import requests

from NaturalLanguageAnalyzer import NaturalLanguageAnalyzer
from DialoguePolicy import DialoguePolicy
from DialogueStateTracker import DialogueStateTracker
from convlab.dialog_agent import PipelineAgent
from MachineLearningNLG import MachineLearningNLG  # Importujemy nowy komponent NLG


def translate_text(text, target_language='pl'):
    url = 'https://translate.googleapis.com/translate_a/single?client=gtx&sl=auto&tl={}&dt=t&q={}'.format(
        target_language, text)
    response = requests.get(url)
    if response.status_code == 200:
        translated_text = response.json()[0]
        translated_text_joined = ''.join([sentence[0] for sentence in translated_text])
        return translated_text_joined
    else:
        return None


if __name__ == "__main__":
    text = "chciałbym zarezerwować drogi hotel z parkingiem 1 stycznia w Warszawie w centrum"
    nlu = NaturalLanguageAnalyzer()
    dst = DialogueStateTracker()
    policy = DialoguePolicy()
    nlg = MachineLearningNLG()

    agent = PipelineAgent(nlu=nlu, dst=dst, policy=policy, nlg=nlg, name='sys')
    response = agent.response(text)
    print(translate_text(response))