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app.py

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+#!/usr/bin/env python
+
+"""
+Gradio app for R1-Distill-LLama-8b training interface.
+"""
+
+import os
+import sys
+import json
+import gradio as gr
+import subprocess
+from pathlib import Path
+import logging
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+    handlers=[logging.StreamHandler(sys.stdout)]
+)
+logger = logging.getLogger(__name__)
+
+def load_config(config_path):
+    """Load a JSON configuration file."""
+    try:
+        with open(config_path, 'r') as f:
+            return json.load(f)
+    except Exception as e:
+        logger.error(f"Error loading config from {config_path}: {e}")
+        return None
+
+def start_training():
+    """Start the training process."""
+    try:
+        # Check if training is already in progress
+        lock_file = Path("TRAINING_IN_PROGRESS.lock")
+        if lock_file.exists():
+            return "Training is already in progress. Please wait for it to complete."
+        
+        # Start training script
+        cmd = [sys.executable, "run_transformers_training.py"]
+        process = subprocess.Popen(
+            cmd,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT,
+            universal_newlines=True
+        )
+        
+        # Return immediate confirmation
+        return "Training started successfully! Check the logs for progress."
+    except Exception as e:
+        logger.error(f"Error starting training: {e}")
+        return f"Error starting training: {str(e)}"
+
+def check_training_status():
+    """Check the current status of training."""
+    try:
+        # Check lock file
+        lock_file = Path("TRAINING_IN_PROGRESS.lock")
+        if not lock_file.exists():
+            return "No training in progress"
+        
+        # Read lock file content
+        with open(lock_file, 'r') as f:
+            status = f.read()
+        return f"Training in progress:\n{status}"
+    except Exception as e:
+        logger.error(f"Error checking training status: {e}")
+        return f"Error checking status: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks(title="R1-Distill-LLama-8b Training") as demo:
+    gr.Markdown("# R1-Distill-LLama-8b Training Interface")
+    gr.Markdown("This interface allows you to control and monitor the training process.")
+    
+    with gr.Row():
+        start_btn = gr.Button("Start Training")
+        status_btn = gr.Button("Check Status")
+    
+    output = gr.Textbox(label="Output", lines=5)
+    
+    start_btn.click(start_training, outputs=output)
+    status_btn.click(check_training_status, outputs=output)
+
+if __name__ == "__main__":
+    demo.launch()