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The embedding backfill (TriggerEmbeddings + the scheduled runEmbeddings) ran under a hardcoded 30-minute context. That is fine for a fast hosted embedding API, but local/self-hosted embedders (e.g. Ollama on CPU) are far slower — on a large catalog they embed only a few thousand items before the context deadline aborts the run with "context deadline exceeded". The job is idempotent and resumable, so progress is not lost, but it never finishes without repeatedly re-triggering it. Make the per-run timeout configurable via a new `recommendations.embeddings_job_timeout` setting (default 24h), threaded through RecommendationsConfig -> NewWorker and applied to both the manual trigger and the cron-scheduled run. A non-positive value falls back to 24h. Default behavior is unchanged for hosted users (a full backfill comfortably fits in 24h); local LLM users can now complete a one-shot backfill instead of stalling. AI-use disclosure: implemented with assistance from Claude Code. Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>