api.py

import logging

import flask
from flasgger import Swagger
from flask import Flask, request, jsonify, Response
from flask_cors import CORS
import predict
from predict import predicting
from predict import load_model

logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
logger = logging.getLogger(__name__)

# NOTE this import needs to happen after the logger is configured


# Initialize the Flask application
application = Flask(__name__)

application.config['ALLOWED_EXTENSIONS'] = set(['pdf'])
application.config['CONTENT_TYPES'] = {"pdf": "application/pdf"}
application.config["Access-Control-Allow-Origin"] = "*"


CORS(application)

swagger = Swagger(application)

model, char2idx, idx2char = load_model()

def clienterror(error):
    resp = jsonify(error)
    resp.status_code = 400
    return resp


def notfound(error):
    resp = jsonify(error)
    resp.status_code = 404
    return resp


@application.route('/Stephen-King-Bot', methods=['POST'])
def sentiment_classification():
    """Run Stephen King text generator given text.
        ---
        parameters:
          - name: body
            in: body
            schema:
              id: text
              required:
                - text
              properties:
                text:
                  type: string
            description: Starter string for the bot to generate text in the style of Stephen King from
            required: true
        definitions:
          SentimentResponse:
          Project:
            properties:
              status:
                type: string
              ml-result:
                type: object
        responses:
          Generated Text:
            description: Example Output
            examples:
                          [
{
  "Input": "Stephen",
  "Output": "Stephen King is the greatest author."
},]
        """
    json_request = request.get_json()
    if not json_request:
        return Response("No json provided.", status=400)
    text = json_request['text']
    if text is None:
        return Response("No text provided.", status=400)
    else:
        label = predicting(model, char2idx, idx2char, text)
        return label

if __name__ == '__main__':
    application.run(debug=True, use_reloader=True)