks, including OCR text extraction, generating detailed image captions, detecting specific objects with bounding boxes, recognizing content tags, and performing smart cropping. Use it when building applications that require deep visual understanding of images.

This SDK provides a comprehensive Python client for Azure AI Vision 4.0, enabling advanced image understanding tasks. It supports generating descriptive captions, extracting content tags, detecting objects and people with bounding boxes, performing OCR (text recognition), and suggesting smart crop regions. It is ideal for computer vision applications and detailed image content analysis.

This SDK provides a comprehensive interface for building real-time, bidirectional voice AI applications using Azure AI services. It supports streaming audio input/output via WebSocket, handling transcription, text-to-speech, and complex session management. Ideal for developing robust voice assistants and interactive AI agents in both Node.js and modern browser environments.

This SDK provides a comprehensive interface for managing application configuration within Azure App Configuration using Python. It enables centralized management of settings, allows controlling feature flags for gradual rollouts, and facilitates version control through configuration snapshots. It supports various authentication methods, including connection strings and Entra ID, making it ideal for robust, dynamic microservices deployment.

This SDK provides a comprehensive interface for managing application configuration within Azure App Configuration using Python. It enables centralized management of settings, allows controlling feature flags for gradual rollouts, and facilitates version control through configuration snapshots. It supports various authentication methods, including connection strings and Entra ID, making it ideal for robust, dynamic microservices deployment.

This Java client library provides comprehensive SDK support for Azure Batch service. It enables developers to manage and execute large-scale, parallel, and high-performance computing (HPC) batch jobs in Azure. Users can programmatically manage compute pools, create structured jobs, schedule tasks, and monitor job lifecycle using Java.

This Java client library provides comprehensive SDK support for Azure Batch service. It enables developers to manage and execute large-scale, parallel, and high-performance computing (HPC) batch jobs in Azure. Users can programmatically manage compute pools, create structured jobs, schedule tasks, and monitor job lifecycle using Java.

A comprehensive guide and client library for interacting with Azure Cosmos DB, a globally distributed, multi-model NoSQL database, using Python. It provides full support for performing document CRUD operations, executing complex partitioned and cross-partition queries, managing containers, and handling advanced concepts like throughput and asynchronous operations.

A comprehensive client library for interacting with Azure Cosmos DB's NoSQL API in Rust. It enables performing core database operations, including CRUD (Create, Read, Update, Delete), patching, and managing globally distributed data. Ideal for building robust, data-intensive, and high-performance backend services on the Azure cloud platform.