import grpc
import logging
from concurrent import futures
 
import predict_pb2, predict_pb2_grpc
from predict_pb2 import *
from predict_pb2_grpc import *

import numpy
from keras.models import load_model
from data import load_pay_data, load_gift_data
pay_model = load_model("./predict_pay")
gift_model = load_model("./predict_gift")
 
class Predict(predict_pb2_grpc.PredictServicer):
    def PayDay(self, request, context):
        # print(request)
        inputx = numpy.reshape([request.Hour, request.Coin / request.YesterdayCoin, request.Coin], (1, 3, 1)) 
        predict_value = pay_model.predict(inputx)
        return ReplyPay(Header=ReplyHeader(Code=0, Message=""), Result=int(predict_value[0][0]))
        # return super().PayDay(request, context)
    def GiftDay(self, request, context):
        # print(request)
        inputx = numpy.reshape([request.Hour, request.Coin / request.YesterdayCoin, request.Coin], (1, 3, 1)) 
        predict_value = gift_model.predict(inputx)
        return ReplyGift(Header=ReplyHeader(Code=0, Message=""), Result=int(predict_value[0][0]))

def server():
    grpc_server = grpc.server(futures.ThreadPoolExecutor(max_workers=2))
    predict_pb2_grpc.add_PredictServicer_to_server(Predict(), grpc_server)
    grpc_server.add_insecure_port('0.0.0.0:50051')
    grpc_server.start()
    grpc_server.wait_for_termination()

if __name__ == '__main__':
    logging.basicConfig()
    server()