jlightner e80094dc05 feat: Truncation detection, batched classification, and pipeline auto-resume ... Three resilience improvements to the pipeline: 1. LLMResponse(str) subclass carries finish_reason metadata from the LLM. _safe_parse_llm_response detects truncation (finish=length) and raises LLMTruncationError instead of wastefully retrying with a JSON nudge that makes the prompt even longer. 2. Stage 4 classification now batches moments (20 per call) instead of sending all moments in a single LLM call. Prevents context window overflow for videos with many moments. Batch results are merged with reindexed moment_index values. 3. run_pipeline auto-resumes from the last completed stage on error/retry instead of always restarting from stage 2. Queries pipeline_events for the most recent run to find completed stages. clean_reprocess trigger still forces a full restart. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>		2026-03-31 17:48:19 -05:00
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__init__.py	fix: restore complete project tree from ub01 canonical state	2026-03-31 02:10:41 +00:00
embedding_client.py	fix: restore complete project tree from ub01 canonical state	2026-03-31 02:10:41 +00:00
llm_client.py	feat: Truncation detection, batched classification, and pipeline auto-resume	2026-03-31 17:48:19 -05:00
qdrant_client.py	feat: Add bulk pipeline reprocessing — creator filter, multi-select, clean retrigger	2026-03-31 15:24:59 +00:00
schemas.py	fix: restore complete project tree from ub01 canonical state	2026-03-31 02:10:41 +00:00
stages.py	feat: Truncation detection, batched classification, and pipeline auto-resume	2026-03-31 17:48:19 -05:00