import gradio as gr
import json
import os

def check_status():
    return "🧬 EVEZ Training Pipeline\n\nStatus: Space online (CPU)\nTraining data: 96 examples loaded\n\n⚠️ For GPU training: Settings → Hardware → T4 GPU ($0.05/hr)"

def run_training(epochs, lr):
    try:
        import torch
        if not torch.cuda.is_available():
            return "⚠️ No GPU. Enable T4 in Space Settings → Hardware → Factory Rebuild."
        return f"🧠 Training: {epochs} epochs, lr={lr}\nGPU: {torch.cuda.get_device_name(0)}"
    except ImportError:
        return "⚠️ PyTorch missing. Enable GPU hardware to install torch."

with gr.Blocks(title="EVEZ Trainer") as demo:
    gr.Markdown("# 🧬 EVEZ Self-Training Pipeline\nnFine-tune on 96 EVEZ instruction pairs.")
    with gr.Row():
        epochs = gr.Slider(1, 10, value=3, step=1, label="Epochs")
        lr = gr.Slider(1e-6, 1e-3, value=2e-4, label="Learning Rate")
    train_btn = gr.Button("Start Training", variant="primary")
    output = gr.Textbox(label="Output", lines=10)
    train_btn.click(run_training, [epochs, lr], output)

if __name__ == "__main__":
    demo.launch()