Create app.py

app.py

@@ -0,0 +1,29 @@
+import os
+import gradio as gr
+
+from train_seallm_khm_sum import main as train_main
+
+HAS_TRAINED_FLAG = "TRAIN_DONE.flag"
+
+def maybe_run_training():
+    # Avoid retraining every restart
+    if os.path.exists(HAS_TRAINED_FLAG):
+        return "Training already finished."
+
+    train_main()
+    with open(HAS_TRAINED_FLAG, "w") as f:
+        f.write("ok")
+    return "Training finished. LoRA saved to ./seallm-khm-sum-lora"
+
+def ui_train():
+    msg = maybe_run_training()
+    return msg
+
+with gr.Blocks() as demo:
+    gr.Markdown("## SeaLLM Khmer Summarization Fine-tune")
+    btn = gr.Button("Run training (QLoRA on khm subset)")
+    out = gr.Textbox(lines=4)
+    btn.click(ui_train, outputs=out)
+
+if __name__ == "__main__":
+    demo.launch()