Update src/streamlit_app.py
Browse files- src/streamlit_app.py +459 -38
src/streamlit_app.py
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import altair as alt
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import numpy as np
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import pandas as pd
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import streamlit as st
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"""
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#
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If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
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forums](https://discuss.streamlit.io).
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In the meantime, below is an example of what you can do with just a few lines of code:
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"""
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num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
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num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
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indices = np.linspace(0, 1, num_points)
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theta = 2 * np.pi * num_turns * indices
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radius = indices
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x = radius * np.cos(theta)
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y = radius * np.sin(theta)
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df = pd.DataFrame({
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"x": x,
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"y": y,
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"idx": indices,
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"rand": np.random.randn(num_points),
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})
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st.altair_chart(alt.Chart(df, height=700, width=700)
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.mark_point(filled=True)
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.encode(
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x=alt.X("x", axis=None),
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y=alt.Y("y", axis=None),
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color=alt.Color("idx", legend=None, scale=alt.Scale()),
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size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
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))
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import streamlit as st
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import plotly.graph_objects as go
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import pandas as pd
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# ββ Page config βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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st.set_page_config(
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page_title="T2.3 Β· Grid Outage Forecaster",
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page_icon="β‘",
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layout="wide",
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)
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# ββ Custom CSS βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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st.markdown("""
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<style>
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[data-testid="stAppViewContainer"] { background: #0f1117; color: #e8eaf6; }
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[data-testid="stSidebar"] { background: #1a1d27; }
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.metric-card {
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background: #1a1d27; border: 1px solid #2e3350; border-radius: 10px;
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padding: 14px 18px; text-align: center;
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}
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.metric-val { font-size: 1.6rem; font-weight: 800; color: #6366f1; }
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.metric-lbl { font-size: 11px; color: #8892b0; text-transform: uppercase; letter-spacing: .05em; }
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.badge {
