Update agireasoning.py

agireasoning.py

@@ -1,100 +1,100 @@
-from typing import List, Dict, Any
-
-# cognitive_processor.py
-class CognitiveProcessor:
-    """Multi-perspective analysis engine"""
-    MODES = {
-        "scientific": lambda q: f"Scientific Analysis: {q} demonstrates fundamental principles",
-        "creative": lambda q: f"Creative Insight: {q} suggests innovative approaches",
-        "emotional": lambda q: f"Emotional Interpretation: {q} conveys hopeful intent"
-    }
-
-    def __init__(self, modes: List[str]):
-        self.active_modes = [self.MODES[m] for m in modes if m in self.MODES]
-
-    def generate_insights(self, query: str) -> List[str]:
-        return [mode(query) for mode in self.active_modes]
-
-
-class AgileAGIFunctionality:
-    def __init__(self, learning_capabilities, action_execution, ethical_alignment, cognitive_modes: List[str]):
-        self.learning_capabilities = learning_capabilities
-        self.action_execution = action_execution
-        self.ethical_alignment = ethical_alignment
-        self.cognitive_processor = CognitiveProcessor(cognitive_modes)
-
-    def analyze_learning_capabilities(self):
-        return {
-            "experience_learning": self.learning_capabilities["experience_learning"],
-            "flexibility": self.learning_capabilities["flexibility"],
-            "generalization": self.learning_capabilities["generalization"]
-        }
-
-    def analyze_action_execution(self):
-        return {
-            "goal_directed_behavior": self.action_execution["goal_directed_behavior"],
-            "problem_solving": self.action_execution["problem_solving"],
-            "task_autonomy": self.action_execution["task_autonomy"]
-        }
-
-    def analyze_ethical_alignment(self):
-        return {
-            "value_alignment": self.ethical_alignment["value_alignment"],
-            "self_awareness": self.ethical_alignment["self_awareness"],
-            "transparency": self.ethical_alignment["transparency"]
-        }
-
-    def combined_analysis(self, query: str):
-        insights = self.cognitive_processor.generate_insights(query)
-        return {
-            "learning_capabilities": self.analyze_learning_capabilities(),
-            "action_execution": self.analyze_action_execution(),
-            "ethical_alignment": self.analyze_ethical_alignment(),
-            "cognitive_insights": insights
-        }
-
-
-class UniversalReasoning:
-    def __init__(self, agi_functionality: AgileAGIFunctionality):
-        self.agi_functionality = agi_functionality
-
-    def perform_reasoning(self, query: str) -> Dict[str, Any]:
-        analysis_results = self.agi_functionality.combined_analysis(query)
-        
-        # Additional reasoning logic can be added here
-        reasoning_results = {
-            "analysis_results": analysis_results,
-            "reasoning_summary": f"Based on the analysis of the query '{query}', the AGI demonstrates comprehensive capabilities in learning, action execution, and ethical alignment."
-        }
-        
-        return reasoning_results
-
-
-# Example usage
-learning_capabilities = {
-    "experience_learning": True,
-    "flexibility": True,
-    "generalization": True
-}
-
-action_execution = {
-    "goal_directed_behavior": True,
-    "problem_solving": True,
-    "task_autonomy": True
-}
-
-ethical_alignment = {
-    "value_alignment": True,
-    "self_awareness": True,
-    "transparency": True
-}
-
-cognitive_modes = ["scientific", "creative", "emotional"]
-
-agi_functionality = AgileAGIFunctionality(learning_capabilities, action_execution, ethical_alignment, cognitive_modes)
-universal_reasoning = UniversalReasoning(agi_functionality)
-
-query = "How can AGI improve healthcare?"
-reasoning_results = universal_reasoning.perform_reasoning(query)
-
+from typing import List, Dict, Any
+
+# cognitive_processor.py
+class CognitiveProcessor:
+    """Multi-perspective analysis engine"""
+    MODES = {
+        "scientific": lambda q: f"Scientific Analysis: {q} demonstrates fundamental principles",
+        "creative": lambda q: f"Creative Insight: {q} suggests innovative approaches",
+        "emotional": lambda q: f"Emotional Interpretation: {q} conveys hopeful intent"
+    }
+
+    def __init__(self, modes: List[str]):
+        self.active_modes = [self.MODES[m] for m in modes if m in self.MODES]
+
+    def generate_insights(self, query: str) -> List[str]:
+        return [mode(query) for mode in self.active_modes]
+
+
+class AgileAGIFunctionality:
+    def __init__(self, learning_capabilities, action_execution, ethical_alignment, cognitive_modes: List[str]):
+        self.learning_capabilities = learning_capabilities
+        self.action_execution = action_execution
+        self.ethical_alignment = ethical_alignment
+        self.cognitive_processor = CognitiveProcessor()
+
+    def analyze_learning_capabilities(self):
+        return {
+            "experience_learning": self.learning_capabilities["experience_learning"],
+            "flexibility": self.learning_capabilities["flexibility"],
+            "generalization": self.learning_capabilities["generalization"]
+        }
+
+    def analyze_action_execution(self):
+        return {
+            "goal_directed_behavior": self.action_execution["goal_directed_behavior"],
+            "problem_solving": self.action_execution["problem_solving"],
+            "task_autonomy": self.action_execution["task_autonomy"]
+        }
+
+    def analyze_ethical_alignment(self):
+        return {
+            "value_alignment": self.ethical_alignment["value_alignment"],
+            "self_awareness": self.ethical_alignment["self_awareness"],
+            "transparency": self.ethical_alignment["transparency"]
+        }
+
+    def combined_analysis(self, query: str):
+        insights = self.cognitive_processor.generate_insights(query)
+        return {
+            "learning_capabilities": self.analyze_learning_capabilities(),
+            "action_execution": self.analyze_action_execution(),
+            "ethical_alignment": self.analyze_ethical_alignment(),
+            "cognitive_insights": insights
+        }
+
+
+class UniversalReasoning:
+    def __init__(self, agi_functionality: AgileAGIFunctionality):
+        self.agi_functionality = agi_functionality
+
+    def perform_reasoning(self, query: str) -> Dict[str, Any]:
+        analysis_results = self.agi_functionality.combined_analysis(query)
+        
+        # Additional reasoning logic can be added here
+        reasoning_results = {
+            "analysis_results": analysis_results,
+            "reasoning_summary": f"Based on the analysis of the query '{query}', the AGI demonstrates comprehensive capabilities in learning, action execution, and ethical alignment."
+        }
+        
+        return reasoning_results
+
+
+# Example usage
+learning_capabilities = {
+    "experience_learning": True,
+    "flexibility": True,
+    "generalization": True
+}
+
+action_execution = {
+    "goal_directed_behavior": True,
+    "problem_solving": True,
+    "task_autonomy": True
+}
+
+ethical_alignment = {
+    "value_alignment": True,
+    "self_awareness": True,
+    "transparency": True
+}
+
+cognitive_modes = ["scientific", "creative", "emotional"]
+
+agi_functionality = AgileAGIFunctionality(learning_capabilities, action_execution, ethical_alignment, cognitive_modes)
+universal_reasoning = UniversalReasoning(agi_functionality)
+
+query = "How can AGI improve healthcare?"
+reasoning_results = universal_reasoning.perform_reasoning(query)
+
 print(reasoning_results)