Update AegisCore.py

AegisCore.py

@@ -23,12 +23,13 @@ class AIConfig:
         "model_name": "mistralai/Mistral-7B-Instruct-v0.2",
         "perspectives": ["newton", "davinci", "quantum", "emotional"],
         "safety_thresholds": {
-            "memory": 80,
-            "cpu": 85,
+            "memory": 85,  # Changed from 80
+            "cpu": 90,     # Changed from 85
             "response_time": 2.0
         },
         "max_retries": 3,
-        "max_input_length": 2048
+        "max_input_length": 4096,  # Changed from 2048
+        "max_response_length": 1024  # Added to control output size
     }
 
     def __init__(self, config_path: str = "config.json"):
@@ -38,6 +39,7 @@ class AIConfig:
         self.safety_thresholds: Dict[str, float] = self.config["safety_thresholds"]
         self.max_retries = self.config["max_retries"]
         self.max_input_length = self.config["max_input_length"]
+        self.max_response_length = self.config["max_response_length"]
         
         # Encryption key management
         key_path = os.path.expanduser("~/.ai_system.key")
@@ -96,7 +98,7 @@ class Element:
     def execute_defense_function(self, system: Any):
         if self.defense_ability in self.DEFENSE_FUNCTIONS:
             logging.info(f"{self.name} {self.defense_ability} activated")
-            self.DEFENSE_FUNCTIONS[self.defense_ability](system)
+            self.DEFENSE_FUNCTIONS*An external link was removed to protect your privacy.*
         else:
             logging.warning(f"No defense mechanism for {self.defense_ability}")
 
@@ -109,7 +111,7 @@ class CognitiveEngine:
     }
 
     def get_insight(self, perspective: str, query: str) -> str:
-        return self.PERSPECTIVES[perspective](self, query)
+        return self.PERSPECTIVES*An external link was removed to protect your privacy.*
 
     def ethical_guidelines(self) -> str:
         return "Ethical framework: Prioritize human safety, transparency, and accountability"
@@ -154,9 +156,12 @@ class SelfHealingSystem:
             latest = np.array([[self.metric_history[-1]['memory'],
                               self.metric_history[-1]['cpu'],
                               self.metric_history[-1]['response_time']]])
-            if self.anomaly_detector.predict(latest)[0] == -1:
+            if self.anomaly_detector.predict(latest) == -1:
                 await self._mitigate_issue()
 
+        logging.info(f"Memory usage: {metrics['memory']}% (Threshold: {self.config.safety_thresholds['memory']}%)")
+        logging.info(f"CPU load: {metrics['cpu']}% (Threshold: {self.config.safety_thresholds['cpu']}%)")
+
     async def _mitigate_issue(self):
         logging.warning("System anomaly detected! Initiating corrective measures...")
         self.failure_count += 1
@@ -186,8 +191,8 @@ class SafetySystem:
 
     def analyze(self, text: str) -> dict:
         return {
-            "toxicity": self.toxicity(text[:512])[0]['score'],
-            "bias": self.bias(text[:512])[0]['score'],
+            "toxicity": self.toxicity(text[:512])['score'],
+            "bias": self.bias(text[:512])['score'],
             "pii": self._detect_pii(text)
         }
 
@@ -286,7 +291,7 @@ class AICore:
                     top_p=0.95,
                     do_sample=True
                 )
-                response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+                response = self.tokenizer.decode(outputs, skip_special_tokens=True)
                 return self._apply_defenses(response)
             except torch.cuda.OutOfMemoryError:
                 logging.warning("GPU memory overflow! Reducing load...")
@@ -305,7 +310,7 @@ class AICore:
         for filter_func in self.response_filters:
             response = filter_func(response)
             
-        return response[:2000]  # Ensure final response length limit
+        return response[:self.config.max_response_length]  # Ensure final response length limit
 
     async def shutdown(self):
         if hasattr(self, 'model'):