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display: inline-block; padding: 2px 8px; border-radius: 4px;
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font-size: 11px; font-weight: 700; text-transform: uppercase; letter-spacing: .05em;
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}
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.badge-high { background: #7f1d1d; color: #fca5a5; }
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.badge-medium { background: #78350f; color: #fcd34d; }
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.badge-low { background: #14532d; color: #86efac; }
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.badge-on { background: #14532d; color: #86efac; }
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.badge-off { background: #3f3f46; color: #a1a1aa; }
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.badge-critical{ background: #1e3a8a; color: #93c5fd; }
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.badge-comfort { background: #4a1d96; color: #c4b5fd; }
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.badge-luxury { background: #374151; color: #9ca3af; }
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.ap-card {
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background: #1a1d27; border: 1px solid #2e3350; border-radius: 8px;
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padding: 12px 14px; margin-bottom: 8px;
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}
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.ap-card.off { opacity: .6; border-color: #3f3f46; }
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.ap-name { font-weight: 600; font-size: 14px; color: #e8eaf6; margin-bottom: 4px; }
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.ap-meta { display: flex; gap: 6px; margin-bottom: 4px; }
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.ap-shed { font-size: 10px; color: #9ca3af; margin-top: 3px; }
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.ap-right { text-align: right; font-size: 12px; color: #8892b0; }
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.ap-rev { color: #22c55e; font-weight: 600; font-size: 13px; }
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.sms-box {
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background: #22263a; border: 1px solid #2e3350; border-radius: 8px;
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padding: 14px; margin-bottom: 10px; font-family: monospace; font-size: 13px;
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line-height: 1.6; color: #e8eaf6;
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}
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.plan-header {
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background: #1a1d27; border: 1px solid #2e3350; border-radius: 8px;
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padding: 12px 16px; margin-bottom: 12px;
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}
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.section-title { font-size: 1rem; font-weight: 600; color: #e8eaf6; margin-bottom: 10px; }
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h1, h2, h3 { color: #e8eaf6 !important; }
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.stSelectbox label, .stSlider label { color: #8892b0 !important; }
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div[data-testid="metric-container"] {
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background: #1a1d27; border: 1px solid #2e3350; border-radius: 8px; padding: 8px;
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}
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</style>
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""", unsafe_allow_html=True)
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# ββ Embedded Data βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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FORECAST = [
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{"hour_offset":0,"timestamp":"2024-06-29 00:00","hour":0,"p_outage":0.2708,"p_outage_low":0.1908,"p_outage_high":0.3508,"expected_duration_min":89.8,"risk_level":"HIGH"},
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{"hour_offset":1,"timestamp":"2024-06-29 01:00","hour":1,"p_outage":0.2554,"p_outage_low":0.1754,"p_outage_high":0.3354,"expected_duration_min":83.2,"risk_level":"HIGH"},
