Adding new engines

OpenDDE’s modular architecture makes it straightforward to add new computational engines. This guide walks through the process step by step.

Overview

1. Create a Docker service for the new tool
2. Implement the adapter interface in the backend
3. Register the service in docker-compose.yml
4. Update the backend configuration to use the new engine

Step 1: Create the Docker service

Create a new directory for your engine:

mkdir services/my-engine
cd services/my-engine

Write a minimal Flask/FastAPI wrapper:

# services/my-engine/app.py
from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route('/health')
def health():
    return jsonify({"status": "ok"})

@app.route('/predict', methods=['POST'])
def predict():
    data = request.json
    # ... your prediction logic ...
    return jsonify({"result": result})

Create a Dockerfile:

FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "-m", "flask", "run", "--host=0.0.0.0", "--port=5004"]

Step 2: Implement the adapter

See Engine swap layer for the adapter interface pattern. Implement the appropriate abstract class for your engine type.

Step 3: Register in Docker Compose

# docker-compose.yml
services:
  my-engine:
    build: ./services/my-engine
    ports:
      - "5004:5004"
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:5004/health"]
      interval: 30s
      timeout: 10s
      retries: 3

Step 4: Update configuration

Update the backend configuration to point to your new engine. The exact mechanism depends on which engine type you’re replacing or adding.

Next: Code structure →