Build real-time voice and video AI agents with LLMs, STT/TTS, and MCP-style tools.
npx skills add https://github.com/emSoumik/SuperPong --skill agent-emsoumik
Please help me install this Agent Skill. Skill: Agent Source: https://github.com/emSoumik/SuperPong/tree/main Command: npx skills add https://github.com/emSoumik/SuperPong --skill agent-emsoumik
Builds and coordinates real-time voice and video AI agents that orchestrate multiple providers and run in production.
Install Vision Agents, configure your environment, and run the agent in server mode to start an autonomous voice and vision agent.
High-intent search queries and answers about installing and using this skill.
To build real-time voice and video AI agents, you use a unified Agent class to orchestrate LLMs, STT/TTS, and computer vision pipelines. It targets production-grade deployments on HTTP servers with robust session management for live interactions.
Yes, you can orchestrate multiple LLM providers and computer vision pipelines using a unified Agent class. It manages function-call execution and MCP-style tooling to coordinate live voice, video, and AI streaming across different services.
Deploying autonomous voice and vision agents on an HTTP server requires the Vision Agents SDK, configured environment variables, and plugin integrations. You run the agent in server mode to start handling real-time WebRTC and edge deployments.
Yes, real-time WebRTC streaming is supported for live AI interactions. The framework handles voice and video streaming directly, enabling autonomous agents to process live inputs and manage function calls during active sessions.
You manage function calls and tool integrations for live voice agents using MCP-style tooling within the unified Agent class. This architecture handles robust session management and coordinates tool execution during real-time interactions.
Use a unified agent architecture for voice and video processing when building production-grade systems that require coordinating LLMs, STT/TTS, and computer vision simultaneously. It is designed for autonomous live interactions, analytics, and automation across multiple providers.
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sangrokjungImplement object detection and train custom vision models with PyTorch and OpenCV.
AshutoshIIT1234Orchestrate LLMs, STT/TTS, and vision processors for real-time voice and video AI applications.
