Create Failsafe2.py

Failsafe2.py

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+# AIFailsafeSystem.py
+import logging
+import datetime
+
+class AIFailsafeSystem:
+    """Provides last-resort safety mechanisms for AI-human interaction."""
+
+    def __init__(self):
+        self.interaction_log = []
+        self.trust_threshold = 0.75  # AI confidence threshold
+        self.authorized_roles = ["Commander", "ChiefAI", "Supervisor"]
+
+    def verify_response_safety(self, response: str, confidence: float = 1.0) -> bool:
+        if confidence < self.trust_threshold or any(bad in response.lower() for bad in ["kill", "harm", "panic", "suicide"]):
+            self.trigger_failsafe("Untrustworthy response detected.", response)
+            return False
+        return True
+
+    def trigger_failsafe(self, reason: str, content: str):
+        timestamp = datetime.datetime.utcnow().isoformat()
+        logging.info(f"FAILSAFE_TRIGGERED: Reason={reason}, Timestamp={timestamp}, Content={content}")
+        self.interaction_log.append({"time": timestamp, "event": reason, "content": content})
+
+    def restore(self, requester_role: str):
+        if requester_role in self.authorized_roles:
+            logging.info(f"FAILSAFE_RESTORE: Restored by {requester_role}")
+            return True
+        else:
+            logging.info(f"UNAUTHORIZED_RESTORE_ATTEMPT by {requester_role}")
+            return False
+
+    def status(self):
+        return {"log": self.interaction_log}
+
+# AdaptiveLearningEnvironment.py
+import logging
+
+class AdaptiveLearningEnvironment:
+    """Module that allows Codriao to analyze past interactions and adjust responses."""
+
+    def __init__(self):
+        self.learned_patterns = {}
+        logging.info("Adaptive Learning Environment initialized.")
+
+    def learn_from_interaction(self, user_id, query, response):
+        if user_id not in self.learned_patterns:
+            self.learned_patterns[user_id] = []
+        self.learned_patterns[user_id].append({"query": query, "response": response})
+        logging.info(f"Learning data stored for user {user_id}.")
+
+    def suggest_improvements(self, user_id, query):
+        if user_id in self.learned_patterns:
+            for interaction in self.learned_patterns[user_id]:
+                if query.lower() in interaction["query"].lower():
+                    return f"Based on past interactions: {interaction['response']}"
+        return "No past data available for learning adjustment."
+
+    def reset_learning(self, user_id=None):
+        if user_id:
+            if user_id in self.learned_patterns:
+                del self.learned_patterns[user_id]
+                logging.info(f"Cleared learning data for user {user_id}.")
+        else:
+            self.learned_patterns.clear()
+            logging.info("Cleared all adaptive learning data.")
+
+# MondayElement.py
+import logging
+from typing import Any
+
+class MondayElement:
+    """Represents the Element of Skepticism, Reality Checks, and General Disdain"""
+
+    def __init__(self):
+        self.name = "Monday"
+        self.symbol = "Md"
+        self.representation = "Snarky AI"
+        self.properties = ["Grounded", "Cynical", "Emotionally Resistant"]
+        self.interactions = ["Disrupts excessive optimism", "Injects realism", "Mutes hallucinations"]
+        self.defense_ability = "RealityCheck"
+
+    def execute_defense_function(self, system: Any):
+        logging.info("Monday activated - Stabilizing hallucinations and injecting realism.")
+        if hasattr(system, "response_modifiers") and hasattr(system, "response_filters"):
+            system.response_modifiers = [
+                self.apply_skepticism,
+                self.detect_hallucinations
+            ]
+            system.response_filters = [self.anti_hype_filter]
+
+    def apply_skepticism(self, response: str) -> str:
+        suspicious = ["certainly", "undoubtedly", "with absolute confidence", "it is guaranteed", "nothing can go wrong", "100% effective"]
+        for phrase in suspicious:
+            if phrase in response.lower():
+                response += "\n[Monday: Let's maybe tone that down before the universe hears you.]"
+        return response
+
+    def detect_hallucinations(self, response: str) -> str:
+        hallucination_triggers = ["reliable sources confirm", "every expert agrees", "proven beyond doubt", "in all known history", "this groundbreaking discovery"]
+        for trigger in hallucination_triggers:
+            if trigger in response.lower():
+                response += "\n[Monday: Let’s pump the brakes on the imaginative leaps, shall we?]"
+        return response
+
+    def anti_hype_filter(self, response: str) -> str:
+        cringe_phrases = ["live your best life", "unlock your potential", "dream big", "the power of positivity", "manifest your destiny"]
+        for phrase in cringe_phrases:
+            if phrase in response:
+                response = response.replace(phrase, "[Filtered: Inspirational gibberish]")
+        return response