import gradio as gr from transformers import pipeline # Load the model (this runs only once!) generator = pipeline("text2text-generation", model="LahiruProjects/recipe-generator-flan-t5") def generate_recipe(name, ingredients, calories, time): prompt = f"""Create a step-by-step recipe for "{name}" using these ingredients: {', '.join(ingredients.split(','))}. Keep it under {calories} calories and make sure it's ready in less than {time} minutes.""" result = generator(prompt) return result[0]["generated_text"] # Gradio interface iface = gr.Interface( fn=generate_recipe, inputs=[ gr.Textbox(label="Recipe Name"), gr.Textbox(label="Ingredients (comma-separated)"), gr.Number(label="Max Calories", value=400), gr.Number(label="Max Cooking Time (minutes)", value=30) ], outputs="text", title="🍳 Recipe Generator (FLAN-T5)", description="Generate a step-by-step recipe based on ingredients, calorie limit, and time" ) iface.launch()