update app.py

app.py

@@ -1,23 +1,31 @@
-import gradio as gr
 from transformers import pipeline
+import gradio as gr
 
-# Pipeline-ni o'rnatish
-pipe = pipeline("text-classification", model="AbrorBalxiyev/my_awesome_model")
+# Pipeline
+pipe = pipeline("text-classification", model="AbrorBalxiyev/my_awesome_model", return_all_scores=True)
 
-# Klassifikatsiya funksiyasi
+# Gradio interfeysi uchun funksiyani qayta yozish
 def classify_text(text):
-    results = pipe(text)
-    output = {result['label']: f"{result['score'] * 100:.2f}%" for result in results[0]}
-    return output
-
-# Gradio interfeysini yaratish
-with gr.Blocks() as demo:
-    gr.Markdown("## Text Classification Pipeline")
-    text_input = gr.Textbox(label="Enter Text", placeholder="Type something here...")
-    output_label = gr.Label(label="Classification Results")
-    classify_button = gr.Button("Classify")
+    results = pipe(text)[0]
+    results.sort(key=lambda x: x["score"], reverse=True)
+    result = ""
+    for item in results:
+        percentage = item["score"] * 100
+        result += f"{item['label']}: {percentage:.1f}%\n"
     
-    classify_button.click(classify_text, inputs=text_input, outputs=output_label)
+    return result
+# Gradio interfeysi
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(placeholder="Enter text to classify...", label="Input Text"),
+    outputs=gr.Textbox(label="Classification Results"),
+    title="Text Category Classification",
+    description="Enter text to see its category classification percentages.",
+    examples=[
+        ["Mercedes is one of the best quality cars."],
+        ["Perevalda Damas va Lacetti avtomobillari avtoxalokatga uchradi"],
+        ["Kitob o'qish foydali"]
+    ]
+)
 
-# Interfeysni ishga tushirish
-demo.launch()
+iface.launch()