Guys, I have a question: Why would vscode complain about this?

https://www.pinecone.io/learn/hybrid-search/ any chance we could get smth similar to this in qDrant? Would be hugely valuable for semantic search use cases, they really nailed it

Once the cloud offering moves out of beta, will it be possible to shift our nodes to a location other than the US, while retaining the data? Right now I only see AWS & one location in the US as an option.

Hi I have various of vector if the number of data increase I will face the problem of ram how to solve it? Can we search in two collection for search for one input?

seeing more of this broken pipe and socket timeout errors which we had noticed before , https://discord.com/channels/907569970500743200/928649303898075196/1059893176082645043 the only thing which we are having diff is the efs , and not storing data in ebs. ( is anyone else has noticed this errors) now i am seeing at a retrofit calls as well at read time , and happening at read time makes it critical. sharing the stacktrace at readtime

Out of file descriptors

Hi We have an application which makes a lot of use of vector representations of images and text. As part of our development aims I am evaluating vector databases. We have a slightly different need - where we have a vector we are not so much interested in the most similar vector, we need to know the most *disimilar* - so it's furthest neighbour rather than nearest neighbour - how would qdrant cope with this ? thanks !

Replicas? Can you expand a bit on that? thanks

Is there a way we can use txtai with qdrant cloud? looking into this https://github.com/qdrant/qdrant-txtai but not able to pinpoint the API key option

*Description:* Right around 590 upserts (~35 min in) I get a `service unavailable (503)` or a `bad gateway (502)` response. It starts intermittent, then it just becomes persistent. Wondering if I am triggering something in the load balancer. Is there recommended way of upserting? I’m doing it in ~1000 batches for 1.7 million embeddings so ~1700 upserts. Qdrant cloud dashboard says my cluster is `DOWN`. It goes back to healthy once I kill the upset script and give it a break from upserting. *Some specs:* **Embeddings size**: 384 (`all-MiniLM-L12-v2`) **Cloud instance specs**: 4GB RAM, 1vCPU, 16GB Disk **Hosting info**: AWS - US East *Other Info:* I am behind a VPN to access the data I am embedding, but I wouldn’t think that’d be an issue.