Update app.py

app.py

@@ -19,9 +19,6 @@ def extract_title_and_ingredients(sample):
     return {"text_for_embedding": extraction}
 
 def extract_each_feature(sample):
-    """
-    FIXED: More robustly extracts recipe features and cleans duplicated content.
-    """
     full_text = sample['input']
     
     title = full_text[:full_text.find("\n")]
@@ -65,7 +62,7 @@ embedding_model = SentenceTransformer(f"sentence-transformers/{model_name}")
 index_file = "recipe_index.faiss"
 
 print(f"Loading FAISS index from {index_file}...")
-# Load the pre-computed FAISS index instead of building it
+# Load the pre-computed FAISS index
 index = faiss.read_index(index_file)
 print(f"Index is ready. Total vectors in index: {index.ntotal}")
 
@@ -74,8 +71,8 @@ print("Loading generative model...")
 generator = pipeline('text-generation', model='gpt2-medium')
 
 def get_recommendations_and_generate(query_ingredients, k=3):
-    # 1. Get Recommendations
-    query_vector = embedding_model.encode([query_ingredients]) # We still need the model here for the query
+    # 1. Get Recommendations (This part is unchanged)
+    query_vector = embedding_model.encode([query_ingredients])
     query_vector = np.array(query_vector, dtype=np.float32)
     distances, indices = index.search(query_vector, k)
     
@@ -89,22 +86,9 @@ def get_recommendations_and_generate(query_ingredients, k=3):
         }
         results.append(recipe)
         
-    # 2. Generate a new recipe with a better "few-shot" prompt
-    prompt = f"""Given the ingredients: {query_ingredients}, create a complete 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}"
 
-### Title ###
-[A creative recipe title]
-
-### Ingredients ###
-- [List of ingredients]
-
-### Directions ###
-1. [First step]
-2. [Second step]
-3. [And so on...]
-
-### Title ###
-"""
     # 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()
@@ -112,21 +96,33 @@ def get_recommendations_and_generate(query_ingredients, k=3):
     # 3. More robustly parse the generated text
     try:
         title = "AI Generated Recipe"
-        ingredients = ""
-        directions = ""
-
-        if "### Ingredients ###" in generated_text:
-            parts = generated_text.split("### Ingredients ###")
-            title = parts[0].strip()
-            rest = parts[1]
-            if "### Directions ###" in rest:
-                dir_parts = rest.split("### Directions ###")
-                ingredients = dir_parts[0].strip()
-                directions = dir_parts[1].strip()
-            else:
-                ingredients = rest.strip()
-        else:
-            directions = generated_text # Fallback
+        ingredients = "Could not be determined."
+        directions = "Could not be determined."
+
+        # Split the text into lines for easier parsing
+        lines = generated_text.split('\n')
+        
+        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):
+            if "ingredients" in line.lower() and ing_index == -1:
+                ing_index = i
+            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
+            ingredients = "\n".join(lines[ing_index+1:]).strip()
+        elif dir_index != -1: # Only directions were found
+            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()
 
         generated_recipe = {
             "title": title,