Update app.py

app.py

@@ -1,85 +1,34 @@
 import streamlit as st
 import pandas as pd
-import plotly.express as px
-import numpy as np
-import time
-
-# Simulated data (you can replace this with data from salesforce_integration.py or simulator.py)
-def generate_mock_data(n=100):
-    np.random.seed(42)
-    data = {
-        "PoleID": [f"Pole_{i:05}" for i in range(n)],
-        "Site": np.random.choice(["Site 1", "Site 2", "Site 3", "Site 4"], n),
-        "SolarGen(kWh)": np.random.uniform(2.0, 6.0, n),
-        "WindGen(kWh)": np.random.uniform(0.5, 2.0, n),
-        "Tilt(°)": np.random.uniform(0, 15, n),
-        "Vibration(g)": np.random.uniform(0, 3, n),
-        "CameraStatus": np.random.choice(["Online", "Offline"], n),
-        "PowerSufficient": np.random.choice(["Yes", "No"], n),
-    }
-    df = pd.DataFrame(data)
-    
-    # Rule-based alert level
-    df["Anomalies"] = df.apply(lambda row: [
-        "LowSolarOutput" if row["SolarGen(kWh)"] < 4.0 else "",
-        "LowWindOutput" if row["WindGen(kWh)"] < 0.7 else "",
-        "PoleTiltRisk" if row["Tilt(°)"] > 10 else "",
-        "VibrationAlert" if row["Vibration(g)"] > 2.0 else "",
-        "CameraOffline" if row["CameraStatus"] == "Offline" else "",
-        "PowerInsufficient" if row["PowerSufficient"] == "No" else "",
-    ], axis=1)
-    
-    df["Anomalies"] = df["Anomalies"].apply(lambda x: [a for a in x if a])
-    df["AlertLevel"] = df["Anomalies"].apply(lambda x: "Green" if len(x) == 0 else "Yellow" if len(x) == 1 else "Red")
-    return df
-
-# Visuals
-def show_heatmap(df):
-    st.subheader("🌡️ Fault Distribution Heatmap")
-
-    map_data = df.groupby(['Site', 'AlertLevel']).size().reset_index(name="Count")
-    fig = px.density_heatmap(
-        map_data, x="Site", y="AlertLevel", z="Count", color_continuous_scale="Reds", title="Alerts per Site"
-    )
-    st.plotly_chart(fig, use_container_width=True)
-
-def show_red_alerts(df):
-    st.subheader("🚨 Blinking Red Alert Poles")
-    red_df = df[df["AlertLevel"] == "Red"]
-    if red_df.empty:
-        st.success("No red alerts right now!")
-        return
-
-    for _, row in red_df.iterrows():
-        with st.container():
-            st.markdown(
-                f"<div style='padding:8px; background-color:#ffcccc; animation: blink 1s infinite;'>"
-                f"<strong>{row['PoleID']}</strong>: {', '.join(row['Anomalies'])}</div>",
-                unsafe_allow_html=True
-            )
-
-    st.markdown(
-        """
-        <style>
-        @keyframes blink {
-            50% { background-color: #ff4d4d; }
-        }
-        </style>
-        """,
-        unsafe_allow_html=True
-    )
-
-# Main
-st.set_page_config("VIEP Heatmap Dashboard", layout="wide")
-st.title("🌍 Vedavathi Smart Pole Monitoring Dashboard")
-
-df = generate_mock_data()
-
-# Filters
-alert_filter = st.selectbox("Filter by Alert Level", ["All", "Green", "Yellow", "Red"])
-if alert_filter != "All":
-    df = df[df["AlertLevel"] == alert_filter]
-
-# Views
-show_heatmap(df)
-show_red_alerts(df)
+from modules.simulator import simulate_data
+from modules.filters import apply_filters
+from modules.visuals import display_dashboard, display_charts, display_map_with_alerts
+from modules.ai_engine import AIEngine
+
+st.set_page_config(page_title="Vedavathi Smart Pole Monitoring", layout="wide")
+st.title("📡 Vedavathi Smart Pole Monitoring - Heatmap AI Simulator")
+
+# Sidebar Controls
+st.sidebar.header("🛠️ Simulation Controls")
+num_poles = st.sidebar.slider("Number of Poles", min_value=10, max_value=500, value=50)
+simulate_faults = st.sidebar.checkbox("Simulate Random Faults", value=True)
+
+# Simulate Data
+df = simulate_data(num_poles, simulate_faults)
+
+# AI-based Health Prediction
+ai = AIEngine()
+df = ai.predict_health(df)
+
+# Sidebar Filters
+st.sidebar.header("📂 Filter Data")
+alert_filter = st.sidebar.multiselect("Alert Level", ["Green", "Yellow", "Red"], default=["Green", "Yellow", "Red"])
+cam_filter = st.sidebar.selectbox("Camera Status", ["All", "Online", "Offline"], index=0)
+df = apply_filters(df, alert_filter, cam_filter)
+
+# Dashboard UI
+display_dashboard(df)
+st.subheader("📍 Live Pole Map")
+display_map_with_alerts(df)
+st.subheader("📈 Energy + Sensor Charts")
+display_charts(df)