Vision Agents

Vision Agents is an open-source Python framework designed for building real-time, low-latency AI agents that process both voice and video. The platform enables users to create agents for a variety of applications, such as telehealth, voice support, live coaching, security monitoring, sports commentary, virtual try-on experiences, and interactive avatars. Its architecture allows for sub-500ms latency by leveraging Stream’s global edge network.

The framework supports integration with more than 35 AI providers, including OpenAI, Gemini, Anthropic, Deepgram, ElevenLabs, and YOLO. Users can plug in any large language model, speech, or vision model from these providers to tailor agents to specific use cases. Vision Agents offers two operational modes: Realtime APIs using WebRTC or WebSocket, and custom pipelines that connect speech-to-text, large language models, and text-to-speech components. For video processing, the tool enables running models such as YOLO or Roboflow on each video frame, while phone support is available through Twilio integration, allowing agents to handle voice calls with bi-directional audio.

Additional features include support for retrieval-augmented generation (RAG) using TurboPuffer vector search and Gemini FileSearch for knowledge retrieval. The platform is production-ready, offering an HTTP server, Prometheus metrics, and deployment via Docker or Kubernetes. Example applications highlighted in the documentation include an AI golf coach using YOLO pose detection, a phone support agent powered by Twilio and RAG, a smart security camera with face and package detection, a live sports commentator that tracks players and the ball, and a live video try-on experience.

Vision Agents is positioned as a flexible tool for developers seeking to build sophisticated AI agents that respond to real-time voice and video inputs. Its open-source nature and broad integration capabilities make it suitable for a wide range of real-time AI agent scenarios.