ocr-service
Python FastAPI microservice that performs the actual handwritten text recognition (HTR) and OCR. The Spring Boot backend orchestrates jobs; this service executes them.
What this service owns
- Text recognition: Surya (typewritten text) and Kraken (Kurrent/Sütterlin historical handwriting)
- Baseline layout analysis: Kraken BLLA model
- Sender recognition: trained per-archive sender models
- HTTP API at port 8000 (internal Docker network — no external port)
What this service does NOT own
- Job lifecycle — tracked in the backend's
ocr/ domain
- MinIO storage — the service fetches PDFs via presigned URLs generated by the backend; it does not hold credentials
- Transcription block storage — results are streamed back to the backend, which writes them to PostgreSQL
API endpoints
| Endpoint |
Auth |
Purpose |
POST /ocr |
None (internal network only) |
Run OCR on a PDF (presigned MinIO URL in request body) |
POST /train |
X-Training-Token header |
Trigger sender-model training |
POST /segtrain |
X-Training-Token header |
Trigger segmentation training |
GET /health |
None |
Health check |
Environment variables
| Variable |
Default |
Required? |
Sensitive? |
Purpose |
TRAINING_TOKEN |
— |
YES (prod) |
YES |
Guards /train and /segtrain. Do not leave empty in production. |
ALLOWED_PDF_HOSTS |
minio,localhost,127.0.0.1 |
YES |
— |
SSRF protection — comma-separated allowed PDF source hosts. Never set to *. |
KRAKEN_MODEL_PATH |
/app/models/ |
— |
— |
Directory where Kraken HTR models are stored (populated by download-kraken-models.sh) |
BLLA_MODEL_PATH |
/app/models/blla.mlmodel |
— |
— |
Kraken baseline layout analysis model. Auto-downloaded via ensure_blla_model.py on startup if missing. |
Key files
| File |
Purpose |
main.py |
FastAPI app, endpoint definitions, SSRF validation |
engines/ |
Surya and Kraken engine wrappers |
models.py |
Pydantic request/response models |
preprocessing.py |
PDF-to-image conversion before OCR |
confidence.py |
Per-block confidence scoring |
spell_check.py |
Post-OCR spell correction using historical dictionaries |
ensure_blla_model.py |
Startup script that downloads the BLLA model if missing |
entrypoint.sh |
Docker entrypoint — runs ensure_blla_model.py then starts the server |
Backend counterpart
backend/src/main/java/org/raddatz/familienarchiv/ocr/README.md