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{"hour_offset":2,"timestamp":"2024-06-29 02:00","hour":2,"p_outage":0.2169,"p_outage_low":0.1369,"p_outage_high":0.2969,"expected_duration_min":85.0,"risk_level":"MEDIUM"},
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{"hour_offset":3,"timestamp":"2024-06-29 03:00","hour":3,"p_outage":0.2554,"p_outage_low":0.1754,"p_outage_high":0.3354,"expected_duration_min":85.0,"risk_level":"HIGH"},
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{"hour_offset":4,"timestamp":"2024-06-29 04:00","hour":4,"p_outage":0.2602,"p_outage_low":0.1802,"p_outage_high":0.3402,"expected_duration_min":78.8,"risk_level":"HIGH"},
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{"hour_offset":5,"timestamp":"2024-06-29 05:00","hour":5,"p_outage":0.2503,"p_outage_low":0.1703,"p_outage_high":0.3303,"expected_duration_min":85.0,"risk_level":"HIGH"},
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{"hour_offset":6,"timestamp":"2024-06-29 06:00","hour":6,"p_outage":0.24, "p_outage_low":0.16, "p_outage_high":0.32, "expected_duration_min":83.2,"risk_level":"MEDIUM"},
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{"hour_offset":7,"timestamp":"2024-06-29 07:00","hour":7,"p_outage":0.2208,"p_outage_low":0.1408,"p_outage_high":0.3008,"expected_duration_min":78.5,"risk_level":"MEDIUM"},
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{"hour_offset":8,"timestamp":"2024-06-29 08:00","hour":8,"p_outage":0.2208,"p_outage_low":0.1408,"p_outage_high":0.3008,"expected_duration_min":78.5,"risk_level":"MEDIUM"},
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{"hour_offset":9,"timestamp":"2024-06-29 09:00","hour":9,"p_outage":0.198, "p_outage_low":0.118, "p_outage_high":0.278, "expected_duration_min":86.0,"risk_level":"MEDIUM"},
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{"hour_offset":10,"timestamp":"2024-06-29 10:00","hour":10,"p_outage":0.24, "p_outage_low":0.16, "p_outage_high":0.32, "expected_duration_min":71.3,"risk_level":"MEDIUM"},
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{"hour_offset":11,"timestamp":"2024-06-29 11:00","hour":11,"p_outage":0.2531,"p_outage_low":0.1731,"p_outage_high":0.3331,"expected_duration_min":73.1,"risk_level":"HIGH"},
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{"hour_offset":12,"timestamp":"2024-06-29 12:00","hour":12,"p_outage":0.2457,"p_outage_low":0.1657,"p_outage_high":0.3257,"expected_duration_min":76.9,"risk_level":"MEDIUM"},
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| 78 |
+
{"hour_offset":13,"timestamp":"2024-06-29 13:00","hour":13,"p_outage":0.263, "p_outage_low":0.183, "p_outage_high":0.343, "expected_duration_min":68.8,"risk_level":"HIGH"},
|
| 79 |
+
{"hour_offset":14,"timestamp":"2024-06-29 14:00","hour":14,"p_outage":0.2582,"p_outage_low":0.1782,"p_outage_high":0.3382,"expected_duration_min":72.5,"risk_level":"HIGH"},
|
| 80 |
+
{"hour_offset":15,"timestamp":"2024-06-29 15:00","hour":15,"p_outage":0.2194,"p_outage_low":0.1394,"p_outage_high":0.2994,"expected_duration_min":76.9,"risk_level":"MEDIUM"},
|
| 81 |
+
{"hour_offset":16,"timestamp":"2024-06-29 16:00","hour":16,"p_outage":0.2688,"p_outage_low":0.1888,"p_outage_high":0.3488,"expected_duration_min":83.4,"risk_level":"HIGH"},
|
| 82 |
+
{"hour_offset":17,"timestamp":"2024-06-29 17:00","hour":17,"p_outage":0.309, "p_outage_low":0.229, "p_outage_high":0.389, "expected_duration_min":84.6,"risk_level":"HIGH"},
|
| 83 |
+
{"hour_offset":18,"timestamp":"2024-06-29 18:00","hour":18,"p_outage":0.3353,"p_outage_low":0.2553,"p_outage_high":0.4153,"expected_duration_min":84.6,"risk_level":"HIGH"},
|
| 84 |
+
{"hour_offset":19,"timestamp":"2024-06-29 19:00","hour":19,"p_outage":0.3408,"p_outage_low":0.2608,"p_outage_high":0.4208,"expected_duration_min":76.1,"risk_level":"HIGH"},
|
| 85 |
+
{"hour_offset":20,"timestamp":"2024-06-29 20:00","hour":20,"p_outage":0.3353,"p_outage_low":0.2553,"p_outage_high":0.4153,"expected_duration_min":99.4,"risk_level":"HIGH"},
|
| 86 |
+
{"hour_offset":21,"timestamp":"2024-06-29 21:00","hour":21,"p_outage":0.3466,"p_outage_low":0.2666,"p_outage_high":0.4266,"expected_duration_min":100.6,"risk_level":"HIGH"},
|
| 87 |
+
{"hour_offset":22,"timestamp":"2024-06-29 22:00","hour":22,"p_outage":0.2834,"p_outage_low":0.2034,"p_outage_high":0.3634,"expected_duration_min":102.5,"risk_level":"HIGH"},
|
| 88 |
+
{"hour_offset":23,"timestamp":"2024-06-29 23:00","hour":23,"p_outage":0.2596,"p_outage_low":0.1796,"p_outage_high":0.3396,"expected_duration_min":106.9,"risk_level":"HIGH"},
|
| 89 |
+
]
|
| 90 |
+
|
| 91 |
+
