Update AICoreAGIX_with_TB.py

AICoreAGIX_with_TB.py

@@ -24,7 +24,7 @@ from utils.logger import logger
 from codriao_tb_module import CodriaoHealthModule
 from fail_safe import AIFailsafeSystem
 from quarantine_engine import QuarantineEngine
-    from anomaly_score import AnomalyScorer
+from anomaly_score import AnomalyScorer
 
 class AICoreAGIX:
     def __init__(self, config_path: str = "config.json"):
@@ -74,7 +74,7 @@ def engage_lockdown_mode(self, reason="Unspecified anomaly"):
         secure_memory_module = load_secure_memory_module()
         SecureMemorySession = secure_memory_module.SecureMemorySession
         self.secure_memory_loader = SecureMemorySession(self._encryption_key)
-
+        self.training_memory = []
         self.speech_engine = pyttsx3.init()
         self.health_module = CodriaoHealthModule(ai_core=self)
     
@@ -83,7 +83,15 @@ def engage_lockdown_mode(self, reason="Unspecified anomaly"):
         self.anomaly_scorer = AnomalyScorer()
     
 
-
+def learn_from_interaction(self, query: str, response: str, user_feedback: str = None):
+    training_event = {
+        "query": query,
+        "response": response,
+        "feedback": user_feedback,
+        "timestamp": datetime.utcnow().isoformat()
+    }
+    self.training_memory.append(training_event)
+    logger.info(f"[Codriao Learning] Stored new training sample. Feedback: {user_feedback or 'none'}")
 def analyze_event_for_anomalies(self, event_type: str, data: dict):
     score = self.anomaly_scorer.score_event(event_type, data)
     if score["score"] >= 70:
@@ -188,7 +196,22 @@ def _load_config(self, config_path: str) -> dict:
             except Exception as e:
                 logger.warning(f"Blockchain logging failed: {e}")
                 continue
-
+    def fine_tune_from_memory(self):
+    if not self.training_memory:
+        logger.info("[Codriao Training] No training data to learn from.")
+        return "No training data available."
+
+    # Simulate learning pattern: Adjust internal weights or strategies
+    learned_insights = []
+    for record in self.training_memory:
+        if "panic" in record["query"].lower() or "unsafe" in record["response"].lower():
+            learned_insights.append("Avoid panic triggers in response phrasing.")
+
+    logger.info(f"[Codriao Training] Learned {len(learned_insights)} behavioral insights.")
+    return {
+        "insights": learned_insights,
+        "trained_samples": len(self.training_memory)
+    }
     def _speak_response(self, response: str):
         """Speaks out the generated response."""
         try:
@@ -196,7 +219,8 @@ def _load_config(self, config_path: str) -> dict:
             self.speech_engine.runAndWait()
         except Exception as e:
             logger.error(f"Speech synthesis failed: {e}")
-
+    # Store training data (you can customize feedback later)
+self.learn_from_interaction(query, final_response, user_feedback="auto-pass")
   async def shutdown(self):
         """Closes asynchronous resources."""
         await self.http_session.close()