Results for “z-ai-web-dev-sdk”

Manage Azure AI Foundry projects with .NET SDK: create and run agents, manage connections, datasets, deployments, evaluations, and indexes.

Build AI applications using the Azure AI Projects SDK for TypeScript, managing agents, connections, deployments, datasets, indexes, and evaluations.

Create and manage persistent AI agents with threads, messages, runs, and tools using the Azure SDK for Java.

Build real-time voice AI applications with bidirectional WebSocket communication using the Azure AI Voice Live SDK for .NET.

Manage Azure AI Foundry projects, connections, datasets, indexes, and evaluations using the Java SDK.

Create and manage persistent AI agents with threads, messages, runs, and tools using the Azure AI Agents SDK for .NET.

Analyze text and images for harmful content using Azure AI Content Safety SDK for Java. Supports hate, violence, sexual content, and self-harm detection with blocklist management.

Build real-time voice AI applications with bidirectional WebSocket communication using the Azure AI Voice Live SDK for JavaScript/TypeScript.

Build search applications with full-text, vector, semantic, and hybrid search using the Azure AI Search SDK for .NET.

Guides through interactive deployment of Azure OpenAI models with full control over version, SKU, capacity, content filtering, and advanced options.

Build AI applications on Microsoft Foundry using the Azure AI Projects Python SDK, including agent creation, tool integration, thread management, and evaluation.

Build real-time web applications with Azure Web PubSub SDK for Java, enabling WebSocket-based messaging, live updates, chat, and server-to-client push notifications.

Build, deploy, and modify GitHub Copilot SDK apps on Azure with scaffolding, model configuration, and deployment orchestration.

Extract text, tables, and structured data from documents using Azure AI Document Intelligence SDK for .NET, with support for prebuilt and custom models.

Create, configure, and deploy Azure Static Web Apps using the SWA CLI, including local development, runtime configuration, and CI/CD setup.

Integrate Azure OpenAI and OpenAI services in .NET applications for chat completions, embeddings, image generation, audio transcription, and assistants.

Integrate real-time bidirectional voice conversations with AI assistants using the Azure AI VoiceLive SDK for Java, including WebSocket streaming, turn detection, and voice configuration.

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter.

Deploys applications, static sites, and edge functions to Azion using the Azion CLI, with preflight checks for authentication and build configuration.

Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Triggers: "PersistentAgentsClient", "persistent agents java", "agent threads java", "agent runs java", "streaming agents java".

Build messaging applications using Azure Service Bus SDK for JavaScript, implementing queues, topics, subscriptions, message sessions, dead-letter handling, and enterprise messaging patterns.

Build real-time voice AI applications using the Azure AI Voice Live SDK for bidirectional WebSocket audio communication.

Translate text in real-time, detect languages, transliterate between scripts, and look up dictionary entries using Azure AI Translator SDK for Python.

Manage Arize AI Observability and Evaluation resources on Azure using the .NET SDK. Create, read, update, and delete Arize organizations via Azure Marketplace.

Detect anomalies in time-series data using the Azure AI Anomaly Detector SDK for Java, with support for univariate and multivariate analysis, model training, and inference.

Search Azure AI Search indexes using the Python SDK for full-text, vector, hybrid, and semantic search with AI enrichment.

Configure Gemini and Codex CLI tools with Cloudflare AI Gateway endpoints and MCP servers.

Expert knowledge for Azure Dev Box development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Dev Box images, catalogs, policies, schedules, RBAC/SSO access, or VS Code dev tunnel workflows, and other Azure Dev Box related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Lab Services (use azure-lab-services), Azure Virtual Desktop (use azure-virtual-desktop).