if parts[0]=='xboard':
print('tellics say Monte Carlo Tree Search experimental chess engine')
print('tellics say based on SlyMlego deep learning platform')
print('tellics say by Stefano Marago\' 2018')
print('tellics say https://github.com/stevexyz/SlyMlego')
elif parts[0]=='protover' and parts[1]=='2':
print('feature done=0')
sys.stdout.flush() # ensure xboard wait to activate network
print('feature debug=1')
from Eval import Eval
if len(sys.argv)<=1:
modeleval = Eval(quiet=True)
else:
modeleval = Eval(modelfile=sys.argv[1], quiet=True)
modeleval.EvaluatePositionB(chess.Board()) # just to startup engine
print('feature myname="mcts-mlego-v0.1"')
print('feature variants="normal"')
print('feature setboard=0')
print('feature ping=1')
print('feature usermove=1')
print('feature analyze=0')
print('feature pause=0')
print('feature nps=0')
print('feature memory=0')
print('feature sigint=0')
print('feature done=1')
elif parts[0]=='quit':
break
