Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| # Ensure SentencePiece is installed | |
| try: | |
| import sentencepiece | |
| except ImportError: | |
| st.error("SentencePiece is not installed. Please install it using: pip install sentencepiece") | |
| st.stop() | |
| # Load the model and tokenizer with caching | |
| def load_model(): | |
| model_name = "flax-community/t5-recipe-generation" | |
| try: | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name) | |
| # Explicitly set to CPU and use float32 to reduce memory usage | |
| model = model.to('cpu').float() | |
| return tokenizer, model | |
| except Exception as e: | |
| st.error(f"Error loading model: {e}") | |
| st.stop() | |
| # Generate recipe function with error handling | |
| def generate_recipe(ingredients, tokenizer, model, max_length=512): | |
| # Prepare input | |
| input_text = f"Generate recipe with: {ingredients}" | |
| try: | |
| # Use torch no_grad to reduce memory consumption | |
| with torch.no_grad(): | |
| input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=max_length, truncation=True) | |
| # Adjust generation parameters for faster CPU inference | |
| output_ids = model.generate( | |
| input_ids, | |
| max_length=max_length, | |
| num_return_sequences=1, | |
| no_repeat_ngram_size=2, | |
| num_beams=4, # Reduced beam search for faster CPU processing | |
| early_stopping=True | |
| ) | |
| # Decode and clean the output | |
| recipe = tokenizer.decode(output_ids[0], skip_special_tokens=True) | |
| return recipe | |
| except Exception as e: | |
| st.error(f"Error generating recipe: {e}") | |
| return None | |
| # Streamlit app | |
| def main(): | |
| st.title("🍳 AI Recipe Generator") | |
| # Sidebar for input | |
| st.sidebar.header("Ingredient Input") | |
| ingredients_input = st.sidebar.text_area( | |
| "Enter ingredients (comma-separated):", | |
| placeholder="e.g. chicken, tomatoes, onions, garlic" | |
| ) | |
| # Load model | |
| tokenizer, model = load_model() | |
| # Generate button | |
| if st.sidebar.button("Generate Recipe"): | |
| if ingredients_input: | |
| with st.spinner("Generating recipe..."): | |
| recipe = generate_recipe(ingredients_input, tokenizer, model) | |
| if recipe: | |
| # Display recipe sections | |
| st.subheader("🥘 Generated Recipe") | |
| st.write(recipe) | |
| else: | |
| st.error("Failed to generate recipe. Please try again.") | |
| else: | |
| st.warning("Please enter some ingredients!") | |
| # Additional UI elements | |
| st.sidebar.markdown("---") | |
| st.sidebar.info("Enter ingredients and click 'Generate Recipe'") | |
| if __name__ == "__main__": | |
| main() |