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| from logging import getLogger | |
| from pathlib import Path | |
| import joblib | |
| import pandas as pd | |
| import plotly.express as px | |
| import plotly.graph_objects as go | |
| import streamlit as st | |
| from top2vec import Top2Vec | |
| def initialize_state(): | |
| with st.spinner("Loading app..."): | |
| if 'model' not in st.session_state: | |
| model = Top2Vec.load('models/model.pkl') | |
| model._check_model_status() | |
| model.hierarchical_topic_reduction(num_topics=20) | |
| st.session_state.model = model | |
| st.session_state.umap_model = joblib.load(proj_dir / 'models' / 'umap.sav') | |
| logger.info("loading data...") | |
| data = pd.read_csv(proj_dir/'data'/'data.csv') | |
| data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}') | |
| st.session_state.data = data | |
| topics = pd.read_csv(proj_dir/'data'/'topics.csv') | |
| topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}') | |
| st.session_state.topics = topics | |
| if 'data' not in st.session_state: | |
| logger.info("loading data...") | |
| data = pd.read_csv(proj_dir/'data'/'data.csv') | |
| data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}') | |
| st.session_state.data = data | |
| st.session_state.selected_data = data | |
| st.session_state.all_topics = list(data.topic_id.unique()) | |
| if 'topics' not in st.session_state: | |
| logger.info("loading topics...") | |
| topics = pd.read_csv(proj_dir/'data'/'topics.csv') | |
| topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}') | |
| st.session_state.topics = topics | |
| def main(): | |
| st.write(""" | |
| A way to dive into each topic. Use the slider on the left to choose the topic. | |
| The `y` axis shows which words are closest to a topic centroid. The `x` axis shows how correlated they are.""") | |
| topic_num = st.sidebar.slider("Topic Number", 0, 19, value=0) | |
| fig = go.Figure(go.Bar( | |
| x=st.session_state.model.topic_word_scores_reduced[topic_num][::-1], | |
| y=st.session_state.model.topic_words_reduced[topic_num][::-1], | |
| orientation='h')) | |
| fig.update_layout( | |
| title=f'Words for Topic {topic_num}', | |
| yaxis_title='Top 20 topic words', | |
| xaxis_title='Distance to topic centroid' | |
| ) | |
| st.plotly_chart(fig, True) | |
| if __name__ == "__main__": | |
| # Setting up Logger and proj_dir | |
| logger = getLogger(__name__) | |
| proj_dir = Path(__file__).parents[2] | |
| # For max width tables | |
| pd.set_option('display.max_colwidth', 0) | |
| # Streamlit settings | |
| st.set_page_config(layout="wide") | |
| md_title = "# Topic Explorer 📚" | |
| st.markdown(md_title) | |
| st.sidebar.markdown(md_title) | |
| initialize_state() | |
| main() |