Deploy main.py to backend/ directory

backend/main.py

@@ -28,7 +28,7 @@ from clinical_synthesis_service import get_synthesis_service
 # Import monitoring and infrastructure modules
 from monitoring_service import get_monitoring_service
 from model_versioning import get_versioning_system
-from production_logging import get_medical_logger
+from production_logging import get_medical_logger, EventCategory
 from compliance_reporting import get_compliance_system
 from admin_endpoints import admin_router
 
@@ -72,12 +72,12 @@ async def monitoring_middleware(request: Request, call_next):
     request_id = str(uuid.uuid4())
     
     # Log request start
-    medical_logger.info("Request received", {
-        "request_id": request_id,
-        "method": request.method,
-        "path": request.url.path,
-        "client": request.client.host if request.client else "unknown"
-    })
+    medical_logger.info("Request received", 
+                        EventCategory.SYSTEM_EVENT,
+                        request_id=request_id,
+                        method=request.method,
+                        path=request.url.path,
+                        client=request.client.host if request.client else "unknown")
     
     try:
         # Process request
@@ -95,13 +95,13 @@ async def monitoring_middleware(request: Request, call_next):
         )
         
         # Log request completion
-        medical_logger.info("Request completed", {
-            "request_id": request_id,
-            "method": request.method,
-            "path": request.url.path,
-            "status_code": response.status_code,
-            "latency_ms": round(latency_ms, 2)
-        })
+        medical_logger.info("Request completed", 
+                            EventCategory.SYSTEM_EVENT,
+                            request_id=request_id,
+                            method=request.method,
+                            path=request.url.path,
+                            status_code=response.status_code,
+                            latency_ms=round(latency_ms, 2))
         
         return response
         
@@ -118,14 +118,14 @@ async def monitoring_middleware(request: Request, call_next):
         )
         
         # Log error
-        medical_logger.error("Request failed", {
-            "request_id": request_id,
-            "method": request.method,
-            "path": request.url.path,
-            "error": str(e),
-            "error_type": type(e).__name__,
-            "latency_ms": round(latency_ms, 2)
-        })
+        medical_logger.error("Request failed", 
+                            EventCategory.ERROR_EVENT,
+                            request_id=request_id,
+                            method=request.method,
+                            path=request.url.path,
+                            error=str(e),
+                            error_type=type(e).__name__,
+                            latency_ms=round(latency_ms, 2))
         
         # Re-raise the exception
         raise
@@ -172,17 +172,17 @@ async def startup_event():
     Ensures all infrastructure components are ready before accepting requests
     """
     
-    medical_logger.info("Starting Medical AI Platform initialization", {
-        "version": "2.0.0",
-        "timestamp": datetime.utcnow().isoformat()
-    })
+    medical_logger.info("Starting Medical AI Platform initialization", 
+                        EventCategory.SYSTEM_EVENT,
+                        version="2.0.0",
+                        timestamp=datetime.utcnow().isoformat())
     
     # Initialize monitoring service
     monitoring_service.start_monitoring()
-    medical_logger.info("Monitoring service initialized", {
-        "cache_enabled": True,
-        "alert_threshold": 0.05  # 5% error rate
-    })
+    medical_logger.info("Monitoring service initialized", 
+                        EventCategory.SYSTEM_EVENT,
+                        cache_enabled=True,
+                        alert_threshold=0.05)
     
     # Initialize versioning system with current models
     model_versions = [
@@ -201,15 +201,15 @@ async def startup_event():
             metadata={"source": model_config["source"]}
         )
     
-    medical_logger.info("Model versioning initialized", {
-        "total_models": len(model_versions)
-    })
+    medical_logger.info("Model versioning initialized", 
+                        EventCategory.SYSTEM_EVENT,
+                        total_models=len(model_versions))
     
     # Initialize compliance reporting
-    medical_logger.info("Compliance reporting system initialized", {
-        "standards": ["HIPAA", "GDPR"],
-        "audit_enabled": True
-    })
+    medical_logger.info("Compliance reporting system initialized", 
+                        EventCategory.SYSTEM_EVENT,
+                        standards=["HIPAA", "GDPR"],
+                        audit_enabled=True)
     
     # Log system configuration
     system_config = {
@@ -237,9 +237,9 @@ async def startup_event():
             "components_ready": True
         })
     except Exception as e:
-        medical_logger.error("Health check failed during startup", {
-            "error": str(e)
-        })
+    medical_logger.error("Health check failed during startup", 
+                        EventCategory.ERROR_EVENT,
+                        error=str(e))
     
     medical_logger.info("Medical AI Platform startup complete", {
         "status": "ready",
@@ -371,7 +371,9 @@ async def get_health_dashboard():
                             "last_used": perf.get("last_used", "never")
                         }
         except Exception as e:
-            medical_logger.warning("Failed to get model metrics", {"error": str(e)})
+            medical_logger.warning("Failed to get model metrics", 
+                                   EventCategory.PERFORMANCE_EVENT,
+                                   error=str(e))
         
         # Get pipeline statistics
         pipeline_stats = {
@@ -392,7 +394,9 @@ async def get_health_dashboard():
         try:
             synthesis_stats = synthesis_service.get_synthesis_statistics()
         except Exception as e:
-            medical_logger.warning("Failed to get synthesis stats", {"error": str(e)})
+            medical_logger.warning("Failed to get synthesis stats", 
+                                   EventCategory.PERFORMANCE_EVENT,
+                                   error=str(e))
         
         # Compliance overview
         compliance_overview = {
@@ -463,10 +467,10 @@ async def get_health_dashboard():
         return dashboard
         
     except Exception as e:
-        medical_logger.error("Dashboard generation failed", {
-            "error": str(e),
-            "timestamp": datetime.utcnow().isoformat()
-        })
+        medical_logger.error("Dashboard generation failed", 
+                            EventCategory.ERROR_EVENT,
+                            error=str(e),
+                            timestamp=datetime.utcnow().isoformat())
         
         # Return minimal dashboard on error
         return {