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Michael Rabinovich
submit: shard large submissions across HF Jobs + merge (UC3)
293bc3b 5 months ago
55 kB
# Copyright 2026 Hugging Face
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Submit-tab handler for the CADGenBench leaderboard Space.
Step 6 (E) chunks 2 + 3 + 4 + 6 + Step 10 (jobs migration): cheap-sync
validation + pending-row write + zip upload + background dispatch +
poll of an HF Jobs GPU eval + boot-time stuck-pending sweep. The
handler validates the upload, uploads the zip to
``submissions/<id>.zip``, appends a ``status: pending`` row to
``results.jsonl`` (under a process-wide lock), spawns a daemon thread
that dispatches a per-submission HF Job against the eval-gpu
Docker Space image and polls
``inspect_job`` until the job's stage is terminal. On COMPLETED the
worker downloads ``reports/<id>.json`` (the Job already uploaded
``reports/<id>.{html,json}`` to the submissions dataset), reads
``run_summary`` out of it, and flips the row ``pending -> completed``.
On ERROR (or any dispatch / poll exception) the row flips to ``failed``
with a short ``failure_reason``. At module import a one-shot daemon
sweep flips any ``pending`` row whose ``submitted_at`` is older than
30 min to ``failed`` with a "Space restart" reason, so rows stranded by
a deploy / OOM / crash / orphaned Job don't sit pending forever.
Validation gates, in order:
1. Form-level: a file was attached.
2. Zip safety: parseable as a zip, no absolute / parent-traversing
   entry names, no symlinks.
3. ``meta.json`` schema: required keys present, types sane,
   ``agree_to_publish`` is literally ``true`` (the sole consent
   gate; no separate UI checkbox), ``notes`` is non-empty when
   present and within the per-submission cap.
4. Fixture-set match: the set of folders inside the zip equals the
   set of fixture directories in :func:`cadgenbench.common.paths.data_inputs_dir`
   (no missing, no extras).
5. STEP parseability: each ``<fixture>/output.step`` loads as STEP
   geometry. Per-fixture validity (watertight, manifold, etc) is
   *not* checked here, that's the evaluator's job and contributes to
   the per-fixture score; this gate only rejects "not actually STEP".
Hub-write ordering (after validation passes):
1. Upload ``submissions/<id>.zip``. Unique path per submission, no
   lock needed.
2. Build pending row (metadata + null scores + ``submission_blob_url``).
3. Acquire ``_HUB_LOCK``; download current ``results.jsonl`` (or
   start empty); append the pending row; re-upload.
4. Spawn worker thread (daemon, named after submission_id). The
   worker owns the tempdir's lifecycle past this point.
If step 1 fails the user sees a clean rejection. If step 3 fails the
zip is left orphaned in ``submissions/`` and the user sees a clean
rejection; an orphan-zip sweep is a future-chunk concern.
Background worker, per submission:
1. ``huggingface_hub.run_job(...)`` dispatches an HF Job against
   the ``cadgenbench-eval-gpu`` Space image on ``a10g-large``,
   passing the submission_id + zip blob URL as command args and
   ``HF_TOKEN`` as a secret.
2. Poll ``inspect_job(job_id)`` every few seconds until the job's
   stage is terminal (``COMPLETED`` or ``ERROR``). Outer deadline
   guards against an unresponsive poll surface.
3. On ``COMPLETED``: download ``reports/<id>.json`` from the
   submissions dataset (the Job uploaded both
   ``reports/<id>.{html,json}`` before exiting), read
   ``run_summary`` out of the bundled payload, under ``_HUB_LOCK``
   flip the row to ``"completed"`` and merge the score fields.
4. On ``ERROR`` (or any dispatch / poll exception), flip the row to
   ``"failed"`` with a short ``failure_reason`` (the job's
   ``status.message`` plus the last N lines of ``fetch_job_logs``).
"""
from __future__ import annotations

import hashlib
import json
import logging
import os
import re
import shutil
import tempfile
import threading
import time
import zipfile
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any

import cadgenbench
import gradio as gr
from cadgenbench.common.paths import data_inputs_dir
from cadgenbench.common.validity import parse_step
from huggingface_hub import (
    HfApi,
    fetch_job_logs,
    hf_hub_download,
    inspect_job,
    run_job,
    snapshot_download,
)
from huggingface_hub.errors import EntryNotFoundError

from leaderboard import HF_DATA_REPO, HF_ORG, HF_SUBMISSIONS_REPO

logger = logging.getLogger(__name__)

NOTES_MAX_CHARS = 500
REQUIRED_META_KEYS: tuple[str, ...] = (
    "submitter_name",
    "submission_name",
    "agent_url",
    "notes",
    "agree_to_publish",
)
SUBMISSION_ID_SLUG_MAX = 40
RESULTS_FILENAME = "results.jsonl"
SUBMISSIONS_DIR = "submissions"
REPORTS_DIR = "reports"
RENDERS_DIR = "renders"
# Single canonical view staged per fixture for the leaderboard gallery
# thumbnail (matches eval_job.py's GALLERY_THUMB_VIEW). The merged-shard
# path stages these from the merged run dir, exactly as the single-job
# eval_job does from its in-job run dir.
GALLERY_THUMB_VIEW = "iso"
DATA_REV_SHORT_LEN = 12
FAILURE_REASON_MAX_CHARS = 200
SHA256_BLOCK_SIZE = 64 * 1024
STUCK_PENDING_THRESHOLD_SECONDS = 30 * 60
SUBMITTED_AT_FORMAT = "%Y-%m-%dT%H:%M:%SZ"
STUCK_PENDING_REASON = "evaluation interrupted by Space restart"
BOOT_SWEEP_ENV = "CADGENBENCH_DISABLE_BOOT_SWEEP"

# HF Jobs target. The eval-gpu image is a Docker Space (paused;
# image-only) that lives in the org, so its repo id is derived from
# HF_ORG and an org rename stays a single Space-variable change.
# The job NAMESPACE is the account dispatch is billed to and must
# stay `michaelr27` (no-bill for HF employees per Round 6 of
# space-setup/leandro.md); it is a fixed constant, never env-driven.
# a10g-large fits cadgenbench evaluate --workers 8 in 46 GB RAM.
EVAL_GPU_SPACE = os.getenv(
    "CADGENBENCH_EVAL_GPU_SPACE", f"{HF_ORG}/cadgenbench-eval-gpu"
)
EVAL_JOB_FLAVOR = "a10g-large"
EVAL_JOB_NAMESPACE = "michaelr27"
EVAL_JOB_TIMEOUT = "30m"
EVAL_JOB_WORKER_COUNT = "8"

