How do I deploy Teavision on Railway?

You can deploy Teavision on Railway by clicking the "Deploy Now" button on this page. Railway will automatically set up all the necessary services and configurations for you.

What are the system requirements?

Railway handles all the infrastructure requirements. You only need a web browser to deploy and manage your application.

Is this template free to use?

Yes, this template is free to use within your existing Railway account.

Can I customize this template?

Yes, you can fully customize this template. After deployment, you will have full control of what you've deployed in your Railway project.

How do I get support for this template?

You can get support through our community forum: earnest-courage-3f8d6c3a, or click "Get template help" for this template for more assistance.

Deploy and Host earnest-courage on Railway

[TEAVISION_APP is a full-stack application for advanced image analysis and prediction. It integrates a Python/Flask backend with a React/Vite frontend, providing users with AI-driven insights, image processing features, and real-time predictions through a seamless web interface.]

About Hosting earnest-courage

[Hosting TEAVISION_APP involves deploying both the frontend and backend services on Railway. The backend runs as a Flask API, serving predictions, file uploads, and AI model processing, while the frontend is a static React/Vite application served via Nginx. Deployment requires setting up environment variables, exposing the correct ports, and ensuring the frontend can correctly call the backend API endpoints. Railway handles infrastructure scaling, automatic deployment from Docker images or GitHub repositories, and offers easy monitoring of logs and health checks.]

Common Use Cases

[Real-time image analysis and prediction for research or industrial applications]
[Uploading and processing images for feature extraction and AI-driven insights]
[Hosting a scalable full-stack AI web application with minimal DevOps overhead]

Dependencies for earnest-courage Hosting

[Backend: Python 3.10+, Flask, Flask-Cors, Waitress, OpenCV (headless), Scikit-learn, Pandas, NumPy]
[Frontend: Node 20+, React/Vite, Nginx for serving static files]

Deployment Dependencies

[Railway account and CLI: https://railway.app]

Implementation Details

[CMD ["waitress-serve", "--listen=0.0.0.0:$PORT", "app:app"]]

Deploy Teavision