app.py

import streamlit as st
import pandas as pd

from sentence_transformers import SentenceTransformer
model = SentenceTransformer('paraphrase-MiniLM-L6-v2')

#Sentences we want to encode. Example:
sentence = ['This framework generates embeddings for each input sentence']


#Sentences are encoded by calling model.encode()
embedding = model.encode(sentence)

x = st.slider('Select a value')
st.write(x, 'squared is', x * x, 'embedding', embedding[0][0])


uploaded_file = st.file_uploader("Choose a file")
if uploaded_file is not None:
    #read csv
    df1=pd.read_csv(uploaded_file)