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Update src/streamlit_app.py
Browse files- src/streamlit_app.py +61 -40
src/streamlit_app.py
CHANGED
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@@ -5,11 +5,7 @@ import numpy as np
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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from normalizer import normalize
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st.set_page_config(page_title="Political Sentiment", page_icon="
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", layout="wide")
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st.markdown("""
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<style>
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@@ -17,53 +13,68 @@ st.markdown("""
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html, body, [class*="css"] {
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font-family: 'Inter', sans-serif;
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}
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.stApp {
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background-color: #
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}
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.main-card {
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background-color: white;
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padding: 30px;
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border-radius: 15px;
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box-shadow: 0 4px
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margin-bottom: 25px;
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text-align: center;
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}
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.result-title {
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color: #
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font-size:
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text-transform: uppercase;
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letter-spacing:
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margin-bottom: 10px;
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font-weight:
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}
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.result-value {
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font-size:
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font-weight: 800;
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margin: 0;
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}
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.model-card {
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background-color: white;
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padding: 20px;
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border-radius: 12px;
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box-shadow: 0 2px
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margin-bottom: 15px;
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}
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.model-card:hover {
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transform: translateY(-
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box-shadow: 0
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}
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.model-name {
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color: #
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font-size: 14px;
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font-weight: 600;
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margin-bottom: 8px;
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@@ -71,36 +82,37 @@ st.markdown("""
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padding-bottom: 5px;
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}
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.prob-label {
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font-size:
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color: #
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display: flex;
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justify-content: space-between;
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}
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.prob-bar-bg {
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width: 100%;
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height:
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background-color: #e5e7eb;
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border-radius:
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overflow: hidden;
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}
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.prob-bar-fill {
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height: 100%;
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border-radius:
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transition: width 0.5s ease;
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}
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.stTextArea textarea {
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border-radius: 12px !important;
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border:
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padding: 15px !important;
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div[data-testid="stMetricValue"] {
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font-size: 20px !important;
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}
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</style>
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""", unsafe_allow_html=True)
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@@ -149,7 +161,7 @@ def get_detailed_prediction(text):
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final_vote = max(set(votes), key=votes.count)
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return final_vote, votes, avg_probs
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st.markdown("<h1 style='text-align: center;
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with st.container():
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col_input, col_action = st.columns([4, 1])
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@@ -163,29 +175,38 @@ if analyze_btn and user_input.strip():
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with st.spinner('Running Ensemble Analysis...'):
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final_res, all_votes, avg_probs = get_detailed_prediction(user_input)
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st.markdown("<div style='height:
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main_col, details_col = st.columns([1, 1.5], gap="large")
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with main_col:
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st.markdown(f"""
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<div class="main-card" style="border-top:
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<div class="result-title">Ensemble Consensus</div>
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<div class="result-value" style="color: {label_colors[final_res]}">{final_res}</div>
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</div>
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""", unsafe_allow_html=True)
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st.markdown(
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for i in range(5):
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label = id2label[i]
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color = label_colors[label]
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st.markdown(f"""
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<div
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<div class="prob-label">
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<span
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<span>{prob:.1f}%</span>
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</div>
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<div class="prob-bar-bg">
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@@ -195,7 +216,7 @@ if analyze_btn and user_input.strip():
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""", unsafe_allow_html=True)
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with details_col:
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st.markdown(
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m_names = list(models_dict.keys())
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row1 = st.columns(2)
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@@ -210,7 +231,7 @@ if analyze_btn and user_input.strip():
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st.markdown(f"""
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<div class="model-card">
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<div class="model-name">{model_name}</div>
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<div style="color: {color}; font-weight: 700; font-size:
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</div>
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""", unsafe_allow_html=True)
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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from normalizer import normalize
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st.set_page_config(page_title="Political Sentiment", page_icon="🇧🇩", layout="wide")
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st.markdown("""
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<style>
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html, body, [class*="css"] {
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font-family: 'Inter', sans-serif;
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color: #000000;
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}
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.stApp {
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background-color: #f4f6f9;
