Fix Dziękuję

Reviewed-on: #1

DialoguePolicy.py

@@ -1,12 +1,20 @@
 from collections import defaultdict
 import json
+import random
+import string
 from copy import deepcopy
 from convlab.policy.policy import Policy
 
 db_path = './hotels_data.json'
 
 
+def generate_reference_number(length=8):
+    letters_and_digits = string.ascii_uppercase + string.digits
+    reference_number = ''.join(random.choice(letters_and_digits) for _ in range(length))
+    return reference_number
+
 class DialoguePolicy(Policy):
+    info_dict = None
     def __init__(self):
         Policy.__init__(self)
         self.db = self.load_database(db_path)
@@ -40,7 +48,8 @@ class DialoguePolicy(Policy):
         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 = {('Booking', 'Book'): [["Ref", self.results[0].get('Ref', 'N/A')]]}
+                reference_number = generate_reference_number()
+                system_action = {('Booking', 'Book'): [["Ref", reference_number]]}
 
         system_acts = [[intent, domain, slot, value] for (domain, intent), slots in system_action.items() for
                        slot, value in slots]
@@ -49,28 +58,29 @@ class DialoguePolicy(Policy):
 
     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]['info'].items() if value != '']
-        # print(f"Constraints: {constraints}")
-        self.results = deepcopy(self.query(domain.lower(), constraints))
-        # print(f"Query results: {self.results}")
+        if domain in state['belief_state']:
+            constraints = [(slot, value) for slot, value in state['belief_state'][domain]['info'].items() if value != '']
+            # print(f"Constraints: {constraints}")
+            self.results = deepcopy(self.query(domain.lower(), constraints))
+            # print(f"Query results: {self.results}")
 
-        if intent == 'request':
-            if len(self.results) == 0:
-                system_action[(domain, 'NoOffer')] = []
-            else:
-                for slot in user_action[user_act]:
-                    if slot[0] in self.results[0]:
-                        system_action[(domain, 'Inform')].append([slot[0], self.results[0].get(slot[0], 'unknown')])
+            if intent == 'request':
+                if len(self.results) == 0:
+                    system_action[(domain, 'NoOffer')] = []
+                else:
+                    for slot in user_action[user_act]:
+                        if slot[0] in self.results[0]:
+                            system_action[(domain, 'Inform')].append([slot[0], self.results[0].get(slot[0], 'unknown')])
 
-        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]
+            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"]:
-                    system_action[(domain, 'Recommend')].append(['Name', choice['name']])
-                    for slot in state['belief_state'][domain]['info']:
-                        if choice.get(slot):
-                            state['belief_state'][domain]['info'][slot] = choice[slot]
+                    if domain in ["hotel"]:
+                        system_action[(domain, 'Recommend')].append(['Name', choice['name']])
+                        for slot in state['belief_state'][domain]['info']:
+                            if choice.get(slot):
+                                state['belief_state'][domain]['info'][slot] = choice[slot]

DialogueStateTracker.py

@@ -27,11 +27,12 @@ def default_state():
         'user_action': [],
         'system_action': [],
         'terminated': False,
-        'booked': []
+        'booked': {}
     }
 
 
 class DialogueStateTracker(DST):
+    info_dict = None
     def __init__(self):
         DST.__init__(self)
         self.state = default_state()

Main.py

@@ -1,16 +1,22 @@
 from NaturalLanguageAnalyzer import NaturalLanguageAnalyzer
 from DialoguePolicy import DialoguePolicy
 from DialogueStateTracker import DialogueStateTracker
+from NaturalLanguageGeneration import NaturalLanguageGeneration
 from convlab.dialog_agent import PipelineAgent
-from MachineLearningNLG import MachineLearningNLG  # Importujemy nowy komponent NLG
+import warnings
+warnings.filterwarnings("ignore")
+
 
 if __name__ == "__main__":
-    text = "chciałbym zarezerwować drogi hotel z parkingiem 1 stycznia w Warszawie w centrum"
     nlu = NaturalLanguageAnalyzer()
     dst = DialogueStateTracker()
     policy = DialoguePolicy()
-    nlg = MachineLearningNLG()
+    nlg = NaturalLanguageGeneration()
 
     agent = PipelineAgent(nlu=nlu, dst=dst, policy=policy, nlg=nlg, name='sys')
-    response = agent.response(text)
-    print(response)
+
+    print("Witam, jestem systemem do rezerwowania pokoi hotelowych. W czym mogę Ci pomóc?")
+    while True:
+        text = input()
+        response = agent.response(text)
+        print(response)

NaturalLanguageAnalyzer.py

@@ -14,6 +14,7 @@ def translate_text(text, target_language='en'):
 
 
 class NaturalLanguageAnalyzer:
+    info_dict = None
     def predict(self, text, context=None):
         # Inicjalizacja modelu NLU
         model_name = "ConvLab/t5-small-nlu-multiwoz21"

NaturalLanguageGeneration.py

@@ -1,12 +1,28 @@
-import re
+import requests
+
+from convlab.nlg.template.multiwoz import TemplateNLG
+
+
+def translate_text(text, target_language='pl'):
+    url = 'https://translate.googleapis.com/translate_a/single?client=gtx&sl=auto&tl={}&dt=t&q={}'.format(
+        target_language, text)
+    response = requests.get(url)
+    if response.status_code == 200:
+        translated_text = response.json()[0]
+        translated_text_joined = ''.join([sentence[0] for sentence in translated_text])
+        return translated_text_joined
+    else:
+        return None
 
 class NaturalLanguageGeneration:
+    info_dict = None
+    def generate(self, system_act):
+        if len(system_act) == 0:
+            return "Nie rozumiem."
+        tnlg = TemplateNLG(is_user=False)
+        response_en = tnlg.generate(system_act)
+        return translate_text(response_en)
 
-    def nlg(self, system_act):
-        response = None
-        pattern = r'inform\(name=([^\)]+)\)'
-        matching = re.search(pattern, system_act)
-        if matching:
-            name = matching.group(1)
-            response = f"Witaj, nazywam się {name}"
-        return response
+
+    def init_session(self):
+        pass  # Dodanie pustej metody init_session