How to Deploy a Standalone VLM Kiosk on NVIDIA Jetson with Codex
This tutorial demonstrates how to transform a live Vision-Language Model (VLM) demonstration into a self-contained, standalone kiosk experience on an NVIDIA Jetson device. Using Codex for AI-assisted development, the process involves deploying the Live VLM WebUI, ensuring all necessary assets are served locally for offline reliability, and configuring the Jetson to automatically boot into the full-screen application. The final reboot test verifies that the Jetson operates independently, maintaining camera capture and local inference without requiring a connected development machine (Mac).
Key takeaways
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AI-Assisted Deployment with Codex
Codex is used to validate hardware compatibility, review application requirements, and generate a deployment plan for the Live VLM WebUI, reusing compatible files already on the Jetson system.
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Ensuring Offline Reliability
2:00
To guarantee operation without internet access, Codex updates the application to serve all necessary browser assets locally, while keeping the inference service isolated on the Jetson.
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Configuring Standalone Kiosk Mode
5:20
The setup involves configuring the Jetson to boot directly into the full-screen application, enabling automatic camera capture, and setting up automatic login for the demo account to ensure continuous operation after reboot.