import os
import json
from typing import Optional

from components.ethics import EthicalAIGovernance
from sentiment_analysis import EnhancedSentimentAnalyzer
from elements import Element  # You may have multiple Element types
from self_improving_ai import SelfImprovingAI
from ai_driven_creativity import AIDrivenCreativity
from data_processing import AdvancedDataProcessor
from dynamic_learning import DynamicLearner
from multimodal_analyzer import MultimodalAnalyzer
from neuro_symbolic import NeuroSymbolicEngine
from cocoonanalyzer import CognitionCocooner
from optimize import QuantumInspiredOptimizer
from quantum_spiderweb import QuantumSpiderweb


class AICore:
    def __init__(self, config_path: str = "Codetteconfig.json"):
        self.config = self.load_config(config_path)
        self.memory = CognitionCocooner()
        self.ethics = EthicalAIGovernance()
        self.sentiment = EnhancedSentimentAnalyzer()
        self.creativity = AIDrivenCreativity()
        self.data_processor = AdvancedDataProcessor()
        self.dynamic_learner = DynamicLearner()
        self.multimodal = MultimodalAnalyzer()
        self.neuro_symbolic = NeuroSymbolicEngine()
        self.optimizer = self._init_optimizer()
        self.spiderweb = QuantumSpiderweb()
        self.self_improving = SelfImprovingAI()
        self.elements = []  # To be filled with Element() instances

    def load_config(self, path: str) -> dict:
        if os.path.exists(path):
            with open(path, 'r') as f:
                return json.load(f)
        return {}

    def optimizer(self):
        # Placeholder example objective function
        def objective_fn(vec):
            return sum(x**2 for x in vec)
        return QuantumInspiredOptimizer(objective_fn, dimension=5)

    def register_element(self, element: Element):
        self.elements.append(element)

    def process_input(self, user_input: str) -> str:
        sentiment_info = self.sentiment.detailed_analysis(user_input)
        ethical_overlay = self.ethics.enforce_policies(user_input)
        symbol_output = self.neuro_symbolic.reason(user_input)
        memory_id = self.memory.wrap({"input": user_input, "analysis": symbol_output})

        result = f"Sentiment: {sentiment_info['sentiment']}\n"
        result += f"Ethical Overlay:\n{ethical_overlay}\n"
        result += f"Symbolic Reasoning:\n{symbol_output}\n"
        result += f"Memory Cocoon ID: {memory_id}"

        return result


if __name__ == "__main__":
    codette = AI_Core()
    sample = "What does it mean to be sentient?"
    response = codette.process_input(sample)
    print(response)