app.py

import gradio as gr
import subprocess
import os

logs = []
inference_logs = []

# تأكد من أن مجلد /data موجود وآمن للكتابة
DATA_DIR = os.path.join(os.getcwd(), "data")
os.makedirs(DATA_DIR, exist_ok=True)

def run_training():
    global logs
    logs = []

    # تنفيذ سكربت التدريب
    process = subprocess.Popen(
        ["python", "run.py"],
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT,
        text=True,
        bufsize=1
    )

    # عرض اللوجات بشكل مباشر
    for line in process.stdout:
        logs.append(line)
        yield "\n".join(logs[:])  # عرض آخر 50 سطر فقط

def run_inference():
    global inference_logs
    inference_logs = []
    output_lines = []

    # تنفيذ سكربت التنبؤ
    process = subprocess.Popen(
        ["python", "inference.py"],
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT,
        text=True,
        bufsize=1
    )

    for line in process.stdout:
        inference_logs.append(line)
        output_lines.append(line)

    # حفظ نتائج التنبؤ في ملف داخل /data
    inference_output_path = os.path.join(DATA_DIR, "inference_results.txt")
    with open(inference_output_path, "a") as f:
        f.write("=== New Inference Run ===\n")
        f.writelines(output_lines)
        f.write("\n")

    yield "\n".join(inference_logs[:])  # عرض آخر 50 سطر فقط

# واجهة Gradio
with gr.Blocks(title="VRP Transformer Training & Inference") as demo:
    gr.Markdown("# 🚛 Vehicle Routing Problem Solver with Transformer + Reinforcement Learning")

    with gr.Tab("🚀 Start Training"):
        with gr.Row():
            start_btn = gr.Button("Start Training")
        output = gr.Textbox(label="Training Logs", lines=25)
        start_btn.click(fn=run_training, outputs=output)

    with gr.Tab("🔍 Run Inference"):
        with gr.Row():
            infer_btn = gr.Button("Run Inference on New Batch")
        infer_output = gr.Textbox(label="Inference Results", lines=15)
        infer_btn.click(fn=run_inference, outputs=infer_output)

demo.launch()