apps/intro.py

import plotly.express as px
import streamlit as st
from sentence_transformers import SentenceTransformer
from huggingface_hub import hf_hub_url, cached_download
import umap.umap_ as umap
import pandas as pd
import os
import joblib

def app():
    with st.container():
        question = st.text_input("Please enter your text here and we will embed it for you.",
                                         value="Woman",)
        
        if st.button("Embed"):
            with st.spinner("👑 load language model (sentence transformer)"):
                model_name = 'sentence-transformers/all-MiniLM-L6-v2'
                model = SentenceTransformer(model_name)
                REPO_ID = "peter2000/umap_embed_3d_all-MiniLM-L6-v2"
                FILENAME = "umap_embed_3d_all-MiniLM-L6-v2.sav"
                model_umap = joblib.load(cached_download(hf_hub_url(REPO_ID, FILENAME)))
                
                docs_umap = umap_model.transform(docs_embeddings)
                
                examples_embeddings = model.encode(question)
                examples_umap = umap_model.transform(examples_embeddings)

                st.write(examples_umap.shape)