Full Stack Deep Learning Model

This repository is a starter-kit for deploying a deep lelarning model. The objective is to create a seq2seq model in pytorch and expose the prediction as a REST API using python flask module.

The code is broken into 2 pieces. Mainly

• train_API.py
• predict_API.py
• config.yaml
• param.json

Currently train_API.py is not ready. It's only available as a vanila train.py file which saves the model in the appropriate folder. A train/ API will be added later. However the predict_API.py is ready. The original predic.py is available in folder 99_testdir/. The flask API /predict is added on top of it and predict_API.py is created. Also some basic logging feature is added in the api for easy debugging.

The config.yaml contains all the meta information for the project. The directory structure and the API ip and port information.

Application Archtecture

Main Scripts

• The predict_API.py holds the actual code for prediciton module for the /predict api.

Start the PREDICTION SERVER (/predict API):

• python predict_API.R

Run the client from terminal

• following curl command can be used:
  • Syntax
    • curl http://localhost:5000/predict --data '[{"UID":"1","AGE":"15"}]' -H "Content-Type: application/json"
    • /predict is the prediction API end point

TODO

1. update the train_api.py
2. update the curl syntax for prediction
3. update the README.md