The naive LIFO tag stack pushed every start tag and popped on any end tag by
position, not name. Real email HTML almost always writes void elements
(<meta>, <br>, <img>, ...) without a self-closing slash -- e.g. <head><meta
charset=...><meta name=viewport ...></head> pops a "meta" frame for the
literal </head>, leaving skip_depth stuck at 1 for the rest of the document.
Caught live during the faza-mailowa Etap A dry-run spot-check (plan §7,
Krok 4 calibration step) against real archived mail: a genuine HTML-only
promotional email extracted to '' entirely. Re-running the Etap A dry-run
after the fix dropped body_empty from 3253/13300 (24.5%) to 291/13300
(2.2%) -- the bug was silently discarding real content from a meaningful
slice of HTML-only mail.
Fix: void elements are never pushed onto the stack (so they can never
desync it); every other closing tag searches backward for its matching
open tag and truncates the stack from there, which also self-heals other
malformed nesting instead of only the void-tag case. 3 new regression
tests reproduce the exact <head><meta>...</head> pattern, br/hr line
breaks, and a stray unmatched closing tag.
retrieval_eval.py now runs every existing query through hybrid_query
alongside flat/cascade, and gate criteria 1/3 (no degradation, negative
controls) check hybrid too -- this is the phase's key regression test: does
adding mail chunks to the HNSW index degrade the 7 existing paperless
queries? Criterion 4 (mail hit@3 in hybrid) is wired but skipped with an
explicit report note when queries.yaml's new `mail_queries` placeholder is
empty, rather than silently PASSing/FAILing on absent data.
queries.yaml: added an empty `mail_queries: []` placeholder + inline format
docs. The existing 7-query `queries:` list is untouched.
REMINDER for the operator (per plan §8, Krok 5): 3-5 mail queries are still
needed -- things you know are in last year's mail, plus each one's expected
gmail Message-ID -- before criterion 4 and the full plan §8 gate can PASS.
Until then this only re-verifies the paperless regression check.
docs/kb/modules/05-faza-mailowa-plan.md, §8.
Second full pass over the gmail .eml archive (gmail-bulk-import's first pass
skipped inline text/plain and text/html on purpose). Per envelope: typed
parse with compat32 fallback -> body extraction (inline text/plain preferred,
HTML->text via a small stdlib HTMLParser otherwise) -> quote-strip (reply
markers + `>`-quoted lines, EN/PL/Outlook patterns) -> newsletter
classification (List-Unsubscribe/List-Id/Precedence, chunked but not
embedded, excluded_reason='newsletter') -> Temat/Od/Data prefix from the
already-backfilled entities[type=headers] (zero header re-parse) -> chunk via
kb_mail.chunking -> batched embed_batch (64) -> INSERT document_chunk.
In-Reply-To/References are appended as entities[type=threading] during the
same read (idempotent WHERE NOT EXISTS append, 1:1 with
gmail-header-backfill) -- the only DB writes are document_chunk INSERTs and
an additive envelope.entities UPDATE; the .eml archive stays read-only.
--dsn/KB_DSN, --archive-root, --since/--limit/--offset, --batch-size,
--apply (dry-run default). Idempotency keys on (envelope_id, chunk_index)
pre-fetched scoped to --model, built correctly from the start per the
plan's flagged chunk_embed.py precedent. A failed embed batch is isolated
(chunks_errors, no abort) for Ollama's documented instability; a wrong
embedding dimension aborts the whole run.
48 tests, DoD smoke run against live kb-postgres@PIHA confirmed wiring
(archive not yet rsync'd to SOLARIA, so all 5 rows correctly reported
missing_file). docs/kb/modules/05-faza-mailowa-plan.md, §5.
chunk_text/hard_split/split_paragraphs + 2400/600-char constants move out of
documents_ingest.chunk_embed into kb_mail.chunking so the upcoming
jobs/mail-body-ingest shares the exact same chunker instead of a copy-pasted
drift (the phase-4 lesson for retrieval.py -> packages/kb-retrieval, applied
again). chunk_embed.py re-exports unchanged; zero behavior change, tests moved
1:1 alongside the code (docs/kb/modules/05-faza-mailowa-plan.md, §3).