SMS = [
|
| 92 |
+
"UMURIRO FORECAST 24H: Risk=HIGH at 0h,1h,3h. Shed: Standing+TV. Est.save: 12,418RWF. Stay alert!",
|
| 93 |
+
"PLAN: Turn OFF Standing+TV during risk hrs (0h,1h,3h). Keep dryer+clippers+lights ON. Generator ready?",
|
| 94 |
+
"If no signal by 13h, use YESTERDAY plan. Risk valid 6h. Call 0788-GRID for live update. Good business!",
|
| 95 |
+
]
|
| 96 |
+
|
| 97 |
+
# ββ Appliance plan generators βββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 98 |
+
def salon_appliances(hour, risk):
|
| 99 |
+
open_ = 7 <= hour <= 20
|
| 100 |
+
peak = 9 <= hour <= 17
|
| 101 |
+
scale = 1.0 if peak else (0.75 if open_ else 0.0)
|
| 102 |
+
if not open_:
|
| 103 |
+
return [
|
| 104 |
+
{"name":"Hair Dryer (2Γ)", "category":"critical","state":"OFF","watts":2400,"revenue_rwf":0,"shed_reason":"Business closed"},
|
| 105 |
+
{"name":"Electric Clippers (3Γ)","category":"critical","state":"OFF","watts":120, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 106 |
+
{"name":"LED Lights", "category":"critical","state":"ON", "watts":20, "revenue_rwf":0},
|
| 107 |
+
{"name":"Standing Fan", "category":"comfort", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 108 |
+
{"name":"TV / Display", "category":"comfort", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 109 |
+
{"name":"Music System", "category":"luxury", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 110 |
+
{"name":"Neon Sign", "category":"luxury", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 111 |
+
]
|
| 112 |
+
shed_lux = risk in ("HIGH","MEDIUM")
|
| 113 |
+
shed_com = risk == "HIGH"
|
| 114 |
+
return [
|
| 115 |
+
{"name":"Hair Dryer (2Γ)", "category":"critical","state":"ON", "watts":2400,"revenue_rwf":round(2133*scale)},
|
| 116 |
+
{"name":"Electric Clippers (3Γ)","category":"critical","state":"ON", "watts":120, "revenue_rwf":round(1422*scale)},
|
| 117 |
+
{"name":"LED Lights", "category":"critical","state":"ON", "watts":80, "revenue_rwf":round(711*scale)},
|
| 118 |
+
{"name":"Standing Fan", "category":"comfort","state":"OFF" if shed_com else "ON","watts":0 if shed_com else 75, "revenue_rwf":0 if shed_com else round(285*scale), **({"shed_reason":"HIGH risk β comfort shed"} if shed_com else {})},
|
| 119 |
+
{"name":"TV / Display", "category":"comfort","state":"OFF" if shed_com else "ON","watts":0 if shed_com else 150,"revenue_rwf":0 if shed_com else round(142*scale), **({"shed_reason":"HIGH risk β comfort shed"} if shed_com else {})},
|
| 120 |
+
{"name":"Music System", "category":"luxury", "state":"OFF" if shed_lux else "ON","watts":0 if shed_lux else 80, "revenue_rwf":0, **({"shed_reason":"Risk β₯ MEDIUM β luxury shed"} if shed_lux else {})},
|
| 121 |
+
{"name":"Neon Sign", "category":"luxury", "state":"OFF" if shed_lux else "ON","watts":0 if shed_lux else 40, "revenue_rwf":0, **({"shed_reason":"Risk β₯ MEDIUM β luxury shed"} if shed_lux else {})},
|
| 122 |
+
]
|
| 123 |
+
|
| 124 |
+
def cold_appliances(hour, risk):
|
| 125 |
+
open_ = 6 <= hour <= 20
|
| 126 |
+
peak = 8 <= hour <= 18
|
| 127 |
+
scale = 1.0 if peak else (0.6 if open_ else 0.0)
|
| 128 |
+
fridge_rev = round(1850*scale) if open_ else 0
|
| 129 |
+
pump_rev = round(1100*scale) if open_ else 0
|
| 130 |
+
light_rev = round(740*scale) if open_ else 0
|
| 131 |
+
fan_rev = round(296*scale) if open_ else 0
|
| 132 |
+
tv_rev = round(148*scale) if open_ else 0
|
| 133 |
+
shed_com = risk == "HIGH"
|
| 134 |
+
shed_fan = shed_com or not open_
|
| 135 |
+
shed_tv = shed_com or not open_
|
| 136 |
+
return [
|
| 137 |
+
{"name":"Commercial Refrigerator","category":"critical","state":"ON", "watts":350,"revenue_rwf":fridge_rev or 200,**({"shed_reason":"After-hours β standby mode"} if not open_ else {})},
|
| 138 |
+
{"name":"Water Pump", "category":"critical","state":"ON" if open_ else "OFF","watts":750 if open_ else 0,"revenue_rwf":pump_rev, **({"shed_reason":"After-hours β pump off"} if not open_ else {})},
|
| 139 |
+
{"name":"LED Lights", "category":"critical","state":"ON" if open_ else "OFF","watts":80 if open_ else 0,"revenue_rwf":light_rev,**({"shed_reason":"After-hours β lights off"} if not open_ else {})},
|
| 140 |
+
{"name":"Standing Fan", "category":"comfort", "state":"OFF" if shed_fan else "ON","watts":0 if shed_fan else 75, "revenue_rwf":0 if shed_fan else fan_rev,**({"shed_reason":"HIGH risk β comfort shed" if shed_com else "After-hours"} if shed_fan else {})},
|
| 141 |
+
