Create app.py

app.py

@@ -0,0 +1,28 @@
+import pandas as pd
+import gradio as gr
+
+from datasets import load_dataset
+
+LOGS_DATASET_URI = 'pgurazada1/machine-failure-mlops-demo-logs'
+
+
+def get_data():
+    """
+    Connect to the HuggingFace dataset where the logs are stored.
+    Pull the data into a dataframe
+    """
+    data = load_dataset(LOGS_DATASET_URI)
+    data_df = data['train'].to_pandas()
+
+    return data_df
+
+# Every 5 seconds, pull in the latest data from the dataset and make a 
+# Bar plot of the predictions
+    
+with gr.Blocks() as demo:
+    gr.Demo("Real-time Monitoring Dashboard")
+    with gr.Row():
+        with gr.Column():
+            gr.BarPlot(get_data, every=5, x='prediction', width=500, height=500)
+
+demo.queue().launch()