Module 5 phase 4 step 0 (docs/kb/modules/05-faza4-plan.md, §3, decision 1):
kb-query is a long-lived Docker service, documents-ingest is a venv job with
an `anthropic` dependency and CLI scripts it doesn't need. Move
embed_chunk/_vector_literal/cascade_query/flat_query into a shared package
with minimal deps (asyncpg, aiohttp only) so both can depend on the same
tested retrieval code without the service image pulling in the job's extras.
documents_ingest.chunk_embed/retrieval keep thin re-exports so nothing
importing the old paths breaks. Pure refactor: retrieval_eval.py run live
against kb-postgres@PIHA + Ollama@SOLARIA before/after gives byte-identical
`dist`/hit@3/gate results (still PASS) — zero behavior change in the cascade.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
documents-ingest-cyclic (jobs/documents-ingest/src/documents_ingest/cyclic_ingest.py):
orkiestruje paperless_adapter -> chunk_embed -> summarize(--backend anthropic,
claude-haiku-4-5) -> summarize(--embed-summaries) bez zmian w samych jobach. Ollama@SOLARIA
(availability_target: medium) jest tolerowana offline: probe GET /api/tags przed obu
etapami embed, brak -> pominięcie, nie fail (oba embed passy idempotentne, nadrobią się na
kolejnym ticku). Czwarty etap (embed-summaries) dopisany ponad plan §7.1 (który wymieniał
tylko 3 kroki) — bez niego nowe streszczenia miałyby embedding=NULL i byłyby niewidoczne dla
cascade_query (bramka kroku 4, WHERE embedding IS NOT NULL); potwierdzone z Oskarem.
Predykaty pass/fail każdego etapu 1:1 z exit-checkiem danego joba (chunks_errors,
llm_errors, stats-balance itd.) — etapy izolowane, nie fail-fast (wcześniejszy fail nie
blokuje kolejnych, tak jak joby izolują błędy per wiersz). Metryki .prom (atomowy zapis,
last_success_timestamp trzymany z poprzedniego pliku przy failu) do
/opt/homelab/state/node-exporter/kb-ingest.prom. 36 nowych testów (202/202 pakietu).
systemd (jobs/documents-ingest/systemd/): pierwszy systemd-timer w repo — kb-ingest.timer
(OnCalendar=*-*-* 03:30, Persistent=true, plan §7.1) + kb-ingest.service (host-level, User
oskar, EnvironmentFile /opt/homelab/kb/.env) + kb-ingest-run.sh (log per-run do
/opt/homelab/logs/kb-ingest/, konwencja repo). Instalacja i sekrety udokumentowane w
README (Faza 3 krok 5) — instalacja na PIHA dopiero po merge.
fleet-prometheus (rules/kb-ingest.yml): KbIngestStale (>172800s od last_success, critical)
+ KbEmbedBacklogGrowing (backlog>0 przez 72h, warning) — dostawa istniejącym torem
brain-watchdog->Telegram, bez Alertmanagera (konwencja liveness.yml).
node_exporter: owner_node vps -> per-host (service.yaml) + wpis + override
(--collector.textfile.directory, bez nowego mountu — czyta przez istniejący /:/host:ro) +
topology.yaml dla PIHA. Domyka pozycję z docs/backlog.md "stability-agent / node_exporter
owner_node single, biegaja wielomiejscowo -> per-host" (połowę — node_exporter; stability-agent
zostaje osobnym follow-upem) w ramach paczki B inwentaryzacji monitoringu dla PIHA.
