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

Does any vector database like Qdrant exist for the browser/IndexDB?

@andrey.vasnetsov What is the server HTTP timeout value?

Hi all! We made some experiments with mmap and summarized in in the article "Minimal RAM you need to serve a million vectors" https://qdrant.tech/articles/memory-consumption/ We found that using `htop` for checking memory consumption is wrong. So we did it in a hard way. As a result, we could serve 1+ million vectors using just 135Mb of RAM! But spoiler: ||you would need fast disks for that||

Simple and easy way to expose Qdrant from your Kubernetes cluster, and use Authentication. https://bichuetti.net/qdrant-authentication

Hey all, happy holidays. Complete newb here but how do I make vectors to upload with my documents? I feel like there is a fundamental gap in my knowledge. I’m trying to make a product search engine.

Hi everyone. Where can I learn about what status of collection means. For example status=green/yellow/red. And how to manage them? Thank you.

Qdrant Docker Consuming Full Memory

hi guys! Is someone here that could help me with one small issue ? I installed qdrant to kubernetes services, it deployed just fine. It is exposed as service in ingress route. qdrant is accessible thought REST API (web or insomnia) but when I am using python-client it fails. Sending stack trace. Thanks! ``` File ~/miniforge3/lib/python3.9/site-packages/qdrant_client/qdrant_client.py:1332, in QdrantClient.recreate_collection(self, collection_name, vectors_config, shard_number, replication_factor, write_consistency_factor, on_disk_payload, hnsw_config, optimizers_config, wal_config, timeout) 1329 if isinstance(wal_config, grpc.WalConfigDiff): 1330 wal_config = GrpcToRest.convert_wal_config_diff(wal_config) -> 1332 self.delete_collection(collection_name) 1334 create_collection_request = rest.CreateCollection( 1335 vectors=vectors_config, 1336 shard_number=shard_number, (...) 1342 wal_config=wal_config 1343 ) 1345 self.http.collections_api.create_collection( ... ---> 91 raise UnexpectedResponse.for_response(response) UnexpectedResponse: Unexpected Response: 308 (Permanent Redirect) Raw response content: b'\r\n308 Permanent Redirect\r\n\r\n

308 Permanent Redirect

hi, we have been doing some testing with the qdrant python client with low load (around 5 queries per second). The latencies of the QdrantClient.search() call can spike significantly higher than the latency of the actual server-side search (the search call can spike up to 400ms, while the Qdrant query takes up to 20ms). Is this an expected behavior? I've been playing around with trying to change the http connection pool settings but it hasn't yielded too many improvements.