word2vec server

import gensim.models.keyedvectors as word2vec
import numpy as np
import socket
import sys


model=word2vec.KeyedVectors.load_word2vec_format('./GoogleNews-vectors-negative300.bin',binary=True)


# Create a TCP/IP socket
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server_address = ('localhost', 10004)
print (sys.stderr, 'starting up on %s port %s' % server_address)
sock.bind(server_address)
sock.listen(1)

while True:
    # Wait for a connection
    print (sys.stderr, 'waiting for a connection')
    connection, client_address = sock.accept()
    try:
        print (sys.stderr, 'connection from', client_address)

        # Receive the data in small chunks and retransmit it
        while True:
            data = connection.recv(1001)
            print (sys.stderr, 'received ', data)
            if data:
                print (sys.stderr, 'sending data back to the client')
                data = data.decode("utf-8")
                words = data.split(',')
                try:
                    result=model.similarity(words[0],words[1])
                except KeyError:
                    result=-1
                result = str(result) + "\n"
                print(str(result))
                connection.sendall(bytes(result, "utf-8"))
            else:
                print (sys.stderr, 'no more data from', client_address)
                break
           
    finally:
        # Clean up the connection
        connection.close()