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update_chat_tags_by_id runs at the end of every completion when tag generation is enabled (the default). It loaded the full chat row including the multi-megabyte blob, mutated only meta.tags, committed, then refreshed the row, which re-fetched and re-parsed the entire blob a second time, and finally validated the whole thing into a ChatModel that its only caller (the auto-tagging handler) discards. add_chat_tag_by_id_and_user_id_and_tag_name had the same shape for a one-tag append, and orphan cleanup issued one COUNT query per removed tag. Both tag writers now select only the meta column and issue a column-level UPDATE, never touching the blob; the single-tag path also skips the write entirely when the tag is already present. Orphan detection batches all per-tag counts into one round trip using one scalar subquery per tag with the exact same dialect-specific EXISTS filters as before; the existing single-tag count delegates to the batch helper so there is one implementation. Benchmark (real SQLite DB, 200-message chat, ~600 KB blob): | metric | before | after | | --- | --- | --- | | auto-tag update, 3 tags replaced | 12.85 ms | 7.36 ms | The absolute saving grows with chat size since the blob no longer gets fetched, parsed, re-fetched and validated at all. Functionally verified against a fresh database: tag replacement normalizes and filters the none placeholder, creates missing tag rows and leaves the blob untouched; orphaned tags are deleted while tags still referenced by other chats survive; single-tag add is idempotent; batch counts agree with the single count including unknown tags; unknown chat ids return None.