Update app.py

app.py

@@ -1,14 +1,13 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 """
-Gradio App - Intelligent Stacking Classifier (Dark Mode, Cards + Loading)
+Gradio App - Intelligent Stacking Classifier (Dark Mode + Cards)
 """
 import gradio as gr
 import numpy as np
 import joblib
 import re
 from pathlib import Path
-from time import sleep  # para simular loading (se necessário)
 
 # Sklearn
 from sklearn.feature_extraction.text import TfidfVectorizer
@@ -135,9 +134,7 @@ class PortugueseClassifier:
 classifier = PortugueseClassifier()
 
 
-def classify_text_with_loading(text):
-    """Simula loading, depois retorna cards"""
-    sleep(0.5)  # delay curto para efeito visual de loading
+def classify_text(text):
     preds = classifier.predict(text)
     cards = ""
     for p in preds[:10]:
@@ -149,21 +146,20 @@ def classify_text_with_loading(text):
 
         cards += f"""
         <div style="
-            border-left: 6px solid {color};
+            border-left: 5px solid {color};
             background-color:#1E1E1E;
-            padding:12px;
-            margin-bottom:10px;
-            border-radius:8px;
-            transition: transform 0.2s;
+            padding:10px;
+            margin-bottom:8px;
+            border-radius:6px;
         ">
-            <strong style="color:#fff; font-size:16px;">{label}</strong> {emoji}<br>
+            <strong style="color:#fff">{label}</strong> {emoji}<br>
             <small style="color:#ccc">Probability: {prob:.1%}</small>
         </div>
         """
     return cards
 
 
-# CSS Dark Theme + smooth
+# Dark theme CSS
 css = """
 body { background-color: #121212; color: #f5f5f5; font-family: 'Segoe UI', sans-serif; }
 h1, h2, h3, h4 { color: #1E90FF; }
@@ -171,7 +167,6 @@ input, textarea { background-color: #1E1E1E; color: #f5f5f5; border: 1px solid #
 button { background-color: #1E90FF; color: white; border-radius: 6px; border: none; }
 .gradio-container { background-color: #121212; }
 .output_html { background-color: #121212; color: #f5f5f5; }
-.progress-bar { height: 4px; background-color:#1E90FF; width:0%; transition: width 0.5s; border-radius:2px; }
 """
 
 with gr.Blocks(css=css, theme=None) as demo:
@@ -182,16 +177,9 @@ with gr.Blocks(css=css, theme=None) as demo:
             text_input = gr.Textbox(label="Enter Portuguese administrative text", lines=10,
                                     placeholder="Cole aqui o texto do documento...")
             classify_btn = gr.Button("🔍 Classify")
-            progress = gr.HTML("<div class='progress-bar' id='loading-bar'></div>")
         with gr.Column():
             output = gr.HTML(label="Predicted Categories")
 
-    def wrapped_click(text):
-        progress_bar = "<div class='progress-bar' style='width:100%'></div>"
-        # animação temporária
-        result = classify_text_with_loading(text)
-        return result
-
-    classify_btn.click(wrapped_click, inputs=text_input, outputs=output)
+    classify_btn.click(classify_text, inputs=text_input, outputs=output)
 
 demo.launch()