Test end-to-end na żywo na PIHA (2× --apply, po potwierdzeniu z Oskarem): pierwszy run
złapał 5 dokumentów faktycznie nowych w Paperless (nieoczekiwane, niezwiązane z tym
taskiem) -> 82 nowe chunki (2 ocr_junk), 5 nowych streszczeń, 5 embeddingów streszczeń,
0 błędów, metryki zapisane. Drugi run: pełna idempotencja, wszystko 0. ANTHROPIC_API_KEY
dodany przez Oskara ręcznie do /opt/homelab/kb/.env (nigdy nie logowany/generowany).
Co dalej: prawdziwa instalacja systemd (services.yaml już przygotowany, po merge),
zdecydowanie czy stability-agent też idzie na per-host przy okazji.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
documents_ingest.retrieval: flat_query (baseline) i cascade_query (stage1
document_summary model='claude-haiku-4-5' -> stage2 document_chunk), jedno
dzielone wywołanie embeddingu bge-m3 per zapytanie, tylko +1 SQL na kaskadę.
Czyste query_text -> wyniki(dist, source) pod przyszłe kb-query fazy 4.
166/166 testów (10 nowych, mocki: stage1->stage2, koperta bez chunków,
N > liczba kopert, no-summaries short-circuit).
Eval-set utrwalony 1:1 z pilota (docs/kb/eval/retrieval-pilot-2026-07-16.md,
nietknięty) w eval/queries.yaml + skrypt bramki eval/retrieval_eval.py
(integracyjny, read-only, poza pytest).
Wynik bramki (żywa baza, N=10 k=5): kryterium 1 (brak degradacji) PASS,
kryterium 2 (hit@3 kaskada=5/5 vs płaski=5/5) PASS, kryterium 3 (kontrole
negatywne 0.644/0.553 > 0.55 w obu torach) PASS. Sweep N∈{1,2,3,5,10,20}:
N=5 to zmierzony próg bezpieczny (N<5 degraduje zapytania 3-4), N=10 ma
2x margines — potwierdza domyślną wartość z planu zamiast przyjmować ją
z założenia. Kaskada nie poprawia jakości na 186-dok. korpusie (dystanse
identyczne z płaskim przy N≥5) — zgodnie z przewidywaniem planu: to test
architektury pod skalę mailową, nie optymalizacja pilota.
Decyzja: kaskada (N=10, k=5, claude-haiku-4-5) = domyślna ścieżka retrievalu.
Plan-doc §6.3 zaktualizowany wynikiem; §2 D3 zamknięte rozstrzygnięciem
Oskara (tor kompilacyjny=claude-haiku-4-5, gemma3:12b w odwodzie, decyzja
mailowa odłożona do reconu z flagą prywatności/kosztu).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Migracja 004: document_summary (envelope_id, summary, tags JSONB, model, embedding
VECTOR(1024) + HNSW cosine, embedding_model, UNIQUE(envelope_id, model) od razu — wzorzec
002/003). Zastosowana na żywej bazie kb-postgres@PIHA.
Job documents-ingest-summarize: wejście = document_chunk.text WHERE excluded_reason IS NULL
per koperta source='paperless' (duplikaty przez entities[duplicate_of] pomijane w całości),
wymuszony JSON {summary, tags} przez --backend ollama|anthropic, słownik tagów kontrolowany
(tags-vocab.yaml) z max 3 free-form, map-reduce dla dokumentów >200k znaków (grupy ~20
chunków), bilans + idempotencja + izolacja błędów per wiersz wg wzorców rodziny jobów.
Osobny --embed-summaries (bge-m3, reużywa chunk_embed.embed_chunk).
Bug znaleziony i naprawiony w trakcie pilota: brak options.num_ctx w wywołaniach Ollamy
powodował, że gemma3:12b używał domyślnego runtime kontekstu (~2048 tok), nie
zadeklarowanego 128k — dla 71/157 dokumentów (45%, >8k znaków) treść była cicho ucinana
(zweryfikowane: prompt_eval_count=2051 dla dokumentu 93k znaków). Naprawa: compute_num_ctx()
liczy num_ctx z długości promptu (~3 znaki/token, cap 131072). Cały tor lokalny przeliczony
od zera po naprawie.
