import gradio as gr
from transformers import pipeline

# تحميل نموذج التصحيح الموثوق من CAMeL-Lab
CORRECTOR_MODEL_ID = "CAMeL-Lab/arabart-qalb15-gec-ged-13"

try:
    # هذا النموذج يستخدم "text2text-generation"
    corrector_pipe = pipeline("text2text-generation", model=CORRECTOR_MODEL_ID)
    print("Text correction pipeline loaded successfully!")
except Exception as e:
    print(f"Error loading pipeline: {e}")
    corrector_pipe = None

# دالة لتصحيح النص
def correct_text(text_input):
    if corrector_pipe is None:
        return "Error: Model pipeline could not be loaded."
    if not text_input or not text_input.strip():
        return "Please provide text to correct."

    try:
        # نقوم بتمرير النص مباشرة إلى النموذج
        corrected_result = corrector_pipe(text_input, max_length=1024)
        corrected_text = corrected_result[0]['generated_text']
        
        return corrected_text
    except Exception as e:
        return f"An error occurred: {str(e)}"

# الواجهة تستقبل نصًا كمُدخل وتُخرج نصًا مصححًا
gr.Interface(
    fn=correct_text,
    inputs=gr.Textbox(lines=5, label="النص الأصلي"),
    outputs=gr.Textbox(label="النص المصحح"),
    title="Arabic Text Correction (Service B)",
    description="This service corrects Arabic text using the AraBART GEC model."
).launch(debug=True)