Skill UI

Scaffolds production-ready generative AI agents on Vertex AI with Gemini models, multi-modal tools, RAG, and Cloud Run/Endpoint deployment, including observability and evaluation for enterprise scenarios.

Automates Vertex AI's multimodal media workflows—video understanding, image/audio generation, and marketing campaign assets—so teams can produce cross-channel creatives from a single prompt.

ZAI CLI provides comprehensive access to Z.AI's advanced capabilities, including image/video analysis, real-time web search, web page extraction, and GitHub code exploration. It is designed for users needing multi-modal content analysis, error diagnosis, and complex data processing through a unified command-line interface. Ideal for developers and analysts requiring robust, API-driven AI functionality.

Transform briefs into cinematic videos via Seedance 2.0, guiding text/image/video/audio inputs through director-level directives, multimodal tagging, and synchronized sound for 4-15s outputs.

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.

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.

Transformers.js allows developers to run state-of-the-art machine learning models directly within JavaScript/TypeScript environments (browser, Node.js). It supports a comprehensive range of tasks including NLP (text generation, summarization, translation), Computer Vision (image classification, object detection), and Audio processing. This capability enables building fully client-side, multimodal AI applications without requiring a dedicated Python backend or server infrastructure.

scvi-tools is a comprehensive Python framework for probabilistic deep generative models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it enables batch correction, transfer learning, differential expression analysis with uncertainty, and multi-modal data integration. Best for advanced modeling of single-cell RNA-seq, ATAC-seq, CITE-seq, spatial transcriptomics, and specialized modalities like methylation and cytometry.

Load Hugging Face Hub models, run pipeline inference, generate text, and fine-tune with the Trainer API across NLP, vision, audio, and multimodal tasks using Python and PyTorch.

This guide covers advanced usage of the Anthropic Messages API. Learn how to implement real-time streaming responses, utilize system prompts for persona control, process visual inputs (Vision), and enforce structured data output (JSON). This is essential for building sophisticated, robust, and multi-modal Claude-powered applications.

This skill provides the comprehensive workflow for interacting with the Anthropic Messages API. It covers advanced features including streaming responses, multimodal vision input, generating structured JSON output using system prompts, and managing multi-turn conversations. It redirects users to the current, primary guide for all Claude API patterns.

This powerful CLI allows users to interact with the MiniMax AI platform directly from the terminal. It supports generating and managing diverse multi-modal content, including text, images, video, speech, and music, in addition to performing web searches and analyzing images. It is essential for integrating complex AI capabilities into automated workflows, CI/CD pipelines, or agent-based systems.