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FabledCurator/tests/test_api_gpu.py
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feat(b3): ml-worker becomes optional — embed-only role, decoupled GPU coordination, cpu-embed switch
The ml-worker's ONLY processing role is now the CPU whole-image embed fallback
(tag_and_embed renamed embed_image — Camie tagging was retired #1189 and the
name kept implying otherwise; videos were already handled agent-style: frame
sampling + mean-pool). Detection/cropping/CCIP stay GPU-agent-only, and their
completion is judged per-pipeline: ccip by gpu_job rows, siglip by concept
regions at the current model version — never by image_record.siglip_embedding.
A CPU embed therefore can NEVER close crop work for the agent (regression test
pins this; only the whole-image 'embed' job, the same artifact, is satisfied).

Making removal actually safe (operator will drop the container):
- GPU-queue coordination (enqueue_gpu_backfill, recover_orphaned_gpu_jobs,
  reprocess_gpu_jobs) moved verbatim to tasks/gpu_queue.py on the maintenance
  quick lane — it lived on the 'ml' queue only by module colocation, which made
  the ml-worker a hard dependency of the whole agent pipeline.
- New ml_settings.cpu_embed_enabled (migration 0074, default ON so agent-less
  installs keep working): OFF stops the four import hooks queueing embed work
  nothing will consume and no-ops the manual backfill; switch lives on the
  renamed 'CPU embedding backfill' card.
- NB heads training / auto-apply still run on the ml image (sklearn) — a stack
  that removes the container gives those up too.

Deploy note: in-flight messages under the old task names are dropped by the
new workers; the 60s orphan sweep + hourly backfill re-fire under the new
names immediately.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
2026-07-02 16:53:08 -04:00

293 lines
11 KiB
Python

"""GPU-job HTTP API (#114): bearer auth + lease/submit round-trip + backfill."""
from datetime import UTC, datetime, timedelta
import pytest
from sqlalchemy import func, select
from backend.app.models import GpuJob, ImageRecord
from backend.app.services.ml.gpu_jobs import GpuJobService
from backend.app.services.ml.regions import RegionService
pytestmark = pytest.mark.integration
async def _img(db, sha) -> ImageRecord:
img = ImageRecord(
path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
width=1, height=1, origin="imported_filesystem", integrity_status="unknown",
)
db.add(img)
await db.flush()
return img
@pytest.mark.asyncio
async def test_agent_endpoints_require_bearer(client, db):
resp = await client.post("/api/gpu/jobs/lease", json={"agent_id": "a1"})
assert resp.status_code == 401
# A wrong token is also rejected.
await (await client.post("/api/gpu/token/rotate")).get_json()
bad = await client.post(
"/api/gpu/jobs/lease", json={"agent_id": "a1"},
headers={"Authorization": "Bearer nope"},
)
assert bad.status_code == 401
@pytest.mark.asyncio
async def test_lease_submit_round_trip(client, db):
img = await _img(db, "a" * 64)
await GpuJobService(db).enqueue(img.id, "ccip")
await db.commit()
token = (await (await client.post("/api/gpu/token/rotate")).get_json())["token"]
hdr = {"Authorization": f"Bearer {token}"}
leased = await client.post(
"/api/gpu/jobs/lease", json={"agent_id": "a1", "batch_size": 5}, headers=hdr,
)
assert leased.status_code == 200
jobs = (await leased.get_json())["jobs"]
assert len(jobs) == 1
j = jobs[0]
assert j["image_id"] == img.id and j["task"] == "ccip"
assert j["image_url"].startswith("/images/")
submitted = await client.post("/api/gpu/jobs/submit", json={
"agent_id": "a1", "job_id": j["job_id"],
"regions": [{
"kind": "figure", "bbox": [0.1, 0.1, 0.4, 0.4],
"ccip_embedding": [0.1] * 768, "embedding_version": "ccip-test",
}],
}, headers=hdr)
assert submitted.status_code == 200
assert (await submitted.get_json())["stored"] == 1
# Job closed (read on the app's own connection via the status endpoint).
st = await (await client.get("/api/gpu/status")).get_json()