{"name":"TV / Display", "category":"comfort", "state":"OFF" if shed_tv else "ON","watts":0 if shed_tv else 150,"revenue_rwf":0 if shed_tv else tv_rev, **({"shed_reason":"HIGH risk β comfort shed" if shed_com else "After-hours"} if shed_tv else {})},
|
| 142 |
+
{"name":"Backup Battery Charger","category":"luxury","state":"ON" if (risk=="LOW" and open_) else "OFF","watts":200 if (risk=="LOW" and open_) else 0,"revenue_rwf":0,**({"shed_reason":"Risk β₯ MEDIUM β luxury shed"} if not (risk=="LOW" and open_) else {})},
|
| 143 |
+
]
|
| 144 |
+
|
| 145 |
+
def tailor_appliances(hour, risk):
|
| 146 |
+
open_ = 8 <= hour <= 18
|
| 147 |
+
peak = 9 <= hour <= 16
|
| 148 |
+
scale = 1.0 if peak else (0.6 if open_ else 0.0)
|
| 149 |
+
if not open_:
|
| 150 |
+
return [
|
| 151 |
+
{"name":"Sewing Machine (2Γ)","category":"critical","state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 152 |
+
{"name":"Overlocker", "category":"critical","state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 153 |
+
{"name":"LED Lights", "category":"critical","state":"ON", "watts":20, "revenue_rwf":0},
|
| 154 |
+
{"name":"Iron Press", "category":"comfort", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 155 |
+
{"name":"Standing Fan", "category":"comfort", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 156 |
+
{"name":"Music System", "category":"luxury", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 157 |
+
{"name":"TV / Display", "category":"luxury", "state":"OFF","watts":0, "revenue_rwf":0,"shed_reason":"Business closed"},
|
| 158 |
+
]
|
| 159 |
+
shed_lux = risk in ("HIGH","MEDIUM")
|
| 160 |
+
shed_com = risk == "HIGH"
|
| 161 |
+
shed_iron= risk == "HIGH"
|
| 162 |
+
return [
|
| 163 |
+
{"name":"Sewing Machine (2Γ)","category":"critical","state":"ON","watts":180,"revenue_rwf":round(590*scale)},
|
| 164 |
+
{"name":"Overlocker", "category":"critical","state":"ON","watts":100,"revenue_rwf":round(310*scale)},
|
| 165 |
+
{"name":"LED Lights", "category":"critical","state":"ON","watts":80, "revenue_rwf":round(180*scale)},
|
| 166 |
+
{"name":"Iron Press", "category":"comfort","state":"OFF" if shed_iron else "ON","watts":0 if shed_iron else 1000,"revenue_rwf":0 if shed_iron else round(260*scale),**({"shed_reason":"HIGH risk β heavy load shed"} if shed_iron else {})},
|
| 167 |
+
{"name":"Standing Fan", "category":"comfort","state":"OFF" if shed_com else "ON","watts":0 if shed_com else 75, "revenue_rwf":0 if shed_com else round(120*scale),**({"shed_reason":"HIGH risk β comfort shed"} if shed_com else {})},
|
| 168 |
+
{"name":"Music System", "category":"luxury", "state":"OFF" if shed_lux else "ON","watts":0 if shed_lux else 80, "revenue_rwf":0,**({"shed_reason":"Risk β₯ MEDIUM β luxury shed"} if shed_lux else {})},
|
| 169 |
+
{"name":"TV / Display", "category":"luxury", "state":"OFF" if shed_lux else "ON","watts":0 if shed_lux else 150, "revenue_rwf":0,**({"shed_reason":"Risk β₯ MEDIUM β luxury shed"} if shed_lux else {})},
|
| 170 |
+
]
|
| 171 |
+
|
| 172 |
+
PLANS = {
|
| 173 |
+
"salon": {
|
| 174 |
+
"label": "π Beauty Salon",
|
| 175 |
+
"summary": {"total_revenue_plan_rwf":93850,"total_revenue_naive_rwf":101790,"net_benefit_rwf":12418,"hours_with_shed":24},
|
| 176 |
+
"fn": salon_appliances,
|
| 177 |
+
},
|
| 178 |
+
"cold_room": {
|
| 179 |
+
"label": "π§ Cold Room",
|
| 180 |
+
"summary": {"total_revenue_plan_rwf":118000,"total_revenue_naive_rwf":125000,"net_benefit_rwf":18000,"hours_with_shed":16},
|
| 181 |
+
"fn": cold_appliances,
|
| 182 |
+
},
|
| 183 |
+
"tailor": {
|
| 184 |
+
"label": "π§΅ Tailor Shop",
|
| 185 |
+
"summary": {"total_revenue_plan_rwf":42000,"total_revenue_naive_rwf":48000,"net_benefit_rwf":3600,"hours_with_shed":14},
|
| 186 |
+
"fn": tailor_appliances,
|
| 187 |
+
},
|
| 188 |
+
}
|
| 189 |
+
|
| 190 |
+
RISK_COLOR = {"HIGH": "#ef4444", "MEDIUM": "#f97316", "LOW": "#22c55e"}
|
| 191 |
+
|
| 192 |
+
# ββ Sidebar βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 193 |
+
with st.sidebar:
|
| 194 |
+
st.markdown("## β‘ Grid Outage Forecaster")
|
| 195 |
+
st.markdown("<span style='color:#8892b0;font-size:12px'>T2.3 Β· AIMS KTT Hackathon 2026 Β· Kigali, Rwanda</span>", unsafe_allow_html=True)
|
| 196 |
+
st.divider()
|
| 197 |
+
|
| 198 |
+
st.markdown("### Model Metrics")
|
| 199 |
+
st.metric("Brier Score", "0.176")
|
| 200 |
+
st.metric("MAE (min)", "61.2")
|
| 201 |
+
st.metric("Avg Lead Time", "2.79h")
|
| 202 |
+
st.divider()
|
| 203 |
+
|
| 204 |
+
st.markdown("### Business")
|
| 205 |
+
biz_key = st.radio(
|
| 206 |
+
"Select business",
|
| 207 |
+
