Fix: Abort if text ist not eng

app.py

@@ -112,7 +112,7 @@ def is_eng(review: str):
     lang_label = lang_labels[0]
     lang_prob = float(lang_probs[0])
 
-    return lang_label[1] == "__label__en", lang_prob
+    return lang_label[1] == "__label__en", lang_label[1], lang_prob
 
 ### Do actual prediction #########################################################
 @spaces.GPU(duration=10)  # Sekunden GPU-Zeit pro Call
@@ -120,23 +120,32 @@ def predict(review: str):
 
     review = (review or "").strip()
 
+    # Abort if no text if given
     if not review:
         # immer zwei Outputs zurückgeben
         return "<i>Please enter a review.</i>", {}
     
+    # Check for lang of text
+    review_is_eng, review_lang_label, review_lang_prob = is_eng(review)
+
+    # Abort if text is not english
+    if not review_is_eng:
+        # immer zwei Outputs zurückgeben
+        return "<i>English texts only</i>", {"is_en": {
+            "lang": review_lang_label.replace("__label__", ""),
+            "prob": review_lang_prob
+        }}
+    
     prediction_flavours = {}
     prediction_flavours_list = [0, 0, 0, 0, 0, 0, 0, 0]
 
-    review_is_eng, review_is_eng_prob = is_eng(review)
-
-    if review_is_eng:
-        # Do actual predictions if is english and whisky note
-        t_start_flavours = time.time()
-        prediction_flavours = predict_flavours(review, model_flavours, tokenizer_flavours, device)
-        prediction_flavours_list = list(prediction_flavours.values())
-        t_end_flavours = time.time()
+    # Do actual predictions if is english and whisky note
+    t_start_flavours = time.time()
+    prediction_flavours = predict_flavours(review, model_flavours, tokenizer_flavours, device)
+    prediction_flavours_list = list(prediction_flavours.values())
+    t_end_flavours = time.time()
 
-        #html_out = f"<b>{html.escape(review)}</b>"
+    #html_out = f"<b>{html.escape(review)}</b>"
 
     html_out = build_svg_with_values(prediction_flavours_list)
 
@@ -145,10 +154,6 @@ def predict(review: str):
         "model": FILENAME,
         "device": device,
         "duration": round((t_end_flavours - t_start_flavours), 3),
-        "is_en": {
-            "is": review_is_eng,
-            "prob": review_is_eng_prob
-        },
         "results": [{
                 #'icon': ICONS[name],
                 "name": name,