Deploy autofigure-edit

AutoFigure-edit turns paper methods into editable SVG figures

Deploy autofigure-edit

Just deployed

Deploy and Host AutoFigure-Edit on Railway

About Hosting AutoFigure-Edit on Railway

AutoFigure-Edit runs as a single Dockerized FastAPI web application on Railway. Railway gives managed deployment, HTTPS domain, and variable management with no server operations.

Tech Stack

  • Python 3.11
  • FastAPI + Uvicorn
  • Pillow and scientific Python libs
  • Docker Hub image on Railway

Why Deploy AutoFigure-Edit on Railway

  • Single-service deployment with built-in HTTPS
  • Fast rollout from a Docker image
  • Easy variable-based configuration and redeploy
  • Good fit for research demos and internal sharing

Common Use Cases

  • Internal scientific figure generation web service
  • Team-shared AutoFigure-Edit playground
  • Reproducible cloud demo for paper methods

Deployment Notes

  • HTTP container port is 8000
  • Railway routing is controlled by PORT=8000
  • Public domain is enabled for browser/API access
  • HF_TOKEN / HUGGINGFACE_HUB_TOKEN should be set for RMBG-2.0 gated model access
  • ROBOFLOW_API_KEY and FAL_KEY are optional unless those SAM backends are used

Dependencies for AutoFigure-Edit on Railway

This deployment only requires one application service and no external database.

Deployment Dependencies

ServiceImagePortVolume
autofigure-editxiaosong233/autofigure-edit-railway:latest8000-

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