Wynik pilota (186 dok. paperless, 3 duplikaty, 26 bez aktywnych chunków → 157 oczekiwanych
na tor): tor lokalny (gemma3:12b) 155/157 (2 izolowane błędy JSON po retry: paperless:24,
paperless:61), tor referencyjny (claude-haiku-4-5) 157/157, 0 błędów JSON, 0 tagów
ucinanych — słownik przestrzegany w 100% przypadków. Oba komplety zembedowane (bge-m3).
Znaleziony przy okazji: prompt do tagów wymagał dopracowania — pierwsza wersja pozwalała
modelowi zwracać tagi po angielsku spoza słownika; wzmocniona instrukcja (słownik w
pierwszej kolejności, "nigdy po angielsku") poprawiła zgodność w 2/3 przypadków testowych.
Porównanie A/B (~15 dok.) i weryfikacja końcowa (bilans, sanity SQL, retrieval po summary)
odłożone do następnej sesji.
Testy: 157 (152 nowe/summarize.py + istniejące), mocki API/Ollama/DB, bilans, idempotencja,
regresja num_ctx.
Co najmniej 3 decyzje wymagały zatrzymania i potwierdzenia z Oskarem w sesji (sposób podania
klucza API, wybór modelu lokalnego gemma3:12b, naprawa+przeliczenie całego toru lokalnego po
odkryciu buga num_ctx) — udokumentowane w transkrypcie sesji.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Migracja 003 (UNIQUE+model, excluded_reason) zastosowana na żywej bazie kb-postgres@PIHA
(2683 chunki, bez DELETE). Kalibracja heurystyki ocr_junk (3 sygnały z planu §3.1) ujawniła
realną sprzeczność z planem: sygnał 1 (dowolny znak kontrolny) fałszywie łapał paperless:119
(wymagany aktywny) i legalny angielski tekst — próg doprecyzowany do >=5 wystąpień na
podstawie rozkładu na korpusie. 8 chunków oflagowanych ocr_junk po odjęciu potwierdzonych
fałszywych alarmów (kalendarz, mikro-fragmenty referencyjne).
Dedup: SQL z planu (exact content hash) znalazł 2 pary, ale nie wykrył znanego z pilota
duplikatu paperless:14≡74 (różne OCR, 99.2% chunków identycznych treściowo) — dodany fuzzy
check na potwierdzenie. Odrzucono 3 kandydatury o wysokim nakładaniu jako różne
wersje/typy dokumentów dzielące boilerplate PZU, nie duplikaty. 130 chunków oflagowanych
duplicate + entities[duplicate_of] na 3 kopertach.
chunk_embed.py: heurystyka is_ocr_junk() przed embedem (junk -> insert bez wywołania Ollamy,
embedding=NULL), ON CONFLICT rozszerzony o model, nowy licznik chunks_junk_flagged w bilansie,
testy (kody kreskowe, mojibake nie-junk, dot-leader, idempotencja, model w kluczu konfliktu).
Weryfikacja: 7 zapytań eval-setu z WHERE excluded_reason IS NULL — żadne trafienie nie
degraduje, kontrole negatywne bez zmian (>0.55), śmieć zniknął z top-5 zapytania 2,
paperless:119 pozostał aktywnym trafieniem. Bilans: 2545 aktywne / 130 duplicate / 8 ocr_junk.
Co najmniej 3 decyzje wymagały zatrzymania i potwierdzenia z Oskarem w sesji (kalibracja
progu sygnału 1, dołączenie 14≡74 mimo braku exact-hash matcha, odrzucenie 3 fałszywych
kandydatur dedup) — plan przewidywał, że heurystyka będzie się mylić; wszystkie decyzje
udokumentowane w transkrypcie sesji.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Driver fixed 2026-07-16 (nvidia-driver-595-open from distro repo, old
graphics-drivers PPA for jammy disabled) — RTX 4070 Ti SUPER 16GB, CUDA
13.2, nvidia-container-toolkit already present from the 07-15 cutover
prerequisite install. Uncomments deploy.resources.reservations (nvidia
gpu) in services/ollama/docker-compose.yml, restoring clean formatting.