# Poll cadence + outer deadline guarding inspect_job. 5 s is fast
# enough that a 60 s eval lands in <10 s of completion, slow enough
# that we don't hammer the API. Deadline matches the Job's own
# --timeout; the Job is the source of truth, this is just a belt
# for an unresponsive inspect_job surface.
JOB_POLL_INTERVAL_SECONDS = 5
JOB_POLL_DEADLINE_SECONDS = 35 * 60
JOB_LOG_TAIL_LINES = 30
JOB_POLL_MAX_CONSECUTIVE_ERRORS = 5

# Sharded eval (UC3). A submission with more than SHARD_THRESHOLD
# fixtures fans out across several jobs of SHARD_CHUNK_SIZE fixtures
# each, dispatched all at once (HF queues any overflow past the
# account's ~8 concurrent slots; queueing is a speed variable, never a
# failure). Each shard uploads its per-fixture dirs under
# ``reports/<id>/shards/<shard_id>/``; the Space merges them into one
# run dir, recomputes the aggregate run_summary + report + gallery, and
# deletes the shards tree. Eval is CPU-bound (tessellation + Manifold
# booleans), so more machines is the throughput lever. At/under the
# threshold a submission stays a single job (the original path), so the
# extra dispatch/merge machinery only kicks in when it pays off.
SHARD_THRESHOLD = 12
SHARD_CHUNK_SIZE = 12
SHARDS_SUBDIR = "shards"
# ERROR-only retries per shard before the whole submission fails. A
# shard re-run is idempotent (it re-evals its own fixture slice and
# overwrites its upload prefix), so one cheap retry absorbs a transient
# job/runtime blip without re-running the shards that already passed.
SHARD_MAX_RETRIES = 1
# Whole-fan-out poll deadline. Each shard job carries its own
# ``EVAL_JOB_TIMEOUT``; this guards the Space-side poll loop. Generous
# vs. the per-shard ceiling because queued shards (past the ~8
# concurrent slots) wait their turn before their own timeout starts.
SHARD_POLL_DEADLINE_SECONDS = 45 * 60

# One HfApi client per process. HF_TOKEN is picked up from the env at
# construction time and reused for every call.
_HF_API = HfApi()

# Process-wide lock guarding the read-modify-write of results.jsonl.
# The Space is single-process so a threading.Lock is sufficient; held
# only for the duration of the RMW cycle (~1-2s), not for eval time.
_HUB_LOCK = threading.Lock()

# Lazily-resolved cadgenbench-data revision, cached per process.
_DATA_REVISION: str | None = None


class _ValidationError(Exception):
    """Internal sentinel that maps to a user-facing rejection message."""


class _HubWriteError(Exception):
    """Raised when a Hub upload fails after validation succeeded."""


def handle_submit(
    zip_file,
    profile: gr.OAuthProfile | None,
) -> None:
    """Validate a submission upload; surface progress + outcome via toasts.
    Requires the user to be logged in via ``gr.LoginButton`` so the
    row's ``hf_username`` is the canonical HF identity (not a
    free-text claim). The submit button in :mod:`app` is disabled
    until login completes; this function also raises ``gr.Error``
    defensively if it's called without a profile so a UI mishap
    can't write an anonymous row.
    Side-effect-only (returns ``None``): in-flight status surfaces via
    ``gr.Info`` toasts (validating on click, queued after the worker
    spawns) and ``gr.Error`` toasts for rejections. Rejection paths
    raise ``gr.Error``, which Gradio surfaces as a red toast and
    aborts the handler; the outer ``try/finally`` still runs to clean
    up the temp dir.
    Toasts on the happy path:
    1. ``"Validating submission..."`` on click, with a wall-time hint
       so the user knows the post-queue eval takes ~1 minute.
    2. ``"Submission <id> queued ..."`` once the row + zip are on the
       Hub and the worker has been spawned.
    On rejection (login-missing, form-level, validation gate, dedup,
    or Hub write), a single ``gr.Error`` toast carries the message;
    no second toast.
    """
    if profile is None:
        raise gr.Error("Please log in via the HF button before submitting.")
    form_err = _validate_form(zip_file)
    if form_err is not None:
        raise gr.Error(form_err)

    # Immediate ack on click. The eval itself (after queuing) is the
    # slow part, so hint at the wall time up front so the user knows
    # what to expect instead of waiting on a silent button.
    gr.Info(
        "Validating submission... evaluation usually takes "
        "~1 minute after queuing."
    )

    zip_path = Path(zip_file.name)

    # The tempdir lives only for the cheap-sync validation pass
    # (unpack zip, validate meta + fixture set + STEP parseability).
    # The Job downloads the zip itself from the Hub, so the
    # Space-local unpack is throwaway and the tempdir gets cleaned
    # up unconditionally in the outer finally.
    tmp = Path(tempfile.mkdtemp(prefix="cadgenbench-submit-"))
    run_dir = tmp / "run"
    run_dir.mkdir()
    try:
        try:
            _extract_zip(zip_path, run_dir)
            meta = _load_and_validate_meta(run_dir)
            fixture_names = _validate_fixture_set(run_dir)
            _validate_steps_parseable(run_dir, fixture_names)
        except _ValidationError as e:
            raise gr.Error(f"Submission rejected: {e}")

        # Dedup gate: hash the raw zip bytes and reject if an existing
        # row carries the same hash. Runs after validation so a clearly
        # malformed upload still gets the specific validation error.
        zip_sha256 = _compute_sha256(zip_path)
        existing_id = _find_existing_submission_by_sha256(zip_sha256)
        if existing_id is not None:
            raise gr.Error(
                f"This zip's contents are identical to an existing "
                f"submission ({existing_id}). Resubmit only after changing "
                f"at least one byte of the upload."
            )

        submission_id = _mint_submission_id(
            meta["submitter_name"], meta["submission_name"]
        )
        try:
            blob_url = _upload_submission_zip(submission_id, zip_path)
            row = _build_pending_row(
                submission_id, meta, blob_url, zip_sha256,
                hf_username=profile.username,
            )
            _append_pending_row(row)
        except _HubWriteError as e:
            raise gr.Error(f"Submission rejected: {e}")

