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import streamlit as st
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from salesforce_integration import fetch_poles

# Title
st.title("πŸ“‘ VIEP Smart Poles Dashboard")

# Fetch data
df = fetch_poles()

# Sidebar Filters
st.sidebar.header("πŸ“ Filter Data")

# Dynamic values from Salesforce data
alert_levels = df["Alert_Level__c"].dropna().unique().tolist()
sites = df["Site__c"].dropna().unique().tolist()
camera_statuses = df["Camera_Status__c"].dropna().unique().tolist()

selected_alert_levels = st.sidebar.multiselect("Alert Level", alert_levels, default=alert_levels)
selected_sites = st.sidebar.multiselect("Site", sites, default=sites)
selected_camera_status = st.sidebar.selectbox("Camera Status", ["All"] + camera_statuses)

# Apply filters
filtered_df = df[
    (df["Alert_Level__c"].isin(selected_alert_levels)) &
    (df["Site__c"].isin(selected_sites))
]

if selected_camera_status != "All":
    filtered_df = filtered_df[filtered_df["Camera_Status__c"] == selected_camera_status]

# --- System Summary ---
st.subheader("πŸ“Š System Summary")
st.metric("Total Poles", len(filtered_df))
st.metric("Red Alerts", len(filtered_df[filtered_df["Alert_Level__c"] == "Red"]))
st.metric("Offline Cameras", len(filtered_df[filtered_df["Camera_Status__c"] == "Offline"]))

# --- Pole Table ---
st.subheader("πŸ“‹ Pole Table")
st.dataframe(filtered_df, use_container_width=True)

# --- Energy Generation Chart ---
st.subheader("βš™ Energy Generation (Solar vs Wind)")
if not filtered_df.empty:
    energy_chart = px.bar(
        filtered_df,
        x="Name",
        y=["Solar_Generation__c", "Wind_Generation__c"],
        barmode="group",
        title="Solar vs Wind Energy Generation"
    )
    st.plotly_chart(energy_chart, use_container_width=True)
else:
    st.info("No data available for the selected filters.")

# --- Alert Level Breakdown ---
st.subheader("🚨 Alert Level Breakdown")
if not filtered_df.empty:
    alert_counts = filtered_df["Alert_Level__c"].value_counts().reset_index()
    alert_counts.columns = ["Alert Level", "Count"]
    alert_pie = px.pie(alert_counts, values="Count", names="Alert Level", title="Alert Distribution")
    st.plotly_chart(alert_pie, use_container_width=True)
else:
    st.info("No alerts to display.")

# --- Tilt & Vibration Chart ---
st.subheader("πŸ“‰ Tilt & Vibration from RFID")
# Example RFID_Tag__c format: "Tilt:12;Vib:34" or "Tilt=12|Vib=34"
filtered_df["Tilt"] = filtered_df["RFID_Tag__c"].str.extract(r'Tilt[:=](\d+)').astype(float)
filtered_df["Vibration"] = filtered_df["RFID_Tag__c"].str.extract(r'Vib[:=](\d+)').astype(float)

if not filtered_df[["Tilt", "Vibration"]].dropna().empty:
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=filtered_df["Name"], y=filtered_df["Tilt"],
                             mode='lines+markers', name='Tilt'))
    fig.add_trace(go.Scatter(x=filtered_df["Name"], y=filtered_df["Vibration"],
                             mode='lines+markers', name='Vibration'))
    fig.update_layout(title="Tilt and Vibration per Pole", xaxis_title="Pole", yaxis_title="Value")
    st.plotly_chart(fig, use_container_width=True)
else:
    st.info("No Tilt or Vibration data available.")