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| import streamlit as st | |
| import sqlite3 | |
| import pandas as pd | |
| # Initialize SQLite database | |
| conn = sqlite3.connect('word_classification.db') | |
| c = conn.cursor() | |
| # Create table if it doesn't exist | |
| c.execute(''' | |
| CREATE TABLE IF NOT EXISTS word_classification ( | |
| word TEXT, | |
| category TEXT | |
| ) | |
| ''') | |
| # Function to save word and its category | |
| def save_word(word, category): | |
| c.execute("INSERT INTO word_classification (word, category) VALUES (?, ?)", | |
| (word, category)) | |
| conn.commit() | |
| # Function to load words | |
| def load_words(): | |
| df = pd.read_sql_query("SELECT * FROM word_classification", conn) | |
| return df | |
| # Streamlit UI | |
| st.title('Word Classification') | |
| # Input fields for word and category | |
| word = st.text_input('Enter Word') | |
| category = st.selectbox('Select Category', ['Theme', 'Subtheme', 'Keywords']) | |
| if st.button('Save Word'): | |
| save_word(word, category) | |
| st.success(f'Word "{word}" saved under category "{category}"!') | |
| if st.button('View All Entries'): | |
| df = load_words() | |
| st.dataframe(df) | |
| # Close the database connection when the app is done | |
| conn.close() | |