import gradio as gr
import pandas as pd

df = pd.read_csv("filtered_openfoodfacts(Sheet1).csv", sep=";", encoding="utf-8")
df.columns = [col.lower().replace(" ", "_") for col in df.columns]
df = df[df['warning'].str.lower() != 'warning']

def search_product(query, filters):
    query = query.strip().lower()
    filtered_df = df.copy()

    for f in filters:
        filtered_df = filtered_df[filtered_df['labels_tags'].str.lower().str.contains(f.lower(), na=False)]

    matched = filtered_df[
        filtered_df['product_reference'].str.lower().str.contains(query, na=False) |
        filtered_df['product_brand'].str.lower().str.contains(query, na=False) |
        filtered_df['product_name'].str.lower().str.contains(query, na=False)
    ]

    if matched.empty:
        return "❌ Product not found."

    result = ""
    for _, row in matched.head(3).iterrows():
        result += f"🔎 Reference: {row.get('product_reference', '-') }\n"
        result += f"🏷️ Brand: {row.get('product_brand', '-') }\n"
        result += f"🧾 Product: {row.get('product_name', '-') }\n"
        result += f"- Ingredients: {row.get('ingredients_text', '-') }\n"
        result += f"- Additives: {row.get('additives', '-') }\n"
        result += f"- Allergens: {row.get('allergens', '-') }\n"
        result += f"- Tags: {row.get('labels_tags', '-') }\n"
        warning = str(row.get('warning', '')).strip()
        if warning and warning.lower() != "none":
            cleaned = warning.lower().replace("⚠️", "").replace("✅", "").replace("warning:", "").strip().capitalize()
            if "safe for general consumption" in cleaned.lower():
                result += f"✅ {cleaned}\n"
            else:
                result += f"⚠️ {cleaned}\n"
        result += "\n"

    return result.strip()

demo = gr.Interface(
    fn=search_product,
    inputs=[
        gr.Textbox(label="Search by product name, brand or REF code"),
        gr.CheckboxGroup(
            choices=["vegan", "organic", "gluten-free", "lactose-free", "halal", "kosher"],
            label="Filter by tags"
        )
    ],
    outputs=gr.Textbox(label="Product Details"),
    title="NutriCheck Bot",
    description="Search by name, brand, or reference. Warnings styled cleanly with one emoji max."
)

demo.launch()