Old behavior: clicking "עיבוד מחדש" on a source preserved the existing
metadata (title, identifier, dates, summary, labels) and only re-chunked
+ re-embedded the file. Sources whose original AI classification produced
weak metadata (e.g. title="החלטה" with no summary) had no path to recover
short of deleting and re-uploading.
New behavior: re-process now goes through the same two-phase pipeline as
a fresh upload — classify (AI extracts metadata) → awaiting_review (user
sees suggestions in the batch review screen and edits) → commit (kb_source
metadata is overwritten + chunks are replaced + labels are replaced).
Implementation:
• start_reingest now returns {job_id, batch_id} and pre-fills metadata_json
with the existing source's labels + summary so the form has a fallback
if the classifier times out.
• The reingest route schedules ingest_jobs.process_classify_stage instead
of admin_sources.process_reingest_job.
• commit_job branches on job.source_id: NULL → fresh upload (creates new
kb_source); set → re-ingest (UPDATE kb_source + replace chunks).
• New process_reingest_embed_stage replaces the old process_reingest_job;
it bypasses _EDITABLE_FIELDS so the user can also change kind on
re-process (e.g. caselaw uploaded as circular).
The browser opens the same batch review screen, so the UX matches uploads
exactly. Re-ingests are single-file batches.
Frontend changes (KnowledgeBase extension v0.9.0) ship in a separate repo.
chaim
4ad569d54c