Uporządkowanie katalogów

rasa_domains/banking_bbot/README.md

-Uczenie modelu:
-```
-rasa train
-```
-
-Uruchamianie:
-
-w jednym terminalu:
-```
-rasa run actions
-```
-w drugim terminalu: 
-```
-export MAX_NUMBER_OF_PREDICTIONS=30
-rasa shell
-```

rasa_domains/banking_bbot/actions/actions.py

-from typing import Any, Text, Dict, List, Union
-
-import random
-
-from rasa_sdk import Action, Tracker
-from rasa_sdk.events import SlotSet
-from rasa_sdk.executor import CollectingDispatcher
-from rasa_sdk.forms import FormValidationAction
-
-
-def is_male_pesel(pesel: str) -> bool:
-    if len(pesel) < 2:
-        return False
-    else:
-        x = pesel[len(pesel)-2]
-        if x == '1' or x == '3' or x == '5' or x == '7' or x == '9':
-            return True
-        else:
-            return False
-
-def is_female_pesel(pesel: str) -> bool:
-    if len(pesel) < 2:
-        return False
-    else:
-        x = pesel[len(pesel)-2]
-        if x == '0' or x == '2' or x == '4' or x == '6' or x == '8':
-            return True
-        else:
-            return False
-
-class ActionFun(Action):
-
-    def name(self) -> Text:
-        return "action_Fun"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return []
-
-
-class ActionGetSexPeselClientSex(Action):
-
-    def name(self) -> Text:
-        return "action_get_sex_pesel_client_sex"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        if is_male_pesel(str(tracker.get_slot("pesel"))):
-            return [SlotSet("client_sex", "male")]
-        else:
-            if is_female_pesel(str(tracker.get_slot("pesel"))):
-                return [SlotSet("client_sex", "female")]
-            else:
-                return []
-
-
-class ActionIsFeeCollectedCorrectlyIsFeeCollectedCorrectly(Action):
-
-    def name(self) -> Text:
-        return "action_is_fee_collected_correctly_is_fee_collected_correctly"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        if 0.5 >= random.uniform(0, 1):
-            return [SlotSet("is_fee_collected_correctly", "true")]
-        else:
-            return [SlotSet("is_fee_collected_correctly", "false")]
-
-
-class ActionIsIdentificationSuccesfullIssue(Action):
-
-    def name(self) -> Text:
-        return "action_is_identification_succesfull_issue"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        if 0.857 >= random.uniform(0, 1):
-            return []
-        else:
-            return [SlotSet("issue", "verification_failure")]
-
-
-class ActionIsPersonalIdValidIssue(Action):
-
-    def name(self) -> Text:
-        return "action_is_personal_id_valid_issue"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        if 0.833 >= random.uniform(0, 1):
-            return []
-        else:
-            return [SlotSet("issue", "expired_identity_document")]
-
-
-class ActionSetExitNull(Action):
-
-    def name(self) -> Text:
-        return "action_set_exit-null"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("exit", None)]
-
-
-class ActionSetStateAnswerToQuestionAboutBlockedAccount(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_blocked_account"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_blocked_account")]
-
-
-class ActionSetStateAnswerToQuestionAboutFactors(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_factors"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_factors")]
-
-
-class ActionSetStateAnswerToQuestionAboutFactors2(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_factors2"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_factors2")]
-
-
-class ActionSetStateAnswerToQuestionAboutIssue(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_issue"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_issue")]
-
-
-class ActionSetStateAnswerToQuestionAboutMessage(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_message"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_message")]
-
-
-class ActionSetStateAnswerToQuestionAboutSpecifyingIssue(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-answer_to_question_about_specifying_issue"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "answer_to_question_about_specifying_issue")]
-
-
-class ActionSetStateFinishWaiting(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-finish_waiting"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "finish_waiting")]
-
-
-class ActionSetStateInitGoodbye(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-init_goodbye"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", "init_goodbye")]
-
-
-class ActionSetStateNull(Action):
-
-    def name(self) -> Text:
-        return "action_set_state-null"
-
-    def run(self, dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        return [SlotSet("state", None)]

rasa_domains/banking_bbot/config.yml

-recipe: default.v1
-language: pl
-pipeline:
-- name: WhitespaceTokenizer
-- name: RegexFeaturizer
-- name: LexicalSyntacticFeaturizer
-- name: CountVectorsFeaturizer
-- name: CountVectorsFeaturizer
-  analyzer: char_wb
-  min_ngram: 1
-  max_ngram: 4
-- name: DIETClassifier
-  epochs: 100
-  constrain_similarities: true
-- name: EntitySynonymMapper
-- name: ResponseSelector
-  epochs: 100
-  constrain_similarities: true
-- name: FallbackClassifier
-  threshold: 0.3
-  ambiguity_threshold: 0.1
-policies:
-- name: RulePolicy

