Update app.py

app.py

@@ -5,21 +5,8 @@ from langchain_community.embeddings.sentence_transformer import SentenceTransfor
 from langchain_community.vectorstores import Chroma
 import streamlit as st
 
-text_loader_kwargs={'autodetect_encoding': True}
-loader = DirectoryLoader("src_info_hf", glob="./*.txt", loader_cls=TextLoader, loader_kwargs=text_loader_kwargs)
-docs = loader.load()
-
-# split it into chunks
-#text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
-#docs = text_splitter.split_documents(documents)
-
-# create the open-source embedding function
-#embedding_function = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
 embedding_function = SentenceTransformerEmbeddings(model_name="all-mpnet-base-v2")
-
-# load it into Chroma
-chdb = Chroma.from_documents(docs, embedding_function, collection_metadata={"hnsw:space": "cosine"}, persist_directory='chroma_db_info')
-
+chdb = Chroma(persist_directory="./chroma_db_info", embedding_function=embedding_function)
 
 text = st.text_area("enter text")
 if text: