Upload AI_core.py

AI_core.py

@@ -0,0 +1,70 @@
+import os
+import json
+from typing import Optional
+
+# === Core Imports from Your Modules === #
+from ethical_governance 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 _init_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 = AICore()
+    sample = "What does it mean to be sentient?"
+    response = codette.process_input(sample)
+    print(response)
+