import argparse, json, sys, time, random
import utterance.voice
import utterance.utils
import utterance.osc
import examine.metric

UTTERANCE_LEN = 16
broadcast = None

def format_str(text: str) -> str:
	t = utterance.utils.clean(text)
	return utterance.utils.format(t)	

def broadcast_utterance(v, utterance):	

	global broadcast

	text = v.name.upper() + ":\n"

	broadcast.utterance(text, v.channel)
	time.sleep(2)

	frags = v.fragments(utterance)

	for f in frags:
		text += f
		broadcast.utterance(text, v.channel)
		time.sleep(2)

	broadcast.command('clear')
	time.sleep(2)

				
def main() -> int:

	global broadcast

	p = argparse.ArgumentParser()
	p.add_argument("-c", "--config", type=str, default="voice.config.json", help="configuratin file")
	p.add_argument("-i", "--iterations", type=int, default=10, help="number of iterations")
	args = p.parse_args()

	with open(args.config) as f:
		conf = json.load(f)

	voices = []
	for v in conf['voices']:
		model = v['model']
		voice = utterance.voice.Voice(name=v["name"].upper(), model=model['model_dir'], tokenizer=model['tokeniser_file'], temp=float(model["temperature"]), lenght=UTTERANCE_LEN)
		voice.set_channel(v['osc_channel']['root'], v['osc_channel']['utterance'])
		voices.append(voice)

	broadcast = utterance.osc.OscBroadcaster(name="osc_broadcast", host=conf['host'], port=conf['port'], command_channel=conf['command_osc_channel'])
	broadcast.start_osc()

	nbr_voices = len(voices)

	state = 'c'

	metric = examine.metric.Metric(model_input='data/models/doc2vec.model')

	s = set(range(0, nbr_voices - 1))

	rindex = random.sample(s, 1)[0]

	v = voices[rindex]
	uv = v.utter_one()
	uv = format_str(uv)

	v_vec = metric.vector(uv)
	

	while state == 'c':
		
		candidates = random.sample(s, 3)

		results = []
		for c in candidates:
			if c == rindex:
				continue
			vc = voices[c]
			vc_texts = vc.utter_n(n=50)
			for t in vc_texts:
				t = format_str(t)
				t_vec = metric.vector(t)
				d = examine.metric.cos_dist(v_vec, t_vec)
				results.append([d, t, c])


		results.sort(key=lambda t: t[0], reverse=True)


		broadcast_utterance(v, uv)


		# new round

		top = results[0]
		rindex = top[2]
		v = voices[rindex]
		uv = top[1]
		v_vec = metric.vector(top[1])


		# state = input("Continue? ")



	broadcast.terminate_osc()


if __name__ == '__main__':
    sys.exit(main())