How to optimize vector similarity search
I use prisma as ORM and execute a raw query.
In my table I have these rows :
titleEmbedded Unsupported("vector")?
descriptionEmbedded Unsupported("vector")?
locationEmbedded Unsupported("vector")?
Each of my vectors have 3072 dimensions (from openai embedding)
From what I see HNSW can only be up to 2k dimensions.
I have more than 100k rows
How can I optimize my query ? (right now its pretty slow)
In my table I have these rows :
titleEmbedded Unsupported("vector")?
descriptionEmbedded Unsupported("vector")?
locationEmbedded Unsupported("vector")?
Each of my vectors have 3072 dimensions (from openai embedding)
From what I see HNSW can only be up to 2k dimensions.
I have more than 100k rows
How can I optimize my query ? (right now its pretty slow)
