fix model DL doe 4-th time
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docs/issues/47-model-source-download-visibility.md
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58
docs/issues/47-model-source-download-visibility.md
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# US-047 — Model-source race: visibility, sane timeouts, quiet tracker aborts
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Status: in progress
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Priority: High (follow-up to US-044/US-046; blocks usable LAN downloads)
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## Context
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Reported 2026-07-06 (Windows CPU node, 79.2 GB RAM, `--tracker
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http://192.168.0.179:8080 --model Qwen3.6-35B-A3B`):
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1. Startup prints `(auto-join unavailable: HTTP Error 503)` even though the
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user explicitly named a model. The auto-join query (`/v1/network/assign`)
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never sends the requested model, so a fresh tracker + a caller too small
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for the *recommended* preset 503s (expected per US-046) — but the whole
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auto-join step is pointless when the user already picked a model: the
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`/v1/nodes/assign?model=…` call right after it succeeds (assigned layers
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0–2 with tracker `model_sources`).
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2. The tracker-vs-HuggingFace race then starts, but only HuggingFace shows
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progress (hf tqdm bars). The tracker tar download prints nothing and
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swallows every failure (`except Exception: return None`), so the node
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*appears* to download only from slow HF; the user killed it. Tracker-side
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log showed the tar stream reset mid-`archive.add` — with no way to tell
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whether the client timed out or the user aborted.
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3. `_download_model_source` inherits `peer_timeout` (2.0 s) as its urlopen
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socket timeout. Any 2 s read stall during a multi-GB tar stream silently
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kills the tracker source and leaves HF as the only contender.
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4. Every client abort spams the tracker console with a full
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`BrokenPipeError`/`ConnectionResetError` traceback from `socketserver`.
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## Fix
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1. `startup.py`: skip the network auto-join query entirely when a model was
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explicitly requested (`model` set and not `"stub-model"`); path 3b
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(`/v1/nodes/assign?model=…`) is the authoritative one there.
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2. `downloader.py`: model-source downloads get their own timeout constant
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(30 s socket timeout) instead of the 2 s peer-probe timeout. Peer shard
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downloads keep 2 s — they run sequentially before the race, and a dead
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peer must not hang startup for 30 s; the race is concurrent so a slow
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source costs nothing.
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3. `downloader.py`: progress + failure visibility for the race —
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`_download_model_source` prints received bytes every 512 MB and prints
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the exception when a source fails, so "downloads only from HF" can never
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happen silently again.
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4. Tracker `_handle_model_files_download`: catch
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`BrokenPipeError`/`ConnectionResetError` around the tar stream and log a
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single line instead of a traceback.
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## Acceptance criteria
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- [ ] Node started with an explicit `--model` never queries
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`/v1/network/assign` and never prints `auto-join unavailable`.
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- [ ] During the race, tracker-source progress lines appear alongside HF
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tqdm output; a failing tracker source prints its exception.
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- [ ] A ≥2 s read stall no longer aborts a tracker model-source download
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(30 s socket timeout).
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- [ ] Client disconnect during `/v1/model-files/download` logs one line on
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the tracker, no traceback.
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- [ ] `python -m pytest` passes from repo root.
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@@ -19,6 +19,11 @@ from typing import Any
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_DEFAULT_CACHE = Path.home() / ".cache" / "meshnet" / "shards"
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_PEER_TIMEOUT_SECONDS = 2.0
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# Model-source tar streams are multi-GB; a short socket timeout must not kill
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# them on a transient read stall. Peer probes keep the short timeout because
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# they run sequentially before the race and may hit dead endpoints.
