Update app.py

app.py

@@ -13,27 +13,28 @@ def load_image_classification_pipeline():
 
 pipe_classification = load_image_classification_pipeline()
 
-# Load the GPT-Neo model for ingredient generation
+# Load the BLOOM model for ingredient generation
 @st.cache_resource
-def load_llama_pipeline():
+def load_bloom_pipeline():
     """
-    Load the GPT-Neo model for ingredient generation.
+    Load the BLOOM model for ingredient generation.
     """
-    return pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
+    return pipeline("text-generation", model="bigscience/bloom-1b7")
 
-pipe_llama = load_llama_pipeline()
+pipe_bloom = load_bloom_pipeline()
 
-def get_ingredients_llama(food_name):
+# Function to generate ingredients using BLOOM
+def get_ingredients_bloom(food_name):
     """
-    Generate a list of ingredients for the given food item using GPT-Neo.
+    Generate a list of ingredients for the given food item using BLOOM.
     Returns a clean, comma-separated list of ingredients.
     """
     prompt = (
-        f"List only the ingredients for {food_name}. "
-        "Output the ingredients as a simple, comma-separated list such as: ingredient1, ingredient2, ingredient3."
+        f"List only the main ingredients typically used to prepare {food_name}. "
+        "Provide the ingredients as a simple, comma-separated list such as: ingredient1, ingredient2, ingredient3."
     )
     try:
-        response = pipe_llama(prompt, max_length=50, num_return_sequences=1)
+        response = pipe_bloom(prompt, max_length=50, num_return_sequences=1)
         generated_text = response[0]["generated_text"].strip()
         
         # Post-process to extract only the list of ingredients
@@ -47,13 +48,7 @@ def get_ingredients_llama(food_name):
         return ingredients
     except Exception as e:
         return f"Error generating ingredients: {e}"
-        
-        # Process the response to ensure it's a clean, comma-separated list
-        ingredients = generated_text.split(":")[-1].strip()  # Handle cases like "Ingredients: ..."
-        ingredients = ingredients.replace(".", "").strip()  # Remove periods and extra spaces
-        return ingredients
-    except Exception as e:
-        return f"Error generating ingredients: {e}"
+
 # Streamlit app setup
 st.title("Food Image Recognition with Ingredients")
 
@@ -63,7 +58,7 @@ st.image("IR_IMAGE.png", caption="Food Recognition Model", use_column_width=True
 # Sidebar for model information
 st.sidebar.title("Model Information")
 st.sidebar.write("**Image Classification Model**: Shresthadev403/food-image-classification")
-st.sidebar.write("**LLM for Ingredients**: EleutherAI/gpt-neo-1.3B")
+st.sidebar.write("**LLM for Ingredients**: bigscience/bloom-1b7")
 
 # Upload image
 uploaded_file = st.file_uploader("Choose a food image...", type=["jpg", "png", "jpeg"])
@@ -84,7 +79,7 @@ if uploaded_file is not None:
     # Generate and display ingredients for the top prediction
     st.subheader("Ingredients")
     try:
-        ingredients = get_ingredients_llama(top_food)
+        ingredients = get_ingredients_bloom(top_food)
         st.write(ingredients)
     except Exception as e:
         st.error(f"Error generating ingredients: {e}")