How to improve the search accuracy of MongoDBAtlasVectorSearch

MongoDB Atlas
1

`embed_model = ZhipuAIEmbeddings(
model=EMBEDDING_MODEL,
api_key=MODEL_API_KEY,
)

vector_search = MongoDBAtlasVectorSearch(
collection=collection,
embedding=embed_model,
index_name=“vector_index”,
embedding_key=“embedding”,
text_key=“text”
)

llm = ChatOpenAI(
temperature=0.95,
model=MODEL_NAME,
openai_api_key=MODEL_API_KEY,
openai_api_base=OPEN_API_BASE
)

qa_retriever = vector_search.as_retriever(
search_type=“similarity”
)

def get_db_chat():
#answer = vector_search.similarity_search(“劳动法第29条”)
answer = vector_search.similarity_search_with_score(
query=“劳动法第29条”, k=10
)
print(answer)```` The database contains the content of “中华人民共和国劳动法第二十九条”, but when searching, it is not found. How can I search accurately?