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app.py

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+import gradio as gr
+import subprocess
+import os
+
+def train_model():
+    """Start training the CELESTIAL model"""
+    try:
+        result = subprocess.run(["python", "train_celestial.py"], 
+                              capture_output=True, text=True, timeout=3600)
+        return f"Training Output:\n{result.stdout}\n\nErrors:\n{result.stderr}"
+    except Exception as e:
+        return f"Training failed: {e}"
+
+def test_model(prompt):
+    """Test the trained model"""
+    # This would load and test the trained model
+    return f"Testing with prompt: {prompt}\n\nThis is a placeholder response."
+
+# Create Gradio interface
+with gr.Blocks(title="CELESTIAL Mistral 7B v0.3 Training") as demo:
+    gr.Markdown("# 🌟 CELESTIAL Spiritual AI Training")
+    gr.Markdown("Train and test Mistral 7B v0.3 for comprehensive spiritual guidance")
+    
+    with gr.Tab("Training"):
+        train_btn = gr.Button("🚀 Start Training", variant="primary")
+        train_output = gr.Textbox(label="Training Output", lines=20)
+        train_btn.click(train_model, outputs=train_output)
+    
+    with gr.Tab("Testing"):
+        test_input = gr.Textbox(label="Test Prompt", 
+                               placeholder="What is the significance of Om mantra?")
+        test_btn = gr.Button("🧪 Test Model")
+        test_output = gr.Textbox(label="Model Response", lines=10)
+        test_btn.click(test_model, inputs=test_input, outputs=test_output)
+
+if __name__ == "__main__":
+    demo.launch()