Indexing Time in Concurrent API Requests

Bill asks the best way for multi-term searches in a recommendation system they developed. Kishore Nallan suggested using embeddings and remote embedder or storing and averaging vectors. Despite testing several suggested solutions, Bill continued to face performance issues, leading to unresolved discussions about scalability and recommendation system performance.

Bill faced performance issues with vector search using multi_search feature. Jason and Kishore Nallan suggested running models on a GPU and excluding large fields from the search. Through discussion, it was established that adding more CPUs and enabling server-side caching could enhance performance. The thread concluded with the user reaching a resolution.

Erik sought advice for semantic search implementation in Typesense and raised issues around slow document import and excessive latency. Upon implementing advice from Kishore Nallan to try different models, Erik reported faster times, ultimately deciding to rate-limit imports.