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import json |
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import os |
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import random |
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from fuzzywuzzy import fuzz |
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from itertools import chain |
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from zipfile import ZipFile |
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from copy import deepcopy |
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from convlab.util.unified_datasets_util import BaseDatabase |
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class Database(BaseDatabase): |
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def __init__(self): |
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"""extract data.zip and load the database.""" |
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archive = ZipFile(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data.zip')) |
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self.domains = ['restaurant', 'hotel', 'attraction', 'train', 'hospital', 'police'] |
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self.dbs = {} |
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for domain in self.domains: |
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with archive.open('data/{}_db.json'.format(domain)) as f: |
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self.dbs[domain] = json.loads(f.read()) |
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self.dbs['taxi'] = { |
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"taxi_colors": ["black","white","red","yellow","blue","grey"], |
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"taxi_types": ["toyota","skoda","bmw","honda","ford","audi","lexus","volvo","volkswagen","tesla"], |
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"taxi_phone": ["^[0-9]{10}$"] |
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} |
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self.dbs['police'][0]['postcode'] = "cb11jg" |
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for entity in self.dbs['hospital']: |
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entity['postcode'] = "cb20qq" |
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entity['address'] = "Hills Rd, Cambridge" |
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self.slot2dbattr = { |
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'open hours': 'openhours', |
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'price range': 'pricerange', |
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'arrive by': 'arriveBy', |
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'leave at': 'leaveAt', |
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'train id': 'trainID' |
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} |
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def query(self, domain: str, state: dict, topk: int, ignore_open=False, soft_contraints=(), fuzzy_match_ratio=60) -> list: |
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"""return a list of topk entities (dict containing slot-value pairs) for a given domain based on the dialogue state.""" |
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if domain == 'taxi': |
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return [{'taxi_colors': random.choice(self.dbs[domain]['taxi_colors']), |
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'taxi_types': random.choice(self.dbs[domain]['taxi_types']), |
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'taxi_phone': ''.join([str(random.randint(1, 9)) for _ in range(11)])}] |
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if domain == 'police': |
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return deepcopy(self.dbs['police']) |
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if domain == 'hospital': |
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department = None |
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for key, val in state: |
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if key == 'department': |
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department = val |
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if not department: |
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return deepcopy(self.dbs['hospital']) |
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else: |
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return [deepcopy(x) for x in self.dbs['hospital'] if x['department'].lower() == department.strip().lower()] |
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state = list(map(lambda ele: (self.slot2dbattr.get(ele[0], ele[0]), ele[1]) if not(ele[0] == 'area' and ele[1] == 'center') else ('area', 'centre'), state)) |
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found = [] |
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for i, record in enumerate(self.dbs[domain]): |
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constraints_iterator = zip(state, [False] * len(state)) |
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soft_contraints_iterator = zip(soft_contraints, [True] * len(soft_contraints)) |
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for (key, val), fuzzy_match in chain(constraints_iterator, soft_contraints_iterator): |
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if val in ["", "dont care", 'not mentioned', "don't care", "dontcare", "do n't care"]: |
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pass |
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else: |
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try: |
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if key not in record: |
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continue |
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if key == 'leaveAt': |
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val1 = int(val.split(':')[0]) * 100 + int(val.split(':')[1]) |
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val2 = int(record['leaveAt'].split(':')[0]) * 100 + int(record['leaveAt'].split(':')[1]) |
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if val1 > val2: |
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break |
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elif key == 'arriveBy': |
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val1 = int(val.split(':')[0]) * 100 + int(val.split(':')[1]) |
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val2 = int(record['arriveBy'].split(':')[0]) * 100 + int(record['arriveBy'].split(':')[1]) |
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if val1 < val2: |
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break |
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elif ignore_open and key in ['destination', 'departure']: |
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continue |
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elif record[key].strip() == '?': |
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continue |
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else: |
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if not fuzzy_match: |
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if val.strip().lower() != record[key].strip().lower(): |
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break |
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else: |
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if fuzz.partial_ratio(val.strip().lower(), record[key].strip().lower()) < fuzzy_match_ratio: |
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break |
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except: |
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continue |
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else: |
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res = deepcopy(record) |
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res['Ref'] = '{0:08d}'.format(i) |
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found.append(res) |
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if len(found) == topk: |
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return found |
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return found |
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if __name__ == '__main__': |
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db = Database() |
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assert issubclass(Database, BaseDatabase) |
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assert isinstance(db, BaseDatabase) |
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res = db.query("restaurant", [['price range', 'expensive']], topk=3) |
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print(res, len(res)) |
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