        _spawn_worker(submission_id, blob_url, sorted(fixture_names))
        gr.Info(
            f"Submission {submission_id} queued for evaluation "
            f"({len(fixture_names)} fixtures). The eval runs on an "
            f"HF Jobs GPU; the row flips to completed when the job "
            f"finishes (typically 1-3 minutes)."
        )
    finally:
        shutil.rmtree(tmp, ignore_errors=True)


def _validate_form(zip_file) -> str | None:
    """Form-level check before any zip parsing.
    Returns a plain-text rejection message (no markdown wrapping;
    the caller wraps it into a ``gr.Error`` toast) or ``None`` when
    the form is acceptable.
    """
    if zip_file is None:
        return "Please attach a submission zip."
    return None


def _extract_zip(zip_path: Path, target: Path) -> None:
    """Extract *zip_path* into *target* with zip-slip + symlink rejection.
    Python's ``ZipFile.extractall`` since 3.12 normalises away unsafe
    paths silently; we'd rather reject the upload outright so the
    submitter sees a clear error instead of getting a "fixture set
    mismatch" downstream because half their files were dropped.
    """
    try:
        with zipfile.ZipFile(zip_path) as zf:
            for info in zf.infolist():
                if info.is_dir():
                    continue
                name = Path(info.filename)
                if name.is_absolute() or ".." in name.parts:
                    raise _ValidationError(
                        f"Zip contains an unsafe path: {info.filename!r}."
                    )
                # Unix mode lives in the high 16 bits of external_attr;
                # symlinks are mode 0o120000 (S_IFLNK).
                mode = info.external_attr >> 16
                if mode and (mode & 0o170000) == 0o120000:
                    raise _ValidationError(
                        f"Zip contains a symlink ({info.filename!r}); "
                        f"submissions must be plain files."
                    )
            zf.extractall(target)
    except zipfile.BadZipFile as e:
        raise _ValidationError(f"Upload is not a valid zip file: {e}") from e


def _load_and_validate_meta(unpacked: Path) -> dict[str, Any]:
    meta_path = unpacked / "meta.json"
    if not meta_path.is_file():
        raise _ValidationError(
            "Zip is missing top-level `meta.json` (expected at the root of "
            "the zip, alongside the per-fixture folders)."
        )
    try:
        meta = json.loads(meta_path.read_text())
    except json.JSONDecodeError as e:
        raise _ValidationError(
            f"`meta.json` is not valid JSON: {e.msg} (line {e.lineno})."
        ) from e
    if not isinstance(meta, dict):
        raise _ValidationError(
            "`meta.json` must be a JSON object at the top level."
        )

    missing = [k for k in REQUIRED_META_KEYS if k not in meta]
    if missing:
        raise _ValidationError(
            f"`meta.json` is missing required key(s): {', '.join(missing)}."
        )

    for k in ("submitter_name", "submission_name"):
        v = meta[k]
        if not isinstance(v, str) or not v.strip():
            raise _ValidationError(
                f"`meta.json` field `{k}` must be a non-empty string."
            )

    for k in ("agent_url", "notes"):
        v = meta[k]
        if v is not None and not isinstance(v, str):
            raise _ValidationError(
                f"`meta.json` field `{k}` must be a string or null."
            )

    if meta["agree_to_publish"] is not True:
        raise _ValidationError(
            "`meta.json` field `agree_to_publish` must be the literal boolean "
            "`true`."
        )

    if meta["notes"] is not None:
        meta["notes"] = _normalize_notes(meta["notes"])

    return meta


def _normalize_notes(raw: str) -> str:
    """Collapse newlines + tabs to spaces, strip, enforce the char cap."""
    one_line = re.sub(r"[\r\n\t]+", " ", raw).strip()
    if len(one_line) > NOTES_MAX_CHARS:
        raise _ValidationError(
            f"`meta.json` field `notes` exceeds the {NOTES_MAX_CHARS}-char "
            f"cap (got {len(one_line)} after stripping). Trim and resubmit."
        )
    return one_line


def _validate_fixture_set(unpacked: Path) -> set[str]:
    """Compare unpacked top-level dirs to the inputs dataset's fixture set."""
    actual = {p.name for p in unpacked.iterdir() if p.is_dir()}

    try:
        inputs_root = data_inputs_dir()
    except Exception as e:  # noqa: BLE001 - paths.py raises a few types
        raise _ValidationError(
            f"Server-side error resolving the fixture set "
            f"({type(e).__name__}: {e})."
        ) from e
    expected = {p.name for p in inputs_root.iterdir() if p.is_dir()}

    missing = expected - actual
    extras = actual - expected
    if missing or extras:
        parts: list[str] = []
        if missing:
            parts.append(f"missing fixture(s): {', '.join(sorted(missing))}")
        if extras:
            parts.append(f"unexpected folder(s): {', '.join(sorted(extras))}")
        raise _ValidationError(
            "Fixture set does not match the dataset. " + "; ".join(parts) + "."
        )
    return expected


def _validate_steps_parseable(unpacked: Path, fixture_names: set[str]) -> None:
    # Threads (not processes): OCC's parse_step releases the GIL during
    # the C++ STEP read, and this gate doesn't touch the VTK renderer
    # (which is the only piece in the eval pipeline that needs the
    # ProcessPoolExecutor + spawn dance). Per-fixture I/O + OCC load is
    # 1-5s, so fanning out a 5+ fixture set across cpu-upgrade vCPUs
    # cuts wall time roughly linearly. ex.map raises the first child
    # exception when its iterator is consumed, so wrapping in list()
    # preserves the same `Fixture <name>` rejection text as the
    # sequential loop did.
    def _check_one_step(name: str) -> None:
        step = unpacked / name / "output.step"
        if not step.is_file():
            raise _ValidationError(
                f"Fixture `{name}` is missing its `output.step` file."
            )
        if step.stat().st_size == 0:
            raise _ValidationError(
                f"Fixture `{name}` has an empty `output.step`."
            )
        try:
            parse_step(step)
        except RuntimeError as e:
            raise _ValidationError(
                f"Fixture `{name}` has an `output.step` that is not loadable "
                f"as STEP geometry: {e}"
            ) from e

    with ThreadPoolExecutor(
        max_workers=min(8, os.cpu_count() or 1),
    ) as ex:
        list(ex.map(_check_one_step, sorted(fixture_names)))


def _mint_submission_id(submitter_name: str, submission_name: str) -> str:
    """Build the basename used for ``submissions/<id>.zip`` and ``reports/<id>.*``."""
    ts = datetime.now(timezone.utc).strftime("%Y%m%d-%H%M%S")
    return f"{_slug(submitter_name)}_{_slug(submission_name)}_{ts}"


def _slug(s: str) -> str:
    """Filesystem-safe slug. Lowercase, ``[a-z0-9-]``, collapsed dashes."""
    cleaned = re.sub(r"[^A-Za-z0-9]+", "-", s).strip("-").lower()
    return cleaned[:SUBMISSION_ID_SLUG_MAX] or "unnamed"


def _upload_submission_zip(submission_id: str, zip_path: Path) -> str:
    """Upload the submission zip to ``submissions/<id>.zip``.
    Returns the canonical Hub blob URL on success. Raises
    :class:`_HubWriteError` with a short user-facing reason on
    failure.
    """
    repo_path = f"{SUBMISSIONS_DIR}/{submission_id}.zip"
    try:
        _HF_API.upload_file(
            path_or_fileobj=str(zip_path),
            path_in_repo=repo_path,
            repo_id=HF_SUBMISSIONS_REPO,
            repo_type="dataset",
            commit_message=f"add submission zip for {submission_id}",
        )
    except Exception as e:  # noqa: BLE001 - Hub API surface is broad
        logger.exception("Failed to upload submission zip %s", submission_id)
        raise _HubWriteError(
            f"Server-side error uploading submission zip "
            f"({type(e).__name__}: {e}). Please try again later."
        ) from e
    return (
        f"https://huggingface.co/datasets/{HF_SUBMISSIONS_REPO}"
        f"/resolve/main/{repo_path}"
    )


