chaim
0d678da25f
Phase 6 of the multi-topic KB refactor (backend half). Subsumes the original Task #19 design discussion (subject vs labels). EspoCRM extension UI ships separately. Migrations (4 new, all idempotent, transaction-wrapped): 004_kind_tool — adds 'tool' to kb_source/kb_ingest_job CHECK 005_source_description — kb_source.description + ai_classified_at 006_labels — kb_label + kb_source_label (M:N), GRANTs 007_ingest_classifier — awaiting_review status + processing_stage + ai_suggestions JSONB + batch_id Two-phase ingest (api/services/kb/ingest_jobs.py): queued → processing(stage=classifying) → awaiting_review ← user reviews AI output → processing(stage=embedding) ← after user commits → done | failed process_classify_stage() pulls the file, runs parse_first_pages (3-page text extract), calls classifier.classify (Claude tool-call via ai-gateway, 45s timeout, 5-concurrent semaphore, fail-soft on any error → empty suggestions), writes ai_suggestions JSONB, transitions to awaiting_review. commit_job() resolves user-confirmed labels (existing by slug, new ones via slugify+ON CONFLICT DO NOTHING), transitions to processing(embedding), schedules process_embed_stage. process_embed_stage() runs the legacy ingest_source path with user-edited metadata + summary as kb_source.description, then apply_to_source for labels. discard_job() removes a file from a batch (status=failed, S3 deleted). list_jobs_by_batch() — single-roundtrip review-screen load. Labels (NEW api/services/kb/labels.py): Hebrew → ASCII slugify (letter-by-letter map, no external dep); CRUD; lookup_or_create_batch (race-safe); apply_to_source + replace_for_source maintain usage_count; merge race-safely (UPDATE assignments + ON CONFLICT DO NOTHING). Classifier (NEW api/services/kb/classifier.py): AsyncOpenAI to ai-gateway, Sonnet, OpenAI-style tool calling for guaranteed JSON shape, Hebrew system prompt with 5 kind values, citation format examples, "do not invent" rule, summary length bounds 80-200 chars. Routes (api/routes/admin_kb.py — 8 new on top of existing 11): POST /admin/kb/upload-batch (multi-file, AI classify) GET /admin/kb/batch/{batch_id} (review-screen load) POST /admin/kb/jobs/{id}/commit (user confirms metadata) POST /admin/kb/jobs/{id}/discard (user removes from batch) GET /admin/kb/labels (typeahead) POST /admin/kb/labels (explicit create) POST /admin/kb/labels/{id}/merge (admin cleanup) DELETE /admin/kb/labels/{id} (only if usage=0) Public /kb/search gains optional label_id filter. admin_sources.list_sources LEFT JOINs labels into each row's output. update_source accepts label_ids to replace the set. End-to-end smoke test passed: synthetic Hebrew circular → upload-batch → background classify → awaiting_review with kind, title, subject, summary, identifier, published_at all populated correctly. Refs Task Master #20 (espocrm-extensions/KnowledgeBase v0.8.0) Subsumes: Task #19 (labels for sub-topics) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
22 lines
874 B
PL/PgSQL
22 lines
874 B
PL/PgSQL
-- Migration 005: kb_source gains a one-line description + AI-classification timestamp.
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--
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-- Task Master #20 (v0.8.0). The classifier (api/services/kb/classifier.py)
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-- returns a 40–200 char Hebrew summary for each uploaded document. It's
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-- worth surfacing on search hit cards and in the management table, so we
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-- store it as a permanent column on kb_source rather than only on the
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-- ephemeral kb_ingest_job row. ai_classified_at marks AI-touched sources
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-- for future audits / metrics; null for legacy rows.
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--
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-- Idempotent — wrapped in a single transaction.
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--
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-- Run as postgres superuser:
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-- docker exec -i <pg-container> psql -U postgres -d insurance_kb \
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-- -f /tmp/005_source_description.sql
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BEGIN;
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ALTER TABLE kb_source ADD COLUMN IF NOT EXISTS description TEXT;
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ALTER TABLE kb_source ADD COLUMN IF NOT EXISTS ai_classified_at TIMESTAMPTZ;
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COMMIT;
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