app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

st.set_page_config(page_title="Chat with AI", page_icon="🤖")
st.title("💬 دردشة مع AI")

@st.cache_resource(show_spinner="جاري التحميل...")
def load_model():
    # نستخدم نسخة أصغر وأبسط
    model_name = "microsoft/DialoGPT-large"  # حجمه 1.3GB فقط
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    model = AutoModelForCausalLM.from_pretrained(model_name)
    return tokenizer, model

tokenizer, model = load_model()

if "messages" not in st.session_state:
    st.session_state.messages = []

for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

if prompt := st.chat_input("اكتب رسالتك..."):
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    with st.chat_message("assistant"):
        with st.spinner("جاري التفكير..."):
            # تجهيز الإدخال
            inputs = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors="pt")
            
            # توليد الرد
            with torch.no_grad():
                outputs = model.generate(
                    inputs,
                    max_length=1000,
                    pad_token_id=tokenizer.eos_token_id,
                    do_sample=True,
                    temperature=0.7
                )
            
            response = tokenizer.decode(outputs[:, inputs.shape[-1]:][0], skip_special_tokens=True)
            st.markdown(response)
    
    st.session_state.messages.append({"role": "assistant", "content": response})