app.py

from Models.modules.utils import *
from Models.stock_embedder import *

import streamlit as st
import pandas as pd
import os

# Initializing
model_dir = "ver_6_2"

def main():
    # Set up streamlit
    st.set_page_config(page_title="Stock Embedder", page_icon=":robot:", layout='centered')
    st.header("📈Stock Embedder📉")

    # Load model
    model = StockEmbedder(cfg = load_model_config(model_dir=model_dir))

    # Upload files
    with st.sidebar:
        uploaded_file = st.file_uploader("Upload files", type='csv')

    # Read csv file
    if uploaded_file is not None:
        df = pd.read_csv(uploaded_file)
        st.write("Your uploaded data: ", df.head())
    
    if st.button("Get Stock Embedding"):
        # Create data
        stock_data = torch.rand(128, model.config['ts_size'], model.config['z_dim'])
        stock_data = normalize(stock_data, min_val=model.config['min_val'], max_val=model.config['max_val'])
        st.write("Your stock data has been created: ", stock_data)
        # Get embedding
        stock_embedding = model.get_embedding(stock_data=stock_data, embedding_used='encoder')
        st.write("Your stock embedding has been created: ", stock_embedding)

if __name__ == '__main__':
    main()