def _build_pending_row(
    submission_id: str,
    meta: dict[str, Any],
    blob_url: str,
    submission_sha256: str,
    hf_username: str | None = None,
) -> dict[str, Any]:
    """Construct the JSON row written for a freshly-queued submission.
    Mirrors the pending regime in ``cadgenbench-submissions/schema.md``:
    metadata + ``status: pending`` + ``submission_blob_url`` +
    ``submission_sha256``; every score-shaped field is ``null`` until
    the worker flips the row.
    Validation-tier fields default per the validation-policy decision
    doc: ``validation_status: "unvalidated"`` (maintainers promote
    post-eval), ``validation_method: None``. ``hf_username`` defaults
    to ``None``; callers post-OAuth pass ``profile.username`` so the
    row carries the canonical HF identity. Pre-OAuth-era rows
    (anything written before C10 landed) and any test paths that
    don't supply the kwarg keep ``null``.
    """
    return {
        "submission_id": submission_id,
        "status": "pending",
        "failure_reason": None,
        "submitter_name": meta["submitter_name"],
        "submission_name": meta["submission_name"],
        "agent_url": meta["agent_url"],
        "notes": meta["notes"],
        "submitted_at": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
        "cadgenbench_version": cadgenbench.__version__,
        "cadgenbench_data_revision": _resolve_data_revision(),
        "validity_rate": None,
        "aggregate_score": None,
        "score_by_task_type": None,
        "per_task_scores": None,
        "per_fixture_scores": None,
        "per_fixture_breakdown": None,
        "submission_blob_url": blob_url,
        "submission_sha256": submission_sha256,
        "validation_status": "unvalidated",
        "validation_method": None,
        "hf_username": hf_username,
    }


def _compute_sha256(path: Path) -> str:
    """Hex-encoded SHA-256 of the file at *path*. Streams in 64 KiB chunks."""
    h = hashlib.sha256()
    with path.open("rb") as f:
        for chunk in iter(lambda: f.read(SHA256_BLOCK_SIZE), b""):
            h.update(chunk)
    return h.hexdigest()


def _find_existing_submission_by_sha256(zip_sha256: str) -> str | None:
    """Return the ``submission_id`` of an existing row with the same hash, else None.
    Reads the current ``results.jsonl`` once (no lock; a worst-case
    race lands a duplicate row, which is recoverable by a cleanup pass
    if it ever happens). Hub-fetch failures are non-fatal: the caller
    just doesn't get the dedup gate this submit (logged).
    """
    try:
        body = _download_results_jsonl()
    except Exception as e:  # noqa: BLE001 - Hub API surface is broad
        logger.warning(
            "Dedup check skipped, Hub fetch failed (%s: %s)",
            type(e).__name__, e,
        )
        return None
    for line in body.splitlines():
        if not line.strip():
            continue
        try:
            row = json.loads(line)
        except json.JSONDecodeError:
            continue
        if row.get("submission_sha256") == zip_sha256:
            return row.get("submission_id")
    return None


def _append_pending_row(row: dict[str, Any]) -> None:
    """Append a pending row to ``results.jsonl`` on the Hub under the lock."""
    submission_id = row["submission_id"]

    def mutate(rows: list[dict[str, Any]]) -> None:
        rows.append(row)

    try:
        _hub_rmw_results(
            mutate, commit_message=f"add pending row for {submission_id}"
        )
    except Exception as e:  # noqa: BLE001 - Hub API surface is broad
        logger.exception(
            "Failed RMW of results.jsonl while appending pending row for %s",
            submission_id,
        )
        raise _HubWriteError(
            f"Server-side error writing the submissions table "
            f"({type(e).__name__}: {e}). The submission zip was uploaded "
            f"but the row was not; please try again later."
        ) from e


def _update_row(submission_id: str, updates: dict[str, Any]) -> None:
    """Find the row for *submission_id* and merge *updates* into it.
    Raises ``LookupError`` if no row with that id exists (worker fired
    before the pending row was committed, which shouldn't happen, but
    surfaces clearly if it ever does).
    """
    def mutate(rows: list[dict[str, Any]]) -> None:
        for r in rows:
            if r.get("submission_id") == submission_id:
                r.update(updates)
                return
        raise LookupError(
            f"No row with submission_id={submission_id!r} in results.jsonl."
        )

    _hub_rmw_results(
        mutate,
        commit_message=(
            f"flip row for {submission_id} -> {updates.get('status', '?')}"
        ),
    )


def _hub_rmw_results(
    mutate, *, commit_message: str,
) -> None:
    """Lock + download + mutate + upload of ``results.jsonl``.
    The lock is held only for the read-modify-write cycle (~1-2s),
    never for eval time. Concurrent submitters serialise here, not
    in the eval pipeline. Treats a missing file as the empty list.
    """
    with _HUB_LOCK:
        existing = _download_results_jsonl()
        rows: list[dict[str, Any]] = [
            json.loads(line) for line in existing.splitlines() if line.strip()
        ]
        mutate(rows)
        new_body = (
            "\n".join(json.dumps(r, ensure_ascii=False) for r in rows) + "\n"
            if rows
            else ""
        )
        _HF_API.upload_file(
            path_or_fileobj=new_body.encode("utf-8"),
            path_in_repo=RESULTS_FILENAME,
            repo_id=HF_SUBMISSIONS_REPO,
            repo_type="dataset",
            commit_message=commit_message,
        )


def _download_results_jsonl() -> str:
    """Fetch the current ``results.jsonl`` body as text, or ``""`` if absent."""
    from huggingface_hub import hf_hub_download

    try:
        path = hf_hub_download(
            repo_id=HF_SUBMISSIONS_REPO,
            filename=RESULTS_FILENAME,
            repo_type="dataset",
            force_download=True,
        )
    except EntryNotFoundError:
        return ""
    return Path(path).read_text(encoding="utf-8")


def _resolve_data_revision() -> str:
    """Return a short sha for the cadgenbench-data dataset, cached per process.
    Falls back to ``"unknown"`` on Hub errors so a flaky network can't
    block a submission over a metadata field.
    """
    global _DATA_REVISION
    if _DATA_REVISION is not None:
        return _DATA_REVISION
    try:
        info = _HF_API.dataset_info(HF_DATA_REPO)
        _DATA_REVISION = (info.sha or "unknown")[:DATA_REV_SHORT_LEN]
    except Exception as e:  # noqa: BLE001 - metadata only, don't fail the submit
        logger.warning(
            "Failed to resolve cadgenbench-data revision (%s: %s)",
            type(e).__name__, e,
        )
        _DATA_REVISION = "unknown"
    return _DATA_REVISION