assert st["done"] == 1 and st["pending"] == 0 and st["leased"] == 0
# Region persisted with its CCIP vector.
regs = await RegionService(db).get_regions(img.id, kinds=["figure"])
assert len(regs) == 1 and len(list(regs[0].ccip_embedding)) == 768
@pytest.mark.asyncio
async def test_lease_announces_embed_model_then_submit_embedding(client, db):
# Whole-image GPU re-embed (#1190): the lease announces the embedder model so
# the agent loads the right one, and submit_embedding writes it back onto
# image_record with its version stamp.
img = await _img(db, "b" * 64)
await GpuJobService(db).enqueue(img.id, "embed")
await db.commit()
token = (await (await client.post("/api/gpu/token/rotate")).get_json())["token"]
hdr = {"Authorization": f"Bearer {token}"}
leased = await client.post(
"/api/gpu/jobs/lease", json={"agent_id": "a1", "batch_size": 5}, headers=hdr,
)
j = (await leased.get_json())["jobs"][0]
assert j["task"] == "embed"
assert j["embed_model_name"] and j["embed_version"] # server-announced model
submitted = await client.post("/api/gpu/jobs/submit_embedding", json={
"agent_id": "a1", "job_id": j["job_id"],
"embedding": [0.2] * 1152, "embedding_version": "siglip2-test-v9",
}, headers=hdr)
assert submitted.status_code == 200
st = await (await client.get("/api/gpu/status")).get_json()
assert st["done"] == 1 and st["leased"] == 0
await db.refresh(img)
assert img.siglip_model_version == "siglip2-test-v9"
assert img.siglip_embedding is not None and len(list(img.siglip_embedding)) == 1152
@pytest.mark.asyncio
async def test_submit_with_stale_lease_is_409(client, db):
img = await _img(db, "b" * 64)
await GpuJobService(db).enqueue(img.id, "ccip")
await db.commit()
token = (await (await client.post("/api/gpu/token/rotate")).get_json())["token"]
hdr = {"Authorization": f"Bearer {token}"}
j = (await (await client.post(
"/api/gpu/jobs/lease", json={"agent_id": "a1"}, headers=hdr,
)).get_json())["jobs"][0]
# A different agent can't submit someone else's lease.
resp = await client.post("/api/gpu/jobs/submit", json={
"agent_id": "other", "job_id": j["job_id"], "regions": [],
}, headers=hdr)
assert resp.status_code == 409
@pytest.mark.asyncio
async def test_backfill_enqueues_then_is_idempotent(db):
await _img(db, "c" * 64)
await _img(db, "d" * 64)
await db.commit()
from backend.app.tasks.gpu_queue import enqueue_gpu_backfill
n = enqueue_gpu_backfill("ccip") # sync task, own session
assert n >= 2
assert enqueue_gpu_backfill("ccip") == 0 # all already pending
@pytest.mark.asyncio
async def test_release_hands_job_back_to_pending(client, db):
img = await _img(db, "e" * 64)
await GpuJobService(db).enqueue(img.id, "ccip")
await db.commit()
token = (await (await client.post("/api/gpu/token/rotate")).get_json())["token"]
hdr = {"Authorization": f"Bearer {token}"}
j = (await (await client.post(
"/api/gpu/jobs/lease", json={"agent_id": "a1"}, headers=hdr,
)).get_json())["jobs"][0]
resp = await client.post("/api/gpu/jobs/release", json={
"agent_id": "a1", "job_ids": [j["job_id"]],
}, headers=hdr)
assert resp.status_code == 200 and (await resp.get_json())["released"] == 1
st = await (await client.get("/api/gpu/status")).get_json()
assert st["pending"] == 1 and st["leased"] == 0
@pytest.mark.asyncio
async def test_retry_errors_requeues_only_errored(client, db):
"""/retry_errors prunes stale tombstones first (older duplicates + rows a
later success made moot), then resets the SURVIVING errored jobs to pending
with a fresh retry budget — and leaves done work untouched (NOT /reprocess).
The prune is what stops one failing file fanning out into duplicate pending
jobs (the 2026-07-02 tombstone loop minted one error row per hour)."""
