Update agent.py

agent.py

@@ -353,7 +353,7 @@ docs = [
     Document(page_content="She continued releasing music well into the 2000s.")
 ]
 # Get the embeddings for the documents
-embeddings = embedding_model.embed([doc.page_content for doc in docs])
+vector_store = FAISS.from_documents(docs, embedding_model)
 
 # Now, you can use the embeddings with FAISS or other retrieval systems
 # For example, with FAISS: