Estimating Memory Space for Embedding Records
TLDR Jerry wanted help estimating memory space for embedding. Jason provided the formula to calculate this using Typesense.
Jul 31, 2023 (4 months ago)
So for 1M records with vector data, you’d need 7 bytes * 1536 * 1M = ~10.8GB of RAM
Indexed 3015 threads (79% resolved)
Configuring Typesense Server for Large Record Embedding
Akash asked for typesense server config for 2.5lakh records. Jason and Kishore Nallan gave advice and resource links.
Memory Usage Difference between Typesense 0.23 and 0.25.1
Six was inquiring about the change in memory usage when moving from typesense 0.23 to 0.25.1. Jason confirmed that vectors do use additional memory.
Optimum Cluster for 1M Documents with OpenAI Embedding
Denny inquired about the ideal cluster configuration for handling 1M documents with openAI embedding. Jason recommended a specific configuration, explained record size calculation, and clarified embedding generation speed factors and the conditions that trigger openAI.