mod app.py

app.py

@@ -32,12 +32,12 @@ embedding_model = SentenceTransformerEmbeddings(model_name='thenlper/gte-large')
 # Load the persisted vectorDB
 persisted_vectordb_location = '10k-reports_db'
 collection_name = '10k-reports'
-reports_db = Chroma(
+vectorstore_persisted = Chroma(
     collection_name=collection_name,
     persist_directory=persisted_vectordb_location,
     embedding_function=embedding_model
 )
-reports_db.get()
+vectorstore_persisted.get()
 
 # Prepare the logging functionality
 log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"