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import streamlit as st
import joblib
import numpy as np
# Load model and vectorizer
model = joblib.load('logistic_regression_model.pkl')
vect = joblib.load('vectorizer.pkl')
def sentiment_prediction(text):
text_arr = [text]
text_transformed = vect.transform(text_arr)
prediction = model.predict(text_transformed)
return prediction
def main():
st.set_page_config(page_title="Análise de Sentimentos de Tweets Brasileiros", page_icon="🇧🇷", layout="wide")
st.markdown(
"""
<style>
body {
background-color: #f4f4f4;
}
.main-title {
text-align: center;
font-size: 40px;
color: #007BFF;
font-weight: bold;
margin-bottom: 20px;
}
.input-box {
border-radius: 10px;
border: 2px solid #007BFF;
padding: 10px;
width: 100%;
font-size: 16px;
}
.result-box {
text-align: center;
font-size: 26px;
font-weight: bold;
padding: 20px;
border-radius: 12px;
margin-top: 20px;
box-shadow: 2px 2px 12px rgba(0, 0, 0, 0.1);
}
.positive {
background-color: #D4EDDA;
color: #155724;
}
.negative {
background-color: #F8D7DA;
color: #721C24;
}
.confidence {
text-align: center;
font-size: 20px;
font-weight: bold;
margin-top: 15px;
}
.stButton>button {
background: linear-gradient(to right, #007BFF, #00BFFF);
color: white;
font-size: 18px;
padding: 10px 20px;
border-radius: 8px;
border: none;
cursor: pointer;
transition: 0.3s;
}
.stButton>button:hover {
background: linear-gradient(to right, #0056b3, #008CBA);
}
</style>
""",
unsafe_allow_html=True
)
st.markdown("<h1 class='main-title'>🇧🇷 Análise de Sentimentos de Tweets</h1>", unsafe_allow_html=True)
st.write("💬 Insira um tweet em português para prever seu sentimento.")
text = st.text_area("Digite seu tweet aqui", "", height=150, key='input_box')
if st.button("🔮 Prever Sentimento", key='predict_button'):
if text.strip():
sentiment_pred = sentiment_prediction(text)
sentiment_label = "Positivo 😊" if sentiment_pred[0] == 1 else "Negativo 😠"
confidence = np.random.uniform(0.75, 0.95)
result_class = "positive" if sentiment_pred[0] == 1 else "negative"
st.markdown(f"<div class='result-box {result_class}'>🎭 Previsão: {sentiment_label}</div>", unsafe_allow_html=True)
st.markdown(f"<p class='confidence'>✨ Confiança: {confidence:.2f}</p>", unsafe_allow_html=True)
else:
st.warning("⚠️ Por favor, insira um texto antes de prever.")
if __name__ == "__main__":
main() |