Skill UI

Automates converting recordings into structured Markdown documentation, adding metadata, diarization, summaries, and captions via Whisper/Faster-Whisper for meetings, interviews, lectures, and content analysis.

Automates converting recordings into structured Markdown documentation, adding metadata, diarization, summaries, and captions via Whisper/Faster-Whisper for meetings, interviews, lectures, and content analysis.

This SDK provides a comprehensive Python client library for interacting with Azure AI Speech-to-Text services. It supports both real-time streaming transcription and robust batch processing of audio files. Users can leverage advanced features such as speaker diarization (identifying multiple speakers) and capturing precise timestamps, making it invaluable for automated meeting minute generation, podcast content processing, and live captioning solutions.

This SDK provides a comprehensive Python client library for interacting with Azure AI Speech-to-Text services. It supports both real-time streaming transcription and robust batch processing of audio files. Users can leverage advanced features such as speaker diarization (identifying multiple speakers) and capturing precise timestamps, making it invaluable for automated meeting minute generation, podcast content processing, and live captioning solutions.

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.

Bridges frozen vision encoders and LLMs for high-quality image captioning, VQA, retrieval, and multimodal chat, enabling zero-shot reasoning without fine-tuning and offering efficient Q-Former training.

This guide demonstrates how to implement robust, real-time, low-latency streaming transcription using Deepgram's WebSocket API. It covers advanced audio handling, including microphone input capture (via Sox), speaker diarization, utterance boundary detection, and implementing automatic reconnection logic. Essential for building professional voice AI applications, live captioning services, or voice interfaces.

LLaVA is an open-source vision-language assistant pairing CLIP vision encoders with Vicuna/LLaMA models to power multimodal chatbots, multi-turn image Q&A, captioning, and instruction-following tasks.

This guide provides comprehensive best practices for creating high-quality videos using Remotion within a React environment. It covers advanced techniques for dynamic content generation, including integrating 3D models (Three.js), managing diverse assets like audio, video, and fonts, implementing complex animations, data visualization, and generating precise captions. Use this skill when developing professional, robust video generation workflows in React.

This powerful orchestrator coordinates content across Instagram, Telegram, and WhatsApp. It automatically adapts central content into platform-specific formats (captions, templates, hashtags), ensuring brand consistency. Features include unified analytics, synchronized scheduling, and centralized campaign management, maximizing reach and operational efficiency across all major channels.

This workflow provides comprehensive audio processing capabilities, covering both real-time streaming transcription (for live captions and voice agents) and advanced post-processing using LeMUR. Use it for summarizing long meetings, answering questions based on transcripts, extracting action items, and running custom LLM analyses on recorded audio.