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Stratum — API Reference

This document describes the backend HTTP API implemented by the image-to-psd backend.

Base path: /api

Endpoints

  • POST /api/upload

    • Multipart form upload: file (image/png | image/jpeg | image/webp)
    • Response: 200 { "job_id": "<uuid>", "status": "queued" }
    • Starts a background pipeline that performs segmentation, detection, OCR, manifest assembly and PSD generation.

  • POST /api/generate_psd

    • Query parameter: job_id (string)
    • Response: 200 { "success": true, "psd_path": "<path>", "layer_count": <int>, "file_size_kb": <float> }
    • Manually triggers PSD assembly and compilation from the compiled layers.json manifest.

  • GET /api/status/{job_id}

    • Response: 200 { "job_id": "<id>", "status": "queued|preprocessing|segmenting|segmented|ocr|assembling|done|failed", "progress": <0-100> }
    • 404 if job not found

  • GET /api/result/{job_id}

    • If processing not finished: 202 { "status": "processing" }
    • If done: 200 { "job_id": "<id>", "status": "done", "layers": [ { layer objects... } ] }
    • Each layer object: { "layer_id", "type", "label", "bounding_box", "thumbnail_url" }
    • 404 if job not found

  • GET /api/download/{job_id}

    • If processing not finished: 202 { "status": "processing" }
    • If done: 200 — returns result.psd as binary with header Content-Disposition: attachment; filename=result.psd and media type application/octet-stream.
    • 404 if file is missing or job not found

  • GET /api/outputs/{job_id}/{file_path}

    • Serves static artifacts produced by the pipeline (thumbnails, intermediate PNGs, text_manifest.json, etc.).
    • 404 if file not found, 403 for forbidden/path traversal attempts.

  • GET /api/health

    • Response: 200 { "status": "ok" }
    • Service health check endpoint.

Notes

  • The API is implemented in image-to-psd-backend/routes/api.py.
  • Pipeline stages live under image-to-psd-backend/services/ and are executed in a background thread started by /api/upload.
  • For production use you should replace the in-memory job_store with a persistent store (Redis/DB) and run the pipeline as a proper worker (Celery/RQ) rather than threads.