app.py

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()