Files
FabledCurator/backend/app/api/gpu.py
T
bvandeusen c6f38b0dac feat(tagging): SigLIP concept crops + max-over-bag scoring (#114)
Lift recall on small/local concepts (glasses, cum, stomach-bulge, xray,
lactation) that the whole-image SigLIP vector washes out: the GPU agent now
embeds figure crops with SigLIP too, stored as kind='concept' regions, and the
suggestion rail scores each image as a BAG (whole-image + every concept crop),
taking each head's MAX over the bag. The whole-image vector is always in the
bag, so this can never score lower than before.

Model-agnostic by construction: the server ANNOUNCES the embedding model
(HF name + version) in the lease, so the agent loads whatever the heads were
trained in and stays in lock-step — a model swap is a server setting + a
re-embed migration, never an agent change.

- agent: model-agnostic CropEmbedder (torch/transformers get_image_features,
  fp16 on CUDA, inference-locked); worker branches on job.task — 'ccip' emits
  figure(CCIP)+concept(SigLIP) in one pass, 'siglip' emits concept-only so the
  back-catalogue backfill never churns figure/CCIP regions; torch cu124 +
  transformers in the image.
- server: lease announces embed_model_name/embed_version; score_image is
  max-over-bag (version-filtered region embeddings); enqueue_gpu_backfill
  'siglip' gates on a missing concept region (drains the back-catalogue,
  retries failures, no double-enqueue); daily siglip-backfill beat; UI button;
  /api/ccip/overview reports images_with_concept_siglip.
- v1 scope: suggestion rail only — auto-apply stays whole-image (conservative;
  heads' thresholds were calibrated on whole-image). Bulk-apply bag = follow-up.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
2026-06-30 08:17:47 -04:00

