How it’s possible to create a vectorsearch index programmatically with python?
With langchain-mongodb, I try this:
self.vectorstore = MongoDBAtlasVectorSearch(
embedding=embeddings,
collection=collection,
index_name=index_name,
)
self.vectorstore.create_vector_search_index(
dimensions=embedding_size,
filters=None,
update=False,
)
but i receive this error:
pymongo.errors.OperationFailure: command not found, full error: {'ok': 0, 'errmsg': 'command not found', 'code': 59, 'codeName': 'CommandNotFound'}
Hi @Philippe_Prados what version of MongoDB Atlas are you running against?
Right now the create_vector_search_index
call only works on M10+ clusters running a specific minimum version of Atlas. To see what the prerequisites are, check the information here.