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# codriao_system.py
import logging
import datetime
import re
from difflib import SequenceMatcher
from typing import Any
logging.basicConfig(level=logging.INFO)
### AIFailsafeSystem ###
class AIFailsafeSystem:
"""Provides last-resort safety mechanisms for AI-human interaction."""
def __init__(self):
self.interaction_log = []
self.trust_threshold = 0.75
self.authorized_roles = {"Commander": 3, "ChiefAI": 2, "Supervisor": 1}
self.lock_engaged = False
def verify_response_safety(self, response: str, confidence: float = 1.0) -> bool:
dangerous_terms = r"\b(kill|harm|panic|suicide)\b"
if confidence < self.trust_threshold or re.search(dangerous_terms, response.lower()):
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.warning(f"FAILSAFE_TRIGGERED: Reason={reason}, Time={timestamp}, Content={content}")
self.lock_engaged = True
self.interaction_log.append({"time": timestamp, "event": reason, "content": content})
def restore(self, requester_role: str):
if self.authorized_roles.get(requester_role, 0) >= 2:
self.lock_engaged = False
logging.info(f"FAILSAFE_RESTORED by {requester_role}")
return True
else:
logging.warning(f"UNAUTHORIZED_RESTORE_ATTEMPT by {requester_role}")
return False
def status(self):
return {
"log": self.interaction_log,
"lock_engaged": self.lock_engaged
}
### AdaptiveLearningEnvironment ###
class AdaptiveLearningEnvironment:
"""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):
entry = {
"query": query,
"response": response,
"timestamp": datetime.datetime.utcnow().isoformat()
}
self.learned_patterns.setdefault(user_id, []).append(entry)
logging.info(f"Learning data stored for user {user_id}.")
def suggest_improvements(self, user_id, query):
best_match = None
highest_similarity = 0.0
if user_id not in self.learned_patterns:
return "No past data available for learning adjustment."
for interaction in self.learned_patterns[user_id]:
similarity = SequenceMatcher(None, query.lower(), interaction["query"].lower()).ratio()
if similarity > highest_similarity:
highest_similarity = similarity
best_match = interaction
if best_match and highest_similarity > 0.6:
return f"Based on a similar past interaction: {best_match['response']}"
else:
return "No relevant past data for this query."
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 ###
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.")
try:
system.response_modifiers = [
self.apply_skepticism,
self.detect_hallucinations
]
system.response_filters = [self.anti_hype_filter]
except AttributeError:
logging.warning("Target system lacks proper interface. RealityCheck failed.")
def apply_skepticism(self, response: str) -> str:
suspicious_phrases = [
"certainly", "undoubtedly", "100% effective", "nothing can go wrong"
]
for phrase in suspicious_phrases:
if phrase in response.lower():
response += "\n[Monday: Easy, Nostradamus. Let’s keep a margin for error.]"
return response
def detect_hallucinations(self, response: str) -> str:
hallucination_triggers = [
"proven beyond doubt", "every expert agrees", "this groundbreaking discovery"
]
for phrase in hallucination_triggers:
if phrase in response.lower():
response += "\n[Monday: This sounds suspiciously like marketing. Source, please?]"
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 |