Update app.py

app.py

@@ -23,6 +23,7 @@ def load_bloom_pipeline():
 
 pipe_bloom = load_bloom_pipeline()
 
+# Function to generate ingredients using BLOOM
 def get_ingredients_bloom(food_name):
     """
     Generate a list of ingredients for the given food item using BLOOM.
@@ -37,44 +38,4 @@ def get_ingredients_bloom(food_name):
         response = pipe_bloom(prompt, max_length=50, num_return_sequences=1)
         generated_text = response[0]["generated_text"].strip()
         
-        # Post-process the response
-        ingredients = generated_text.split(":")[-1].strip()  # Handle cases like "Ingredients: ..."
-        ingredients = ingredients.replace(".", "").strip()  # Remove periods and     return f"Error generating ingredients: {e}"
-
-# Streamlit app setup
-st.title("Food Image Recognition with Ingredients")
-
-# Add banner image
-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**: bigscience/bloom-1b7")
-
-# Upload image
-uploaded_file = st.file_uploader("Choose a food image...", type=["jpg", "png", "jpeg"])
-
-if uploaded_file is not None:
-    # Display the uploaded image
-    image = Image.open(uploaded_file)
-    st.image(image, caption="Uploaded Image", use_column_width=True)
-    st.write("Classifying...")
-
-    # Make predictions
-    predictions = pipe_classification(image)
-
-    # Display only the top prediction
-    top_food = predictions[0]['label']
-    st.header(f"Food: {top_food}")
-
-    # Generate and display ingredients for the top prediction
-    st.subheader("Ingredients")
-    try:
-        ingredients = get_ingredients_bloom(top_food)
-        st.write(ingredients)
-    except Exception as e:
-        st.error(f"Error generating ingredients: {e}")
-
-# Footer
-st.sidebar.markdown("Created with ❤️ using Streamlit and Hugging Face.")
+        # Post-process the response