forked from s151636/Generic_DialogSystem
68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
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import spacy
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nlp = spacy.load("pl_core_news_md")
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product_type_rules = {
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"pieczywo": ["chleb", "bułka", "rogalik", "bagietka"],
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"owoce": ["jabłko", "banan", "gruszka", "pomarańcza"],
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"warzywa": ["marchew", "ziemniak", "cebula", "pomidor"],
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"mięso": ["kurczak", "wołowina", "wieprzowina", "indyk"],
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"produkty mrożone": ["lody", "frytki", "pierogi mrożone", "nuggetsy"],
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"słodycze": ["czekolada", "ciastko", "lizak", "guma do żucia"],
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"przyprawy": ["sól", "pieprz", "oregano", "cynamon"],
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"napoje": ["woda", "sok", "herbata", "kawa"],
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"napoje alkoholowe": ["piwo", "wino", "wódka", "whisky"],
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"higiena": ["pasta do zębów", "mydło", "szampon", "papier toaletowy"],
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"chemia gospodarcza": ["płyn do naczyń", "proszek do prania", "odświeżacz powietrza"],
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"inne": ["długopis", "baterie", "śrubokręt", "nożyczki"],
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"nabiał": ["mleko"]
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}
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class DialogAct:
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def __init__(self, act_type, slots=None):
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self.act_type = act_type
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self.slots = slots if slots else {}
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def extract_acts_and_slots(text):
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doc = nlp(text)
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acts = []
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for token in doc:
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if token.lower_ == "cześć":
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acts.append(DialogAct("hello"))
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elif token.lower_ == "do widzenia":
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acts.append(DialogAct("bye"))
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elif token.lower_ == "dziękuję":
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acts.append(DialogAct("thankyou"))
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elif token.lower_ == "proszę":
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acts.append(DialogAct("request"))
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elif token.lower_ == "powtórz":
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acts.append(DialogAct("repeat"))
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elif token.lower_ == "reset":
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acts.append(DialogAct("restart"))
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elif token.lower_ in ["tak", "oczywiście"]:
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acts.append(DialogAct("affirm"))
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elif token.lower_ in ["nie", "nie chcę"]:
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acts.append(DialogAct("deny"))
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elif token.pos_ == "NOUN":
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product_type, product = find_product_type(token.lemma_)
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if product_type and product:
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act = DialogAct("inform", {"product type": product_type, "product": product})
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acts.append(act)
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return acts
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def find_product_type(product):
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for product_type, products in product_type_rules.items():
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if product in products:
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return product_type, product
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return None, None
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text = "Cześć, chciałbym kupić mleko"
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acts = extract_acts_and_slots(text)
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for act in acts:
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print(f"Type: {act.act_type}")
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print(f"Slots: {act.slots}")
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print()
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