cd ai-rec/backend/back2
pip install -r requirements.txt
uvicorn saas_api:app --reload

This runs the ML recommender API on http://localhost:8000

cd ai-rec/backend/back2
mlflow ui --backend-store-uri sqlite:///mlflow.db --default-artifact-root ./mlflow_artifacts

This runs MLflow UI on http://localhost:5000

cd ai-rec/backend/webhooks_services
npm install
node server.js

This runs the webhook and app registration service on http://localhost:3001

cd ai-rec/frontend/s
npm install
npm run dev

This runs the frontend on http://localhost:5173

cd ai-rec/backend/webhooks_services
node mock_webhook_server.js

This runs a mock webhook listener on http://localhost:4000 to test webhook notifications

1. Start all services in the order above
2. Open http://localhost:5173 in your browser
3. Go to the Webhook Dashboard tab
4. Register a new app with:
   • App Name: "My Music App" (or any name)
   • Webhook URL: "http://localhost:4000/api/music"
5. Copy the generated API Key
6. Use the API Key in the external client or test with curl

1. Open xternal_client/index.html in a browser
2. Paste your API Key
3. Enter a song title (e.g., "Fader")
4. Enter the Project ID (e.g., 7)
5. Click "Get Recommendations"

You should see recommendations and webhook notifications in the mock webhook server terminal!