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from logging import getLogger
from pathlib import Path
import joblib
import pandas as pd
import streamlit as st
from top2vec import Top2Vec
logger = getLogger(__name__)
proj_dir = Path(__file__).parents[1]
def initialization():
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...")
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
topics_dict = topics[['topic_id', 'topic_0']].to_dict()
topic_str_to_word = {topics_dict['topic_id'][i]: topics_dict['topic_0'][i] for i in range(20)}
st.session_state.topic_str_to_word = topic_str_to_word
if 'selected_points' not in st.session_state:
st.session_state.selected_points = []
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