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""" |
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Created on Sat Dec 23 13:22:00 2023 |
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@author: Essio Rubin C. |
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""" |
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from PIL import Image |
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import streamlit as st |
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from st_pages import add_page_title |
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import time |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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from as_bert_df import batch_predict_sentiment_stars |
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c1 = st.container() |
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c2 = st.container() |
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def show_base_page(): |
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with c1: |
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add_page_title() |
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text_css = """ |
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<p style="font-family: Verdana; font-size: 15px; font-weight: 400; ; color: #5b5f62;"> |
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El archivo de reseñas debe ser un archivo de texto que contenga una reseña por cada línea. |
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La reseña puede estar escrita en idioma español, holandés, italiano, alemán, francés o inglés. |
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</p> |
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<p style="font-family: Verdana; font-size: 15px; font-weight: 400; ; color: #5b5f62;"> |
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El resultado de la predicción (sentimiento) es un numero de extrellas, entre 1 y 5. |
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<ul style="font-family: Verdana; font-size: 15px; font-weight: 400; ; color: #5b5f62;"> |
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<li>1 estrellas: DEPLORABLE</li> |
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<li>2 estrellas: MALO</li> |
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<li>3 estrellas: NEUTRAL</li> |
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<li>4 estrellas: BUENO</li> |
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<li>5 estrellas: EXCELENTE</li> |
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<ul> |
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</p> |
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<p> </p> |
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""" |
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st.write(text_css, unsafe_allow_html=True) |
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img = Image.open("assets/flags.jpg") |
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st.image(img, width=200) |
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global placeholder, placeholder2 |
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placeholder = st.empty() |
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placeholder2 = st.empty() |
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global uploaded_file |
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uploaded_file = placeholder.file_uploader("Cargar archivo de reseñas ...", type=['txt', 'csv'], key='uploader') |
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global button_1 |
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button_1 = placeholder2.button(" :gear: Predecir", type="primary", key='but_1') |
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def predecir(): |
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if uploaded_file is not None: |
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global data_df |
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progress_text = "Procesando. Espere." |
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my_bar = st.progress(0, text=progress_text) |
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for percent_complete in range(100): |
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time.sleep(0.01) |
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my_bar.progress(percent_complete + 1, text=progress_text) |
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time.sleep(1) |
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my_bar.empty() |
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data_df = pd.read_csv(uploaded_file, sep=";") |
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if data_df.shape[0] > 0: |
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if data_df.shape[1] < 2: |
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data_df['review'] = 0 |
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data_df.columns = ["review","predict"] |
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result = batch_predict_sentiment_stars(data_df) |
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show_data_editor(result) |
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show_chart(result) |
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placeholder.empty() |
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placeholder2.empty() |
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else: |
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st.error("Archivo se encuentra vacío.") |
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else: |
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st.error("Debe subir un archivo de texto") |
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def show_data_editor(data_df): |
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with c2: |
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st.data_editor( |
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data_df, |
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column_config={ |
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"review": st.column_config.TextColumn( |
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"review", |
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help="Ingrese la reseña.", |
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width="large", |
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required=True, |
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max_chars=500, |
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validate="[a-zA-Z]+$" |
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), |
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"predict": st.column_config.NumberColumn( |
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"predict", |
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help="Sentimiento expresado en cantidad de estrellas.", |
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width="small", |
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required=False, |
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default=0, |
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min_value=0, |
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max_value=5, |
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format="%d ⭐", |
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) |
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}, |
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hide_index=True, |
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num_rows="dynamic", |
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height = 260, |
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width = 900, |
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) |
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def show_chart(data): |
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fig, ax = plt.subplots() |
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fig.set_figwidth(5) |
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fig.set_figheight(3) |
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ax.set_title("Histograma de Frecuencias", fontsize = 8) |
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ax.set_xlim([0, 6]) |
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ax.set_xlabel('Sentimiento (Número de estrellas)', fontsize = 6) |
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ax.set_ylabel('Frecuencia', fontsize = 6) |
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ax.hist(data['predict'], bins=20, color ="green") |
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st.pyplot(fig) |
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show_base_page() |
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if button_1: |
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predecir() |
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