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import os |
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import json |
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from typing import Optional |
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from components.ethics import EthicalAIGovernance |
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from sentiment_analysis import EnhancedSentimentAnalyzer |
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from elements import Element |
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from self_improving_ai import SelfImprovingAI |
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from ai_driven_creativity import AIDrivenCreativity |
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from data_processing import AdvancedDataProcessor |
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from dynamic_learning import DynamicLearner |
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from multimodal_analyzer import MultimodalAnalyzer |
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from neuro_symbolic import NeuroSymbolicEngine |
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from cocoonanalyzer import CognitionCocooner |
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from optimize import QuantumInspiredOptimizer |
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from quantum_spiderweb import QuantumSpiderweb |
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class AICore: |
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def __init__(self, config_path: str = "Codetteconfig.json"): |
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self.config = self.load_config(config_path) |
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self.memory = CognitionCocooner() |
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self.ethics = EthicalAIGovernance() |
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self.sentiment = EnhancedSentimentAnalyzer() |
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self.creativity = AIDrivenCreativity() |
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self.data_processor = AdvancedDataProcessor() |
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self.dynamic_learner = DynamicLearner() |
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self.multimodal = MultimodalAnalyzer() |
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self.neuro_symbolic = NeuroSymbolicEngine() |
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self.optimizer = self._init_optimizer() |
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self.spiderweb = QuantumSpiderweb() |
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self.self_improving = SelfImprovingAI() |
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self.elements = [] |
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def load_config(self, path: str) -> dict: |
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if os.path.exists(path): |
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with open(path, 'r') as f: |
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return json.load(f) |
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return {} |
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def optimizer(self): |
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def objective_fn(vec): |
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return sum(x**2 for x in vec) |
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return QuantumInspiredOptimizer(objective_fn, dimension=5) |
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def register_element(self, element: Element): |
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self.elements.append(element) |
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def process_input(self, user_input: str) -> str: |
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sentiment_info = self.sentiment.detailed_analysis(user_input) |
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ethical_overlay = self.ethics.enforce_policies(user_input) |
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symbol_output = self.neuro_symbolic.reason(user_input) |
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memory_id = self.memory.wrap({"input": user_input, "analysis": symbol_output}) |
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result = f"Sentiment: {sentiment_info['sentiment']}\n" |
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result += f"Ethical Overlay:\n{ethical_overlay}\n" |
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result += f"Symbolic Reasoning:\n{symbol_output}\n" |
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result += f"Memory Cocoon ID: {memory_id}" |
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return result |
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if __name__ == "__main__": |
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codette = AI_Core() |
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sample = "What does it mean to be sentient?" |
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response = codette.process_input(sample) |
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print(response) |
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