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FabledCurator/backend/app/services/ml/gpu_jobs.py
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feat(gpu): video-ready regions + the HTTP GPU-job queue engine (#114 slice 3)
Answers "how are videos/all media handled by the GPU worker": a job is per ITEM,
but the agent fans a VIDEO into per-frame instances (ffmpeg in the agent, the
existing cadence), each stored with a timestamp — so a video becomes a BAG of
frame embeddings (fixes the mean-embedding muddle) instead of one washed-out
vector. Stills → frame_time NULL; animated GIF/WebP treated like short video.

- image_region.frame_time (migration 0061, not yet deployed so folded in): the
  source frame's seconds for video/animated media; NULL for stills. RegionService
  passes it through. A whole frame is just kind='frame'.
- gpu_job + GpuJobService (migration 0062): the durable work list that keeps the
  desktop agent HTTP-only — enqueue (dedupes (image,task)) / lease (FOR UPDATE
  SKIP LOCKED, re-claims expired leases so the queue self-heals) / heartbeat /
  complete / fail (re-queues until MAX_ATTEMPTS then 'error'). The server enqueues;
  the agent leases+submits over the web API; Redis/Postgres stay private.

Tests: enqueue dedupe, lease-then-skip-when-held, expired-lease reclaim, scoped
heartbeat, complete, fail-requeue-then-error. region test now covers frame_time.

NEXT: the thin HTTP API (lease/submit/heartbeat) + bearer-token auth, then the
agent container + control UI.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
2026-06-29 11:18:28 -04:00

135 lines
4.9 KiB
Python

"""GPU-job queue engine (#114): enqueue / lease / heartbeat / complete / fail.
Backs the HTTP API the desktop agent pulls work from. The lease claims pending
OR expired-leased jobs with FOR UPDATE SKIP LOCKED, so concurrent agents (or a
retry after an agent died) never grab the same job and the queue self-heals
without a separate recovery sweep. Result-writing (regions) is done by the API
handler via RegionService; complete() just closes the job.
"""
from datetime import UTC, datetime, timedelta
from sqlalchemy import and_, or_, select, update
from sqlalchemy.ext.asyncio import AsyncSession
from ...models import GpuJob
DEFAULT_LEASE_TTL = 300 # seconds an agent holds a job before it can be re-leased
DEFAULT_BATCH = 8
MAX_ATTEMPTS = 3
class GpuJobService:
def __init__(self, session: AsyncSession):
self.session = session
async def enqueue(self, image_id: int, task: str) -> GpuJob | None:
"""Queue a (image, task) job. Idempotent: returns None if one is already
pending/leased for the same pair (no duplicate work)."""
dup = (
await self.session.execute(
select(GpuJob.id).where(
GpuJob.image_record_id == image_id,
GpuJob.task == task,
GpuJob.status.in_(["pending", "leased"]),
)
)
).first()
if dup:
return None
job = GpuJob(image_record_id=image_id, task=task, status="pending")
self.session.add(job)
await self.session.flush()
return job
async def lease(
self, token: str, batch_size: int = DEFAULT_BATCH, ttl: int = DEFAULT_LEASE_TTL
) -> list[GpuJob]:
"""Claim up to batch_size pending (or expired-leased) jobs for `token`."""
now = datetime.now(UTC)
picked = (
await self.session.execute(
select(GpuJob.id)
.where(
or_(
GpuJob.status == "pending",
and_(
GpuJob.status == "leased",
GpuJob.lease_expires_at < now,
),
)
)
.order_by(GpuJob.id)
.limit(batch_size)
.with_for_update(skip_locked=True)
)
).scalars().all()
if not picked:
return []
await self.session.execute(
update(GpuJob)
.where(GpuJob.id.in_(picked))
.values(
status="leased", lease_token=token, leased_at=now,
lease_expires_at=now + timedelta(seconds=ttl),
attempts=GpuJob.attempts + 1, updated_at=now,
)
)
# populate_existing: overwrite identity-map copies with the post-UPDATE
# values so the returned jobs reflect the new lease/attempts, not stale
# pre-lease state.
return list(
(
await self.session.execute(
select(GpuJob)
.where(GpuJob.id.in_(picked))
.order_by(GpuJob.id)
.execution_options(populate_existing=True)
)
).scalars()
)
async def heartbeat(
self, token: str, job_ids: list[int], ttl: int = DEFAULT_LEASE_TTL
) -> int:
"""Extend the lease on the agent's in-flight jobs. Returns rows touched."""
now = datetime.now(UTC)
res = await self.session.execute(
update(GpuJob)
.where(
GpuJob.id.in_(job_ids),
GpuJob.lease_token == token,
GpuJob.status == "leased",
)
.values(lease_expires_at=now + timedelta(seconds=ttl), updated_at=now)
)
return res.rowcount or 0
async def complete(self, token: str, job_id: int) -> bool:
"""Close a leased job (after its results were stored). False if the job
isn't leased by this token (a stale/expired submit)."""
job = await self.session.get(GpuJob, job_id)
if job is None or job.status != "leased" or job.lease_token != token:
return False
job.status = "done"
job.lease_token = None
job.lease_expires_at = None
job.error = None
job.updated_at = datetime.now(UTC)
return True
async def fail(self, token: str, job_id: int, error: str) -> bool:
"""Report a failure: re-queue (pending) until MAX_ATTEMPTS, then 'error'."""
job = await self.session.get(GpuJob, job_id)
if job is None or job.lease_token != token:
return False
if job.attempts >= MAX_ATTEMPTS:
job.status = "error"
else:
job.status = "pending"
job.lease_token = None
job.lease_expires_at = None
job.error = (error or "")[:1000]
job.updated_at = datetime.now(UTC)
return True