Skill UI

This SDK allows developers to build persistent, sophisticated AI agents directly on Azure AI Foundry. It supports complex conversational workflows by integrating external functions (tools), enabling code execution, web search, and maintaining conversation history through dedicated thread management. Ideal for developing enterprise-grade, production-ready AI applications.

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.

This is a high-level SDK for .NET that provides comprehensive client access to Azure AI Foundry services. It enables developers to manage complex AI workflows, including creating and managing conversational agents, handling data connections, uploading datasets, managing model deployments, and setting up search indexes within an Azure AI project structure. Ideal for integrating advanced AI capabilities into enterprise applications.

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.

The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

This is a high-level SDK designed for managing the complete lifecycle of AI projects within Azure AI Foundry. It provides comprehensive tools in TypeScript to create, manage, and evaluate sophisticated AI agents, handle resource connections, process datasets, deploy models, and build custom search indexes.

This is a high-level SDK designed for managing the complete lifecycle of AI projects within Azure AI Foundry. It provides comprehensive tools in TypeScript to create, manage, and evaluate sophisticated AI agents, handle resource connections, process datasets, deploy models, and build custom search indexes.

This comprehensive guide covers universal coding standards, best practices, and architectural patterns for modern web development using TypeScript, JavaScript, React, and Node.js. It emphasizes fundamental principles like Readability, DRY, and Immutability, while providing detailed guidelines on component structure, state management, asynchronous programming, and designing robust REST APIs.

Provides a comprehensive workflow for developing against Customer.io in local or staging environments. It implements environment isolation, dry-run clients, and service mocks to ensure development work does not affect production data, making unit and integration testing safe and reliable.

Provides a comprehensive guide and Python implementation for creating container-based hosted agents in Azure AI Projects. It utilizes ImageBasedHostedAgentDefinition to define the agent's container image, required resources (CPU/memory), supported tools, and communication protocols. Essential for deploying robust, production-ready AI agents within the Azure ecosystem.