rasa_domains/banking_bbot/data/stories.yml

-version: "3.0"
-stories:

rasa_domains/banking_bot/actions/actions.py

-# This files contains your custom actions which can be used to run
-# custom Python code.
-#
-# See this guide on how to implement these action:
-# https://rasa.com/docs/rasa/custom-actions
-
-
-# This is a simple example for a custom action which utters "Hello World!"
-
 from typing import Any, Text, Dict, List, Union
 
+import random
+
 from rasa_sdk import Action, Tracker
 from rasa_sdk.events import SlotSet
 from rasa_sdk.executor import CollectingDispatcher
 from rasa_sdk.forms import FormValidationAction
 
 
-PESEL_CONTROL_WEIGHTS = [1, 3, 7, 9, 1, 3, 7, 9, 1, 3]
-
-def calculate_control_digit(value: str) -> int:
-    return 10 - (sum([int(value[it]) * PESEL_CONTROL_WEIGHTS[it] for it in range(10)]) % 10)
-
-
-def check_pesel(value: str) -> bool:
-    if len(value) != 11:
+def is_male_pesel(pesel: str) -> bool:
+    if len(pesel) < 2:
         return False
-    elif not value.isdigit():
+    else:
+        x = pesel[len(pesel)-2]
+        if x == '1' or x == '3' or x == '5' or x == '7' or x == '9':
+            return True
+        else:
+            return False
+
+def is_female_pesel(pesel: str) -> bool:
+    if len(pesel) < 2:
         return False
     else:
-#Poniższe sprawdzenie jest wyłączone na czas testowania systemu, aby nie trzeba było podawać prawdziwych numerów PESEL
-#        return calculate_control_digit(value) == int(value[10])
+        x = pesel[len(pesel)-2]
+        if x == '0' or x == '2' or x == '4' or x == '6' or x == '8':
             return True
+        else:
+            return False
+
+class ActionFun(Action):
+
+    def name(self) -> Text:
+        return "action_Fun"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return []
+
+
+class ActionGetSexPeselClientSex(Action):
+
+    def name(self) -> Text:
+        return "action_get_sex_pesel_client_sex"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        if is_male_pesel(str(tracker.get_slot("pesel"))):
+            return [SlotSet("client_sex", "male")]
+        else:
+            if is_female_pesel(str(tracker.get_slot("pesel"))):
+                return [SlotSet("client_sex", "female")]
+            else:
+                return []
 
-def get_sex(pesel: str) -> str:
-    return 'female' if int(pesel[9]) % 2 == 0 else 'male'
 
+class ActionIsFeeCollectedCorrectlyIsFeeCollectedCorrectly(Action):
+
+    def name(self) -> Text:
+        return "action_is_fee_collected_correctly_is_fee_collected_correctly"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        if 0.5 >= random.uniform(0, 1):
+            return [SlotSet("is_fee_collected_correctly", "true")]
+        else:
+            return [SlotSet("is_fee_collected_correctly", "false")]
 
-class ValidateIdentityForm(FormValidationAction):
+
+class ActionIsIdentificationSuccesfullIssue(Action):
 
     def name(self) -> Text:
-        return "validate_identity_form"
+        return "action_is_identification_succesfull_issue"
 
-    def validate_client_pesel(
-        self,
-        pesel_value: Text,
-        dispatcher: CollectingDispatcher,
+    def run(self, dispatcher: CollectingDispatcher,
             tracker: Tracker,
-        domain: Dict[Text, Any],
-    ) -> Dict[Text, Any]:
-        """Validate client_pesel value."""
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        if 0.857 >= random.uniform(0, 1):
+            return []
+        else:
+            return [SlotSet("issue", "verification_failure")]
+
+
+class ActionIsPersonalIdValidIssue(Action):
+
+    def name(self) -> Text:
+        return "action_is_personal_id_valid_issue"
 
