switching to intfloat/e5-base embedding model

ingest_data.py

@@ -1,7 +1,7 @@
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.document_loaders import PyPDFLoader
 from langchain.vectorstores import Chroma
-from langchain.embeddings import TensorflowHubEmbeddings
+from langchain.embeddings import HuggingFaceEmbeddings, SentenceTransformerEmbeddings
 import os
 import time
 import streamlit as st
@@ -26,7 +26,7 @@ def embed_doc(filename):
 
 
         start = time.time()
-        embeddings = TensorflowHubEmbeddings(model_url="https://tfhub.dev/google/universal-sentence-encoder-multilingual-qa/3")
+        embeddings = HuggingFaceEmbeddings(model_name="intfloat/e5-base")
         end = time.time()
         st.text("Embedding time: "+str(round(end - start,1)))
         start = time.time()