app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

# تحميل النموذج من Hugging Face
model_id = "silma-ai/SILMA-9B-Instruct-v1.0"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.bfloat16)

# دالة تنفيذ التلخيص
def summarize(text):
    prompt = f"[INST] قم بتلخيص النص التالي بطريقة واضحة:\n{text} [/INST]"
    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
    outputs = model.generate(**inputs, max_new_tokens=256)
    summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return summary

# إنشاء واجهة `Gradio`
iface = gr.Interface(fn=summarize, inputs="text", outputs="text", title="SILMA AI Summarizer")
iface.launch()