-        pesel_correct = check_pesel(pesel_value)
-        if pesel_correct:
-            return {"client_pesel": pesel_value, "is_client_pesel_correct": True, "client_sex": get_sex(pesel_value)}
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        if 0.833 >= random.uniform(0, 1):
+            return []
         else:
-#            dispatcher.utter_message(response="utter_wrong_client_pesel")
-            return {"client_pesel": None, "is_client_pesel_correct": False}
-        
-#    def run(self, dispatcher: CollectingDispatcher,
-#            tracker: Tracker,
-#            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-#        pesel_value = tracker.get_slot("client_pesel")
-#        pesel_correct = check_pesel(pesel_value)
-#        if pesel_correct:
-#            return [SlotSet("client_pesel_correct", True), SlotSet("client_sex", get_sex(pesel_value))]
-#        else:
-#            return [SlotSet("client_pesel_correct", False)]
+            return [SlotSet("issue", "expired_identity_document")]
+
+
+class ActionSetExitNull(Action):
+
+    def name(self) -> Text:
+        return "action_set_exit-null"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("exit", None)]
+
+
+class ActionSetStateAnswerToQuestionAboutBlockedAccount(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_blocked_account"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_blocked_account")]
+
+
+class ActionSetStateAnswerToQuestionAboutFactors(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_factors"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_factors")]
+
+
+class ActionSetStateAnswerToQuestionAboutFactors2(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_factors2"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_factors2")]
+
+
+class ActionSetStateAnswerToQuestionAboutIssue(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_issue"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_issue")]
+
+
+class ActionSetStateAnswerToQuestionAboutMessage(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_message"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_message")]
+
+
+class ActionSetStateAnswerToQuestionAboutSpecifyingIssue(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-answer_to_question_about_specifying_issue"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "answer_to_question_about_specifying_issue")]
+
+
+class ActionSetStateFinishWaiting(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-finish_waiting"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "finish_waiting")]
+
+
+class ActionSetStateInitGoodbye(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-init_goodbye"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", "init_goodbye")]
+
+
+class ActionSetStateNull(Action):
+
+    def name(self) -> Text:
+        return "action_set_state-null"
+
+    def run(self, dispatcher: CollectingDispatcher,
+            tracker: Tracker,
+            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+        return [SlotSet("state", None)]

rasa_domains/banking_bot/config.yml

-# The config recipe.
-# https://rasa.com/docs/rasa/model-configuration/
 recipe: default.v1
-
-# Configuration for Rasa NLU.
-# https://rasa.com/docs/rasa/nlu/components/
 language: pl
-
 pipeline:
-  # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
-  # If you'd like to customize it, uncomment and adjust the pipeline.
-  # See https://rasa.com/docs/rasa/tuning-your-model for more information.
 - name: WhitespaceTokenizer
 - name: RegexFeaturizer
 - name: LexicalSyntacticFeaturizer
 - name: CountVectorsFeaturizer
-#   - name: custom_components.herbert_featurizer.HerbertFeaturizer
-#  - name: custom_components.remote_component.RemoteComponent
-#    component_url: http://localhost:5000/process_component
-#    component_auth_token: test1234
 - name: CountVectorsFeaturizer
   analyzer: char_wb
   min_ngram: 1
@@ -32,19 +19,5 @@ pipeline:
 - name: FallbackClassifier
   threshold: 0.3
   ambiguity_threshold: 0.1
-
-# Configuration for Rasa Core.
-# https://rasa.com/docs/rasa/core/policies/
 policies:
-# # No configuration for policies was provided. The following default policies were used to train your model.
-# # If you'd like to customize them, uncomment and adjust the policies.
-# # See https://rasa.com/docs/rasa/policies for more information.
-#   - name: MemoizationPolicy
-#   - name: RulePolicy
-#   - name: UnexpecTEDIntentPolicy
-#     max_history: 5
-#     epochs: 100
-#   - name: TEDPolicy
-#     max_history: 5
-#     epochs: 100
-#     constrain_similarities: true
+- name: RulePolicy

rasa_domains/banking_bot/data/stories.yml

 version: "3.0"
-
 stories:
-
-#- story: simple_path
-#  steps:
-#  - intent: greet
-#  - action: utter_greet
-
-#  - story: stop form + continue
-#    steps:
-#      - intent: request_restaurant
-#      - action: restaurant_form
-#      - active_loop: restaurant_form
-#      - intent: stop
-#      - action: utter_ask_continue
-#      - intent: affirm
-#      - action: restaurant_form
-#      - active_loop: null
-#      - action: utter_submit
-#      - action: utter_slot_values
-#
-#  - story: stop form + stop
-#    steps:
-#      - intent: request_restaurant
-#      - action: restaurant_form
-#      - active_loop: restaurant_form
-#      - intent: stop
-#      - action: utter_ask_continue
-#      - intent: deny
-#      - action: action_deactivate_loop
-#      - active_loop: null

