Skill UI

Python SDK for Azure AI Content Understanding service. Enables multimodal content extraction from documents, images, audio, and video files. Supports prebuilt analyzers for RAG and custom field extraction for automated workflows. Ideal for developers building AI-driven applications.

A framework for building production-ready, low-latency, multimodal AI agents. It allows developers to orchestrate complex pipelines that seamlessly handle real-time audio, video, and text data. Key capabilities include integrating multiple AI services (LLMs, STT, TTS), managing conversation context, and enabling tool use and function calling for advanced, interactive AI applications.

This comprehensive guide covers all aspects of integrating the Google Gemini API into your applications using Python or Node.js. It details basic text generation, advanced multimodal inputs (text, image, audio), streaming responses, function calling/tool use, multi-turn chat implementation, and production best practices like model selection and robust error handling.

Build with the Gemini Interactions API for text, chat, multimodal generation, streaming, managed or background agents, function calling, structured output, and generateContent migrations. Includes current models, agents, SDKs, and critical usage rules.

RouterBase acts as a unified, OpenAI-compatible API gateway, allowing applications to route requests across diverse large language models (LLMs) like GPT, Claude, and Gemini. It helps developers migrate existing OpenAI SDK calls, implement sophisticated primary/fallback model selection based on cost, latency, and quality, and manage multimodal payloads (image, audio, video) from a single, standardized endpoint.

Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes like Node.js, Bun, and Deno, enabling text analysis, image classification, speech recognition, and multimodal AI applications without a Python backend.

This comprehensive skill provides an index of official blueprints and implementation guides for building full-stack, AI-powered applications using Weaviate. It covers advanced patterns such as Retrieval-Augmented Generation (RAG), agentic workflows, data exploration, and multimodal document search, guiding users through best practices for setup, clients, and frontends.