Upload app.py with huggingface_hub

app.py

@@ -41,16 +41,13 @@ SPACE_NAME = os.getenv("HF_SPACE_NAME", "phi4training")
 # Function to start the training process
 def start_training():
     try:
-        # Run the training script using HF's native logging
-        process = subprocess.Popen(
-            ["python", "run_cloud_training.py"], 
-            stdout=subprocess.PIPE, 
-            stderr=subprocess.PIPE,
-            universal_newlines=True
-        )
+        # Run the training script directly - IMPORTANT: Don't redirect output so container logs show
+        # Using nohup to ensure process continues even if web request ends
+        os.system("nohup python run_cloud_training.py > training.log 2>&1 &")
         
         # Log the start of training
         logger.info("Training started - Check Hugging Face logs for details")
+        print("Training process initiated! This will appear in Hugging Face logs.")
         
         return """
         ✅ Training process initiated! 
@@ -125,4 +122,5 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
 if __name__ == "__main__":
     # Start Gradio with minimal features
     logger.info("Starting research training dashboard")
+    print("Research training dashboard started - Logs will be visible here")
     demo.launch(share=False)