rasa_domains/banking_bot_old/actions/actions.py

+# This files contains your custom actions which can be used to run
+# custom Python code.
+#
+# See this guide on how to implement these action:
+# https://rasa.com/docs/rasa/custom-actions
+
+
+# This is a simple example for a custom action which utters "Hello World!"
+
+from typing import Any, Text, Dict, List, Union
+
+from rasa_sdk import Action, Tracker
+from rasa_sdk.events import SlotSet
+from rasa_sdk.executor import CollectingDispatcher
+from rasa_sdk.forms import FormValidationAction
+
+
+PESEL_CONTROL_WEIGHTS = [1, 3, 7, 9, 1, 3, 7, 9, 1, 3]
+
+def calculate_control_digit(value: str) -> int:
+    return 10 - (sum([int(value[it]) * PESEL_CONTROL_WEIGHTS[it] for it in range(10)]) % 10)
+
+
+def check_pesel(value: str) -> bool:
+    if len(value) != 11:
+        return False
+    elif not value.isdigit():
+        return False
+    else:
+#Poniższe sprawdzenie jest wyłączone na czas testowania systemu, aby nie trzeba było podawać prawdziwych numerów PESEL
+#        return calculate_control_digit(value) == int(value[10])
+       return True
+
+def get_sex(pesel: str) -> str:
+    return 'female' if int(pesel[9]) % 2 == 0 else 'male'
+
+
+class ValidateIdentityForm(FormValidationAction):
+
+    def name(self) -> Text:
+        return "validate_identity_form"
+    
+    def validate_client_pesel(
+        self,
+        pesel_value: Text,
+        dispatcher: CollectingDispatcher,
+        tracker: Tracker,
+        domain: Dict[Text, Any],
+    ) -> Dict[Text, Any]:
+        """Validate client_pesel value."""
+
+        pesel_correct = check_pesel(pesel_value)
+        if pesel_correct:
+            return {"client_pesel": pesel_value, "is_client_pesel_correct": True, "client_sex": get_sex(pesel_value)}
+        else:
+#            dispatcher.utter_message(response="utter_wrong_client_pesel")
+            return {"client_pesel": None, "is_client_pesel_correct": False}
+        
+#    def run(self, dispatcher: CollectingDispatcher,
+#            tracker: Tracker,
+#            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+#        pesel_value = tracker.get_slot("client_pesel")
+#        pesel_correct = check_pesel(pesel_value)
+#        if pesel_correct:
+#            return [SlotSet("client_pesel_correct", True), SlotSet("client_sex", get_sex(pesel_value))]
+#        else:
+#            return [SlotSet("client_pesel_correct", False)]

rasa_domains/banking_bot_old/config.yml

+# The config recipe.
+# https://rasa.com/docs/rasa/model-configuration/
+recipe: default.v1
+
+# Configuration for Rasa NLU.
+# https://rasa.com/docs/rasa/nlu/components/
+language: pl
+
+pipeline:
+  # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
+  # If you'd like to customize it, uncomment and adjust the pipeline.
+  # See https://rasa.com/docs/rasa/tuning-your-model for more information.
+  - name: WhitespaceTokenizer
+  - name: RegexFeaturizer
+  - name: LexicalSyntacticFeaturizer
+  - name: CountVectorsFeaturizer
+#   - name: custom_components.herbert_featurizer.HerbertFeaturizer
+#  - name: custom_components.remote_component.RemoteComponent
+#    component_url: http://localhost:5000/process_component
+#    component_auth_token: test1234
+  - name: CountVectorsFeaturizer
+    analyzer: char_wb
+    min_ngram: 1
+    max_ngram: 4
+  - name: DIETClassifier
+    epochs: 100
+    constrain_similarities: true
+  - name: EntitySynonymMapper
+  - name: ResponseSelector
+    epochs: 100
+    constrain_similarities: true
+  - name: FallbackClassifier
+    threshold: 0.3
+    ambiguity_threshold: 0.1
+
+# Configuration for Rasa Core.
+# https://rasa.com/docs/rasa/core/policies/
+policies:
+# # No configuration for policies was provided. The following default policies were used to train your model.
+# # If you'd like to customize them, uncomment and adjust the policies.
+# # See https://rasa.com/docs/rasa/policies for more information.
+#   - name: MemoizationPolicy
+#   - name: RulePolicy
+#   - name: UnexpecTEDIntentPolicy
+#     max_history: 5
+#     epochs: 100
+#   - name: TEDPolicy
+#     max_history: 5
+#     epochs: 100
+#     constrain_similarities: true