221 lines
8.3 KiB
Python

"""GPU-job API (#114): the HTTP surface the desktop agent pulls work from.
The agent stays HTTP-only — it leases jobs, fetches image pixels via the normal
FC image URLs, and submits embeddings/regions back, all over this API. Redis and
Postgres are never exposed. The agent endpoints are gated by a bearer token
(Authorization: Bearer <token>) stored in AppSetting; the admin endpoints
(token / backfill / status) ride the browser session like the rest of FC's
homelab admin.
"""
import secrets
from quart import Blueprint, jsonify, request
from sqlalchemy import func, select
from sqlalchemy.dialects.postgresql import insert as pg_insert
from ..extensions import get_session
from ..models import AppSetting, GpuJob, ImageRecord, MLSettings
from ..services.gallery_service import image_url
from ..services.ml.embedder import MODEL_NAME as EMBED_MODEL_NAME
from ..services.ml.gpu_jobs import GpuJobService
from ..services.ml.regions import RegionService
gpu_bp = Blueprint("gpu", __name__, url_prefix="/api/gpu")
_TOKEN_KEY = "gpu_agent_token"
def _bearer() -> str | None:
h = request.headers.get("Authorization", "")
return h[7:].strip() if h.startswith("Bearer ") else None
async def _agent_authed(session) -> bool:
supplied = _bearer()
if not supplied:
return False
stored = (
await session.execute(
select(AppSetting.value).where(AppSetting.key == _TOKEN_KEY)
)
).scalar_one_or_none()
return stored is not None and secrets.compare_digest(supplied, stored)
# --- Admin (browser): token + backfill + status -------------------------
@gpu_bp.route("/token", methods=["GET"])
async def get_token():
async with get_session() as session:
tok = (
await session.execute(
select(AppSetting.value).where(AppSetting.key == _TOKEN_KEY)
)
).scalar_one_or_none()
return jsonify({"token": tok, "configured": tok is not None})
@gpu_bp.route("/token/rotate", methods=["POST"])
async def rotate_token():
token = secrets.token_urlsafe(32)
async with get_session() as session:
await session.execute(
pg_insert(AppSetting)
.values(key=_TOKEN_KEY, value=token)
.on_conflict_do_update(index_elements=["key"], set_={"value": token})
)
await session.commit()
return jsonify({"token": token})
@gpu_bp.route("/status", methods=["GET"])
async def status():
async with get_session() as session:
rows = (
await session.execute(
select(GpuJob.status, func.count()).group_by(GpuJob.status)
)
).all()
counts = dict(rows)
return jsonify({
"pending": counts.get("pending", 0),
"leased": counts.get("leased", 0),
"done": counts.get("done", 0),
"error": counts.get("error", 0),
})
@gpu_bp.route("/backfill", methods=["POST"])
async def backfill():
"""Enqueue a job for every image that doesn't already have one for `task`."""
body = await request.get_json(silent=True) or {}
task = str(body.get("task") or "ccip")
from ..tasks.ml import enqueue_gpu_backfill
r = enqueue_gpu_backfill.delay(task)
return jsonify({"celery_task_id": r.id, "task": task}), 202
# --- Agent (bearer token): lease / submit / heartbeat / fail ------------
@gpu_bp.route("/jobs/lease", methods=["POST"])
async def lease():
body = await request.get_json(silent=True) or {}
agent_id = str(body.get("agent_id") or "agent")
try:
batch = min(max(int(body.get("batch_size", 8)), 1), 64)
except (TypeError, ValueError):
batch = 8
async with get_session() as session:
if not await _agent_authed(session):
return jsonify({"error": "unauthorized"}), 401
jobs = await GpuJobService(session).lease(agent_id, batch_size=batch)
ml = (
await session.execute(select(MLSettings).where(MLSettings.id == 1))
).scalar_one()
# image rows for url/mime in one shot
ids = [j.image_record_id for j in jobs]
imgs = {
i.id: i for i in (
await session.execute(
select(ImageRecord).where(ImageRecord.id.in_(ids))
)
).scalars()
} if ids else {}
await session.commit()
out = []
for j in jobs:
img = imgs.get(j.image_record_id)
if img is None:
continue
out.append({
"job_id": j.id,
"image_id": j.image_record_id,
"task": j.task,
"mime": img.mime,
"image_url": image_url(img.path),
# For video/animated: the agent samples at this cadence.
"frame_interval_seconds": ml.video_frame_interval_seconds,
"max_frames": ml.video_max_frames,
# The embedding model the agent must use for concept crops, so
# its region vectors land in the SAME space the heads trained in.
# Server-announced → the agent stays model-agnostic; a swap is a
# server setting + a re-embed migration, never an agent change.
"embed_model_name": EMBED_MODEL_NAME,
"embed_version": ml.embedder_model_version,
})
return jsonify({"jobs": out})
@gpu_bp.route("/jobs/heartbeat", methods=["POST"])
async def heartbeat():
body = await request.get_json(silent=True) or {}
agent_id = str(body.get("agent_id") or "agent")
job_ids = [int(x) for x in (body.get("job_ids") or [])]
async with get_session() as session:
if not await _agent_authed(session):
return jsonify({"error": "unauthorized"}), 401
n = await GpuJobService(session).heartbeat(agent_id, job_ids)
await session.commit()
return jsonify({"extended": n})
@gpu_bp.route("/jobs/submit", methods=["POST"])
async def submit():
"""Store a job's regions + close it. regions: [{kind, bbox:[x,y,w,h],
frame_time?, score?, *_version?, ccip_embedding?, siglip_embedding?}].
replace_kinds defaults to the kinds present in the submitted regions."""
body = await request.get_json(silent=True) or {}
agent_id = str(body.get("agent_id") or "agent")
job_id = body.get("job_id")
regions = body.get("regions") or []
if job_id is None:
return jsonify({"error": "job_id required"}), 400
kinds = body.get("replace_kinds") or sorted({r["kind"] for r in regions})
async with get_session() as session:
if not await _agent_authed(session):
return jsonify({"error": "unauthorized"}), 401
job = await session.get(GpuJob, int(job_id))
if job is None or job.status != "leased" or job.lease_token != agent_id:
return jsonify({"error": "lease_invalid"}), 409
if kinds:
await RegionService(session).replace_regions(
job.image_record_id, kinds, regions
)
await GpuJobService(session).complete(agent_id, int(job_id))
await session.commit()
return jsonify({"ok": True, "stored": len(regions)})
@gpu_bp.route("/jobs/fail", methods=["POST"])
async def fail():
body = await request.get_json(silent=True) or {}
agent_id = str(body.get("agent_id") or "agent")
job_id = body.get("job_id")
if job_id is None:
return jsonify({"error": "job_id required"}), 400
async with get_session() as session:
if not await _agent_authed(session):
return jsonify({"error": "unauthorized"}), 401
ok = await GpuJobService(session).fail(
agent_id, int(job_id), str(body.get("error") or "")
)
await session.commit()
return jsonify({"ok": ok})
@gpu_bp.route("/jobs/release", methods=["POST"])
async def release():
"""Graceful stop: the agent hands its still-leased jobs back to pending so
they're picked up immediately instead of waiting out the lease."""
body = await request.get_json(silent=True) or {}
agent_id = str(body.get("agent_id") or "agent")
job_ids = [int(x) for x in (body.get("job_ids") or [])]
async with get_session() as session:
if not await _agent_authed(session):
return jsonify({"error": "unauthorized"}), 401
n = await GpuJobService(session).release(agent_id, job_ids)
await session.commit()
return jsonify({"released": n})