options=list(PLANS.keys()),
|
| 208 |
+
format_func=lambda k: PLANS[k]["label"],
|
| 209 |
+
label_visibility="collapsed",
|
| 210 |
+
)
|
| 211 |
+
st.divider()
|
| 212 |
+
|
| 213 |
+
biz = PLANS[biz_key]
|
| 214 |
+
s = biz["summary"]
|
| 215 |
+
st.markdown("### Plan Summary")
|
| 216 |
+
st.metric("Net Benefit (RWF)", f"{s['net_benefit_rwf']:,}")
|
| 217 |
+
st.metric("Expected Rev (RWF)", f"{s['total_revenue_plan_rwf']:,}")
|
| 218 |
+
high_h = sum(1 for f in FORECAST if f["risk_level"] == "HIGH")
|
| 219 |
+
st.metric("HIGH Risk Hours", high_h)
|
| 220 |
+
st.metric("Hours with Shed", s["hours_with_shed"])
|
| 221 |
+
|
| 222 |
+
# ββ Main tabs βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 223 |
+
tab_forecast, tab_plan, tab_sms, tab_about = st.tabs(
|
| 224 |
+
["π Forecast", "π Appliance Plan", "π± SMS Digest", "βΉοΈ About"]
|
| 225 |
+
)
|
| 226 |
+
|
| 227 |
+
# ββ FORECAST TAB ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 228 |
+
with tab_forecast:
|
| 229 |
+
st.markdown("### 24-Hour Outage Probability Forecast")
|
| 230 |
+
|
| 231 |
+
hours = [f["hour"] for f in FORECAST]
|
| 232 |
+
p_out = [f["p_outage"] for f in FORECAST]
|
| 233 |
+
p_low = [f["p_outage_low"] for f in FORECAST]
|
| 234 |
+
p_high = [f["p_outage_high"] for f in FORECAST]
|
| 235 |
+
risk_levels = [f["risk_level"] for f in FORECAST]
|
| 236 |
+
bar_colors = [RISK_COLOR[r] for r in risk_levels]
|
| 237 |
+
|
| 238 |
+
fig = go.Figure()
|
| 239 |
+
|
| 240 |
+
# Risk background zones (coloured bar under chart)
|
| 241 |
+
for f in FORECAST:
|
| 242 |
+
col = {"HIGH":"rgba(239,68,68,.10)","MEDIUM":"rgba(249,115,22,.07)","LOW":"rgba(34,197,94,.04)"}[f["risk_level"]]
|
| 243 |
+
fig.add_vrect(x0=f["hour"]-.5, x1=f["hour"]+.5, fillcolor=col, line_width=0, layer="below")
|
| 244 |
+
|
| 245 |
+
# Uncertainty band
|
| 246 |
+
fig.add_trace(go.Scatter(
|
| 247 |
+
x=hours + hours[::-1],
|
| 248 |
+
y=p_high + p_low[::-1],
|
| 249 |
+
fill="toself", fillcolor="rgba(99,102,241,.18)",
|
| 250 |
+
line=dict(color="rgba(0,0,0,0)"),
|
| 251 |
+
hoverinfo="skip", name="Uncertainty band",
|
| 252 |
+
))
|
| 253 |
+
|
| 254 |
+
# Main line
|
| 255 |
+
fig.add_trace(go.Scatter(
|
| 256 |
+
x=hours, y=p_out,
|
| 257 |
+
mode="lines+markers",
|
| 258 |
+
line=dict(color="#6366f1", width=2.5),
|
| 259 |
+
marker=dict(color=bar_colors, size=8, line=dict(color="#0f1117", width=1)),
|
| 260 |
+
name="P(outage)",
|
| 261 |
+
hovertemplate="Hour %{x}:00<br>P(outage)=%{y:.1%}<extra></extra>",
|
| 262 |
+
))
|
| 263 |
+
|
| 264 |
+
# HIGH threshold line
|
| 265 |
+
fig.add_hline(y=0.25, line=dict(color="#ef4444", dash="dash", width=1),
|
| 266 |
+
annotation_text="HIGH threshold", annotation_position="top left",
|
| 267 |
+
annotation_font_color="#ef4444")
|
| 268 |
+
|
| 269 |
+
fig.update_layout(
|
| 270 |
+
paper_bgcolor="#1a1d27", plot_bgcolor="#1a1d27",
|
| 271 |
+
font=dict(color="#e8eaf6", size=12),
|
| 272 |
+
xaxis=dict(title="Hour of day", gridcolor="#2e3350", tickvals=list(range(0,24,2))),
|
| 273 |
+
yaxis=dict(title="P(outage)", gridcolor="#2e3350", tickformat=".0%", range=[0, 0.55]),
|
| 274 |
+
legend=dict(orientation="h", y=1.08, bgcolor="rgba(0,0,0,0)"),
|
| 275 |
+
margin=dict(l=10, r=10, t=10, b=10),
|
| 276 |
+
height=320,
|
| 277 |
+
)
|
| 278 |
+
st.plotly_chart(fig, use_container_width=True)
|
| 279 |
+
|
| 280 |
+
# ββ Hour grid βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 281 |
+
st.markdown("### Hourly Risk β click a cell to drill into plan")
|
| 282 |
+
cols = st.columns(12)
|
| 283 |
+
for i, f in enumerate(FORECAST):
|
| 284 |
+
col_idx = i % 12
|
| 285 |
+
with cols[col_idx]:
|
| 286 |
+
risk = f["risk_level"]
|
| 287 |
+
color = RISK_COLOR[risk]
|
| 288 |
+
pct = f"{f['p_outage']*100:.0f}%"
|
| 289 |
+
st.markdown(f"""
|
| 290 |
+
<div style='background:#1a1d27;border:1px solid #2e3350;border-radius:6px;
|
| 291 |
+
padding:6px 4px;text-align:center;margin-bottom:4px;'>
|
| 292 |
+
<div style='font-size:10px;color:#8892b0'>{f["hour"]}h</div>
|
| 293 |
+
<div style='font-size:14px;font-weight:700;color:{color}'>{pct}</div>
|
| 294 |
+
<div style='margin-top:2px'><span class='badge badge-{risk.lower()}'>{risk}</span></div>
|
| 295 |
+
</div>""", unsafe_allow_html=True)
|
| 296 |
+
|
| 297 |
+
cols2 = st.columns(12)
|
| 298 |
+
for i, f in enumerate(FORECAST):
|
| 299 |
+
with cols2[i % 12]:
|
| 300 |
+
pass # second row of 12 hours already handled above
|
| 301 |
+
|
| 302 |
+
# Second row (hours 12β23)
|
| 303 |
