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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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from model import classifySentiment,groupClassifier
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st.title("🔍 Análisis de Sentimiento para Empresas")
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option = st.sidebar.selectbox("Elige una opción", ["Analizar un comentario", "Subir archivo CSV"])
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if option == "Analizar un comentario":
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user_input = st.text_area("Escribe un comentario:")
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if st.button("Analizar"):
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original_text ,sentiment = classifySentiment(user_input)
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st.write(f"📊 Sentimiento: {sentiment}")
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elif option == "Subir archivo CSV":
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file = st.file_uploader("Sube un archivo con comentarios en formato csv", type=["csv"])
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if file:
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try:
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df = pd.read_csv(file,sep=None, engine="python")
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clasification = groupClassifier(df)
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clasified_data = pd.DataFrame(clasification)
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plt.figure(figsize=(6,4))
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sns.countplot(x=clasified_data["label"], hue=clasified_data["label"], palette="pastel", legend=False)
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plt.xlabel("Sentiment category")
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plt.ylabel("number of texts")
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plt.title("Data distribution")
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st.pyplot(plt)
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except ValueError as e:
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print(f"Error: {e}")
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