Docs close out the loose ends from the 07-15 declarative cutover:
- ollama-solaria-cutover runbook gets a "Wykonanie" section documenting
what actually happened (mv instead of rsync for the model store, the
missing nvidia-container-toolkit prerequisite, the driver-missing
discovery, CPU-only cutover, then the 07-16 GPU fix) plus a note on
the container disappearing after the 07-15 evening reboot (one-off,
boots fine now, root cause not established).
- hosts/solaria/services.yaml: ollama role comment now reflects actual
GPU-backed state instead of the previously-aspirational wording.
- hosts/solaria/README.md: drop stale Open WebUI mention (not in repo).
- docs/backlog.md: close the NVIDIA driver item; leave two follow-ups
(Ollama call batching before the mail phase, UNIQUE(envelope_id,
chunk_index) schema change for multi-model embeddings at phase 3).
- jobs/documents-ingest/README.md: timing section gets a GPU placeholder
line next to the existing 0.79s/chunk CPU baseline, to be filled in
after the live GPU benchmark.
Live recreate + GPU-vs-CPU embedding benchmark deliberately left for the
operator to run from the main checkout after merge, per worktree-aware
discipline — this worktree only owns the declarative fix and the docs.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Adds documents-ingest-embed: chunks source='paperless' envelope content
(paragraph-preferring, ~600 tok/chunk, ~150 tok overlap, hard char-fallback
for oversized paragraphs per plan §2 decision 3), embeds each chunk via
Ollama (bge-m3, dim validated against document_chunk's VECTOR(1024) on
every response) and inserts into document_chunk. Lives in documents-ingest
per the plan's own recommendation (§6 step 6) rather than a new package —
reuses the job family's existing idempotency/stats-balance/dry-run
conventions (paperless_adapter.py, gmail-header-backfill).
A 5-angle multi-agent code review of the initial implementation surfaced
three real bugs, fixed here: hard_split() could infinite-loop if
--chunk-overlap >= --chunk-size (now guarded in both hard_split() and
main()); insert_chunk() wasn't error-isolated like embed_chunk(), so a DB
write failure would crash the whole run instead of being counted and
skipped; and ON CONFLICT DO NOTHING's outcome was discarded, so a silently
skipped row (the known gap where document_chunk's UNIQUE constraint
doesn't include `model`) would have been miscounted as a successful insert
- now tracked separately as chunks_conflict_skipped and treated as a
run failure.
Smoke-tested and run to completion live on SOLARIA against the real Ollama
instance and kb-postgres@PIHA: dry-run matched the known phase-2-step-5
figures exactly (186 fetched, 26 empty_content, 2684 chunks planned), a
--limit 10 apply + idempotent re-run + DB/distance sanity checks all
passed, and the full 186-document run inserted 2683/2684 chunks (1 isolated
error - Ollama's runtime context window rejected one pathological
dot-leader table-of-contents chunk that tokenized far more densely than
estimated; documented as a known limitation, not fixed here given it's a
single-chunk edge case). Timing: ~0.79s/chunk average on CPU (SOLARIA's
Ollama runs GPU-less per the recent GPU-reservation-disabled fix), ~35 min
wall-clock for the full pilot - the real input for scoping the later
mail-corpus embedding phase (plan §7's GPU-based estimate doesn't hold
here).
pytest: 101 passed.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Adds documents-ingest-paperless: paginated GET /api/documents/, maps each
doc to a source='paperless' envelope per plan §4.2-4.3, reusing
kb_mail.Envelope/insert_envelope unchanged (packages/kb-mail not touched).
