Update app.py

app.py

@@ -36,7 +36,7 @@ class GradioInference:
         )
 
         # Sentiment Classifier
-        self.classifier = pipeline("text-classification")
+        self.classifier = pipeline("text-classification", model="lxyuan/distilbert-base-multilingual-cased-sentiments-student", return_all_scores=False)
 
         
         self.tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum")
@@ -116,6 +116,7 @@ class GradioInference:
         )
         predicted = self.keyword_tokenizer.decode(output[0], skip_special_tokens=True)
         keywords = [x.strip() for x in predicted.split(",") if x.strip()]
+        formatted_keywords = "\n".join([f"• {keyword}" for keyword in keywords])
 
         progress(0.80, desc="Extracting Sentiment")
         # Sentiment label
@@ -132,7 +133,7 @@ class GradioInference:
             return (
                 results["text"],
                 transcription_summary[0]["summary_text"],
-                keywords,
+                formatted_keywords,
                 label,
                 wordcloud_image,
             )
@@ -140,7 +141,7 @@ class GradioInference:
             return (
                 results["text"],
                 summary,
-                keywords,
+                formatted_keywords,
                 label,
                 wordcloud_image,
             )
@@ -219,6 +220,7 @@ class GradioInference:
         )
         predicted = self.keyword_tokenizer.decode(output[0], skip_special_tokens=True)
         keywords = [x.strip() for x in predicted.split(",") if x.strip()]
+        formatted_keywords = "\n".join([f"• {keyword}" for keyword in keywords])
 
         progress(0.80, desc="Extracting Sentiment")
         # Sentiment label    
@@ -235,7 +237,7 @@ class GradioInference:
             return (
                 results["text"],
                 transcription_summary[0]["summary_text"],
-                keywords,
+                formatted_keywords,
                 label,
                 wordcloud_image,
             )
@@ -243,7 +245,7 @@ class GradioInference:
             return (
                 results["text"],
                 summary,
-                keywords,
+                formatted_keywords,
                 label,
                 wordcloud_image,
             )