Deploy and Host Smart Marking on Railway

📘 Smart Marking Setup Guide — step by step with screenshots of the real app: read online · download the PDF · on GitHub

Smart Marking marks handwritten scripts that students photograph or scan, against your mark scheme (maths/science) or rubric (essays). An extractor reads the pages, a marker awards each allocation or band, and an independent reviewer checks it; anything illegible, out of scheme or disputed lands in a Review queue for the teacher. Students hand in from their phone with a class code and register number; feedback is shown only after the teacher releases it. Bring your own LLM key (TokenRouter, OpenRouter, OpenAI, Anthropic, Moonshot, Qwen or Google Gemini).

About Hosting Smart Marking

The template deploys two services: web (FastAPI + React, built from the Dockerfile, with the marking worker embedded) and Postgres (assignments, classes, marks and settings; API keys are encrypted at rest with the generated SECRET_KEY). Page images live on a volume mounted at /data and are deleted after marking by default, so storage stays small. After the deploy finishes, open the web domain, sign in with TEACHER_PASSWORD (generated — read it from the service's Variables, or set your own before deploying), go to Settings to paste a provider key and pick a model, then create an assignment and a class. No student accounts or passwords are needed: students use the class link and their register number. Everything runs inside your Railway project; scripts never leave it except for the model calls you configure.

Common Use Cases

Marking a class set of maths or science worksheets against a mark scheme, with M1/A1/B1-style allocations and a teacher check on the doubtful parts
Grading essays against a band rubric and giving students structured feedback (strengths, question by question, what to work on next)
Letting students hand in photographed work from their phones and receiving marks and feedback once the teacher releases them
Producing per-student .docx marking records and a marks CSV for moderation and departmental records

Dependencies for Smart Marking Hosting

An API key for one supported LLM provider with a vision-capable model (free options: OpenRouter :free models, Google Gemini's free tier)
The bundled Postgres service and the /data volume (both created by this template)

Deployment Dependencies

Railway's Postgres template (ghcr.io/railwayapp-templates/postgres-ssl) — created for you
A vision-capable model from any supported provider: https://github.com/twahidin/smart-marking-system#web-app

Implementation Details

Variables you may want to change before deploying: TEACHER_PASSWORD (generated), LLM_PROVIDER (default tokenrouter), and optionally LLM_MODEL / LLM_API_KEY to pre-seed the model and key. Source and documentation: https://github.com/twahidin/smart-marking-system — setup guide (PDF): https://github.com/twahidin/smart-marking-system/raw/main/docs/setup-guide/Smart-Marking-Setup-Guide.pdf

Why Deploy Smart Marking on Railway?

Railway is a singular platform to deploy your infrastructure stack. Railway will host your infrastructure so you don't have to deal with configuration, while allowing you to vertically and horizontally scale it.

By deploying Smart Marking on Railway, you are one step closer to supporting a complete full-stack application with minimal burden. Host your servers, databases, AI agents, and more on Railway.