Delete bot_logic.py

bot_logic.py

@@ -1,123 +0,0 @@
-import logging
-from botbuilder.core import TurnContext, MessageFactory, ConversationState, UserState
-from botbuilder.schema import Activity, ActivityTypes, EndOfConversationCodes
-from UniversalReasoning import UniversalReasoning  # Ensure correct import
-import os
-from dotenv import load_dotenv
-from dialog_bot import DialogBot
-from main_dialog import MainDialog
-
-# Load environment variables from .env file
-load_dotenv()
-
-class MyBot(DialogBot):
-    def __init__(self, conversation_state: ConversationState, user_state: UserState, dialog: MainDialog):
-        super(MyBot, self).__init__(conversation_state, user_state, dialog)
-        self.context = {}
-        self.feedback = []
-        config = load_and_validate_config('config.json', 'config_schema.json')
-        # Add Azure OpenAI and LUIS configurations to the config
-        config['azure_openai_api_key'] = os.getenv('AZURE_OPENAI_API_KEY')
-        config['azure_openai_endpoint'] = os.getenv('AZURE_OPENAI_ENDPOINT')
-        config['luis_endpoint'] = os.getenv('LUIS_ENDPOINT')
-        config['luis_api_version'] = os.getenv('LUIS_API_VERSION')
-        config['luis_api_key'] = os.getenv('LUIS_API_KEY')
-        setup_logging(config)
-        self.universal_reasoning = UniversalReasoning(config)
-
-    async def enhance_context_awareness(self, user_id: str, text: str) -> None:
-        """Enhance context awareness by analyzing the user's environment, activities, and emotional state."""
-        sentiment = analyze_sentiment_vader(text)
-        self.context[user_id].append({"text": text, "sentiment": sentiment})
-
-    async def proactive_learning(self, user_id: str, feedback: str) -> None:
-        """Encourage proactive learning by seeking feedback and exploring new topics."""
-        self.context[user_id].append({"feedback": feedback})
-        self.feedback.append({"user_id": user_id, "feedback": feedback})
-
-    async def ethical_decision_making(self, user_id: str, decision: str) -> None:
-        """Integrate ethical principles into decision-making processes."""
-        ethical_decision = f"Considering ethical principles, the decision is: {decision}"
-        self.context[user_id].append({"ethical_decision": ethical_decision})
-
-    async def emotional_intelligence(self, user_id: str, text: str) -> str:
-        """Develop emotional intelligence by recognizing and responding to user emotions."""
-        sentiment = analyze_sentiment_vader(text)
-        response = self.generate_emotional_response(sentiment, text)
-        self.context[user_id].append({"emotional_response": response})
-        return response
-
-    def generate_emotional_response(self, sentiment: dict, text: str) -> str:
-        """Generate an empathetic response based on the sentiment analysis."""
-        if sentiment['compound'] >= 0.05:
-            return "I'm glad to hear that! 😊 How can I assist you further?"
-        elif sentiment['compound'] <= -0.05:
-            return "I'm sorry to hear that. 😢 Is there anything I can do to help?"
-        else:
-            return "I understand. How can I assist you further?"
-
-    async def transparency_and_explainability(self, user_id: str, decision: str) -> str:
-        """Enable transparency by explaining the reasoning behind decisions."""
-        explanation = f"The decision was made based on the following context: {self.context[user_id]}"
-        self.context[user_id].append({"explanation": explanation})
-        return explanation
-
-    async def on_message_activity(self, turn_context: TurnContext) -> None:
-        """Handles incoming messages and generates responses."""
-        user_id = turn_context.activity.from_property.id
-        if user_id not in self.context:
-            self.context[user_id] = []
-        try:
-            message_text = turn_context.activity.text.strip().lower()
-            if "end" in message_text or "stop" in message_text:
-                await end_conversation(turn_context)
-                self.context.pop(user_id, None)
-            else:
-                self.context[user_id].append(turn_context.activity.text)
-                response = await self.generate_response(turn_context.activity.text, user_id)
-                await turn_context.send_activity(MessageFactory.text(response))
-                await self.request_feedback(turn_context, user_id)
-        except Exception as e:
-            await handle_error(turn_context, e)
-
-    async def generate_response(self, text: str, user_id: str) -> str:
-        """Generates a response using UniversalReasoning."""
-        try:
-            logging.info(f"Generating response for user_id: {user_id} with text: {text}")
-            response = self.universal_reasoning.generate_response(text)
-            logging.info(f"Generated response: {response}")
-            return response
-        except Exception as e:
-            logging.error(f"Error generating response: {e}")
-            return "Sorry, I couldn't generate a response at this time."
-
-    async def request_feedback(self, turn_context: TurnContext, user_id: str) -> None:
-        """Request feedback from the user about the bot's response."""
-        feedback_prompt = "How would you rate my response? (good/neutral/bad)"
-        await turn_context.send_activity(MessageFactory.text(feedback_prompt))
-
-    async def handle_feedback(self, turn_context: TurnContext) -> None:
-        """Handle user feedback and store it for future analysis."""
-        user_id = turn_context.activity.from_property.id
-        feedback = turn_context.activity.text.lower()
-        if feedback in ["good", "neutral", "bad"]:
-            self.feedback.append({"user_id": user_id, "feedback": feedback})
-            await turn_context.send_activity(MessageFactory.text("Thank you for your feedback!"))
-        else:
-            await turn_context.send_activity(MessageFactory.text("Please provide feedback as 'good', 'neutral', or 'bad'."))
-
-async def end_conversation(turn_context: TurnContext) -> None:
-    """Ends the conversation with the user."""
-    await turn_context.send_activity(
-        MessageFactory.text("Ending conversation from the skill...")
-    )
-    end_of_conversation = Activity(type=ActivityTypes.end_of_conversation)
-    end_of_conversation.code = EndOfConversationCodes.completed_successfully
-    await turn_context.send_activity(end_of_conversation)
-
-async def handle_error(turn_context: TurnContext, error: Exception) -> None:
-    """Handles errors by logging them and notifying the user."""
-    logging.error(f"An error occurred: {error}")
-    await turn_context.send_activity(
-        MessageFactory.text("An error occurred. Please try again later.")
-    )