Tower worker now persists faster-whisper's segment-level output
(start/end/text + word-level timing when available) alongside the
existing joined `transcript_text`. The text column stays the canonical
input the extractor reads — this is additive.
Changes:
- alembic v4: sources.transcript_segments JSONB NULL. JSONB rather than
JSON so future equality/containment queries are indexable without a
re-migration. Same lovebug-no-CREATE-on-petalbrain guard as prior
migrations.
- ORM model: Optional[list] mapped to JSONB (postgresql dialect).
- transcribe.py:
- Always pass word_timestamps=True to faster-whisper.transcribe.
- New segment_to_dict() flattens the upstream NamedTuple-shaped
Segment/Word into JSON-safe plain dicts so the JSONB write doesn't
drag faster-whisper into any reader.
- Per-word defensive conversion: a single malformed word can't drop
the surrounding segment.
- transcribe_worker._advance: after a successful transcribe, persist
segments into source.transcript_segments inside a try/except. If the
JSONB write fails (oversize row, malformed dict, etc.) we log a
warning and still commit transcript_text + status=TRANSCRIBED — the
pipeline never crashes over the additive index.
- Tests: three new unit tests against fake Segment/Word objects cover
the happy path (word entries serialise), the no-words case
(`segment.words is None` → empty list), and the malformed-word skip.
json.dumps(d) asserts JSONB-binding compatibility.
Live-verified: migration applied clean against petalbrain (`\d sources`
shows transcript_segments jsonb); ORM round-trip writes and reads the
sample payload identically. GPU large-v3 word-timestamp behaviour is
unchanged from upstream — only the tower can validate that hot path.
Splits pull+transcribe (now tower-side, eager) from extract+embed
(stays on the dev scheduler). Three machine-coordination pieces land
together because they reference each other:
- v3 migration adds sources.claimed_by + claimed_at — observability +
stale-claim recovery columns. The actual race-safety primitive is
`SELECT ... FOR UPDATE SKIP LOCKED` in the new claim helper, so two
machines can poll the queue without doubling work.
- src/second_brain/claim.py owns the claim dance (claim_next_source,
release_claim, reap_stale_claims). Both stage gates filter by
source_type so the tower never grabs articles and the dev side never
grabs videos.
- src/second_brain/transcribe.py wraps faster-whisper (lazy-imported so
it stays out of the dev install). resolve_settings() reads env >
[whisper] block > defaults, falling back to int8 on cpu / float16 on
cuda when compute_type is unspecified. Default model large-v3.
- src/second_brain/scheduler/transcribe_worker.py is the long-running
poll loop. Reads pipeline_settings every iteration so the dashboard's
enable/window/max-items/max-video-length take effect within one
cycle. Reaps stale claims at startup. SIGTERM-clean. DB-unreachable
backs off with a log line; never crash-loops.
- adapters/youtube.py drops the torch-whisper transcribe path; pull
stays. Removes openai-whisper from the default deps and gates
faster-whisper behind a new `tower` extra (uv sync --extra tower).
- main.py: new `second-brain transcribe-worker` (--once for ad-hoc).
`process` now article-only on the pull side but still picks up
TRANSCRIBED of any source_type for the extract step.
Live-verified: migration applies clean, transcribe-worker --once
honors transcription_enabled=false gate.
Introduces second_brain.pipeline_settings — the single-row config row
the upcoming web dashboard edits and the workers read at the start of
each run. Pinned to id=1 by a CHECK constraint so upserts-by-PK keep
the table singleton, and the migration seeds the row with the table's
column defaults via INSERT ... ON CONFLICT DO NOTHING.
Two consumer groups carved out:
- transcription_* fields persist now; future tower-side worker reads them.
- extraction_* fields will be read by the existing scheduler in the next
commit, which is the actual behavior change Travis cares about today.
The settings_store helper centralises get/update + form-parsing
(time-of-day, int-or-none) and active-window math so the routes and the
scheduler don't reimplement them.
The runtime role (lovebug) doesn't have CREATE on the petalbrain database
even though it owns the second_brain schema, so a bare
`CREATE SCHEMA IF NOT EXISTS` errors out with permission denied. Gate
the bootstrap on a pg_namespace lookup so we only attempt the create
when the schema is genuinely missing — operators bootstrap it once as
postgres superuser, alembic just respects it afterward.
The smoke test exercises the full Postgres + embedding path against a
live DB + Ollama (autoskipped otherwise): writes an extraction, embeds
the summary, asserts public.embeddings has the expected row count, and
re-embeds to verify the delete-before-insert idempotency.
Swap the SQLite backing store for petalbrain Postgres + pgvector, modeled
on vault-mcp. All second-brain relational tables now live in the
`second_brain` schema (owned by the lovebug role); embeddings are written
to the shared public.embeddings table.
Locked design decisions (per Travis):
- DB: existing petalbrain Postgres, second_brain schema, lovebug role.
- Connection: containerized homelab-postgres:5432, plain psycopg_pool
(min=1/max=10), no PgBouncer.
- ORM stays SQLAlchemy; int autoincrement PKs + naive UTC DateTime.
- Embeddings: reuse shared public.embeddings keyed by
(source_schema='second_brain', source_table='extractions', source_id,
model='nomic-embed-text'). Summaries only for this round.
- Pipeline: chunk_text → Ollama nomic-embed-text → delete-before-insert
upsert, with graceful degradation (no DB / no Ollama → log + skip).
- Alembic stands up second-brain's own schema; public.embeddings stays
out-of-band.
- File-based wiki compiler is unchanged.
No SQLite data import — starting clean.
This commit is the scaffolding only; `alembic upgrade head` and a smoke
test of the embedding path are the next checkpoint.
