Skill UI

Automate Astica AI workflows through Composio’s Rube MCP bridge by discovering tools with RUBE_SEARCH_TOOLS, managing Astica connections, and executing tasks via RUBE_MULTI_EXECUTE_TOOL while respecting dynamic schemas.

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.

A comprehensive SDK for building real-time, bidirectional voice AI applications using Azure AI services within the .NET framework. This library facilitates seamless voice interactions, supporting WebSocket communication, advanced features like function calling, and handling audio/text streaming events for developing sophisticated virtual assistants.

The Azure AI VoiceLive SDK for Java enables real-time, bidirectional voice conversations with AI assistants. Using WebSocket technology, this SDK supports low-latency streaming, advanced features like turn detection, noise reduction, and customizable voice selection (OpenAI/Azure). It is ideal for developers building sophisticated voice bots or interactive voice applications in Java.

This SDK enables the development of real-time, conversational AI applications using Azure Cognitive Services. It supports bidirectional communication via WebSockets, allowing for continuous audio streaming (mic input) and receiving synthesized speech output. Ideal for building voice assistants, IVR systems, and interactive voice experiences.

This SDK provides a comprehensive interface for building real-time, bidirectional voice AI applications using Azure AI services. It supports streaming audio input/output via WebSocket, handling transcription, text-to-speech, and complex session management. Ideal for developing robust voice assistants and interactive AI agents in both Node.js and modern browser environments.

An expert system for designing and implementing advanced AI context architectures. It specializes in integrating intelligent memory systems, vector databases, and knowledge graphs to ensure AI applications maintain coherent, relevant, and scalable state across complex, multi-agent workflows. Essential for enterprise RAG implementation and stateful AI development.

This skill set provides advanced, structured strategies for optimizing Large Language Model (LLM) interactions. It covers techniques such as intelligent context summarization, dynamic trimming, context routing, and precise token budget allocation to prevent 'context rot'. It is essential for building robust, long-running, multi-turn conversational AI systems.

Uses the Gemini API to autonomously plan, search, read, and synthesize detailed research reports with streaming status updates, structured outputs, and the ability to continue previous investigations for market analysis, technical reviews, or due diligence.

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.

A comprehensive guide to using Groq's high-speed LPU for chat completion. This resource provides code examples in TypeScript and Python, covering basic chat interactions, streaming responses, and advanced multimodal features. Ideal for developers building high-performance, low-latency AI applications using the Groq API.