# ---------------------------------------------------------------------------
# Background worker (dispatch eval to HF Jobs, poll, flip row)
# ---------------------------------------------------------------------------


def _spawn_worker(
    submission_id: str,
    submission_blob_url: str,
    fixture_names: list[str],
) -> None:
    """Start the dispatch+poll worker thread.
    Fire-and-forget; daemon=True so a Space restart doesn't block on
    in-flight workers (the boot-time sweep below flips any rows their
    workers didn't finish to failed). The worker no longer owns any
    Space-local files; the Job(s) download the zip themselves from the
    Hub. *fixture_names* (the validated, dataset-matched set) decides
    single-job vs. sharded dispatch and drives the shard split.
    """
    t = threading.Thread(
        target=_run_worker,
        args=(submission_id, submission_blob_url, fixture_names),
        name=f"cgb-worker-{submission_id}",
        daemon=True,
    )
    t.start()


def _run_worker(
    submission_id: str,
    submission_blob_url: str,
    fixture_names: list[str],
) -> None:
    """Dispatch the eval Job(s), poll to completion, flip the row.
    Submissions at/under :data:`SHARD_THRESHOLD` fixtures run as a
    single job (the original path); larger ones fan out across shards
    and merge. Any exception (dispatch, poll, fetch/merge, flip) maps to
    a ``failed`` row with a short ``failure_reason`` (full traceback
    goes to the Space's runtime logs).
    """
    try:
        if len(fixture_names) > SHARD_THRESHOLD:
            _run_worker_sharded(
                submission_id, submission_blob_url, fixture_names,
            )
            return
        job_id = _dispatch_eval_job(submission_id, submission_blob_url)
        logger.info("Dispatched eval job %s for %s", job_id, submission_id)
        stage, status_message = _poll_until_done(job_id, submission_id)
        if stage == "COMPLETED":
            summary = _fetch_run_summary_from_report(submission_id)
            _flip_row_to_completed(submission_id, summary)
            logger.info("Worker completed for %s", submission_id)
            return
        reason = _job_failure_reason(job_id, stage, status_message)
        _flip_row_to_failed(submission_id, reason)
        logger.warning(
            "Eval job %s for %s ended %s: %s",
            job_id, submission_id, stage, reason,
        )
    except Exception as e:  # noqa: BLE001 - broad on purpose; we map to row state
        logger.exception("Worker failed for %s", submission_id)
        reason = f"{type(e).__name__}: {str(e)}"[:FAILURE_REASON_MAX_CHARS]
        try:
            _flip_row_to_failed(submission_id, reason)
        except Exception:
            # If even the row-flip fails, the row stays pending. The
            # stuck-pending sweep on the next Space boot will catch it.
            logger.exception(
                "Failed to flip row to failed for %s; row stays pending",
                submission_id,
            )


def _run_worker_sharded(
    submission_id: str,
    submission_blob_url: str,
    fixture_names: list[str],
) -> None:
    """Fan a large submission across shard jobs, then merge + flip.
    Dispatches every shard at once (HF queues overflow past the
    account's concurrent-job cap), polls all to terminal retrying only
    ERROR shards, then merges each shard's per-fixture dirs into one run
    dir, recomputes the aggregate ``run_summary`` + report + gallery,
    flips the row to ``completed``, and deletes the shards tree. If any
    shard is still ERROR after its retries the row flips to ``failed``
    and the partial shard artifacts are left for a maintainer to
    inspect. Raised exceptions propagate to :func:`_run_worker`'s
    handler, which maps them to a failed row.
    """
    chunks = _chunk_fixtures(fixture_names, SHARD_CHUNK_SIZE)
    shards: dict[str, dict[str, Any]] = {
        f"shard_{i:03d}": {
            "fixtures": chunk,
            "job_id": None,
            "attempts": 0,
            "stage": None,
            "message": None,
        }
        for i, chunk in enumerate(chunks)
    }
    logger.info(
        "Sharded eval for %s: %d fixtures -> %d shard(s)",
        submission_id, len(fixture_names), len(shards),
    )
    for shard_id, st in shards.items():
        _dispatch_shard(submission_id, submission_blob_url, shard_id, st)

    failures = _poll_shards_until_done(
        submission_id, submission_blob_url, shards,
    )
    if failures:
        reason = ("sharded eval failed: " + "; ".join(failures))[
            :FAILURE_REASON_MAX_CHARS
        ]
        _flip_row_to_failed(submission_id, reason)
        logger.warning("Sharded eval for %s failed: %s", submission_id, reason)
        return

    summary = _merge_shards_and_publish(
        submission_id, list(shards.keys()), fixture_names,
    )
    _flip_row_to_completed(submission_id, summary)
    logger.info("Sharded worker completed for %s", submission_id)
    _cleanup_shard_artifacts(submission_id)


def _chunk_fixtures(fixtures: list[str], chunk_size: int) -> list[list[str]]:
    """Split *fixtures* into contiguous chunks of at most *chunk_size*."""
    return [
        fixtures[i:i + chunk_size]
        for i in range(0, len(fixtures), chunk_size)
    ]


def _dispatch_eval_job(
    submission_id: str, submission_blob_url: str,
) -> str:
    """Dispatch the whole-submission eval Job and return its id."""
    return _dispatch_eval_command(submission_id, submission_blob_url, [])


def _dispatch_eval_command(
    submission_id: str,
    submission_blob_url: str,
    extra_args: list[str],
) -> str:
    """Dispatch an eval Job (whole-submission or one shard) and return its id.
    Passes through every env var ``eval_job.py`` needs to resolve the
    Hub data + GT repos and the target submissions repo; the Job's
    HF_TOKEN secret comes from the Space's own HF_TOKEN env (which
    needs Jobs + repo R/W scopes, see space-setup/jobs-migration.md).
    *extra_args* are appended to the entrypoint argv; empty for the
    whole-submission path, ``--shard-id ... --fixtures ...`` for a shard.
    """
    token = os.environ.get("HF_TOKEN")
    if not token:
        raise RuntimeError(
            "HF_TOKEN is unset on the Space; cannot dispatch eval job."
        )
    env: dict[str, str] = {
        "HF_SUBMISSIONS_REPO": HF_SUBMISSIONS_REPO,
        "EVAL_WORKER_COUNT": EVAL_JOB_WORKER_COUNT,
    }
    for key in ("CADGENBENCH_DATA_REPO", "CADGENBENCH_DATA_GT_REPO"):
        value = os.environ.get(key)
        if value:
            env[key] = value
    job = run_job(
        image=f"hf.co/spaces/{EVAL_GPU_SPACE}",
        command=[
            "python", "/opt/eval_job.py", submission_id, submission_blob_url,
            *extra_args,
        ],
        flavor=EVAL_JOB_FLAVOR,
        namespace=EVAL_JOB_NAMESPACE,
        env=env,
        secrets={"HF_TOKEN": token},
        timeout=EVAL_JOB_TIMEOUT,
        token=token,
    )
    return job.id


