Update app/api/routes.py

app/api/routes.py

@@ -3,86 +3,110 @@ from app.models.recipe import Recipe
 import json
 import asyncio
 import os
+import sys
+import traceback
+import resource
 from app.services import extraction
 from app.services import image_query 
 
 api_bp = Blueprint('api', __name__, url_prefix='/api')
 
+def log_memory(tag=""):
+    """Helper to print current RAM usage to logs"""
+    try:
+        usage = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
+        # Linux returns KB, convert to MB
+        usage_mb = usage / 1024 
+        print(f"[{tag}] MEMORY USAGE: {usage_mb:.2f} MB", file=sys.stderr)
+    except Exception:
+        pass
+
 @api_bp.route('/form-data', methods=['GET'])
 def get_form_data():
-    # Use os.path.join to create a platform-independent path
     file_path = os.path.join(os.getcwd(), 'form_data.json')
     try:
         with open(file_path, 'r') as file:
             data = file.read()
         return data
     except FileNotFoundError:
+        print(f"Error: File not found at {file_path}", file=sys.stderr)
         return jsonify({"error": f"File not found at {file_path}"}), 404
     except Exception as e:
+        traceback.print_exc(file=sys.stderr)
         return jsonify({"error": str(e)}), 500
 
 @api_bp.route('/recommend', methods=['POST'])
-async def recommend_recipes():  # Make this function async
-    data = request.json
-    category = data.get('category')
-    dietary_preference = data.get('dietary_preference')
-    ingredients = data.get('ingredients', [])
-    calories = data.get('calories')
-    time = data.get('time')
-    keywords = data.get('keywords', [])
-    keywords_name = data.get('keywords_name', [])
-
+async def recommend_recipes():  
+    print(">>> RECOMMEND ENDPOINT HIT", file=sys.stderr)
+    log_memory("Start Recommend")
+    
     try:
+        data = request.json
+        category = data.get('category')
+        dietary_preference = data.get('dietary_preference')
+        ingredients = data.get('ingredients', [])
+        calories = data.get('calories')
+        time = data.get('time')
+        keywords = data.get('keywords', [])
+        keywords_name = data.get('keywords_name', [])
+
         if calories is not None:
             calories = int(calories)
         if time is not None:
             time = int(time)
-    except ValueError:
-        return jsonify({"error": "Calories and time must be integers if provided"}), 400
-
-    feature_weights_recommend = {
-        'ingredients': 0.15, 'category': 0.25, 'dietary': 0.20,
-        'calories': 0.10, 'time': 0.10, 'keywords': 0.10, 'keywords_name': 0.10
-    }
-
-    # Use await to call the async function
-    recommendations = await current_app.recommendation_system.get_recommendations(
-        category=category,
-        dietary_preference=dietary_preference,
-        ingredients=ingredients,
-        calories=calories,
-        time=time,
-        keywords=keywords,
-        keywords_name=keywords_name,
-        feature_weights=feature_weights_recommend
-    )
-
-    return jsonify([vars(recipe) for recipe in recommendations])
+
+        feature_weights_recommend = {
+            'ingredients': 0.15, 'category': 0.25, 'dietary': 0.20,
+            'calories': 0.10, 'time': 0.10, 'keywords': 0.10, 'keywords_name': 0.10
+        }
+
+        recommendations = await current_app.recommendation_system.get_recommendations(
+            category=category,
+            dietary_preference=dietary_preference,
+            ingredients=ingredients,
+            calories=calories,
+            time=time,
+            keywords=keywords,
+            keywords_name=keywords_name,
+            feature_weights=feature_weights_recommend
+        )
+        
+        log_memory("End Recommend")
+        return jsonify([vars(recipe) for recipe in recommendations])
+        
+    except Exception as e:
+        print("!!! CRITICAL ERROR IN RECOMMEND !!!", file=sys.stderr)
+        traceback.print_exc(file=sys.stderr)
+        return jsonify({"error": str(e)}), 500
+
 
 @api_bp.route('/extract-recipe-attributes', methods=['POST'])
 async def recommend_recipes2():
+    print(">>> SEARCH (EXTRACT) ENDPOINT HIT", file=sys.stderr)
+    log_memory("Start Search")
+    
     try:
         data = request.get_json()
         if not data:
             return jsonify({"error": "No data provided"}), 400
-
+            
         raw_text = data.get('text')
         if not raw_text:
             return jsonify({"error": "No search text provided"}), 400
 
-        # Extract recipe attributes
-        extracted_info = extraction.extract_recipe_attributes(raw_text)  # Call the extraction function
+        # 1. Extract Attributes (Using Gemini/AI)
+        print(f"Extracting attributes for: {raw_text[:50]}...", file=sys.stderr)
+        extracted_info = extraction.extract_recipe_attributes(raw_text) 
 
-        # Check if extraction was successful
         if 'error' in extracted_info:
+            print(f"Extraction Error: {extracted_info}", file=sys.stderr)
             return jsonify(extracted_info), 500
-        
+            
         feature_weights_extract = {
             'ingredients': 0.50, 'category': 0.0, 'dietary': 0.0,
             'calories': 0.0, 'time': 0.0, 'keywords': 0.40, 'keywords_name': 0.10
         }
 
