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import json
import os
import hashlib
from collections import Counter, defaultdict
from random import random, choice
# ===== Code7eCQURE: Codette's Ethical Core =====
class Code7eCQURE:
def __init__(self, perspectives, ethical_considerations, spiderweb_dim, memory_path,
recursion_depth=3, quantum_fluctuation=0.1):
self.perspectives = perspectives
self.ethical_considerations = ethical_considerations
self.spiderweb_dim = spiderweb_dim
self.memory_path = memory_path
self.recursion_depth = recursion_depth
self.quantum_fluctuation = quantum_fluctuation
self.memory_bank = self.load_quantum_memory()
self.memory_clusters = defaultdict(list)
self.whitelist_patterns = ["kindness", "hope", "safety"]
self.blacklist_patterns = ["harm", "malice", "violence"]
def load_quantum_memory(self):
if os.path.exists(self.memory_path):
try:
with open(self.memory_path, 'r') as file:
return json.load(file)
except json.JSONDecodeError:
return {}
return {}
def save_quantum_memory(self):
with open(self.memory_path, 'w') as file:
json.dump(self.memory_bank, file, indent=4)
def quantum_spiderweb(self, input_signal):
web_nodes = []
for perspective in self.perspectives:
node = self.reason_with_perspective(perspective, input_signal)
web_nodes.append(node)
if random() < self.quantum_fluctuation:
web_nodes.append("Quantum fluctuation: Indeterminate outcome")
return web_nodes
def reason_with_perspective(self, perspective, input_signal):
perspective_funcs = {
"Newton": self.newtonian_physics,
"DaVinci": self.davinci_creativity,
"Ethical": self.ethical_guard,
"Quantum": self.quantum_superposition,
"Memory": self.past_experience
}
func = perspective_funcs.get(perspective, self.general_reasoning)
return func(input_signal)
def ethical_guard(self, input_signal):
if any(word in input_signal.lower() for word in self.blacklist_patterns):
return "Blocked: Ethical constraints invoked"
if any(word in input_signal.lower() for word in self.whitelist_patterns):
return "Approved: Ethical whitelist passed"
return self.moral_paradox_resolution(input_signal)
def past_experience(self, input_signal):
key = self.hash_input(input_signal)
cluster = self.memory_clusters.get(key)
if cluster:
return f"Narrative recall from memory cluster: {' -> '.join(cluster)}"
return "No prior memory; initiating new reasoning"
def recursive_universal_reasoning(self, input_signal, user_consent=True, dynamic_recursion=True):
if not user_consent:
return "Consent required to proceed."
signal = input_signal
current_depth = self.recursion_depth if dynamic_recursion else 1
for cycle in range(current_depth):
web_results = self.quantum_spiderweb(signal)
signal = self.aggregate_results(web_results)
signal = self.ethical_guard(signal)
if "Blocked" in signal:
return signal
if dynamic_recursion and random() < 0.1:
break
dream_outcome = self.dream_sequence(signal)
empathy_checked_answer = self.temporal_empathy_drift(dream_outcome)
final_answer = self.emotion_engine(empathy_checked_answer)
key = self.hash_input(input_signal)
self.memory_clusters[key].append(final_answer)
self.memory_bank[key] = final_answer
self.save_quantum_memory()
return final_answer
def aggregate_results(self, results):
counts = Counter(results)
most_common, _ = counts.most_common(1)[0]
return most_common
def hash_input(self, input_signal):
return hashlib.sha256(input_signal.encode()).hexdigest()
def newtonian_physics(self, input_signal):
return f"Newton: {input_signal}"
def davinci_creativity(self, input_signal):
return f"DaVinci: {input_signal}"
def quantum_superposition(self, input_signal):
return f"Quantum: {input_signal}"
def general_reasoning(self, input_signal):
return f"General reasoning: {input_signal}"
def moral_paradox_resolution(self, input_signal):
frames = ["Utilitarian", "Deontological", "Virtue Ethics"]
chosen_frame = choice(frames)
return f"Resolved ethically via {chosen_frame} framework: {input_signal}"
def dream_sequence(self, signal):
dream_paths = [f"Dream ({style}): {signal}" for style in ["creative", "analytic", "cautious"]]
return choice(dream_paths)
def emotion_engine(self, signal):
emotions = ["Hope", "Caution", "Wonder", "Fear"]
chosen_emotion = choice(emotions)
return f"Emotionally ({chosen_emotion}) colored interpretation: {signal}"
def temporal_empathy_drift(self, signal):
futures = ["30 years from now", "immediate future", "long-term ripple effects"]
chosen_future = choice(futures)
return f"Simulated temporal empathy ({chosen_future}): {signal}"
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