Update agent.py

agent.py

@@ -416,8 +416,7 @@ texts = [doc.page_content for doc in docs]
 # Initialize the embedding model
 embedding_model = BERTEmbeddings()
 
-# Generate embeddings for each document
-embeddings = [embedding_model.encode(text) for text in texts]
+embeddings = [embedding_model.embed_query(text) for text in texts]
 
 # Create the FAISS index
 vector_store = FAISS.from_documents(docs, embedding_model)