add_app3

app.py

@@ -14,11 +14,6 @@ import pandas as pd
 import os
 from typing import List, Optional
 from datetime import datetime
-import logging
-
-Configure logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
 
 # ==========================================
 # Configuration
@@ -251,23 +246,15 @@ def load_model_from_hf():
     global model
     
     try:
-        logger.info(f"📥 Downloading model from HuggingFace: {REPO_ID}")
-        
         model_path = hf_hub_download(
             repo_id=REPO_ID,
             filename=MODEL_FILENAME,
             revision=MODEL_VERSION
         )
-        
-        logger.info(f"✅ Model downloaded to: {model_path}")
-        
         model = joblib.load(model_path)
-        logger.info(f"✅ Model loaded: {type(model).__name__}")
-        
         return True
         
     except Exception as e:
-        logger.error(f"❌ Failed to load model: {e}")
         return False
 
 
@@ -314,15 +301,8 @@ def predict_transaction(data: dict) -> dict:
 
 @app.on_event("startup")
 async def startup_event():
-    """Load model on startup"""
-    logger.info("🚀 Starting Fraud Detection API...")
-    
+    """Load model on startup"""    
     success = load_model_from_hf()
-    
-    if success:
-        logger.info("✅ API ready to serve predictions")
-    else:
-        logger.error("❌ API started but model failed to load")
 
 
 # ==========================================
@@ -465,7 +445,6 @@ async def predict_single(transaction: TransactionInput):
         return result
         
     except Exception as e:
-        logger.error(f"Prediction error: {e}")
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
             detail=f"Prediction failed: {str(e)}"
@@ -538,7 +517,6 @@ async def predict_batch(batch: BatchTransactionInput):
         }
         
     except Exception as e:
-        logger.error(f"Batch prediction error: {e}")
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
             detail=f"Batch prediction failed: {str(e)}"
@@ -559,7 +537,6 @@ async def value_error_handler(request, exc):
 
 @app.exception_handler(Exception)
 async def general_exception_handler(request, exc):
-    logger.error(f"Unhandled exception: {exc}")
     return JSONResponse(
         status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
         content={"error": "Internal server error", "detail": "An unexpected error occurred"}