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import streamlit as st
from streamlit_option_menu import option_menu
from word2vec import *
import pandas as pd
st.set_page_config(page_title="Ancient Greek Word2Vec", layout="centered")
# Horizontal menu
active_tab = option_menu(None, ["Nearest neighbours", "Cosine similarity", "3D graph", 'Dictionary'],
menu_icon="cast", default_index=0, orientation="horizontal")
# Nearest neighbours tab
if active_tab == "Nearest neighbours":
st.write("### TO DO: add description of function")
col1, col2 = st.columns(2)
with st.container():
with col1:
word = st.text_input("Enter a word", placeholder="ἀνήρ")
with col2:
time_slice = st.selectbox("Time slice", ["Archaic", "Classical", "Hellenistic", "Early Roman", "Late Roman"])
n = st.slider("Number of neighbours", 1, 50, 15)
nearest_neighbours_button = st.button("Find nearest neighbours")
# If the button to calculate nearest neighbours is clicked
if nearest_neighbours_button:
# Rewrite timeslices to model names: Archaic -> archaic_cbow
time_slice = time_slice.lower() + "_cbow"
st.write(time_slice)
# Check if all fields are filled in
if validate_nearest_neighbours(word, time_slice, n) == False:
st.error('Please fill in all fields')
else:
nearest_neighbours = get_nearest_neighbours(word, time_slice, n)
df = pd.DataFrame(nearest_neighbours, columns=["Word", "Time slice", "Similarity"])
st.table(df)
# Cosine similarity tab
elif active_tab == "Cosine similarity":
with st.container():
st.write("Cosine similarity tab")
# 3D graph tab
elif active_tab == "3D graph":
with st.container():
st.write("3D graph tab")
# Dictionary tab
elif active_tab == "Dictionary":
with st.container():
st.write("Dictionary tab")
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