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import streamlit as st |
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import joblib |
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import pandas as pd |
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@st.cache_resource(ttl=6*300) |
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def run_model(): |
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model = joblib.load("linear_regression_model.pkl") |
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input_data = pd.DataFrame({ |
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'Temperature': [20.0], |
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'Wind Speed': [10.0], |
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'Humidity': [50.0] |
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}) |
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prediction = model.predict(input_data) |
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return prediction |
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def custom_metric_box(label, value, delta): |
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st.markdown(f""" |
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<div style=" |
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background: rgba(255, 255, 255, 0.05); |
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border-radius: 16px; |
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box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1); |
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backdrop-filter: blur(6px); |
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-webkit-backdrop-filter: blur(6px); |
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border: 1px solid rgba(255, 255, 255, 0.15); |
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padding: 15px; |
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margin-bottom: 10px; |
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width: 200px; /* Fixed width */ |
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"> |
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<h4 style="font-size: 18px; font-weight: normal; margin: 0;">{label}</h4> <!-- Smaller label --> |
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<p style="font-size: 36px; font-weight: bold; margin: 0;">{value}</p> <!-- Larger metric --> |
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<p style="color: {'green' if '+' in delta else 'orange'}; margin: 0;">{delta}</p> |
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</div> |
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""", unsafe_allow_html=True) |
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def pollution_box(label, value, delta): |
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st.markdown(f""" |
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<div style=" |
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background: rgba(255, 255, 255, 0.05); |
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border-radius: 16px; |
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box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1); |
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backdrop-filter: blur(5px); |
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-webkit-backdrop-filter: blur(5px); |
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border: 1px solid rgba(255, 255, 255, 0.15); |
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padding: 15px; |
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margin-bottom: 10px; |
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width: 300px; /* Fixed width */ |
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"> |
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<h4 style="font-size: 18px; font-weight: normal; margin: 0;">{label}</h4> <!-- Smaller label --> |
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<p style="font-size: 36px; font-weight: bold; margin: 0;">{value}</p> <!-- Larger metric --> |
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<p style="color: {'green' if '+' in delta else 'orange'}; margin: 0;">{delta}</p> |
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</div> |
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""", unsafe_allow_html=True) |
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