+
st.markdown("")
|
| 304 |
+
|
| 305 |
+
# ββ PLAN TAB ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 306 |
+
with tab_plan:
|
| 307 |
+
st.markdown("### π Appliance Plan")
|
| 308 |
+
|
| 309 |
+
hour_idx = st.slider(
|
| 310 |
+
"Select hour",
|
| 311 |
+
min_value=0, max_value=23, value=0,
|
| 312 |
+
format="%d:00",
|
| 313 |
+
)
|
| 314 |
+
|
| 315 |
+
fc = FORECAST[hour_idx]
|
| 316 |
+
appliances = biz["fn"](hour_idx, fc["risk_level"])
|
| 317 |
+
risk = fc["risk_level"]
|
| 318 |
+
|
| 319 |
+
# Hour info header
|
| 320 |
+
risk_color = RISK_COLOR[risk]
|
| 321 |
+
st.markdown(f"""
|
| 322 |
+
<div class='plan-header'>
|
| 323 |
+
<b>Hour {hour_idx}</b> Β· {fc['timestamp'].split()[1]}
|
| 324 |
+
<span class='badge badge-{risk.lower()}'>{risk}</span>
|
| 325 |
+
P(outage) = <b>{fc['p_outage']*100:.1f}%</b>
|
| 326 |
+
Exp. duration = <b>{fc['expected_duration_min']:.0f} min</b>
|
| 327 |
+
</div>
|
| 328 |
+
""", unsafe_allow_html=True)
|
| 329 |
+
|
| 330 |
+
# Appliance cards in 2 columns
|
| 331 |
+
left_col, right_col = st.columns(2)
|
| 332 |
+
for i, ap in enumerate(appliances):
|
| 333 |
+
target = left_col if i % 2 == 0 else right_col
|
| 334 |
+
is_off = ap["state"] == "OFF"
|
| 335 |
+
opacity = "opacity:.65;" if is_off else ""
|
| 336 |
+
shed = f"<div class='ap-shed'>β {ap['shed_reason']}</div>" if "shed_reason" in ap else ""
|
| 337 |
+
rev_html = f"<div class='ap-rev'>{ap['revenue_rwf']:,} RWF/h</div>" if ap["state"] == "ON" and ap["revenue_rwf"] > 0 else "<div style='color:#6b7280'>β</div>"
|
| 338 |
+
with target:
|
| 339 |
+
st.markdown(f"""
|
| 340 |
+
<div class='ap-card{"" if not is_off else " off"}' style='{opacity}'>
|
| 341 |
+
<div style='display:flex;justify-content:space-between;align-items:flex-start'>
|
| 342 |
+
<div>
|
| 343 |
+
<div class='ap-name'>{ap['name']}</div>
|
| 344 |
+
<div class='ap-meta'>
|
| 345 |
+
<span class='badge badge-{ap['category']}'>{ap['category']}</span>
|
| 346 |
+
<span class='badge badge-{ap['state'].lower()}'>{ap['state']}</span>
|
| 347 |
+
</div>
|
| 348 |
+
{shed}
|
| 349 |
+
</div>
|
| 350 |
+
<div class='ap-right'>
|
| 351 |
+
<div style='font-size:11px;color:#8892b0'>{ap['watts']}W</div>
|
| 352 |
+
{rev_html}
|
| 353 |
+
</div>
|
| 354 |
+
</div>
|
| 355 |
+
</div>""", unsafe_allow_html=True)
|
| 356 |
+
|
| 357 |
+
st.markdown("""
|
| 358 |
+
<div style='background:#1a1d27;border:1px solid #2e3350;border-radius:8px;
|
| 359 |
+
padding:12px;font-size:12px;color:#8892b0;margin-top:8px;'>
|
| 360 |
+
<b style='color:#e8eaf6'>Shedding Logic:</b>
|
| 361 |
+
Luxury β Comfort β Critical (never shed during peak unless P > 0.50).
|
| 362 |
+
Within category: lowest revenue shed first. Critical always ON during business peak hours.
|
| 363 |
+
</div>""", unsafe_allow_html=True)
|
| 364 |
+
|
| 365 |
+
# ββ SMS TAB βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 366 |
+
with tab_sms:
|
| 367 |
+
st.markdown("### π± Morning Digest β Feature Phone SMS")
|
| 368 |
+
st.markdown("<span style='color:#8892b0;font-size:12px'>Sent at 06:30 CAT. Max 3 messages Γ 160 chars. Works on any GSM phone. No internet required. Language: Kinyarwanda/English mix for maximum reach.</span>", unsafe_allow_html=True)
|
| 369 |
+
st.markdown("")
|
| 370 |
+
|
| 371 |
+
for i, msg in enumerate(SMS):
|
| 372 |
+
st.markdown(f"""
|
| 373 |
+
<div class='sms-box'>
|
| 374 |
+
<div style='display:flex;justify-content:space-between;margin-bottom:6px'>
|
| 375 |
+
<span style='font-size:11px;font-weight:700;color:#6366f1'>SMS {i+1}/3</span>
|
| 376 |
+
<span style='font-size:10px;color:#8892b0'>{len(msg)}/160 chars</span>
|
| 377 |
+
</div>
|
| 378 |
+
{msg}
|
| 379 |
+
</div>""", unsafe_allow_html=True)
|
| 380 |
+
|
| 381 |
+
st.markdown("""
|
| 382 |
+
<div class='sms-box' style='border-color:#6366f1;margin-top:16px;'>
|
| 383 |
+
<div style='font-size:12px;font-weight:700;color:#6366f1;margin-bottom:8px'>π Offline Fallback Protocol</div>
|
| 384 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 385 |
+
<b style='color:#e8eaf6'>If no internet refresh by 13:00:</b> Device shows last cached plan with
|
| 386 |
+
a red β οΈ staleness banner. Risk budget: plan valid for <b style='color:#f97316'>6 hours</b>
|
| 387 |
+
from generation time. After 6h, all HIGH-risk flags remain but MEDIUM degrades to LOW (overly cautious).
|
| 388 |
+
Maximum acceptable staleness: <b style='color:#ef4444'>8 hours</b>.
|
| 389 |
+
Owner sees: "PLAN STALE β use generator, call 0788-GRID."
