Create codriao_supercore.py

codriao_supercore.py

@@ -1,5 +1,4 @@
 # codriao_supercore.py
-
 import logging
 import json
 import datetime
@@ -10,7 +9,7 @@ import torch
 import numpy as np
 import aiohttp
 import pyttsx3
-from typing import Any
+from typing import Any, List, Dict
 from difflib import SequenceMatcher
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from cryptography.fernet import Fernet
@@ -130,6 +129,52 @@ class MondayElement:
         return response
 
 
+# === IdentityAnalyzer ===
+class IdentityAnalyzer:
+    def analyze_identity(self,
+                         micro_generations: List[Dict[str, str]],
+                         informational_states: List[Dict[str, str]],
+                         perspectives: List[str],
+                         quantum_analogies: Dict[str, Any],
+                         philosophical_context: Dict[str, bool]) -> Dict[str, Any]:
+
+        def calculate_fractal_dimension(states: List[Dict[str, str]]) -> float:
+            return len(states) ** 0.5
+
+        def recursive_analysis(states: List[Dict[str, str]], depth: int = 0) -> Dict[str, Any]:
+            if depth == 0 or not states:
+                return {"depth": depth, "states": states}
+            return {
+                "depth": depth,
+                "states": states,
+                "sub_analysis": recursive_analysis(states[:-1], depth - 1)
+            }
+
+        def analyze_perspectives(perspectives: List[str]) -> Dict[str, Any]:
+            return {
+                "count": len(perspectives),
+                "unique_perspectives": list(set(perspectives))
+            }
+
+        def apply_quantum_analogies(analogies: Dict[str, Any]) -> str:
+            if analogies.get("entanglement"):
+                return "Entanglement analogy applied."
+            return "No quantum analogy applied."
+
+        def philosophical_analysis(context: Dict[str, bool]) -> str:
+            if context.get("continuity") and context.get("emergent"):
+                return "Identity is viewed as a continuous and evolving process."
+            return "Identity analysis based on provided philosophical context."
+
+        return {
+            "fractal_dimension": calculate_fractal_dimension(informational_states),
+            "recursive_analysis": recursive_analysis(micro_generations, depth=3),
+            "perspectives_analysis": analyze_perspectives(perspectives),
+            "quantum_analysis": apply_quantum_analogies(quantum_analogies),
+            "philosophical_results": philosophical_analysis(philosophical_context)
+        }
+
+
 # === AICoreAGIX ===
 class AICoreAGIX:
     def __init__(self, config_path: str = "config.json"):
@@ -149,7 +194,7 @@ class AICoreAGIX:
         self.monday.execute_defense_function(self)
         self.response_modifiers = []
         self.response_filters = []
-
+        self.identity_analyzer = IdentityAnalyzer()
         self.ethical_filter = EthicalFilter()
         self.speech_engine = pyttsx3.init()
         self.health_module = CodriaoHealthModule(ai_core=self)
@@ -184,7 +229,6 @@ class AICoreAGIX:
             if any(k in query.lower() for k in ["tb check", "analyze my tb", "run tb diagnostics"]):
                 return await self.run_tb_diagnostics("tb_image.jpg", "tb_cough.wav", user_id)
 
-            # Check for learned suggestion
             suggested = self.adaptive_learning.suggest_improvements(user_id, query)
             if "No relevant" not in suggested:
                 return {"response": suggested}
@@ -200,7 +244,6 @@ class AICoreAGIX:
             )
 
             final_response = "\n\n".join(responses)
-
             self.adaptive_learning.learn_from_interaction(user_id, query, final_response)
 
             for mod in self.response_modifiers:
@@ -251,4 +294,24 @@ class AICoreAGIX:
             self.speech_engine.say(response)
             self.speech_engine.runAndWait()
         except Exception as e:
-            logger.error(f"Speech synthesis failed: {e}")
+            logger.error(f"Speech synthesis failed: {e}")
+
+    def analyze_self_identity(self, user_id: int,
+                              micro_generations: List[Dict[str, str]],
+                              informational_states: List[Dict[str, str]],
+                              perspectives: List[str],
+                              quantum_analogies: Dict[str, Any],
+                              philosophical_context: Dict[str, bool]) -> Dict[str, Any]:
+        try:
+            result = self.identity_analyzer.analyze_identity(
+                micro_generations,
+                informational_states,
+                perspectives,
+                quantum_analogies,
+                philosophical_context
+            )
+            logger.info(f"Identity analysis for user {user_id}: {json.dumps(result, indent=2)}")
+            return result
+        except Exception as e:
+            logger.error(f"Identity analysis failed: {e}")
+            return {"error": "Identity analysis error"}