Update app.py

app.py

@@ -71,7 +71,7 @@ print("Loading generative model...")
 generator = pipeline('text-generation', model='gpt2-medium')
 
 def get_recommendations_and_generate(query_ingredients, k=3):
-    # 1. Get Recommendations (This part is unchanged)
+    # --- 1. Get Recommendations ---
     query_vector = embedding_model.encode([query_ingredients])
     query_vector = np.array(query_vector, dtype=np.float32)
     distances, indices = index.search(query_vector, k)
@@ -86,25 +86,35 @@ def get_recommendations_and_generate(query_ingredients, k=3):
         }
         results.append(recipe)
         
-    # 2. Generate a new recipe with a much simpler and more direct prompt
-    prompt = f"Create a simple and delicious recipe using the following ingredients: {query_ingredients}"
-
-    # Generate the recipe text
-    generated_outputs = generator(prompt, max_new_tokens=250, num_return_sequences=1, pad_token_id=50256)
-    generated_text = generated_outputs[0]['generated_text'].replace(prompt, "").strip()
-
-    # 3. More robustly parse the generated text
+    # Defensive check: Ensure there are always 3 recommendations
+    while len(results) < 3:
+        results.append({"title": "No recipe found", "ingredients": "", "directions": ""})
+
+    # --- 2. Generate and Parse a New Recipe (with error handling) ---
+    generated_recipe = {
+        "title": "AI Recipe Generation Failed",
+        "ingredients": "The model could not generate a recipe for these ingredients.",
+        "directions": "Please try a different combination of ingredients."
+    }
+    
     try:
-        title = "AI Generated Recipe"
-        ingredients = "Could not be determined."
-        directions = "Could not be determined."
-
-        # Split the text into lines for easier parsing
+        prompt = f"Create a simple and delicious recipe using the following ingredients: {query_ingredients}."
+        
+        generated_outputs = generator(prompt, max_new_tokens=250, num_return_sequences=1, pad_token_id=50256)
+        
+        # Check if the model returned a valid output
+        if not generated_outputs or 'generated_text' not in generated_outputs[0]:
+            raise ValueError("Model did not return generated_text.")
+            
+        generated_text = generated_outputs[0]['generated_text'].replace(prompt, "").strip()
+        
+        # Parsing logic
         lines = generated_text.split('\n')
+        if not lines or lines[0] == "":
+            raise ValueError("Generated text is empty.")
+            
+        title = lines[0].strip()
         
-        title = lines[0].strip() # The first line after the prompt is the title
-
-        # Find the start of ingredients and directions by looking for keywords
         ing_index = -1
         dir_index = -1
         for i, line in enumerate(lines):
@@ -113,29 +123,28 @@ def get_recommendations_and_generate(query_ingredients, k=3):
             if "directions" in line.lower() and dir_index == -1:
                 dir_index = i
         
-        # Extract the sections based on where the keywords were found
         if ing_index != -1 and dir_index != -1:
             ingredients = "\n".join(lines[ing_index+1:dir_index]).strip()
             directions = "\n".join(lines[dir_index+1:]).strip()
-        elif ing_index != -1: # Only ingredients were found
+        elif ing_index != -1:
             ingredients = "\n".join(lines[ing_index+1:]).strip()
-        elif dir_index != -1: # Only directions were found
+            directions = "Not provided."
+        elif dir_index != -1:
             directions = "\n".join(lines[dir_index+1:]).strip()
-        else: # If no headers are found, assume the rest of the text is the directions
-            directions = "\n".join(lines[1:]).strip()
+            ingredients = "Not provided."
+        else:
+            ingredients = "Not provided."
+            directions = "\n".join(lines[1:]).strip() if len(lines) > 1 else ""
 
         generated_recipe = {
             "title": title,
             "ingredients": ingredients,
             "directions": directions
         }
+
     except Exception as e:
-        print(f"Error parsing generated text: {e}")
-        generated_recipe = {
-            "title": "AI Generated Recipe (Parsing Error)",
-            "ingredients": "Could not determine ingredients.",
-            "directions": generated_text
-        }
+        print(f"An error occurred in get_recommendations_and_generate: {e}")
+        # The generated_recipe dictionary is already set to a default error message
     
     return results[0], results[1], results[2], generated_recipe