Cross-source link (source_mail entity) is a deterministic join of
original_file_name against the phase-1 registry.json consume_name index —
no heuristics, no correspondent guessing (plan decision 4). Stats always
balance (fetched = already_in_db + inserted + errors) and main() now also
exits non-zero on imbalance, not just on errors>0, matching the exit-code
convention already established in gmail-bulk-import.
Verified live on PIHA (rsync to /tmp, ~/kb/venv, PIHA checkout untouched):
dry-run then --apply inserted 186/186 paperless envelopes (0 errors,
180 source_mail links), a second --apply reported inserted=0/already_in_db=186
(idempotent), gmail rows stayed at 225030 and document_chunk stayed empty.
Rotated the kb-ingest Paperless API token after it was accidentally
partially echoed during recon (old token now dead).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Four audit findings (2026-07-14), each reproduced on crafted mboxes; the
Takeout corpus has proven 8-bit header bytes, so all are real re-import risks.
1. Whole-run crash on 8-bit Message-ID. compat32 .get() returns an
email.header.Header (not str) for raw 8-bit bytes; the old
Header.strip() raised AttributeError. _message_id ran BEFORE the
per-message try, so one bad header killed the entire import.
Fix: str() + sanitize_surrogates() before strip; and move
_message_id/_parse_date/_parse_attachments INSIDE the per-message try —
a broken message is now errors += 1, never run death.
2. Poison batch. pending.clear() ran only AFTER a successful insert, so a
failed flush (DB down / bad row) left pending intact and every later
message re-flushed the doomed batch; the final flush sat in try/finally
with no except and propagated out, losing all stats. Fix: _flush always
clears pending and counts a failed insert as db_insert_failed; the run
always reaches import_complete.
3. Stats didn't reconcile with the DB. imported counts archive writes, not
DB rows, so a partial-insert drift was invisible. Fix: separate
db_inserted/db_insert_failed counters; main() exits non-zero on any
error, DB drift, or a processed = imported + skipped + errors imbalance.
4. 8-bit Date → needless epoch_fallback. parsedate_to_datetime(Header)
raised even when str(header) parses fine. Fix: str() before the epoch
fallback.
Shared helper: _sanitize moved from gmail-header-backfill into
packages/kb-mail (kb_mail.text.sanitize_surrogates) and used by both jobs;
gmail-header-backfill now depends on kb-mail.
Tests: regression coverage for all four findings in gmail-bulk-import
(8-bit id/date, per-message guard, failed-insert non-poisoning, stats
balance) plus kb_mail.text unit tests. Full suites green:
kb-mail 27, gmail-bulk-import 33, gmail-header-backfill 43.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Diagnosis of the 5008 header-less envelopes after the full 225 030-row run
(read-only, on PIHA, 2026-07-14):
- 4999 = one contiguous block at ORDER BY id positions 70001-74999: the
--offset 70000 slice died mid-run. Root cause reproduced: a Date: header
with raw 8-bit bytes makes compat32 .get() return email.header.Header
(not str), and json.dumps([headers]) — which sat OUTSIDE the per-row
try/except — raised TypeError and killed the process, silently losing
the rest of the slice.
- 9 = genuine typed-parse failures: 7x RFC 2047 encoded-word decoding to
CR/LF inside a display name (ValueError in headerregistry), 1x RFC 5322
group syntax in To: ("unlisted-recipients:;"), 1x CPython
_header_value_parser bug on a malformed display name (fixed upstream,
present on PIHA's 3.11).
- 0 missing .eml files.
Fixes:
- date_raw: str() + surrogate sanitization on the compat32 value — the
crash cause, now also covered by a regression test.
- json.dumps moved inside the per-row try: a non-serializable value counts
as that row's parse_error instead of crashing the slice.
- parse_headers_fallback(): on typed-parse failure retry with a pure
compat32 parse — getaddresses over raw header text, raw-string values,
same §4.1 entity shape. Counted separately as parsed_fallback (labeled
subset of updated), logged per row with the original typed error.
