submit.py

"""Submit-tab handler for the CADGenBench leaderboard Space.

Step 6 (E) chunks 2 + 3: cheap-sync validation pipeline + pending-row
write + zip upload. 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), and returns
immediately. No eval and no worker yet, the row stays pending
forever until later chunks add the background thread.

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.

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.
"""
from __future__ import annotations

import json
import logging
import re
import tempfile
import threading
import zipfile
from datetime import datetime, timezone
from pathlib import Path
from typing import Any

import cadgenbench
from cadgenbench.common.paths import data_inputs_dir
from cadgenbench.common.validity import parse_step
from huggingface_hub import HfApi
from huggingface_hub.errors import EntryNotFoundError

from leaderboard import HF_DATA_REPO, 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"
DATA_REV_SHORT_LEN = 12

# 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) -> str:
    """Validate a submission upload and return a markdown UI message.

    Returns one of:
      - An error string starting with ``**Error:**`` for form-level
        rejects (no zip attached).
      - A rejection string starting with ``**Submission rejected.**``
        for any of the deeper validation gates or Hub-write failures.
      - A success string starting with ``**Queued.**`` carrying the
        minted ``submission_id`` once the pending row + zip are on
        the Hub.
    """
    form_err = _validate_form(zip_file)
    if form_err is not None:
        return form_err

    zip_path = Path(zip_file.name)
    with tempfile.TemporaryDirectory(prefix="cadgenbench-validate-") as tmp:
        unpacked = Path(tmp) / "unpacked"
        unpacked.mkdir()
        try:
            _extract_zip(zip_path, unpacked)
            meta = _load_and_validate_meta(unpacked)
            fixture_names = _validate_fixture_set(unpacked)
            _validate_steps_parseable(unpacked, fixture_names)
        except _ValidationError as e:
            return f"**Submission rejected.** {e}"

    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, fixture_names, blob_url)
        _append_pending_row(row)
    except _HubWriteError as e:
        return f"**Submission rejected.** {e}"

    return (
        f"**Queued.** Submission `{submission_id}` has been accepted and a "
        f"`pending` row added to the leaderboard (submitter: "
        f"`{meta['submitter_name']}`, system: `{meta['submission_name']}`, "
        f"{len(fixture_names)} fixtures). Evaluation will populate the "
        f"score columns once the worker lands in a later chunk."
    )


def _validate_form(zip_file) -> str | None:
    if zip_file is None:
        return "**Error:** 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:
    for name in sorted(fixture_names):
        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


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],
    fixture_names: set[str],  # noqa: ARG001 - kept for future per-fixture pre-fill
    blob_url: str,
) -> 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``; every
    score-shaped field is ``null`` until the worker flips the row.
    """
    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,
    }


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

    Read-modify-write: download the current file (or treat as empty if
    it doesn't exist yet), append one line, re-upload. The lock is
    held only for the duration of this cycle (~1-2s), not for any
    background eval; concurrent submitters serialise here, not on the
    eval pipeline.
    """
    with _HUB_LOCK:
        try:
            existing = _download_results_jsonl()
        except Exception as e:  # noqa: BLE001 - Hub API surface is broad
            logger.exception("Failed to download results.jsonl for append")
            raise _HubWriteError(
                f"Server-side error reading the submissions table "
                f"({type(e).__name__}: {e}). Please try again later."
            ) from e

        line = json.dumps(row, ensure_ascii=False)
        new_body = existing + line + "\n" if existing else line + "\n"

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


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