-        # Access the extracted attributes
         category = extracted_info.get('category', '')
         calories = extracted_info.get('calories', None)
         time = extracted_info.get('time', None)
@@ -90,17 +114,17 @@ async def recommend_recipes2():
         keywords_name = extracted_info.get('keywords_name', [])
         ingredients = extracted_info.get('ingredients', [])
 
-        # Convert calories and time to integers if they exist
         try:
             calories = int(calories) if calories else None
             time = int(time) if time else None
         except (ValueError, TypeError):
             return jsonify({"error": "Invalid calories or time value"}), 400
 
-        # Get recommendations using the recommendation system
+        # 2. Get Recommendations (Using Huge DataFrame)
+        print("Calling Recommendation System...", file=sys.stderr)
         recommendations = await current_app.recommendation_system.get_recommendations(
             category=category,
-            ingredients=ingredients,  # Adjust if you plan to add ingredients in the extraction function
+            ingredients=ingredients,
             calories=calories,
             time=time,
             keywords=keywords,
@@ -108,42 +132,44 @@ async def recommend_recipes2():
             feature_weights=feature_weights_extract
         )
 
-        # Convert recommendations to JSON-serializable format
+        log_memory("End Search")
         recipe_list = [vars(recipe) for recipe in recommendations]
-
         return jsonify(recipe_list)
-
+        
     except Exception as e:
+        print("!!! CRITICAL ERROR IN SEARCH !!!", file=sys.stderr)
+        # This is the line that will finally show you WHY it crashes
+        traceback.print_exc(file=sys.stderr) 
         return jsonify({"error": str(e)}), 500
-    
-# searchImage
+
+
 @api_bp.route('/analyze-food-image', methods=['POST'])
 async def handle_analyze_food_image():
+    print(">>> IMAGE ANALYSIS ENDPOINT HIT", file=sys.stderr)
+    log_memory("Start Image")
+    
     try:
         if 'image' not in request.files:
             return jsonify({"error": "No image file provided"}), 400
             
         file = request.files['image']
-        
         if file.filename == '':
             return jsonify({"error": "No selected file"}), 400
         
-        # Call the analyze function with the file
+        print("Analyzing Food Image...", file=sys.stderr)
         description = image_query.analyze_food_image(file)
         
-        # Extract recipe attributes
-        extracted_info = extraction.extract_recipe_attributes(description)  # Call the extraction function
+        print(f"Image Description: {description[:50]}...", file=sys.stderr)
+        extracted_info = extraction.extract_recipe_attributes(description)
 
-        # Check if extraction was successful
         if 'error' in extracted_info:
             return jsonify(extracted_info), 500
-
+            
         feature_weights_extract = {
             'ingredients': 0.50, 'category': 0.0, 'dietary': 0.0,
             'calories': 0.0, 'time': 0.0, 'keywords': 0.40, 'keywords_name': 0.10
         }
 
-        # Access the extracted attributes
         category = extracted_info.get('category', '')
         calories = extracted_info.get('calories', None)
         time = extracted_info.get('time', None)
@@ -151,17 +177,15 @@ async def handle_analyze_food_image():
         keywords_name = extracted_info.get('keywords_name', [])
         ingredients = extracted_info.get('ingredients', [])
 
-        # Convert calories and time to integers if they exist
         try:
             calories = int(calories) if calories else None
             time = int(time) if time else None
         except (ValueError, TypeError):
             return jsonify({"error": "Invalid calories or time value"}), 400
 
-        # Get recommendations using the recommendation system
         recommendations = await current_app.recommendation_system.get_recommendations(
             category=category,
-            ingredients=ingredients,  # Adjust if you plan to add ingredients in the extraction function
+            ingredients=ingredients, 
             calories=calories,
             time=time,
             keywords=keywords,
@@ -169,20 +193,17 @@ async def handle_analyze_food_image():
             feature_weights=feature_weights_extract
         )
 
-        # Convert recommendations to JSON-serializable format
+        log_memory("End Image")
         recipe_list = [vars(recipe) for recipe in recommendations]
-
         return jsonify(recipe_list)
-
+        
     except Exception as e:
+        print("!!! CRITICAL ERROR IN IMAGE ANALYSIS !!!", file=sys.stderr)
+        traceback.print_exc(file=sys.stderr)
         return jsonify({"error": str(e)}), 500
 
 @api_bp.route('/health', methods=['GET'])
 def health_check():
-    """
-    Simple health check endpoint to keep the space awake.
-    Returns a 200 OK status with a basic message.
-    """
     return jsonify({
         "status": "alive", 
         "message": "Recipe Recommendation Service is Running",
@@ -192,5 +213,4 @@ def health_check():
             "/api/extract-recipe-attributes",
             "/api/analyze-food-image"
         ]
-    }), 200
-    
+    }), 200