app.py

import gradio as gr
from transformers import pipeline
import torch # We'll check if GPU is available, though CPU is likely our only option

# Load a very small, efficient Arabic model for text generation
# This model is much smaller and should fit the free CPU constraints
generator = pipeline("text-generation", model="asafaya/albert-base-arabic")

def generate_comeback_efficient(situation):
    # Prompt the model to provide a witty response
    prompt = f"الموقف: {situation}\nالرد الذكي والسريع:"
    
    # Generate the response with a small max_length for efficiency
    # Using 'do_sample=True' can lead to more creative (and sometimes funnier) responses
    result = generator(prompt, max_length=60, num_return_sequences=1, truncation=True, do_sample=True, top_k=50, top_p=0.95)
    comeback = result[0]['generated_text']
    
    # Clean up the output to only include the comeback part
    if "الرد الذكي والسريع:" in comeback:
        comeback = comeback.split("الرد الذكي والسريع:")[-1].strip()
        
    return comeback

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_comeback_efficient,
    inputs=gr.Textbox(lines=2, label="اكتب الموقف المحرج أو السؤال هنا"),
    outputs=gr.Textbox(lines=3, label="الرد الذكي!"),
    title="قاصف الجبهات الذكي (إصدار خفيف) - بواسطة عصوم",
    description="مولد ردود ذكية ومضحكة للمواقف المحرجة، يعمل بكفاءة على المعالج المجاني! تطوير Assoum!"
)

# Launch the app
interface.launch()