Update app.py

app.py

@@ -8,7 +8,7 @@ tokenizer = BertTokenizer.from_pretrained('ProsusAI/finbert')
 # Load pre-trained model
 model = BertForSequenceClassification.from_pretrained('ProsusAI/finbert')
 
-def get_sentiment(입력):
+def get_sentiment(sec_text):  # Ensure the parameter name matches the placeholder name.
     # Encode the text
     tokens = tokenizer.encode_plus(sec_text, add_special_tokens=True, return_tensors="pt")
     
@@ -24,12 +24,20 @@ def get_sentiment(입력):
     # Return the sentiment analysis result
     return f"{sentiment} Sentiment"
 
+# Custom CSS to center the title
+custom_css = """
+    .title {
+        text-align: center;
+    }
+"""
+
 # Define the Gradio interface
 gr_interface = gr.Interface(
     fn=get_sentiment,
-    inputs=gr.Textbox(lines=1, placeholder="..."),
+    inputs=gr.Textbox(lines=1, placeholder=""),
     outputs="text",
-    title="Sentiment Analysis"
+    title="Sentiment Analysis",
+    css=custom_css  # Add the custom CSS to the Interface
 )
 
 # Launch the interface