- missing_file counter + skip.missing_file info log (id, expected path);
run_complete now balances: scanned = updated + already_has_headers +
parse_errors + read_errors + missing_file. Non-zero missing_file also
fails the exit code.
Verified: 43/43 pytest locally (3.13) and on PIHA (3.11); read-only dry
runs on PIHA — all 9 parse failures recover via fallback, the lost slice
completes scanned=5000 updated=4999 already_has_headers=1 with zero errors.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Module 5 phase 2 (docs/kb/modules/05-faza2-plan.md, §5). 225,030 existing
source='gmail' envelope rows carry only an attachment manifest — no
from/to/cc/delivered_to/subject anywhere in the DB, which blocks answering
"is this on me or my wife" / distinguishing aliases (plan §1.8). Separate
job from gmail-bulk-import per plan §2 decision 7: UPDATE semantics against
production data is a different risk profile than the historical INSERT job.
Parses headers only (no MIME-walk of attachments) from the archived .eml
files, appends {"type": "headers", ...} (plan §4.1) via the idempotent
UPDATE ... WHERE NOT EXISTS from §5.2, batched via executemany. --limit/
--offset (ORDER BY id) give stable, deterministic partitioning so the full
backfill can run and be verified in slices instead of one unattended pass.
Plain CLI (pip install -e), no Dockerfile — same convention as
gmail-bulk-import/documents-ingest, which run directly on PIHA for local
filesystem access to the .eml archive.
Verified against kb-postgres@PIHA (100-row dry-run + apply, re-run proved
idempotent no-op, 1000-row timed slice): 1096/225030 rows backfilled,
996/1000 succeeded on the timed slice (4 parse_errors — a 2014 spam message
with an RFC 2047 encoded-word decoding to an embedded newline in the From
display name, correctly caught and skipped rather than crashing the batch).
Extrapolated full-run time ~16 minutes. Full 225,030-row run is out of
scope for this change.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Module 5 phase 1 (docs/kb/modules/05-documents-ingest.md): pulls a sample of
PDF attachments (>50KB, last year, LIMIT 150) out of the Gmail .eml archive
and drops them into Paperless consume/ for OCR, so the RAG layer has real
documents to work with before the full Paperless/Nextcloud envelope adapter
is built. sha256-first attachment matching (manifest filenames can carry raw
RFC 2047 encoded-word artifacts that don't byte-match what email.policy.default
decodes today — confirmed against live data, ~10% of candidates were affected).
Idempotent via a sha256-keyed JSON registry; dry-run by default, --apply to write.
Verified end-to-end on PIHA: dry-run + --apply both run against live
kb-postgres/archive, 185/222 candidate PDFs written to consume/ (37 in-run
duplicates correctly deduped), Paperless picked them up and started OCR
immediately.
- Usuwa Dockerfile i docker-compose.yml; job odpalany lokalnie na PIHA (pip install -e)
- _parse_attachments: manifest MIME → entities[]{type,filename,content_type,size,sha256};
bajty zostają w .eml, wyciąganie/OCR = faza 2
- Batch inserty co 500 wpisów (executemany + ON CONFLICT DO NOTHING); idempotentny
na skipped przez _eml_ref (mirrors archive._UNSAFE); pełna wznawialność
- --limit N: ucina pętlę po N wiadomościach do testów na próbce
- epoch_fallback: licznik + WARNING gdy Date nieparsowalne/brak
- Nowe stats: msgs_with_attachments, total_attachments, total_attachment_bytes
- DSN w docstringu: localhost:5433/kb i piha:5433/kb; usunięto solaria:5433
- 9 nowych testów (24 razem), wszystkie zielone
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
One-shot job `jobs/gmail-bulk-import/` wczytuje plik .mbox z Google Takeout
i importuje każdą wiadomość do archiwum .eml + opcjonalnie do koperty w DB.
Idempotentny (FileExistsError → skip; ON CONFLICT DO NOTHING w DB).
15 testów jednostkowych (bez DB, bez zewnętrznych serwisów) — wszystkie zielone.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