img1 = await _img(db, "1" * 64)
img2 = await _img(db, "2" * 64)
svc = GpuJobService(db)
j_err = await svc.enqueue(img1.id, "ccip")
j_done = await svc.enqueue(img2.id, "siglip")
err_id = j_err.id
done_id = j_done.id
j_err.status = "error"
j_err.attempts = 3
j_err.error = "no frames sampled from video (unprocessable)"
j_err.updated_at = datetime.now(UTC)
j_done.status = "done"
# Loop-era leftovers: an OLDER duplicate error row for img1's ccip, and a
# tombstone img2's done row makes moot — both pruned, never requeued.
dup = GpuJob(
image_record_id=img1.id, task="ccip", status="error",
error="older duplicate", updated_at=datetime.now(UTC) - timedelta(hours=1),
)
moot = GpuJob(
image_record_id=img2.id, task="siglip", status="error",
error="superseded by the done row",
)
db.add(dup)
db.add(moot)
await db.flush()
dup_id = dup.id
moot_id = moot.id
await db.commit()
resp = await client.post("/api/gpu/retry_errors")
assert resp.status_code == 200
body = await resp.get_json()
assert body["requeued"] == 1
assert body["pruned"] == 2
# Column selects, not ORM refresh — the route wrote via Core DML.
row = (await db.execute(
select(GpuJob.status, GpuJob.attempts, GpuJob.error)
.where(GpuJob.id == err_id)
)).one()
assert tuple(row) == ("pending", 0, None)
done_status = await db.scalar(
select(GpuJob.status).where(GpuJob.id == done_id)
)
assert done_status == "done"
survivors = (await db.execute(
select(func.count()).select_from(GpuJob)
.where(GpuJob.id.in_([dup_id, moot_id]))
)).scalar_one()
assert survivors == 0
st = await (await client.get("/api/gpu/status")).get_json()
assert st["pending"] == 1 and st["error"] == 0
@pytest.mark.asyncio
async def test_retry_errors_keeps_triaged_defects(client, db):
"""A probe-confirmed DEFECT is a bad FILE — requeueing it just burns agent
time re-minting the tombstone, so /retry_errors leaves it for the recovery
surface and reports it as defects_kept."""
img1 = await _img(db, "4" * 64)
img2 = await _img(db, "5" * 64)
db.add(GpuJob(image_record_id=img1.id, task="ccip", status="error",
attempts=3, error="moov atom not found",
triage_status="defect"))
db.add(GpuJob(image_record_id=img2.id, task="ccip", status="error",
attempts=3, error="ffmpeg timed out after 1200s"))
await db.commit()
body = await (await client.post("/api/gpu/retry_errors")).get_json()
assert body["requeued"] == 1
assert body["defects_kept"] == 1
rows = dict((await db.execute(
select(GpuJob.image_record_id, GpuJob.status)
)).all())
assert rows[img1.id] == "error" # defect stays tombstoned
assert rows[img2.id] == "pending" # operational failure requeued
@pytest.mark.asyncio
async def test_errors_endpoint_reports_triage_view(client, db):
img = await _img(db, "6" * 64)
db.add(GpuJob(image_record_id=img.id, task="ccip", status="error",
attempts=3,
error="no frames sampled from video — moov atom not found"))
await db.commit()
resp = await client.get("/api/gpu/errors")
assert resp.status_code == 200
body = await resp.get_json()
assert body["total"] == 1
assert body["by_class"] == {"truncated_or_corrupt": 1}
assert body["triage"]["unclassified"] == 1
item = body["items"][0]
assert item["image_id"] == img.id
assert item["task"] == "ccip"
assert item["reason_class"] == "truncated_or_corrupt"
assert item["triage_status"] is None
assert item["image_url"].startswith("/images/")
@pytest.mark.asyncio
async def test_cpu_embed_never_blocks_gpu_crop_backfills(db):
"""B3 invariant (operator 2026-07-02): ccip (detect + character) and
siglip (concept crops) completion is judged per-pipeline — gpu_job rows and
image_region state — never inferred from image_record.siglip_embedding. So
an image the CPU fallback already embedded still gets both crop jobs; only
the whole-image 'embed' job (the SAME artifact the CPU path produces) is
satisfied by it."""
from backend.app.models import MLSettings
from backend.app.tasks.gpu_queue import enqueue_gpu_backfill
img = await _img(db, "7" * 64)
cur = (await db.execute(
select(MLSettings.embedder_model_version).where(MLSettings.id == 1)
)).scalar_one()
# As if the CPU fallback already embedded it under the current model.
img.siglip_embedding = [0.1] * 1152
img.siglip_model_version = cur
await db.commit()
assert enqueue_gpu_backfill("ccip") == 1 # crops still open
assert enqueue_gpu_backfill("siglip") == 1 # concept crops still open
assert enqueue_gpu_backfill("embed") == 0 # same artifact — already done
tasks = set((await db.execute(
select(GpuJob.task).where(GpuJob.image_record_id == img.id)
)).scalars().all())
assert tasks == {"ccip", "siglip"}