Update definitions.py

definitions.py

@@ -410,6 +410,98 @@ class AutonomousAgent:
                 if st.button("Send", key="send_message"):
                     self.process_user_input(user_input)
 
+class RefinementLoop:
+    """Manages the iterative refinement process."""
+    def __init__(self, pipeline):
+        self.pipeline = pipeline
+        self.max_iterations = 10
+        self.quality_metrics = QualityMetrics()
+        self.logger = logging.getLogger(__name__)
+        self.current_iteration = 0
+        self.history = []
+
+    async def run_refinement_cycle(self, task: str) -> Dict[str, Any]:
+        """Run a complete refinement cycle for the given task."""
+        self.logger.info(f"Starting refinement cycle for task: {task}")
+        self.current_iteration = 0
+        
+        try:
+            while self.current_iteration < self.max_iterations:
+                self.logger.info(f"Starting iteration {self.current_iteration + 1}")
+                
+                # Execute pipeline stages
+                planning_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.PLANNING,
+                    {"task": task}
+                )
+                
+                development_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.DEVELOPMENT,
+                    planning_result["result"]
+                )
+                
+                testing_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.TESTING,
+                    development_result["result"]
+                )
+                
+                # Analyze results
+                quality_analysis = self._analyze_quality(testing_result["result"])
+                
+                # Record iteration history
+                self.history.append({
+                    "iteration": self.current_iteration,
+                    "quality_metrics": quality_analysis,
+                    "timestamp": datetime.now()
+                })
+                
+                # Check if quality requirements are met
+                if self._meets_quality_requirements(quality_analysis):
+                    self.logger.info("Quality requirements met. Refinement cycle complete.")
+                    return self._prepare_final_result(quality_analysis)
+                
+                self.current_iteration += 1
+            
+            return {
+                "status": "max_iterations_reached",
+                "iterations_completed": self.current_iteration,
+                "final_quality": quality_analysis
+            }
+            
+        except Exception as e:
+            self.logger.error(f"Error in refinement cycle: {str(e)}")
+            return {"status": "error", "error": str(e)}
+
+    def _analyze_quality(self, result: Dict[str, Any]) -> Dict[str, float]:
+        """Analyze the quality metrics of the current iteration."""
+        return {
+            "code_quality": self.quality_metrics.code_quality_score,
+            "test_coverage": self.quality_metrics.test_coverage,
+            "security_score": float(self.quality_metrics.security_score)
+        }
+
+    def _meets_quality_requirements(self, quality_analysis: Dict[str, float]) -> bool:
+        """Check if the current quality metrics meet the requirements."""
+        thresholds = self.quality_metrics.thresholds
+        return (
+            quality_analysis["code_quality"] >= thresholds["code_quality"] and
+            quality_analysis["test_coverage"] >= thresholds["test_coverage"] and
+            quality_analysis["security_score"] >= thresholds["security"]
+        )
+
+    def _prepare_final_result(self, quality_analysis: Dict[str, float]) -> Dict[str, Any]:
+        """Prepare the final result of the refinement cycle."""
+        return {
+            "status": "success",
+            "iterations_completed": self.current_iteration,
+            "final_quality": quality_analysis,
+            "history": self.history
+        }
+
+    def get_refinement_history(self) -> List[Dict[str, Any]]:
+        """Get the history of refinement iterations."""
+        return self.history
+
 class AutonomousAgentApp:
     """Main application class for the Autonomous Agent System."""
     def __init__(self):