actions.py

actionmeh.py

class ActionAnalyzePreviousMessages(Action):
    def name(self) -> Text:
        return "action_analyze_previous_messages"

    def run(self, dispatcher, tracker: Tracker, domain: Dict[Text, Any]) -> List[EventType]:
        # Your predefined list or dictionary of keywords
        keywords = ["খতিয়ান", "পর্চা", "পর্চার", "খাজনা"]

        # Get the list of events
        events = tracker.events

        # Function to find message events
        def find_message_events(events):
            return [event for event in events if event["event"] == "user"]

        # Extracting the last two user messages
        message_events = find_message_events(events)
        previous_message = message_events[-2]["text"] if len(message_events) > 1 else ""
        previous_of_previous_message = message_events[-3]["text"] if len(message_events) > 2 else ""

        # Check for keywords in messages
        keyword_in_previous = any(keyword in previous_message for keyword in keywords)
        keyword_in_previous_of_previous = any(keyword in previous_of_previous_message for keyword in keywords)

        # Logic based on keyword findings
        if keyword_in_previous:
            # Handle scenario for keyword found in previous message
            # pass
            print("previous")
        elif keyword_in_previous_of_previous:
            # Handle scenario for keyword found in previous of previous message
            # pass
            print("previous of previous")
        else:
            # Handle scenario if no relevant keyword is found
            # pass
            print("no relevant word found")

        # Return an empty list if no events are to be triggered
        return []

You, Thu 6:01 PM
```- rule: Ask the user to rephrase whenever they send a message with low NLU confidence
  steps:
  - intent: nlu_fallback
  - action: action_analyze_previous_messages


- rule: Ask the user to rephrase whenever they send a message with low NLU confidence out of scope
  steps:
  - intent: out_of_scope
  - action: action_analyze_previous_messages```

handleactions.py

class ActionAnalyzePreviousMessages(Action):
    def name(self) -> Text:
        return "action_analyze_previous_messages"

    def run(self, dispatcher, tracker: Tracker, domain: Dict[Text, Any]) -> List[EventType]:
        # Defining keywords and their corresponding Rasa intents
        keyword_intent_mapping = {
            "নামজারি": "ApplyNamzari",
            "Namzari fee": "NamzariFee",
            # Add other keywords and their corresponding intents here
        }

        # Get the list of events
        events = tracker.events

        # Function to find message events
        def find_message_events(events):
            return [event for event in events if event["event"] == "user"]

        # Extracting the last two user messages
        message_events = find_message_events(events)
        previous_message = message_events[-2]["text"] if len(message_events) > 1 else ""
        previous_of_previous_message = message_events[-3]["text"] if len(message_events) > 2 else ""

        # Check for keywords in messages and map to corresponding intent
        for keyword, intent in keyword_intent_mapping.items():
            if keyword in previous_message or keyword in previous_of_previous_message:
                # Dispatch a custom action or message based on the identified intent
                dispatcher.utter_message(text=f"Found keyword related to {intent}. Redirecting to the appropriate action.")
                # Here you would typically return a FollowupAction with the name of the action corresponding to the intent
                # For illustration, we'll just return an empty list
                return [FollowupAction(name=f"action_for_{intent}")]
        
        # Handle scenario if no relevant keyword is found
        dispatcher.utter_message(text="No relevant keyword found. Please rephrase or ask another question.")
        return []

from itertools import combinations
import unicodedata
from rasa_sdk import Action, Tracker
from rasa_sdk.executor import CollectingDispatcher
from rasa_sdk.events import FollowupAction

# Define the function to normalize text using NFC
def normalize_text(text):
    return unicodedata.normalize('NFC', text)

class ActionAnalyzePreviousMessages(Action):
    def name(self) -> Text:
        return "action_analyze_previous_messages"

    def run(self, dispatcher: CollectingDispatcher, tracker: Tracker, domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
        print("Starting to analyze previous messages...")

        # Original keywords intent mapping with normalization applied
        keywords_intent_mapping = {
            (normalize_text('নামজারি'), normalize_text('সময়')): "NamzariTime",
            (normalize_text('নামজারির'), normalize_text('সময়')): "NamzariTime",
            (normalize_text('সময়'), normalize_text('নামজারি')): "NamzariTime",
            (normalize_text('সময়'), normalize_text('নামজারির')): "NamzariTime",
        }

        messages = [event.get("text", "") for event in tracker.events if event.get("event") == "user"][-2:]
        normalized_messages = [normalize_text(msg) for msg in messages]
        print(f"Last two normalized messages: {normalized_messages}")

        combined_keywords_list = " ".join(normalized_messages).split()
        normalized_keyword_pairs = list(combinations(combined_keywords_list, 2))

        print("Generated normalized keyword pairs:")
        for pair in normalized_keyword_pairs:
            print(pair)

        found = False
        for pair in normalized_keyword_pairs:
            normalized_pair = (normalize_text(pair[0]), normalize_text(pair[1]))
            if normalized_pair in keywords_intent_mapping:
                intent = keywords_intent_mapping[normalized_pair]
                print(f"Match found for intent {intent} with normalized keywords {normalized_pair}")
                found = True
                return self.trigger_response(intent, domain, dispatcher)

        if not found:
            print("No match found for any intent based on the provided normalized keywords.")
            dispatcher.utter_message(text="Could not deduce intent from the messages. Please provide more information.")
            return []

    def trigger_response(self, intent: Text, domain: Dict[Text, Any], dispatcher: CollectingDispatcher) -> List[Dict[Text, Any]]:
        if f"utter_{intent}" in domain.get("responses", {}):
            dispatcher.utter_message(response=f"utter_{intent}")
        elif f"action_{intent}" in domain.get("actions", []):
            return [FollowupAction(name=f"action_{intent}")]
        else:
            dispatcher.utter_message(text=f"Recognized intent: {intent}, but no specific action or utterance is configured.")
        return []