Update app.py

app.py

@@ -1,6 +1,7 @@
 from transformers import pipeline
 import requests
 import json
+import gradio as gr
 
 pipe = pipeline("translation", "guymorlan/TokenizerLabeller")
 
@@ -9,23 +10,26 @@ pipe = pipeline("translation", "guymorlan/TokenizerLabeller")
 r = requests.get("https://huggingface.co/guymorlan/TokenizerLabeller/raw/main/playaling_words.json")
 data = json.loads(r.text)
 
-
 # built gradio interface
-import gradio as gr
 
 def predict(input):
 
     out = pipe(input)[0]['translation_text']
-    out = [x.strip() for x in out.split("+")]
+    out = [x.strip() for x in out.split(" + ")]
 
-    output =  ""
+    output =  "<div style='direction: rtl; text-align: right; font-size: 20px; font-family: sans-serif; line-height: 1.5'>"
     for o in out:
-        if o in data:
-            output += f"<span style='color: green' title='{data[o]['translation']}\n{data[o]['features']}'>{data[o]['word']}</span> "
-        else:
-            output += o + " "
-
-    return output
+        oo = [x.strip() for x in o.split("+")]
+        newout = []
+        for ooo in oo:
+            if ooo in data:
+                newout.append(f"<span style='color: green' title='{data[ooo]['translation']}\n{data[ooo]['features']}'>{data[ooo]['word']}</span>")
+            else:
+                newout.append(ooo)
+                        
+        output += "+".join(newout) + " | "
+
+    return output[:-3] + "</div>"
 
 
 gr.Interface(predict, "textbox", "html", title="Ammiya Tokenizer", description="Tokenize Ammiya text and show Playaling words").launch()