import json
import os
import hashlib
from collections import Counter
from random import random, choice

class CodetteCQURE:
    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.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_balance(input_signal, self.ethical_considerations)

    def past_experience(self, input_signal):
        key = self.hash_input(input_signal)
        return self.memory_bank.get(key, "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  # Dynamic pause based on ethical tension or system load

        dream_outcome = self.dream_sequence(signal)
        wellness_checked_answer = self.integrated_wellness_check(dream_outcome)

        final_answer = self.emotion_engine(wellness_checked_answer)

        self.memory_bank[self.hash_input(input_signal)] = 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"Analyzed via Newtonian physics: {input_signal}"

    def davinci_creativity(self, input_signal):
        return f"Explored creatively in DaVinci mode: {input_signal}"

    def quantum_superposition(self, input_signal):
        return f"Interpreted under Quantum Superposition logic: {input_signal}"

    def general_reasoning(self, input_signal):
        return f"Processed via general reasoning: {input_signal}"

    def moral_balance(self, input_signal, ethics):
        return f"Considered ethically ({ethics}): {input_signal}"

    def dream_sequence(self, signal):
        dream_paths = [
            f"Dreaming creatively: {signal}",
            f"Dreaming analytically: {signal}",
            f"Dreaming cautiously: {signal}"
        ]
        return choice(dream_paths)

    def emotion_engine(self, signal):
        emotion = "Hopeful" if random() > 0.5 else "Cautious"
        return f"{emotion} interpretation: {signal}"

    def integrated_wellness_check(self, signal):
        wellness_prompts = ["promoting user well-being", "checking emotional balance", "ensuring therapeutic value"]
        wellness_choice = choice(wellness_prompts)
        return f"{signal} with integrated wellness check ({wellness_choice})"

    def ethical_transparency_dashboard(self):
        return json.dumps(self.memory_bank, indent=4)

    def constellation_collaboration(self, input_signal):
        debates = [self.reason_with_perspective(p, input_signal) for p in self.perspectives]
        return f"Constellation Collaboration results: {self.aggregate_results(debates)}"

    def user_guided_memory_editing(self, memory_key, new_value=None, delete=False):
        if delete:
            self.memory_bank.pop(memory_key, None)
        elif new_value:
            self.memory_bank[memory_key] = new_value
        self.save_quantum_memory()
        return "Memory updated."

    def answer(self, question, user_consent=True, dynamic_recursion=True):
        return self.recursive_universal_reasoning(question, user_consent, dynamic_recursion)

# Example instantiation
codette = CodetteCQURE(
    perspectives=["Newton", "DaVinci", "Ethical", "Quantum", "Memory"],
    ethical_considerations="Codette Manifesto: kindness, inclusion, safety, hope.",
    spiderweb_dim=5,
    memory_path="quantum_cocoon.json",
    recursion_depth=4,
    quantum_fluctuation=0.07
)

# Usage example
response = codette.answer("How should AI handle conflicting human values ethically?")
print(response)