update app.py

app.py

@@ -16,7 +16,7 @@ def predict_sentiment(text):
         encoding = tokenizer_sentiment(text, return_tensors='pt', truncation=True, padding=True, max_length=128)
         output = model_sentiment(**encoding)
         pred = torch.argmax(output.logits, dim=1).item()
-    sentiment_labels = ["Negative", "Neutral", "Positive"]  # Cập nhật nhãn nếu cần
+    sentiment_labels = ["Tiêu cực", "Trung lập", "Tích cực"]
     return sentiment_labels[pred]  # Trả về nhãn cảm xúc
 
 def predict_topic(text):
@@ -25,28 +25,23 @@ def predict_topic(text):
         encoding = tokenizer_topic(text, return_tensors='pt', truncation=True, padding=True, max_length=128)
         output = model_topic(**encoding)
         pred = torch.argmax(output.logits, dim=1).item()
-    topic_labels = ["Topic 0", "Topic 1", "Topic 2", "Topic 3"]  # Cập nhật nhãn nếu cần
+    topic_labels = ["Giảng viên", "Chương trình đào tạo", "Cơ sở vật chất", "Khác"]
     return topic_labels[pred]  # Trả về nhãn chủ đề
 
-# Create Gradio Interface
-iface_sentiment = gr.Interface(
-    fn=predict_sentiment,
-    inputs="text",
-    outputs="text",
-    title="Sentiment Classifier",
-    description="Classify sentiment as Positive, Neutral, or Negative."
-)
+# Define a function to handle both predictions at once
+def classify_sentiment_and_topic(text):
+    sentiment = predict_sentiment(text)
+    topic = predict_topic(text)
+    return sentiment, topic
 
-iface_topic = gr.Interface(
-    fn=predict_topic,
-    inputs="text",
-    outputs="text",
-    title="Topic Classifier",
-    description="Classify the topic of the text."
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=classify_sentiment_and_topic,
+    inputs=gr.Textbox(label="Enter text for Classification", placeholder="Type your text here..."),
+    outputs=[gr.Textbox(label="Sentiment Output"), gr.Textbox(label="Topic Output")],
+    title="Vietnamese students Feedback Corpus Classifier",
+    description="Classify the sentiment and topic of a given text into separate outputs."
 )
 
-# Create Tabbed Interface
-tabbed_interface = gr.TabbedInterface([iface_sentiment, iface_topic], ["Sentiment", "Topic"])
-
 # Launch the app
-tabbed_interface.launch()
+iface.launch()