Update app.py

app.py

@@ -76,25 +76,26 @@ def render_graph():
 
 def update_graph():
     for i in range(60):
-    # Update the graph with new inputs randomly
-    graph.node("📊 Data Collection", label=f"📊 Data Collection\nData {random.randint(0,100)}")
-    graph.node("🧹 Data Cleaning", label=f"🧹 Data Cleaning\nCleaned Data {random.randint(0,100)}")
-    graph.node("🔧 Data Transformation", label=f"🔧 Data Transformation\nTransformed Data {random.randint(0,100)}")
-    graph.node("🔎 Feature Engineering", label=f"🔎 Feature Engineering\nFeatures {random.randint(0,100)}")
-    graph.node("⚙️ Model Selection", label=f"⚙️ Model Selection\nSelected Model {random.randint(0,100)}")
-    graph.node("🎓 Model Training", label=f"🎓 Model Training\nTrained Model {random.randint(0,100)}")
-    graph.node("🚢 Model Deployment", label=f"🚢 Model Deployment\nDeployed Model {random.randint(0,100)}")
-    graph.node("📡 Model Serving", label=f"📡 Model Serving\nServed Model {random.randint(0,100)}")
-    graph.node("🔮 Predictions", label=f"🔮 Predictions\nPredicted Results {random.randint(0,100)}")
-    graph.node("👍 Feedback Collection", label=f"👍 Feedback Collection\nFeedback {random.randint(0,100)}")
-    graph.node("🤔 Feedback Processing", label=f"🤔 Feedback Processing\nProcessed Feedback {random.randint(0,100)}")
-    graph.node("✍️ Model Updating", label=f"✍️ Model Updating\nUpdated Model {random.randint(0,100)}")
-
-# Render the updated graph
-render_graph()
-
-# Wait for 1 second
-time.sleep(1)
+        # Update the graph with new inputs randomly
+        graph.node("📊 Data Collection", label=f"📊 Data Collection\nData {random.randint(0,100)}")
+        graph.node("🧹 Data Cleaning", label=f"🧹 Data Cleaning\nCleaned Data {random.randint(0,100)}")
+        graph.node("🔧 Data Transformation", label=f"🔧 Data Transformation\nTransformed Data {random.randint(0,100)}")
+        graph.node("🔎 Feature Engineering", label=f"🔎 Feature Engineering\nFeatures {random.randint(0,100)}")
+        graph.node("⚙️ Model Selection", label=f"⚙️ Model Selection\nSelected Model {random.randint(0,100)}")
+        graph.node("🎓 Model Training", label=f"🎓 Model Training\nTrained Model {random.randint(0,100)}")
+        graph.node("🚢 Model Deployment", label=f"🚢 Model Deployment\nDeployed Model {random.randint(0,100)}")
+        graph.node("📡 Model Serving", label=f"📡 Model Serving\nServed Model {random.randint(0,100)}")
+        graph.node("🔮 Predictions", label=f"🔮 Predictions\nPredicted Results {random.randint(0,100)}")
+        graph.node("👍 Feedback Collection", label=f"👍 Feedback Collection\nFeedback {random.randint(0,100)}")
+        graph.node("🤔 Feedback Processing", label=f"🤔 Feedback Processing\nProcessed Feedback {random.randint(0,100)}")
+        graph.node("✍️ Model Updating", label=f"✍️ Model Updating\nUpdated Model {random.randint(0,100)}")
+        
+        # Render the updated graph
+        render_graph()
+        
+        # Wait for 1 second
+        time.sleep(1)
+        
 # Render the initial graph
 render_graph()