app.py

import gradio as gr
from transformers import pipeline
from PIL import Image
import torch
import re

# —————————————————————————————
# 1. CLASSIFICATION D’INGReDIENTS
# —————————————————————————————
INGREDIENT_MODEL_ID = "stchakman/Fridge_Items_Model"
ingredient_classifier = pipeline(
    "image-classification",
    model=INGREDIENT_MODEL_ID,
    device=0 if torch.cuda.is_available() else -1,
    top_k=4
)

# —————————————————————————————
# 2. MODeLE DE GeNeRATION
# —————————————————————————————
recipe_generator = pipeline(
    "text2text-generation",
    model="flax-community/t5-recipe-generation",
    device=0 if torch.cuda.is_available() else -1
)

# —————————————————————————————
# 3. FONCTION PRINCIPALE
# —————————————————————————————
def generate_recipe(image: Image.Image):
    try:
        # Detection ingredients
        results = ingredient_classifier(image)
        ingredients = [res["label"].lower() for res in results]
        if not ingredients:
            return {
                "error": "Aucun ingredient detecte.",
                "ingredients_detected": []
            }

        prompt = ", ".join(ingredients)
        generated = recipe_generator(prompt, max_length=200)[0]["generated_text"]

        # extraction par expressions regulieres
        title_match = re.search(r"title\s*:\s*(.+?)(ingredients\s*:|$)", generated, re.IGNORECASE | re.DOTALL)
        ingredients_match = re.search(r"ingredients\s*:\s*(.+?)(directions\s*:|$)", generated, re.IGNORECASE | re.DOTALL)
        directions_match = re.search(r"directions\s*:\s*(.+)", generated, re.IGNORECASE | re.DOTALL)

        title = title_match.group(1).strip() if title_match else None
        ingredients_list = ingredients_match.group(1).strip().split('\n') if ingredients_match else []
        directions_raw = directions_match.group(1).strip() if directions_match else None
        directions_list = re.split(r"\.\s*", directions_raw) if directions_raw else []

        # nettoyage des listes
        ingredients_list = [line.strip("- ").strip() for line in ingredients_list if line.strip()]
        directions_list = [step.strip("- ").strip() for step in directions_list if step.strip()]

        return {
            "ingredients_detected": ingredients,
            "generated": {
                "title": title,
                "ingredients": ingredients_list,
                "instructions": directions_list
            }
        }

    except Exception as e:
        return {"error": str(e)}

# —————————————————————————————
# 4. INTERFACE GRADIO
# —————————————————————————————
interface = gr.Interface(
    fn=generate_recipe,
    inputs=gr.Image(type="pil", label="📷 Image de vos ingredients"),
    outputs=gr.JSON(),
    title="🥕 Generateur de Recettes",
    description="Deposez une image d'ingredients pour generer une recette automatiquement (resultat JSON structure).",
    allow_flagging="never"
)

if __name__ == "__main__":
    interface.launch(share=True)