def _dispatch_shard(
    submission_id: str,
    submission_blob_url: str,
    shard_id: str,
    state: dict[str, Any],
) -> None:
    """Dispatch (or re-dispatch) one shard job and record it in *state*.
    Mutates *state* in place: sets ``job_id``, bumps ``attempts``, and
    clears the prior ``stage``/``message`` so a retried shard is polled
    fresh. The shard re-evals its own fixture slice and overwrites its
    ``reports/<id>/shards/<shard_id>/`` prefix, so a retry is idempotent.
    """
    job_id = _dispatch_eval_command(
        submission_id,
        submission_blob_url,
        ["--shard-id", shard_id, "--fixtures", ",".join(state["fixtures"])],
    )
    state["job_id"] = job_id
    state["attempts"] += 1
    state["stage"] = None
    state["message"] = None
    logger.info(
        "Dispatched shard %s for %s (attempt %d, job %s, %d fixtures)",
        shard_id, submission_id, state["attempts"], job_id,
        len(state["fixtures"]),
    )


def _poll_shards_until_done(
    submission_id: str,
    submission_blob_url: str,
    shards: dict[str, dict[str, Any]],
) -> list[str]:
    """Poll every shard to terminal, retrying only ERROR shards.
    Mirrors the orchestrator's eval poll loop: a single thread sweeps
    all running shards each tick (``inspect_job`` calls are cheap), an
    ERROR shard re-dispatches up to :data:`SHARD_MAX_RETRIES` times,
    and a non-terminal stage just waits. Returns a list of
    ``"<shard_id>: <reason>"`` strings for shards that stayed ERROR
    after their retries (empty list means every shard COMPLETED).
    Transient ``inspect_job`` failures retry up to
    :data:`JOB_POLL_MAX_CONSECUTIVE_ERRORS` before raising.
    """
    deadline = time.monotonic() + SHARD_POLL_DEADLINE_SECONDS
    consecutive_errors = 0
    while True:
        running = [
            sid for sid, st in shards.items()
            if st["stage"] not in ("COMPLETED", "FAILED")
        ]
        if not running:
            break
        for shard_id in running:
            st = shards[shard_id]
            try:
                info = inspect_job(job_id=st["job_id"])
                consecutive_errors = 0
            except Exception as e:  # noqa: BLE001 - retry transient API errors
                consecutive_errors += 1
                logger.warning(
                    "inspect_job(%s) for shard %s failed (%d/%d): %s",
                    st["job_id"], shard_id, consecutive_errors,
                    JOB_POLL_MAX_CONSECUTIVE_ERRORS, e,
                )
                if consecutive_errors >= JOB_POLL_MAX_CONSECUTIVE_ERRORS:
                    raise
                break  # stop this sweep; sleep then retry

            stage = info.status.stage
            if stage == "COMPLETED":
                st["stage"] = "COMPLETED"
                logger.info("Shard %s COMPLETED for %s", shard_id, submission_id)
            elif stage == "ERROR":
                if st["attempts"] <= SHARD_MAX_RETRIES:
                    logger.warning(
                        "Shard %s ERROR; retry %d/%d",
                        shard_id, st["attempts"], SHARD_MAX_RETRIES,
                    )
                    _dispatch_shard(
                        submission_id, submission_blob_url, shard_id, st,
                    )
                else:
                    st["stage"] = "FAILED"
                    st["message"] = _job_failure_reason(
                        st["job_id"], stage, info.status.message,
                    )
                    logger.warning(
                        "Shard %s FAILED after %d attempt(s): %s",
                        shard_id, st["attempts"], st["message"],
                    )

        if time.monotonic() >= deadline:
            for shard_id, st in shards.items():
                if st["stage"] not in ("COMPLETED", "FAILED"):
                    st["stage"] = "FAILED"
                    st["message"] = (
                        f"Space-side poll deadline exceeded "
                        f"({SHARD_POLL_DEADLINE_SECONDS}s)"
                    )
            break
        time.sleep(JOB_POLL_INTERVAL_SECONDS)

    return [
        f"{sid}: {st['message']}"
        for sid, st in shards.items()
        if st["stage"] == "FAILED"
    ]


def _poll_until_done(
    job_id: str, submission_id: str,
) -> tuple[str, str | None]:
    """Poll ``inspect_job`` until terminal; return (stage, message).
    Terminal stages: ``COMPLETED``, ``ERROR``. Anything else after the
    outer deadline counts as a synthetic ``ERROR`` with a "deadline
    exceeded" message; we do not try to cancel the Job from here (the
    Job carries its own ``timeout`` and HF will reap it). Transient
    ``inspect_job`` errors retry up to
    ``JOB_POLL_MAX_CONSECUTIVE_ERRORS`` consecutive failures before
    raising.
    """
    deadline = time.monotonic() + JOB_POLL_DEADLINE_SECONDS
    consecutive_errors = 0
    while True:
        try:
            info = inspect_job(job_id=job_id)
            consecutive_errors = 0
        except Exception as e:  # noqa: BLE001 - retry transient API errors
            consecutive_errors += 1
            logger.warning(
                "inspect_job(%s) failed (%d/%d): %s",
                job_id, consecutive_errors,
                JOB_POLL_MAX_CONSECUTIVE_ERRORS, e,
            )
            if consecutive_errors >= JOB_POLL_MAX_CONSECUTIVE_ERRORS:
                raise
            time.sleep(JOB_POLL_INTERVAL_SECONDS)
            continue

        stage = info.status.stage
        message = info.status.message
        if stage in ("COMPLETED", "ERROR"):
            return stage, message
        if time.monotonic() >= deadline:
            return "ERROR", (
                f"Space-side poll deadline exceeded "
                f"({JOB_POLL_DEADLINE_SECONDS}s); last stage={stage}"
            )
        time.sleep(JOB_POLL_INTERVAL_SECONDS)


