lab9-10 solution templates

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Kacper 2022-05-23 21:07:01 +02:00
parent 17b941219c
commit ad9233a887
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DST_DP_lab_9-10/DP.py Normal file
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from collections import defaultdict
from copy import deepcopy
from convlab2.policy.policy import Policy
from convlab2.util.multiwoz.dbquery import Database
from convlab2.util.multiwoz.multiwoz_slot_trans import REF_SYS_DA
from convlab2.dialog_agent import PipelineAgent
from DST import DST
# Taktyka prowadzenia dialogu
class DP(Policy):
def __init__(self):
Policy.__init__(self)
self.db = Database()
def predict(self, state):
self.results = []
system_action = defaultdict(list)
user_action = defaultdict(list)
for intent, domain, slot, value in state['user_action']:
user_action[(domain, intent)].append((slot, value))
for user_act in user_action:
self.update_system_action(user_act, user_action, state, system_action)
# Reguła 3
if any(True for slots in user_action.values() for (slot, _) in slots if slot in ['Stay', 'Day', 'People']):
if self.results:
system_action = {('Booking', 'Book'): [["Ref", self.results[0].get('Ref', 'N/A')]]}
system_acts = [[intent, domain, slot, value] for (domain, intent), slots in system_action.items() for slot, value in slots]
state['system_action'] = system_acts
return system_acts
def update_system_action(self, user_act, user_action, state, system_action):
domain, intent = user_act
constraints = [(slot, value) for slot, value in state['belief_state'][domain.lower()]['semi'].items() if value != '']
self.results = deepcopy(self.db.query(domain.lower(), constraints))
# Reguła 1
if intent == 'Request':
if len(self.results) == 0:
system_action[(domain, 'NoOffer')] = []
else:
for slot in user_action[user_act]:
kb_slot_name = REF_SYS_DA[domain].get(slot[0], slot[0])
if kb_slot_name in self.results[0]:
system_action[(domain, 'Inform')].append([slot[0], self.results[0].get(kb_slot_name, 'unknown')])
# Reguła 2
elif intent == 'Inform':
if len(self.results) == 0:
system_action[(domain, 'NoOffer')] = []
else:
system_action[(domain, 'Inform')].append(['Choice', str(len(self.results))])
choice = self.results[0]
if domain in ["Hotel", "Attraction", "Police", "Restaurant"]:
system_action[(domain, 'Recommend')].append(['Name', choice['name']])
# Przykładowe uruchomienie dla kodu jeszcze bez zmian pod rezerwację biletów kinowych
"""
dst = DST()
dp = DP()
agent = PipelineAgent(nlu=None, dst=dst, policy=dp, nlg=None, name='sys')
print(agent.response([['Inform', 'Hotel', 'Price', 'cheap'], ['Inform', 'Hotel', 'Parking', 'yes']]))
"""

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DST_DP_lab_9-10/DST.py Normal file
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from dialogue_state import default_state
import json
from convlab2.dst.dst import DST as CL2DST
from convlab2.dst.rule.multiwoz.dst_util import normalize_value
from convlab2.util.multiwoz.multiwoz_slot_trans import REF_SYS_DA
# Monitor stanu dialogu
class DST(CL2DST):
def __init__(self):
CL2DST.__init__(self)
self.state = default_state()
self.value_dict = json.load(open('value_dict.json'))
def update(self, user_act=None):
for intent, domain, slot, value in user_act:
domain = domain.lower()
intent = intent.lower()
if domain in ['unk', 'general', 'booking']:
continue
if intent == 'inform':
k = REF_SYS_DA[domain.capitalize()].get(slot, slot)
if k is None:
continue
domain_dic = self.state['belief_state'][domain]
if k in domain_dic['semi']:
nvalue = normalize_value(self.value_dict, domain, k, value)
self.state['belief_state'][domain]['semi'][k] = nvalue
elif k in domain_dic['book']:
self.state['belief_state'][domain]['book'][k] = value
elif k.lower() in domain_dic['book']:
self.state['belief_state'][domain]['book'][k.lower()] = value
elif intent == 'request':
k = REF_SYS_DA[domain.capitalize()].get(slot, slot)
if domain not in self.state['request_state']:
self.state['request_state'][domain] = {}
if k not in self.state['request_state'][domain]:
self.state['request_state'][domain][k] = 0
return self.state
def init_session(self):
self.state = default_state()
# Przykładowe uruchomienie dla kodu jeszcze bez zmian pod rezerwację biletów kinowych
"""
dst = DST()
print(dst.state)
dst.update([['Inform', 'Hotel', 'Price', 'cheap'], ['Inform', 'Hotel', 'Parking', 'yes']])
print(dst.state['belief_state']['hotel'])
"""

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def default_state():
state = dict(user_action=[],
system_action=[],
belief_state={},
request_state={},
terminated=False,
history=[])
state['belief_state'] = {
"police": {
"book": {
"booked": []
},
"semi": {}
},
"hotel": {
"book": {
"booked": [],
"people": "",
"day": "",
"stay": ""
},
"semi": {
"name": "",
"area": "",
"parking": "",
"pricerange": "",
"stars": "",
"internet": "",
"type": ""
}
},
"attraction": {
"book": {
"booked": []
},
"semi": {
"type": "",
"name": "",
"area": ""
}
},
"restaurant": {
"book": {
"booked": [],
"people": "",
"day": "",
"time": ""
},
"semi": {
"food": "",
"pricerange": "",
"name": "",
"area": "",
}
},
"hospital": {
"book": {
"booked": []
},
"semi": {
"department": ""
}
},
"taxi": {
"book": {
"booked": []
},
"semi": {
"leaveAt": "",
"destination": "",
"departure": "",
"arriveBy": ""
}
},
"train": {
"book": {
"booked": [],
"people": ""
},
"semi": {
"leaveAt": "",
"destination": "",
"day": "",
"arriveBy": "",
"departure": ""
}
}
}
return state

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DST_DP_lab_9-10/value_dict.json Executable file

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