From f0d391b2a17dbbead9cda9595533ee205919daee Mon Sep 17 00:00:00 2001
From: marco370 <48531002-marco370@users.noreply.replit.com>
Date: Tue, 25 Nov 2025 09:34:44 +0000
Subject: [PATCH] Map confidence level strings to numeric values for detection
 results

Converts 'high', 'medium', and 'low' confidence levels to their corresponding numeric values (95.0, 75.0, 50.0) before saving detection results to the database, resolving an invalid input syntax error for type numeric.

Replit-Commit-Author: Agent
Replit-Commit-Session-Id: 7a657272-55ba-4a79-9a2e-f1ed9bc7a528
Replit-Commit-Checkpoint-Type: full_checkpoint
Replit-Commit-Event-Id: fd44e6f4-fc55-4636-aa7a-f4f462ac978a
Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/449cf7c4-c97a-45ae-8234-e5c5b8d6a84f/7a657272-55ba-4a79-9a2e-f1ed9bc7a528/AXTUZmH
---
 python_ml/main.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/python_ml/main.py b/python_ml/main.py
index eede93d..2115952 100644
--- a/python_ml/main.py
+++ b/python_ml/main.py
@@ -323,7 +323,13 @@ async def detect_anomalies(request: DetectRequest):
             detections = ml_detector.detect(df, mode='confidence')
             # Convert to legacy format for compatibility
             for det in detections:
-                det['confidence'] = det['confidence_level']  # Map confidence_level to confidence
+                # Map confidence_level string to numeric value for database
+                confidence_mapping = {
+                    'high': 95.0,
+                    'medium': 75.0,
+                    'low': 50.0
+                }
+                det['confidence'] = confidence_mapping.get(det['confidence_level'], 50.0)
         else:
             print("[DETECT] Using Legacy ML Analyzer")
             detections = ml_analyzer.detect(df, risk_threshold=request.risk_threshold)