Update quantum/optimizer.py

quantum/optimizer.py

@@ -1,14 +1,69 @@
-# quantum/optimizer.py
-def optimize_treatment(query: str):
-    # your stub or real BF-DCQO call
+from services.logger import app_logger
+from typing import Dict, Any
+import time
+import random
+
+# This is a STUB for a quantum optimizer.
+# In a real scenario, this would interface with a quantum computing service
+# or a sophisticated classical optimizer that mimics quantum approaches.
+
+def optimize_treatment(patient_data: Dict[str, Any], current_treatments: list, conditions: list) -> Dict[str, Any]:
+    """
+    Stub for a quantum-inspired treatment optimization.
+    
+    Args:
+        patient_data (Dict[str, Any]): Relevant patient characteristics.
+        current_treatments (list): List of current medications/therapies.
+        conditions (list): List of diagnosed conditions.
+
+    Returns:
+        Dict[str, Any]: A dictionary with optimized treatment suggestions.
+    """
+    app_logger.info(f"Quantum optimizer called for patient data: {patient_data}, treatments: {current_treatments}, conditions: {conditions}")
+    
+    # Simulate a complex computation
+    time.sleep(random.uniform(1, 3)) # Simulate processing time
+
+    # Mocked optimization logic
+    # This would be replaced by actual quantum annealing, VQE, QAOA, etc. calls
+    # or complex classical algorithms.
+    
+    suggestions = []
+    confidence_score = random.uniform(0.65, 0.95)
+
+    if "diabetes" in [c.lower() for c in conditions]:
+        if "metformin" not in [t.lower() for t in current_treatments]:
+            suggestions.append({
+                "action": "ADD",
+                "medication": "Metformin",
+                "dosage": "500mg BID",
+                "rationale": "Standard first-line for type 2 diabetes, potentially enhanced by quantum risk modeling."
+            })
+        else:
+            suggestions.append({
+                "action": "MONITOR",
+                "medication": "Metformin",
+                "rationale": "Continue Metformin. Quantum analysis suggests current efficacy."
+            })
+    
+    if "hypertension" in [c.lower() for c in conditions]:
+        suggestions.append({
+            "action": "CONSIDER_ADD",
+            "medication": "Lisinopril",
+            "dosage": "10mg QD",
+            "rationale": "ACE inhibitor, effective for hypertension. Quantum combinatorial analysis suggests synergy."
+        })
+
+    if not suggestions:
+        suggestions.append({
+            "action": "MAINTAIN",
+            "medication": "Current Regimen",
+            "rationale": "Quantum analysis indicates current treatment plan is near-optimal or requires further data."
+        })
+
     return {
-        "input": query,
-        "optimized_treatment_plan": [
-            {"step": 1, "action": "Order CBC, CMP, and ECG"},
-            {"step": 2, "action": "Start IV diuretics"},
-            {"step": 3, "action": "Monitor electrolytes and renal function"},
-            {"step": 4, "action": "Consider ACE inhibitor if stable"}
-        ],
-        "confidence_score": 0.93,
-        "explanation": "Optimized sequence for symptom relief and safety monitoring."
-    }
+        "optimized_suggestions": suggestions,
+        "confidence": f"{confidence_score:.2f}",
+        "summary": f"Based on quantum-inspired analysis of {len(conditions)} conditions and {len(current_treatments)} current treatments, the following adjustments are suggested.",
+        "iterations": random.randint(1000, 50000) # Mock "quantum" parameter
+    }