32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
import requests
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from NaturalLanguageAnalyzer import NaturalLanguageAnalyzer
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from DialoguePolicy import DialoguePolicy
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from DialogueStateTracker import DialogueStateTracker
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from convlab.dialog_agent import PipelineAgent
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from MachineLearningNLG import MachineLearningNLG # Importujemy nowy komponent NLG
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def translate_text(text, target_language='pl'):
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url = 'https://translate.googleapis.com/translate_a/single?client=gtx&sl=auto&tl={}&dt=t&q={}'.format(
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target_language, text)
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response = requests.get(url)
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if response.status_code == 200:
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translated_text = response.json()[0]
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translated_text_joined = ''.join([sentence[0] for sentence in translated_text])
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return translated_text_joined
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else:
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return None
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if __name__ == "__main__":
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text = "chciałbym zarezerwować drogi hotel z parkingiem 1 stycznia w Warszawie w centrum"
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nlu = NaturalLanguageAnalyzer()
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dst = DialogueStateTracker()
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policy = DialoguePolicy()
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nlg = MachineLearningNLG()
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agent = PipelineAgent(nlu=nlu, dst=dst, policy=policy, nlg=nlg, name='sys')
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response = agent.response(text)
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print(translate_text(response))
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