Upload app.py

app.py

@@ -0,0 +1,58 @@
+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 – Clean & Smart",
+    description="Search by name, brand, or reference. Warnings styled cleanly with one emoji max."
+)
+
+demo.launch()