def _job_failure_reason(
    job_id: str, stage: str, status_message: str | None,
) -> str:
    """Build a short ``failure_reason`` for a non-completed Job.
    Combines the job's own ``status.message`` (if any) with the last
    ``JOB_LOG_TAIL_LINES`` of ``fetch_job_logs`` so the user sees
    something actionable in the row. Log fetch is best-effort.
    """
    parts: list[str] = [f"eval job {stage.lower()}"]
    if status_message:
        parts.append(status_message)
    try:
        tail = list(fetch_job_logs(job_id=job_id))[-JOB_LOG_TAIL_LINES:]
        if tail:
            parts.append("logs: " + " | ".join(tail))
    except Exception as e:  # noqa: BLE001 - logs are best-effort
        logger.warning("fetch_job_logs(%s) failed: %s", job_id, e)
    return ": ".join(parts)[:FAILURE_REASON_MAX_CHARS]


def _fetch_run_summary_from_report(submission_id: str) -> dict[str, Any]:
    """Download ``reports/<id>.json`` and return its ``run_summary`` dict.
    The Job uploaded the report bundle before exiting; by the time
    ``inspect_job`` returns COMPLETED the file is on the Hub. Raises
    if the report or the ``run_summary`` key is missing (which would
    indicate an eval that ran-but-broke contract; we want loud
    failure rather than a silently-empty row).
    """
    path = hf_hub_download(
        repo_id=HF_SUBMISSIONS_REPO,
        filename=f"{REPORTS_DIR}/{submission_id}.json",
        repo_type="dataset",
        force_download=True,
    )
    payload = json.loads(Path(path).read_text(encoding="utf-8"))
    summary = payload.get("run_summary")
    if not isinstance(summary, dict):
        raise RuntimeError(
            f"reports/{submission_id}.json missing or malformed "
            f"`run_summary` block (got {type(summary).__name__})"
        )
    return summary


def _merge_shards_and_publish(
    submission_id: str,
    shard_ids: list[str],
    fixture_names: list[str],
) -> dict[str, Any]:
    """Merge every shard's per-fixture dirs into one run + publish results.
    Downloads ``reports/<id>/shards/**`` from the submissions dataset,
    copies each shard's ``<fixture>/`` dir (``result.json`` + renders)
    into a single merged run dir, then recomputes the aggregate exactly
    as a single-job run would: ``write_run_summary`` over the union
    (the proven merge primitive, importable from the Space's own
    ``cadgenbench`` install -- no private-repo dependency), a
    ``report.json`` bundle, an HTML report via the same ``report
    single`` renderer the job uses, and one ``iso`` gallery thumbnail
    per fixture. Uploads ``reports/<id>.{html,json}`` + the gallery
    renders, and returns the merged ``run_summary`` for the row flip.
    Raises if a shard's tree is missing, a fixture appears in two shards,
    or the merged set doesn't cover every expected fixture -- any of
    which means the fan-out lost or duplicated work and the row should
    fail loudly rather than publish a partial aggregate.
    """
    # Imported from the Space's own cadgenbench install (the same
    # package submit.py imports at module load); these are public eval
    # APIs, not the private orchestrator repo.
    from cadgenbench.eval.report.single_run import discover_run, generate_html
    from cadgenbench.eval.run_summary import write_run_summary

    tmp = Path(tempfile.mkdtemp(prefix=f"cgb-merge-{submission_id}-"))
    try:
        download_root = Path(
            snapshot_download(
                repo_id=HF_SUBMISSIONS_REPO,
                repo_type="dataset",
                allow_patterns=[
                    f"{REPORTS_DIR}/{submission_id}/{SHARDS_SUBDIR}/**"
                ],
                local_dir=str(tmp / "dl"),
            )
        )
        shards_root = (
            download_root / REPORTS_DIR / submission_id / SHARDS_SUBDIR
        )
        if not shards_root.is_dir():
            raise RuntimeError(
                f"No shard artifacts found under {shards_root} after download."
            )

        merged_run = tmp / "run"
        merged_run.mkdir()
        seen: set[str] = set()
        for shard_dir in sorted(p for p in shards_root.iterdir() if p.is_dir()):
            for fixture_dir in sorted(
                p for p in shard_dir.iterdir() if p.is_dir()
            ):
                # Only real fixture dirs carry result.json; skip anything
                # else the shard upload swept in (e.g. a stray run_summary
                # subdir would not, but be defensive).
                if not (fixture_dir / "result.json").is_file():
                    continue
                name = fixture_dir.name
                if name in seen:
                    raise RuntimeError(
                        f"Fixture {name!r} present in more than one shard."
                    )
                seen.add(name)
                shutil.copytree(fixture_dir, merged_run / name)

        missing = set(fixture_names) - seen
        if missing:
            raise RuntimeError(
                f"Merged run missing {len(missing)} fixture(s) after shard "
                f"merge: {', '.join(sorted(missing)[:5])}"
                + ("..." if len(missing) > 5 else "")
            )

        write_run_summary(merged_run)
        report_json = _build_report_json(merged_run)

        run_data = discover_run(merged_run)
        html = generate_html(run_data)
        html_path = tmp / f"{submission_id}.html"
        html_path.write_text(html, encoding="utf-8")

        _upload_reports(submission_id, html_path, report_json)
        _upload_gallery_renders_from_dir(submission_id, merged_run)
        return report_json["run_summary"]
    finally:
        shutil.rmtree(tmp, ignore_errors=True)


def _build_report_json(run_dir: Path) -> dict[str, Any]:
    """Bundle ``run_summary.json`` + every per-fixture ``result.json``.
    Identical shape to ``eval_job.py``'s ``_build_report_json`` so the
    merged report matches a single-job report: the row flip reads
    ``run_summary`` out of this and the bundle is what gets uploaded as
    ``reports/<id>.json``.
    """
    summary_path = run_dir / "run_summary.json"
    if not summary_path.is_file():
        raise RuntimeError(
            f"run_summary.json not produced under {run_dir} (merge issue?)"
        )
    summary = json.loads(summary_path.read_text(encoding="utf-8"))
    per_fixture: dict[str, dict[str, Any]] = {}
    for fixture_dir in sorted(d for d in run_dir.iterdir() if d.is_dir()):
        rp = fixture_dir / "result.json"
        if rp.is_file():
            per_fixture[fixture_dir.name] = json.loads(
                rp.read_text(encoding="utf-8")
            )
    return {"run_summary": summary, "per_fixture_results": per_fixture}


def _upload_reports(
    submission_id: str,
    html_path: Path,
    report_json: dict[str, Any],
) -> None:
    """Upload ``reports/<id>.html`` + ``reports/<id>.json`` to the Hub.
    Mirrors ``eval_job.py``'s ``_upload_reports`` so the merged-shard
    artifacts land at the exact paths the leaderboard + the row-flip
    expect. Uses the process ``HfApi`` (Space HF_TOKEN env).
    """
    _HF_API.upload_file(
        path_or_fileobj=str(html_path),
        path_in_repo=f"{REPORTS_DIR}/{submission_id}.html",
        repo_id=HF_SUBMISSIONS_REPO,
        repo_type="dataset",
        commit_message=f"add merged HTML report for {submission_id}",
    )
    _HF_API.upload_file(
        path_or_fileobj=json.dumps(
            report_json, ensure_ascii=False, indent=2,
        ).encode("utf-8"),
        path_in_repo=f"{REPORTS_DIR}/{submission_id}.json",
        repo_id=HF_SUBMISSIONS_REPO,
        repo_type="dataset",
        commit_message=f"add merged JSON report for {submission_id}",
    )
    logger.info("Uploaded merged reports/%s.{html,json}", submission_id)


