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* fix(journal): dedup llm.ai.response persistence on re-fired on_llm_end LangChain may deliver on_llm_end more than once for the same run_id. RunJournal already dedups token accounting and the run summary (_record_message_summary) on that premise via _counted_message_llm_run_ids, but the durable llm.ai.response self._put() call was left unguarded. The event store is append-only and count_messages/list_messages read raw rows without read-time dedup, so a replayed callback persists a second llm.ai.response row for one logical response while the run's own message_count counts it once. This inflates count_messages, duplicates a message in list_messages pagination, and leaves the durable feed inconsistent with the run summary. Gate the persistence + summary block by the existing per-run_id guard so a replayed callback is a no-op, keeping the durable message feed and the run summary in agreement. Distinct run_ids are unaffected. Adds regression tests: a re-fired callback for one run_id persists exactly one row (red on main), and distinct run_ids each still persist a message. * fix(journal): preserve canonical response on late usage * fix(journal): preserve late usage while deduplicating responses * fix(journal): keep first callback response canonical * fix(journal): snapshot canonical response summaries --------- Co-authored-by: CorgiBoyG <CorgiBoyG@users.noreply.github.com>