from turtle import st from zipfile import ZipFile, ZIP_DEFLATED from shutil import rmtree import json import os from tqdm import tqdm from collections import Counter from pprint import pprint import re import requests from dateutil import parser as date_parser from string import punctuation from copy import deepcopy def value_in_utt(value, utt): """return character level (start, end) if value in utt""" value = value.strip(punctuation).lower() utt = utt p = '(^|[\s,\.:\?!-])(?P{})([\s,\.:\?!-\']|$)'.format(re.escape(value)) p = re.compile(p, re.I) m = re.search(p, utt) if m: # very few value appears more than once, take the first span return True, m.span('v') else: try: # solve date representation, e.g. '3 pm' vs '3pm' date_parser.parse(value) if (value.endswith('pm') or value.endswith('am')) and ''.join(value.split(' ')) in ''.join(utt.split(' ')): return True, None except: if value in utt: # value appears, but may be in the plural, -ing, -ly, etc. return True, None return False, None def preprocess(): data_file = "kvret_dataset_public.zip" if not os.path.exists(data_file): response = requests.get("http://nlp.stanford.edu/projects/kvret/kvret_dataset_public.zip") open(data_file, "wb").write(response.content) archive = ZipFile(data_file) new_data_dir = 'data' os.makedirs(new_data_dir, exist_ok=True) dataset = 'kvret' splits = ['train', 'validation', 'test'] dialogues_by_split = {split:[] for split in splits} ontology = {'domains': {}, 'intents': { 'inform': {'description': ''}, 'request': {'description': ''} }, 'state': {}, 'dialogue_acts': { "categorical": {}, "non-categorical": {}, "binary": {} }} domain2slot = { 'schedule': ['event', 'time', 'date', 'party', 'room', 'agenda'], 'weather': ['location', 'weekly_time', 'temperature', 'weather_attribute'], 'navigate': ['poi', 'traffic_info', 'poi_type', 'address', 'distance'] } slot2domain = {slot: domain for domain in domain2slot for slot in domain2slot[domain]} db = [] with archive.open(f'kvret_entities.json') as f: entities = json.load(f) for slot, values in entities.items(): domain = slot2domain[slot] ontology['domains'].setdefault(domain, {'description': '', 'slots': {}}) if slot == 'poi': for s in ['poi', 'address', 'poi_type']: ontology['domains'][domain]['slots'][s] = {'description': '', 'is_categorical': False, 'possible_values': []} for item in values: poi, address, poi_type = item['poi'], item['address'], item['type'] db.append({'poi': poi, 'address': address, 'poi_type': poi_type}) for s in ['poi', 'address', 'poi_type']: ontology['domains'][domain]['slots'][s]['possible_values'].append(db[-1][s]) continue elif slot == 'weekly_time': slot = 'date' elif slot == 'temperature': values = [f"{x}F" for x in values] elif slot == 'distance': values = [f"{x} miles" for x in values] ontology['domains'][domain]['slots'][slot] = {'description': '', 'is_categorical': False, 'possible_values': values} for domain in ontology['domains']: for slot in ontology['domains'][domain]['slots']: ontology['domains'][domain]['slots'][slot]['possible_values'] = sorted(list(set(ontology['domains'][domain]['slots'][slot]['possible_values']))) for data_split in splits: filename = data_split if data_split != 'validation' else 'dev' with archive.open(f'kvret_{filename}_public.json') as f: data = json.load(f) for item in tqdm(data): if len(item['dialogue']) == 0: continue scenario = item['scenario'] domain = scenario['task']['intent'] slots = scenario['kb']['column_names'] db_results = {domain: []} if scenario['kb']['items']: for entry in scenario['kb']['items']: db_results[domain].append({s: entry[s] for s in slots}) dialogue_id = f'{dataset}-{data_split}-{len(dialogues_by_split[data_split])}' dialogue = { 'dataset': dataset, 'data_split': data_split, 'dialogue_id': dialogue_id, 'original_id': f'{data_split}-{len(dialogues_by_split[data_split])}', 'domains': [domain], 'turns': [] } init_state = {domain: {}} for turn in item['dialogue']: speaker = 'user' if turn['turn'] == 'driver' else 'system' utt = turn['data']['utterance'].strip() if len(dialogue['turns']) > 0 and speaker == dialogue['turns'][-1]['speaker']: # repeat, skip if utt == dialogue['turns'][-1]['utterance']: continue else: dialogue['turns'].pop(-1) dialogue['turns'].append({ 'speaker': speaker, 'utterance': utt, 'utt_idx': len(dialogue['turns']), 'dialogue_acts': { 'binary': [], 'categorical': [], 'non-categorical': [], }, }) if speaker == 'user': dialogue['turns'][-1]['state'] = deepcopy(init_state) else: user_da = {'binary': [], 'categorical': [], 'non-categorical': []} user_utt = dialogue['turns'][-2]['utterance'] for slot, value in turn['data']['slots'].items(): value = value.strip() is_appear, span = value_in_utt(value, user_utt) if is_appear: if span: start, end = span user_da['non-categorical'].append({ 'intent': 'inform', 'domain': domain, 'slot': slot, 'value': user_utt[start:end], 'start': start, 'end': end }) else: user_da['non-categorical'].append({ 'intent': 'inform', 'domain': domain, 'slot': slot, 'value': value, }) init_state[domain][slot] = value ontology['state'].setdefault(domain, {}) ontology['state'][domain].setdefault(slot, '') dialogue['turns'][-2]['state'] = deepcopy(init_state) for slot, present in turn['data']['requested'].items(): if slot not in turn['data']['slots'] and present: user_da['binary'].append({'intent': 'request', 'domain': domain, 'slot': slot}) dialogue['turns'][-2]['dialogue_acts'] = user_da dialogue['turns'][-1]['db_results'] = db_results for da_type in user_da: das = user_da[da_type] for da in das: ontology["dialogue_acts"][da_type].setdefault((da['intent'], da['domain'], da['slot']), {}) ontology["dialogue_acts"][da_type][(da['intent'], da['domain'], da['slot'])]['user'] = True assert all([s in ontology['domains'][domain]['slots'] for s in turn['data']['requested']]), print(turn['data']['requested'], ontology['domains'][domain]['slots'].keys()) assert all([s in ontology['domains'][domain]['slots'] for s in turn['data']['slots']]), print(turn['data']['slots'], ontology['domains'][domain]['slots'].keys()) dialogues_by_split[data_split].append(dialogue) for da_type in ontology['dialogue_acts']: ontology["dialogue_acts"][da_type] = sorted([str({'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent':da[0],'domain':da[1], 'slot':da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()]) dialogues = dialogues_by_split['train']+dialogues_by_split['validation']+dialogues_by_split['test'] json.dump(dialogues[:10], open(f'dummy_data.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) json.dump(ontology, open(f'{new_data_dir}/ontology.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) json.dump(dialogues, open(f'{new_data_dir}/dialogues.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) json.dump(db, open(f'{new_data_dir}/db.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf: for filename in os.listdir(new_data_dir): zf.write(f'{new_data_dir}/{filename}') rmtree(new_data_dir) return dialogues, ontology if __name__ == '__main__': preprocess()