Update app.py

app.py

@@ -118,7 +118,7 @@ texts = [doc.page_content for doc in docs]
 embeddings = embedding_model.encode(texts).tolist()  # Convert numpy arrays to lists
 
 # Create a Chroma vector store and add documents and their embeddings
-vectorstore = Chroma(persist_directory="./data")
+vectorstore = Chroma(persist_directory="./db")
 vectorstore.add_texts(texts)
 for i, embedding in enumerate(embeddings):
     vectorstore._collection.upsert(