Vision Agents is a framework for building multimodal AI agents that process video and audio in real time using any language model or video provider.
The tool addresses the challenge of creating low-latency video AI experiences that combine computer vision models with large language models. It works by providing a pluggable architecture where you can chain together video processors like YOLO or Roboflow with LLM providers such as OpenAI, Gemini, or Claude. The framework handles real-time WebRTC streaming, turn detection through voice activity detection and diarization, and tool calling so agents can execute code or APIs mid-conversation. Stream's edge network keeps join latency under 500ms and maintains audio-video synchronization below 30ms.
The tool suits developers building interactive video AI applications like sports coaching, drone monitoring, physical therapy guidance, or game experiences. It works with any video edge network despite being built by Stream, and provides native API methods that always access the latest capabilities from major LLM providers. The framework includes production features like an HTTP server, Prometheus metrics, horizontal scaling, and Kubernetes deployment. Phone integration via Twilio or Telnyx enables inbound and outbound voice calls with bidirectional audio streaming. You can also add retrieval-augmented generation with vector search, persistent memory across sessions, and silent text messaging to agents during calls.
Maintainers typically respond to new issues and pull requests within a few days. Work in the issue tracker centers on bug fixes, documentation improvements, and OpenAI plugin development.