import pandas as pd import streamlit as st import torch from sentence_transformers import SentenceTransformer @st.cache(allow_output_mutation=True) def load_model(model_name): # Lazy downloading model = SentenceTransformer(model_name) return model def load_embeddings(): # embedding pre-generated corpus_emb = torch.load( "./embeddings/descriptions_emb_10000_examples_github.pt", map_location=torch.device("cpu"), ) return corpus_emb @st.cache(allow_output_mutation=True) def load_texts(): # texts database pre-generated corpus_texts = pd.read_csv("./data/codesearchnet_10000_python_examples_github.csv") return corpus_texts