GetStream/Vision-Agents

What it solves

Vision Agents provides a framework for building low-latency, multi-modal AI agents that can see, hear, and speak in real time. It bridges the gap between raw video/audio streams and large multi-modal models (LMMs), allowing developers to create interactive experiences like AI sports coaches, security monitors, or virtual assistants that respond to visual stimuli with minimal delay.

How it works

The project uses a pluggable architecture that combines real-time WebRTC video streaming with a processing pipeline. It allows developers to chain specialized computer vision models (such as YOLO or Roboflow) to extract specific data from frames before passing that information to a general-purpose LLM (like Gemini Live or OpenAI Realtime). It integrates with various STT (Speech-to-Text) and TTS (Text-to-Speech) providers to handle natural voice conversations, including turn detection and VAD (Voice Activity Detection).

Who it’s for

Developers building real-time interactive AI applications, such as:

• Sports and Fitness Coaching: AI that tracks pose and provides live feedback.
• Security and Moderation: Real-time monitoring and automated fraud response.
• ** uma Virtual Try-ons:** Using video restyling and avatars for retail.
• Customer Service: Voice agents integrated with phone systems (Twilio/Telnyx) and RAG for knowledge retrieval.

Highlights

• Ultra-Low Latency: Achieves join times of 500ms and audio/video latency under 30ms via Stream's edge network.
• LMM Integration: Native support for OpenAI, Gemini, and Claude APIs.
• Pluggable Vision Pipeline: Ability to run custom PyTorch/ONNX models or YOLO/Roboflow alongside LLMs.
• Comprehensive Tooling: Built-in support for RAG (TurboPuffer/Qdrant), tool calling (MCP), and production-ready deployment (Kubernetes, Prometheus).
• Multi-platform SDKs: Supports React, Android, iOS, Flutter, React Native, and Unity.