Hi guys, I am trying Qdrantvector store

At a glance

The community member is experiencing a timeout error while trying to use the Qdrant vector store with the provided code. The comments suggest several potential solutions, such as lowering the batch size, checking for connection issues, disabling indexing during large uploads, and monitoring the CPU and RAM usage. While there is no explicitly marked answer, the community members provide helpful suggestions to troubleshoot the issue.

Useful resources

PPujari12

Hi guys, I am trying Qdrantvector store but getting timed out error while running the below code -
client = QdrantClient(url="http://xxxxxxxxxxxxxxxxxxxxx")

create our vector store with hybrid indexing enabled

batch_size controls how many nodes are encoded with sparse vectors at once

vector_store = QdrantVectorStore(
"llama2_paper", client=client, enable_hybrid=True, batch_size=20
)

storage_context = StorageContext.from_defaults(vector_store=vector_store)
Settings.chunk_size = 512

index = VectorStoreIndex.from_documents(
documents,
storage_context=storage_context,
)
how to solve this?

10 comments

LLogan M

Maybe lower the batch size? 🤷‍♂️ Hard to say without the traceback tho

ssansmoraxz

Shooting in the dark here but can you validate if it is it a connection issue. Check if you can make raw API calls.

ssansmoraxz

isn't it better to do it over larger batches as each insertion triggers reindexing?

EDIT: it's not always anymore.

ssansmoraxz

ideally you should disable indexing when doing large uploads.

ssansmoraxz

and re-enable after.

LLogan M