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app.py

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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()

requirements.txt

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+streamlit
+joblib

vectorizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:53b86f32e1abdc75fdb21e76c6db64a6510c4fc4e3a12f393375dc1b5bb6cc4f
+size 4239482