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_MODEL_SOURCE_TIMEOUT_SECONDS = 30.0
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_PROGRESS_INTERVAL_BYTES = 512 * 1024 * 1024
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def compute_shard_checksum(shard_dir: Path) -> str:
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@@ -111,6 +116,8 @@ def _download_model_source(
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source: dict,
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shard_dir: Path,
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timeout: float,
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progress: bool = False,
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label: str = "model-source",
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) -> Path | None:
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url = source.get("url")
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if not isinstance(url, str) or not url:
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@@ -125,16 +132,26 @@ def _download_model_source(
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extract_dir = tmp_root / "extract"
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extract_dir.mkdir()
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try:
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received = 0
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next_report = _PROGRESS_INTERVAL_BYTES
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with urllib.request.urlopen(url, timeout=timeout) as resp, archive_path.open("wb") as out:
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while True:
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chunk = resp.read(1024 * 1024)
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if not chunk:
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break
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out.write(chunk)
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received += len(chunk)
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if progress and received >= next_report:
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print(f" {label}: {received / 1e9:.1f} GB received ...", flush=True)
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next_report += _PROGRESS_INTERVAL_BYTES
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if progress:
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print(f" {label}: transfer complete ({received / 1e9:.2f} GB), extracting ...", flush=True)
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_safe_extract_shard(archive_path, extract_dir)
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shutil.move(str(extract_dir), str(shard_dir))
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return shard_dir
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except Exception:
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except Exception as exc:
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if progress:
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print(f" {label}: download failed: {exc!r}", flush=True)
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return None
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@@ -178,7 +195,9 @@ def _download_from_fastest_source(
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for index, source in enumerate(model_sources):
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label = str(source.get("type") or "model-source")
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candidate = tmp_root / f"source-{index}"
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jobs[pool.submit(_download_model_source, source, candidate, timeout)] = (label, candidate)
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jobs[pool.submit(
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_download_model_source, source, candidate, timeout, progress, label,
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)] = (label, candidate)
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allow_patterns = _allow_patterns_from_sources(model_sources)
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hf_candidate = tmp_root / "huggingface"
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jobs[pool.submit(_download_huggingface_subset, hf_repo, cache_dir, hf_candidate, allow_patterns)] = (
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@@ -189,7 +208,9 @@ def _download_from_fastest_source(
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label, candidate = jobs[future]
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try:
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result = future.result()
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except Exception:
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except Exception as exc:
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if progress:
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print(f" {label}: download failed: {exc!r}", flush=True)
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continue
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if result is None:
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continue
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@@ -324,7 +345,7 @@ def download_shard(
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cache_dir=cache_dir,
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shard_dir=shard_dir,
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progress=progress,
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timeout=peer_timeout,
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timeout=max(peer_timeout, _MODEL_SOURCE_TIMEOUT_SECONDS),
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)
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if raced is not None:
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return raced[1]
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@@ -561,13 +561,19 @@ def run_startup(
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raise ValueError("--shard-start / --shard-end require --model-id")
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# 3a. Auto-join: query tracker for network-wide HF model assignment.
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print("Querying tracker for network assignment...", flush=True)
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assign_qs = urllib.parse.urlencode({"device": device, "vram_mb": assignment_vram_mb, "ram_mb": ram_mb})
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# Skipped when the user explicitly requested a model — the shard-assignment
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# query below (/v1/nodes/assign?model=…) is authoritative there, and a fresh
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# tracker would otherwise print a scary 503 for the model-less auto-join.
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net_assignment: dict = {}
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try:
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net_assignment = _get_json(f"{tracker_url}/v1/network/assign?{assign_qs}")
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except Exception as exc:
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print(f" (auto-join unavailable: {exc})", flush=True)
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if model and model != "stub-model":
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print(f"Model {model!r} requested explicitly — skipping network auto-join.", flush=True)
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else:
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print("Querying tracker for network assignment...", flush=True)
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assign_qs = urllib.parse.urlencode({"device": device, "vram_mb": assignment_vram_mb, "ram_mb": ram_mb})
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try:
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net_assignment = _get_json(f"{tracker_url}/v1/network/assign?{assign_qs}")
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except Exception as exc:
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print(f" (auto-join unavailable: {exc})", flush=True)
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assigned_hf_repo: str | None = net_assignment.get("hf_repo")
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_gap_found: bool = bool(net_assignment.get("gap_found", False))
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@@ -3879,10 +3879,17 @@ class _TrackerHandler(http.server.BaseHTTPRequestHandler):
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self.send_header("Content-Type", "application/x-tar")
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self.send_header("X-Meshnet-Model-Source", "tracker")
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self.end_headers()
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# dereference: HF cache snapshots are symlinks into blobs/ — ship contents.
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with tarfile.open(fileobj=self.wfile, mode="w|", dereference=True) as archive:
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for rel in rel_files:
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archive.add(snapshot_dir / rel, arcname=rel)
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try:
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# dereference: HF cache snapshots are symlinks into blobs/ — ship contents.
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with tarfile.open(fileobj=self.wfile, mode="w|", dereference=True) as archive:
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for rel in rel_files:
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archive.add(snapshot_dir / rel, arcname=rel)
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except (BrokenPipeError, ConnectionResetError):
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print(
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f"model-file download aborted by client "
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f"({self.client_address[0]}, model={resolved_name})",
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flush=True,
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)
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def _handle_network_assign(self, parsed: urllib.parse.ParseResult):
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"""Assign a new node to fill the biggest uncovered shard gap across HF-model nodes.
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