update

app.py

@@ -105,12 +105,11 @@ def run(barcode: str, min_threshold: float = 0.5):
         text = prediction["text"]
         filtered_entities = [e for e in entities if e["score"] >= min_threshold]
 
-        if filtered_entities:
-            st.divider()
-            image_path = generate_image_path(barcode, image_id)
-            image_url = f"https://static.openfoodfacts.org/images/products{image_path}"
-            st.image(image_url)
-            display_ner_tags(text, filtered_entities)
+        st.divider()
+        image_path = generate_image_path(barcode, image_id)
+        image_url = f"https://static.openfoodfacts.org/images/products{image_path}"
+        st.image(image_url)
+        display_ner_tags(text, filtered_entities)
 
 
 query_params = st.experimental_get_query_params()
@@ -118,9 +117,10 @@ default_barcode = query_params["barcode"][0] if "barcode" in query_params else "
 
 st.title("Ingredient extraction demo")
 st.markdown(
-    "This demo leverages the ingredient entity detection model, that takes the OCR text as input and predict ingredient lists."
+    "This demo leverages the ingredient entity detection model, "
+    "that takes the OCR text as input and predict ingredient lists."
 )
-barcode = st.text_input("barcode", help="Barcode of the product", value=default_barcode)
+barcode = st.text_input("barcode", help="Barcode of the product", value=default_barcode).strip()
 threshold = st.number_input(
     "threshold",
     help="Minimum threshold for entity predictions",