Update app.py

app.py

@@ -83,7 +83,7 @@
 import os
 import sys
 from langchain.chains import ConversationalRetrievalChain
-from langchain.document_loaders import DirectoryLoader, TextLoader
+from langchain.document_loaders import PyPDFLoader, Docx2txtLoader, TextLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import Chroma
 import gradio as gr
@@ -119,14 +119,7 @@ embeddings = embedding_model.encode(texts).tolist()  # Convert numpy arrays to l
 
 # Create a Chroma vector store and add documents and their embeddings
 vectorstore = Chroma(persist_directory="./db")
-vectorstore.add_texts(texts)
-for i, embedding in enumerate(embeddings):
-    vectorstore._collection.upsert(
-        ids=[str(i)],
-        embeddings=[embedding],
-        metadatas=[{"id": i}],
-        documents=[texts[i]]
-    )
+vectorstore.add_texts(texts=texts, metadatas=[{"id": i} for i in range(len(texts))], embeddings=embeddings)
 vectorstore.persist()
 
 # Load the Hugging Face model for text generation
@@ -187,3 +180,4 @@ demo.launch(debug=True)
 
 
 
+