from transformers import pipeline
import gradio as gr

# Pipeline
pipe = pipeline("text-classification", model="AbrorBalxiyev/my_awesome_model", return_all_scores=True)

# Gradio interfeysi uchun funksiyani qayta yozish
def classify_text(text):
    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"
    
    return result
# Gradio interfeysi
iface = gr.Interface(
    fn=classify_text,
    inputs=[
        gr.Textbox(
            placeholder="Enter text to classify...",
            label=None,
            lines=3
        )
    ],
    outputs=gr.HTML(),
    title="Text Category Classification",
    css="""
        .gradio-container {
            font-family: Arial, sans-serif;
        }
        .gradio-interface {
            max-width: 800px !important;
        }
        #component-0 {
            border-radius: 8px;
            border: 1px solid #ddd;
        }
        .submit-button {
            background-color: #ff6b33 !important;
        }
        .clear-button {
            background-color: #f0f0f0 !important;
            color: #333 !important;
        }
    """,
    examples=[
        ["Messi jahon chempioni bo'ldi"],
        ["Yangi iPhone 15 Pro Max sotuvga chiqdi"],
        ["Kitob o'qish foydali"],
        ["Toshkentda ob-havo issiq"]
    ]
)

iface.launch(share=True)