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Parent(s):
ea72d75
Abstracted `session_state`. Should work for multiple users now
Browse files- app/Top2Vec.py +4 -0
- app/pages/01_Topic_Explorer_π.py +32 -39
- app/pages/02_Document_Explorer_π.py +32 -39
- app/pages/03_Semantic_Search_π.py +34 -41
- app/utilities.py +40 -0
app/Top2Vec.py
CHANGED
@@ -1,6 +1,10 @@
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import streamlit as st
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st.set_page_config(page_title="Top2Vec", layout="wide")
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st.markdown(
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"""
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import streamlit as st
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from utilities import initialization
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st.set_page_config(page_title="Top2Vec", layout="wide")
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initialization()
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st.markdown(
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"""
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app/pages/01_Topic_Explorer_π.py
CHANGED
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from logging import getLogger
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from pathlib import Path
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import joblib
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import pandas as pd
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import plotly.graph_objects as go
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import streamlit as st
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from top2vec import Top2Vec
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if 'topics' not in st.session_state:
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logger.info("loading topics...")
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topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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st.session_state.topics = topics
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def main():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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st.set_page_config(layout="wide")
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md_title = "# Topic Explorer π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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initialize_state()
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main()
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from logging import getLogger
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from pathlib import Path
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import pandas as pd
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import plotly.graph_objects as go
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import streamlit as st
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from utilities import initialization
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initialization()
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# @st.cache(show_spinner=False)
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# def initialize_state():
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# with st.spinner("Loading app..."):
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# if 'model' not in st.session_state:
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# model = Top2Vec.load('models/model.pkl')
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# model._check_model_status()
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# model.hierarchical_topic_reduction(num_topics=20)
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#
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# st.session_state.model = model
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# st.session_state.umap_model = joblib.load(proj_dir / 'models' / 'umap.sav')
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# logger.info("loading data...")
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#
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# if 'data' not in st.session_state:
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# logger.info("loading data...")
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# data = pd.read_csv(proj_dir / 'data' / 'data.csv')
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# data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.data = data
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# st.session_state.selected_data = data
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# st.session_state.all_topics = list(data.topic_id.unique())
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#
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# if 'topics' not in st.session_state:
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# logger.info("loading topics...")
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# topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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# topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.topics = topics
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def main():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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# st.set_page_config(layout="wide")
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md_title = "# Topic Explorer π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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# initialize_state()
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main()
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app/pages/02_Document_Explorer_π.py
CHANGED
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from logging import getLogger
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from pathlib import Path
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import joblib
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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from st_aggrid import AgGrid, ColumnsAutoSizeMode, GridOptionsBuilder
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from streamlit_plotly_events import plotly_events
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from top2vec import Top2Vec
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if 'topics' not in st.session_state:
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logger.info("loading topics...")
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topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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st.session_state.topics = topics
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def reset():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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st.set_page_config(layout="wide")
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md_title = "# Document Explorer π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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initialize_state()
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main()
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from logging import getLogger
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from pathlib import Path
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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from st_aggrid import AgGrid, ColumnsAutoSizeMode, GridOptionsBuilder
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from streamlit_plotly_events import plotly_events
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from utilities import initialization
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initialization()
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# @st.cache(show_spinner=False)
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# def initialize_state():
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# with st.spinner("Loading app..."):
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# if 'model' not in st.session_state:
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# model = Top2Vec.load('models/model.pkl')
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# model._check_model_status()
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# model.hierarchical_topic_reduction(num_topics=20)
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#
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# st.session_state.model = model
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# st.session_state.umap_model = joblib.load(proj_dir / 'models' / 'umap.sav')
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# logger.info("loading data...")
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#
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# if 'data' not in st.session_state:
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# logger.info("loading data...")
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# data = pd.read_csv(proj_dir / 'data' / 'data.csv')
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# data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.data = data
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# st.session_state.selected_data = data
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# st.session_state.all_topics = list(data.topic_id.unique())
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#
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# if 'topics' not in st.session_state:
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# logger.info("loading topics...")
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# topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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# topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.topics = topics
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def reset():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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# st.set_page_config(layout="wide")
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md_title = "# Document Explorer π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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# initialize_state()
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main()
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app/pages/03_Semantic_Search_π.py
CHANGED
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from logging import getLogger
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from pathlib import Path
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import joblib
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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from st_aggrid import AgGrid, ColumnsAutoSizeMode, GridOptionsBuilder
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from top2vec import Top2Vec
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topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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st.session_state.topics = topics
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st.session_state.selected_points = []
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def main():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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st.set_page_config(layout="wide")
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md_title = "# Semantic Search π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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initialize_state()
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main()
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from logging import getLogger
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from pathlib import Path
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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from st_aggrid import AgGrid, ColumnsAutoSizeMode, GridOptionsBuilder
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from utilities import initialization
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initialization()
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# @st.cache(show_spinner=False)
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# def initialize_state():
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# with st.spinner("Loading app..."):
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# if 'model' not in st.session_state:
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# model = Top2Vec.load('models/model.pkl')
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# model._check_model_status()
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# model.hierarchical_topic_reduction(num_topics=20)
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#
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# st.session_state.model = model
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# st.session_state.umap_model = joblib.load(proj_dir / 'models' / 'umap.sav')
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# logger.info("loading data...")
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#
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# if 'data' not in st.session_state:
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# logger.info("loading data...")
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# data = pd.read_csv(proj_dir / 'data' / 'data.csv')
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# data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.data = data
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# st.session_state.selected_data = data
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# st.session_state.all_topics = list(data.topic_id.unique())
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#
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# if 'topics' not in st.session_state:
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# logger.info("loading topics...")
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# topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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# topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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# st.session_state.topics = topics
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#
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# st.session_state.selected_points = []
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def main():
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pd.set_option('display.max_colwidth', 0)
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# Streamlit settings
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# st.set_page_config(layout="wide")
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md_title = "# Semantic Search π"
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st.markdown(md_title)
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st.sidebar.markdown(md_title)
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# initialize_state()
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main()
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app/utilities.py
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from logging import getLogger
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from pathlib import Path
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import joblib
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import pandas as pd
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import streamlit as st
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from top2vec import Top2Vec
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logger = getLogger(__name__)
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proj_dir = Path(__file__).parents[1]
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def initialization():
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with st.spinner("Loading app..."):
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if 'model' not in st.session_state:
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model = Top2Vec.load('models/model.pkl')
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model._check_model_status()
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model.hierarchical_topic_reduction(num_topics=20)
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st.session_state.model = model
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st.session_state.umap_model = joblib.load(proj_dir / 'models' / 'umap.sav')
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logger.info("loading data...")
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if 'data' not in st.session_state:
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logger.info("loading data...")
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data = pd.read_csv(proj_dir / 'data' / 'data.csv')
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data['topic_id'] = data['topic_id'].apply(lambda x: f'{x:02d}')
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st.session_state.data = data
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st.session_state.selected_data = data
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st.session_state.all_topics = list(data.topic_id.unique())
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if 'topics' not in st.session_state:
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logger.info("loading topics...")
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topics = pd.read_csv(proj_dir / 'data' / 'topics.csv')
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topics['topic_id'] = topics['topic_id'].apply(lambda x: f'{x:02d}')
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st.session_state.topics = topics
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if 'selected_points' not in st.session_state:
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st.session_state.selected_points = []
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