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s495728 2024-06-09 14:52:22 +02:00
parent 1cd62db966
commit dbdf14bf20
6 changed files with 98 additions and 94 deletions
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2
requirements.txt
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@ -2,5 +2,5 @@ flair==0.13.1
conllu==4.5.3
pandas==1.5.3
numpy==1.26.4
torch==2.3.0
torch==1.13
convlab==3.0.2a0

24
src/service/convlab/policy/policy.py
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@ -1,24 +0,0 @@
"""Policy Interface"""
from convlab.util.module import Module
class Policy(Module):
"""Policy module interface."""
def predict(self, state):
"""Predict the next agent action given dialog state.
Args:
state (dict or list of list):
when the policy takes dialogue state as input, the type is dict.
else when the policy takes dialogue act as input, the type is list of list.
Returns:
action (list of list or str):
when the policy outputs dialogue act, the type is list of list.
else when the policy outputs utterance directly, the type is str.
"""
return []
def update_memory(self, utterance_list, state_list, action_list, reward_list):
pass

25
src/service/convlab/util/module.py
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@ -1,25 +0,0 @@
"""module interface."""
from abc import ABC
class Module(ABC):
def train(self, *args, **kwargs):
"""Model training entry point"""
pass
def test(self, *args, **kwargs):
"""Model testing entry point"""
pass
def from_cache(self, *args, **kwargs):
"""restore internal state for multi-turn dialog"""
return None
def to_cache(self, *args, **kwargs):
"""save internal state for multi-turn dialog"""
return None
def init_session(self):
"""Init the class variables for a new session."""
pass

38
src/service/convlab/util/restaurant/dbquery.py
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@ -1,38 +0,0 @@
"""
"""
import json
import os
import random
from fuzzywuzzy import fuzz
from itertools import chain
from copy import deepcopy
class Database(object):
def __init__(self):
super(Database, self).__init__()
# loading databases
domains = ['menu', 'pizza', 'drink', 'size']
self.dbs = {}
for domain in domains:
with open(os.path.join(os.path.dirname(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))),
'data/restaurant/db/{}_db.json'.format(domain))) as f:
self.dbs[domain] = json.load(f)
def query(self, domain):
"""Returns the list of entities for a given domain
based on the annotation of the belief state"""
# query the db
if domain == 'pizza':
return [{'Name': random.choice(self.dbs[domain]['name'])}]
if domain == 'menu':
return deepcopy(self.dbs[domain])
if domain == 'drink':
return [{'Name': random.choice(self.dbs[domain]['name'])}]
if domain == 'size':
return [{'Size': random.choice(self.dbs[domain]['size'])}]
if __name__ == '__main__':
db = Database()

91
src/service/dbquery.py Normal file
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@ -0,0 +1,91 @@
"""
"""
import json
import os
import random
from fuzzywuzzy import fuzz
from itertools import chain
from copy import deepcopy
class Database(object):
def __init__(self):
super(Database, self).__init__()
# loading databases
domains = ['restaurant', 'hotel', 'attraction', 'train', 'hospital', 'taxi', 'police']
self.dbs = {}
for domain in domains:
with open(os.path.join(os.path.dirname(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))),
'data/restaurant/db/{}_db.json'.format(domain))) as f:
self.dbs[domain] = json.load(f)
def query(self, domain, constraints, ignore_open=False, soft_contraints=(), fuzzy_match_ratio=60):
"""Returns the list of entities for a given domain
based on the annotation of the belief state"""
# query the db
if domain == 'taxi':
return [{'taxi_colors': random.choice(self.dbs[domain]['taxi_colors']),
'taxi_types': random.choice(self.dbs[domain]['taxi_types']),
'taxi_phone': ''.join([str(random.randint(1, 9)) for _ in range(11)])}]
if domain == 'police':
return deepcopy(self.dbs['police'])
if domain == 'hospital':
department = None
for key, val in constraints:
if key == 'department':
department = val
if not department:
return deepcopy(self.dbs['hospital'])
else:
return [deepcopy(x) for x in self.dbs['hospital'] if x['department'].lower() == department.strip().lower()]
constraints = list(map(lambda ele: ele if not(ele[0] == 'area' and ele[1] == 'center') else ('area', 'centre'), constraints))
found = []
for i, record in enumerate(self.dbs[domain]):
constraints_iterator = zip(constraints, [False] * len(constraints))
soft_contraints_iterator = zip(soft_contraints, [True] * len(soft_contraints))
for (key, val), fuzzy_match in chain(constraints_iterator, soft_contraints_iterator):
if val == "" or val == "dont care" or val == 'not mentioned' or val == "don't care" or val == "dontcare" or val == "do n't care":
pass
else:
try:
record_keys = [k.lower() for k in record]
if key.lower() not in record_keys:
continue
if key == 'leaveAt':
val1 = int(val.split(':')[0]) * 100 + int(val.split(':')[1])
val2 = int(record['leaveAt'].split(':')[0]) * 100 + int(record['leaveAt'].split(':')[1])
if val1 > val2:
break
elif key == 'arriveBy':
val1 = int(val.split(':')[0]) * 100 + int(val.split(':')[1])
val2 = int(record['arriveBy'].split(':')[0]) * 100 + int(record['arriveBy'].split(':')[1])
if val1 < val2:
break
# elif ignore_open and key in ['destination', 'departure', 'name']:
elif ignore_open and key in ['destination', 'departure']:
continue
elif record[key].strip() == '?':
# '?' matches any constraint
continue
else:
if not fuzzy_match:
if val.strip().lower() != record[key].strip().lower():
break
else:
if fuzz.partial_ratio(val.strip().lower(), record[key].strip().lower()) < fuzzy_match_ratio:
break
except:
continue
else:
res = deepcopy(record)
res['Ref'] = '{0:08d}'.format(i)
found.append(res)
return found
if __name__ == '__main__':
db = Database()
print(db.query("train", [['departure', 'cambridge'], ['destination','peterborough'], ['day', 'tuesday'], ['arriveBy', '11:15']]))

12
src/service/dialog_policy.py
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@ -4,7 +4,7 @@ import json
from copy import deepcopy
from convlab.policy.policy import Policy
from convlab.util.restaurant.dbquery import Database
from dbquery import Database
class SimpleRulePolicy(Policy):
def __init__(self):
@ -23,9 +23,9 @@ class SimpleRulePolicy(Policy):
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 ['pizza', 'size', 'drink']):
if any(True for slots in user_action.values() for (slot, _) in slots if slot in ['book stay', 'book day', 'book people']):
if self.results:
system_action = {('Ordering', 'Order'): [["Ref", self.results[0].get('Ref', 'N/A')]]}
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
@ -53,7 +53,7 @@ class SimpleRulePolicy(Policy):
system_action[(domain, 'Inform')].append(['Choice', str(len(self.results))])
choice = self.results[0]
if domain in ["pizza", "drink"]:
if domain in ["hotel", "attraction", "police", "restaurant"]:
system_action[(domain, 'Recommend')].append(['Name', choice['name']])
if domain in ["size"]:
system_action[(domain, 'Recommend')].append(['Size', choice['size']])
dialogPolicy = SimpleRulePolicy()