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

# 4 نماذج لتوليد الكود
models = {
    "CodeGen (Salesforce)": "Salesforce/codegen-2B-multi",
    "StarCoder": "bigcode/starcoder",
    "WizardCoder": "WizardLM/WizardCoder-1B-V1.0",
    "Phind LLaMA": "Phind/phind-codeLlama-34b-v2"
}

# تحميل النماذج
loaded_models = {}
for name, model_id in models.items():
    tokenizer = AutoTokenizer.from_pretrained(model_id)
    model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.float16)
    loaded_models[name] = (tokenizer, model)

# دالة توليد الكود
def generate_code(prompt, model_name):
    tokenizer, model = loaded_models[model_name]
    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
    outputs = model.generate(**inputs, max_new_tokens=150)
    code = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return code

# واجهة Gradio
demo = gr.Interface(
    fn=generate_code,
    inputs=[
        gr.Textbox(lines=5, label="اكتب وصف الكود (بالإنجليزية)"),
        gr.Radio(choices=list(models.keys()), label="اختر النموذج")
    ],
    outputs=gr.Code(label="الكود الناتج"),
    title="Code Generation with AI Models",
    description="اختر نموذج AI وادخل وصف الكود ليتم توليده تلقائيًا"
)

demo.launch()