|
| 390 |
+
</div>
|
| 391 |
+
</div>
|
| 392 |
+
<div class='sms-box' style='border-color:#22c55e;margin-top:10px;'>
|
| 393 |
+
<div style='font-size:12px;font-weight:700;color:#22c55e;margin-bottom:8px'>π Illiteracy Adaptation β Voice + LED Relay</div>
|
| 394 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 395 |
+
<b style='color:#e8eaf6'>Design choice: Colored LED relay board</b> (3 LEDs per appliance slot).<br>
|
| 396 |
+
π’ GREEN = ON safe Β· π‘ YELLOW = shed if load high Β· π΄ RED = OFF now.<br>
|
| 397 |
+
Board connects via GPIO to a βUSD 8 ESP32 running cached plan. No reading required.
|
| 398 |
+
Physical override switch lets owner override any LED. $8 hardware cost, zero ongoing data cost.
|
| 399 |
+
</div>
|
| 400 |
+
</div>
|
| 401 |
+
""", unsafe_allow_html=True)
|
| 402 |
+
|
| 403 |
+
# ββ ABOUT TAB βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
| 404 |
+
with tab_about:
|
| 405 |
+
st.markdown("### Technical Notes")
|
| 406 |
+
col1, col2 = st.columns(2)
|
| 407 |
+
|
| 408 |
+
with col1:
|
| 409 |
+
st.markdown("""
|
| 410 |
+
<div class='sms-box'>
|
| 411 |
+
<div style='font-size:12px;font-weight:700;color:#6366f1;margin-bottom:6px'>Model</div>
|
| 412 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 413 |
+
<b style='color:#e8eaf6'>LightGBM</b> classifier for P(outage) + regressor for E[duration | outage].<br>
|
| 414 |
+
Features: lagged load (1h, 2h, 24h, 48h), rolling stats, weather (temp, humidity, rain, wind),
|
| 415 |
+
temporal (hour, DOW, month, peak flags, rainy season). Training: 150-day window.
|
| 416 |
+
</div>
|
| 417 |
+
</div>
|
| 418 |
+
""", unsafe_allow_html=True)
|
| 419 |
+
|
| 420 |
+
st.markdown("""
|
| 421 |
+
<div class='sms-box' style='margin-top:10px'>
|
| 422 |
+
<div style='font-size:12px;font-weight:700;color:#6366f1;margin-bottom:6px'>Hardest Trade-off</div>
|
| 423 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 424 |
+
Chose LightGBM over Prophet: faster retrain, handles irregular time steps,
|
| 425 |
+
natively supports tabular weather features. Trade-off: less interpretable
|
| 426 |
+
seasonality decomposition. Compensated with explicit hour/DOW/month features
|
| 427 |
+
and SHAP values available in eval notebook.
|
| 428 |
+
</div>
|
| 429 |
+
</div>
|
| 430 |
+
""", unsafe_allow_html=True)
|
| 431 |
+
|
| 432 |
+
with col2:
|
| 433 |
+
st.markdown("""
|
| 434 |
+
<div class='sms-box'>
|
| 435 |
+
<div style='font-size:12px;font-weight:700;color:#6366f1;margin-bottom:6px'>Performance</div>
|
| 436 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 437 |
+
Brier score: <b style='color:#22c55e'>0.1756</b> (naΓ―ve base rate = ~0.212)<br>
|
| 438 |
+
Duration MAE: <b style='color:#22c55e'>61.2 min</b><br>
|
| 439 |
+
Avg lead time on true outages: <b style='color:#22c55e'>2.79h</b><br>
|
| 440 |
+
Inference latency: <b style='color:#22c55e'><300ms CPU</b><br>
|
| 441 |
+
Retraining time: <b style='color:#22c55e'><10 min</b>
|
| 442 |
+
</div>
|
| 443 |
+
</div>
|
| 444 |
+
""", unsafe_allow_html=True)
|
| 445 |
+
|
| 446 |
+
st.markdown("""
|
| 447 |
+
<div class='sms-box' style='margin-top:10px'>
|
| 448 |
+
<div style='font-size:12px;font-weight:700;color:#6366f1;margin-bottom:6px'>Constraints Met</div>
|
| 449 |
+
<div style='font-size:12px;color:#8892b0;line-height:1.7'>
|
| 450 |
+
β
CPU-only Β· β
<10 min retrain Β· β
<300ms serve<br>
|
| 451 |
+
β
Feature phone SMS digest Β· β
Offline fallback protocol<br>
|
| 452 |
+
β
Illiteracy adaptation Β· β
3 business archetypes<br>
|
| 453 |
+
β
Critical-before-luxury rule
|
| 454 |
+
</div>
|
| 455 |
+
</div>
|
| 456 |
+
""", unsafe_allow_html=True)
|
| 457 |
|
| 458 |
+
st.markdown("""
|
| 459 |
+
<div style='text-align:center;color:#8892b0;font-size:11px;padding:20px 0 10px'>
|
| 460 |
+
T2.3 Β· Grid Outage Forecaster + Appliance Prioritizer Β· AIMS KTT Hackathon 2026 Β· CPU-only
|
| 461 |
+
</div>""", unsafe_allow_html=True)
|
|
|
|
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