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}
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h1, h2, h3 {
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color: #111827 !important;
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}
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.main-card {
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background-color: white;
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padding: 30px;
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border-radius: 15px;
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box-shadow: 0 4px 10px rgba(0,0,0,0.08);
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margin-bottom: 25px;
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text-align: center;
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border: 1px solid #e5e7eb;
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}
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.result-title {
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color: #374151;
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font-size: 16px;
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text-transform: uppercase;
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letter-spacing: 1.5px;
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margin-bottom: 10px;
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font-weight: 700;
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}
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.result-value {
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font-size: 48px;
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font-weight: 800;
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margin: 0;
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}
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.section-header {
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font-size: 20px;
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font-weight: 700;
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color: #1f2937;
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margin-bottom: 20px;
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border-left: 5px solid #2563eb;
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padding-left: 10px;
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}
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.model-card {
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background-color: white;
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padding: 20px;
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border-radius: 12px;
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box-shadow: 0 2px 5px rgba(0,0,0,0.05);
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margin-bottom: 15px;
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border: 1px solid #e5e7eb;
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transition: all 0.2s ease;
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}
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.model-card:hover {
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transform: translateY(-3px);
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box-shadow: 0 8px 15px rgba(0,0,0,0.1);
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}
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.model-name {
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color: #4b5563;
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font-size: 14px;
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font-weight: 600;
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margin-bottom: 8px;
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padding-bottom: 5px;
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}
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.prob-row {
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margin-bottom: 15px;
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}
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.prob-label {
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font-size: 14px;
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color: #111827;
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font-weight: 600;
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margin-bottom: 5px;
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display: flex;
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justify-content: space-between;
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}
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.prob-bar-bg {
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width: 100%;
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height: 10px;
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background-color: #e5e7eb;
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border-radius: 5px;
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overflow: hidden;
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}
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.prob-bar-fill {
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height: 100%;
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border-radius: 5px;
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}
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.stTextArea textarea {
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border-radius: 12px !important;
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border: 2px solid #d1d5db !important;
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padding: 15px !important;
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font-size: 16px;
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}
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</style>
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""", unsafe_allow_html=True)
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final_vote = max(set(votes), key=votes.count)
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return final_vote, votes, avg_probs
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st.markdown("<h1 style='text-align: center; margin-bottom: 10px;'>🇧🇩 BD Political Sentiment Analysis</h1>", unsafe_allow_html=True)
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with st.container():
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col_input, col_action = st.columns([4, 1])
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with st.spinner('Running Ensemble Analysis...'):
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final_res, all_votes, avg_probs = get_detailed_prediction(user_input)
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st.markdown("<div style='height: 30px'></div>", unsafe_allow_html=True)
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main_col, details_col = st.columns([1, 1.5], gap="large")
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with main_col:
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st.markdown(f"""
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<div class="main-card" style="border-top: 6px solid {label_colors[final_res]}">
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<div class="result-title">Ensemble Consensus</div>
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<div class="result-value" style="color: {label_colors[final_res]}">{final_res}</div>
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</div>
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""", unsafe_allow_html=True)
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st.markdown('<div class="section-header">Probability Distribution</div>', unsafe_allow_html=True)
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for i in range(5):
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label = id2label[i]
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raw_prob = avg_probs[i] * 100
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# Visual cleanup: Force 0% if extremely low to reduce noise
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if raw_prob < 1.0:
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prob = 0.0
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else:
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prob = raw_prob
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color = label_colors[label]
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# High opacity for significant numbers, low for 0-1%
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opacity = "1.0" if prob > 1 else "0.3"
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st.markdown(f"""
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<div class="prob-row" style="opacity: {opacity}">
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<div class="prob-label">
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<span>{label}</span>
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<span>{prob:.1f}%</span>
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</div>
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<div class="prob-bar-bg">
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""", unsafe_allow_html=True)
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with details_col:
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st.markdown('<div class="section-header">Individual Model Predictions</div>', unsafe_allow_html=True)
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m_names = list(models_dict.keys())
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row1 = st.columns(2)
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st.markdown(f"""
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<div class="model-card">
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<div class="model-name">{model_name}</div>
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<div style="color: {color}; font-weight: 700; font-size: 20px;">{vote}</div>
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</div>
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""", unsafe_allow_html=True)
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