def _upload_gallery_renders_from_dir(
    submission_id: str,
    run_dir: Path,
) -> None:
    """Stage one ``iso`` thumbnail per fixture for the leaderboard gallery.
    Mirrors ``eval_job.py``'s ``_upload_gallery_renders`` but reads from
    the merged run dir: every ``<run_dir>/<fixture>/renders/iso.png``
    becomes ``renders/<id>/<fixture>.png``. A fixture with no ``iso.png``
    (missing output / render that never ran) is skipped, matching the
    single-job behaviour; the gallery draws the dashed "invalid" cell
    from the row, so an absent thumbnail is not an error.
    """
    staged: list[tuple[Path, str]] = []
    for fixture_dir in sorted(d for d in run_dir.iterdir() if d.is_dir()):
        iso_png = fixture_dir / "renders" / f"{GALLERY_THUMB_VIEW}.png"
        if iso_png.is_file():
            staged.append((iso_png, fixture_dir.name))
    if not staged:
        logger.info("No gallery renders to upload for %s", submission_id)
        return
    for iso_png, fixture_name in staged:
        _HF_API.upload_file(
            path_or_fileobj=str(iso_png),
            path_in_repo=(
                f"{RENDERS_DIR}/{submission_id}/{fixture_name}.png"
            ),
            repo_id=HF_SUBMISSIONS_REPO,
            repo_type="dataset",
            commit_message=(
                f"add gallery render {fixture_name} for {submission_id}"
            ),
        )
    logger.info(
        "Uploaded %d gallery render(s) under %s/%s/",
        len(staged), RENDERS_DIR, submission_id,
    )


def _cleanup_shard_artifacts(submission_id: str) -> None:
    """Delete ``reports/<id>/shards/`` after a successful merge.
    Best-effort: the merged ``reports/<id>.{html,json}`` + gallery are
    the durable artifacts, so a failed cleanup only leaves recoverable
    scratch behind and must never fail an otherwise-completed
    submission.
    """
    try:
        _HF_API.delete_folder(
            path_in_repo=f"{REPORTS_DIR}/{submission_id}/{SHARDS_SUBDIR}",
            repo_id=HF_SUBMISSIONS_REPO,
            repo_type="dataset",
            commit_message=f"clean up eval shards for {submission_id}",
        )
        logger.info("Cleaned up shard artifacts for %s", submission_id)
    except Exception as e:  # noqa: BLE001 - cleanup is best-effort
        logger.warning(
            "Shard-artifact cleanup failed for %s (%s: %s); leaving scratch",
            submission_id, type(e).__name__, e,
        )


def _flip_row_to_completed(submission_id: str, summary: dict[str, Any]) -> None:
    """Merge ``run_summary.json`` fields into the pending row."""
    updates: dict[str, Any] = {
        "status": "completed",
        "failure_reason": None,
        "cadgenbench_data_revision": _resolve_data_revision(),
        "aggregate_score": summary.get("aggregate_score"),
        "validity_rate": summary.get("validity_rate"),
        "score_by_task_type": summary.get("score_by_task_type"),
        "per_task_scores": summary.get("per_task_scores"),
        "per_fixture_scores": summary.get("per_fixture_scores"),
    }
    _update_row(submission_id, updates)


def _flip_row_to_failed(submission_id: str, reason: str) -> None:
    """Mark the row as ``failed`` with a short reason; scores stay null."""
    _update_row(
        submission_id,
        {"status": "failed", "failure_reason": reason},
    )


# ---------------------------------------------------------------------------
# Boot-time stuck-pending sweep
# ---------------------------------------------------------------------------


def _sweep_stuck_pending() -> None:
    """Flip pending rows older than the threshold to failed.
    A ``pending`` row whose worker died (Space restart, OOM, crash)
    has no one to flip it; without this sweep it stays pending in
    the leaderboard forever. The check is "submitted_at older than
    30 min" - well above the real eval ceiling (~5 min on
    cpu-upgrade), so any genuinely-still-running submission is safe.
    Runs once per process at module-import time inside a daemon
    thread so app boot doesn't block on the Hub read.
    """
    try:
        body = _download_results_jsonl()
    except Exception as e:  # noqa: BLE001 - Hub API surface is broad
        logger.warning(
            "Stuck-pending sweep skipped, Hub fetch failed (%s: %s)",
            type(e).__name__, e,
        )
        return

    cutoff = datetime.now(timezone.utc) - timedelta(
        seconds=STUCK_PENDING_THRESHOLD_SECONDS
    )
    stuck_ids: list[str] = []
    for line in body.splitlines():
        if not line.strip():
            continue
        try:
            row = json.loads(line)
        except json.JSONDecodeError:
            continue
        if row.get("status") != "pending":
            continue
        sid = row.get("submission_id")
        ts_str = row.get("submitted_at")
        if not sid or not ts_str:
            continue
        try:
            ts = datetime.strptime(ts_str, SUBMITTED_AT_FORMAT).replace(
                tzinfo=timezone.utc
            )
        except ValueError:
            logger.warning(
                "Skipping unparseable submitted_at %r on row %s",
                ts_str, sid,
            )
            continue
        if ts < cutoff:
            stuck_ids.append(sid)

    if not stuck_ids:
        logger.info("Stuck-pending sweep: nothing stale")
        return

    logger.warning(
        "Stuck-pending sweep: flipping %d row(s) to failed: %s",
        len(stuck_ids), stuck_ids,
    )
    for sid in stuck_ids:
        try:
            _flip_row_to_failed(sid, STUCK_PENDING_REASON)
        except Exception as e:  # noqa: BLE001 - log + carry on per-row
            logger.exception(
                "Stuck-pending flip failed for %s (%s: %s)",
                sid, type(e).__name__, e,
            )


def _start_boot_sweep() -> None:
    """Spawn the sweep on a daemon thread at module import.
    Setting ``CADGENBENCH_DISABLE_BOOT_SWEEP=1`` opts out (useful
    for unit-test imports that don't want the Hub round-trip).
    """
    if os.getenv(BOOT_SWEEP_ENV) == "1":
        logger.info("Stuck-pending sweep disabled via %s", BOOT_SWEEP_ENV)
        return
    threading.Thread(
        target=_sweep_stuck_pending,
        name="cgb-boot-sweep",
        daemon=True,
    ).start()


_start_boot_sweep()