Update app.py

app.py

@@ -1,17 +1,41 @@
 import streamlit as st
+import pandas as pd
 
-from transformers import pipeline
+# Placeholder data structures (replace with actual data sources)
+drivers = pd.DataFrame(columns=["driver_id", "name", "location", "status"])
+orders = pd.DataFrame(columns=["order_id", "pickup_location", "dropoff_location", "status"])
+zone_pressure = {}  # Dictionary to store zone pressure data
 
-# Initialize the sentiment analysis pipeline
+# Basic UI structure
+st.title("Dispatch Call Scheduler")
 
-pipe = pipeline('sentiment-analysis') 
+# Sidebar for navigation and actions
+with st.sidebar:
+    st.header("Navigation")
+    selected_page = st.radio("Go to", ["Order Management", "Driver Management", "Zone Pressure", "Analytics"])
 
-# Create a text input area in the Streamlit app
+    st.header("Actions")
+    if st.button("Schedule Dispatch"):
+        # Logic to schedule a dispatch based on current data
+        st.write("Dispatch scheduled!")
 
-text = st.text_area('Enter some text!') 
+# Main content area based on selected page
+if selected_page == "Order Management":
+    st.subheader("Order Management")
+    # Display and manage order details (table, filters, etc.)
 
-# Process the text and display the results if there's input
+elif selected_page == "Driver Management":
+    st.subheader("Driver Management")
+    # Display and manage driver details (table, filters, etc.)
 
-if text:
-    out = pipe(text)
-    st.json(out)
+elif selected_page == "Zone Pressure":
+    st.subheader("Zone Pressure Monitoring")
+    # Visualize zone pressure data (heatmap, charts, etc.)
+
+elif selected_page == "Analytics":
+    st.subheader("Analytics Dashboard")
+    # Display key performance indicators and insights
+
+# Placeholder to display data
+st.write(drivers)
+st.write(orders)