"""A bot's own process, in RLCard's own interface: agent.py defines a class Agent with eval_step(state) (returning the
action, or the action and info, as RLCard agents do) or step(state), or a function act(state). The state is RLCard's
raw state: state['raw_obs'] (self, landlord, current_hand, others_hand, played_cards, num_cards_left, seen_cards,
trace, actions) and state['raw_legal_actions'], moves written as RLCard writes them ('33344', '789TJQ', 'BR', 'pass').
  python3 -I referee/child.py <agent.py>
"""
import os, sys

sys.path.insert(0, os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'kit'))
from host import load, serve  # noqa: E402
import random  # noqa: E402
import numpy as np  # noqa: E402

random.seed(0)  # a bot's own randomness is seeded too, so a check gives the same score every time
np.random.seed(0)

made = load(sys.argv[1], 'Agent', 'act')
bot = made() if isinstance(made, type) else None


def handle(msg):
    state = {'raw_obs': msg['raw_obs'], 'raw_legal_actions': msg['raw_obs']['actions']}
    if bot is None:
        return str(made(state))
    out = bot.eval_step(state) if hasattr(bot, 'eval_step') else bot.step(state)
    return str(out[0] if isinstance(out, tuple) else out)


serve(handle)