Teknium
1241 lines
50 KiB
Python
1241 lines
50 KiB
Python
"""Local-models dashboard routes — the desktop's window into the managed
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llama.cpp runtime.
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Every payload carries plain-language, pre-formatted facts the UI can show
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verbatim (what will this model do ON THIS MACHINE, how big is the download,
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what is the runtime doing right now), never raw internals.
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Long jobs (runtime install, model download) follow the repo's job pattern:
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start-POST -> {job_id} -> GET poll with byte progress. Downloads are
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byte-size checked against what the server declared (no hash verification by
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design); a short download deletes the file and reports it plainly.
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"""
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from __future__ import annotations
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import asyncio
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import json
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import logging
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import os
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import re
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import shutil
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import subprocess
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import threading
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import time
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import urllib.parse
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import urllib.request
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import uuid
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from pathlib import Path
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from typing import Any, Callable, Dict, Optional
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from starlette.concurrency import run_in_threadpool
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from hermes_cli import config as config_mod, web_deps
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from hermes_cli.local_runtime import (
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binaries,
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bootstrap,
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catalog,
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context_policy,
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estimator,
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growth,
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hardware,
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hf_browse,
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load_progress,
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presets,
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supervisor,
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)
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from hermes_cli.local_runtime.endpoint import _state_endpoint
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logger = logging.getLogger(__name__)
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router = APIRouter()
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_GIB = 1 << 30
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_JOBS: Dict[str, Dict[str, Any]] = {}
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_JOBS_LOCK = threading.Lock()
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_LLAMACPP_PROVIDERS = ("llamacpp", "llama.cpp", "llama-cpp")
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def _human_gb(n: int | float) -> str:
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return f"{n / _GIB:.1f} GB"
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def _job(kind: str, target: str, model_id: str | None = None) -> Dict[str, Any]:
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job = {
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"job_id": uuid.uuid4().hex[:12],
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"kind": kind, # "runtime-install" | "model-download" | ...
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"target": target,
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"model_id": model_id, # catalog id for downloads; None otherwise
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"status": "running", # running | done | error
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"phase": "starting", # human-readable step name
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"detail": "",
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"total_bytes": None,
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"done_bytes": 0,
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"started_at": time.time(),
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"error": None,
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}
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with _JOBS_LOCK:
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_JOBS[job["job_id"]] = job
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return job
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def _job_view(job: Dict[str, Any]) -> Dict[str, Any]:
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out = dict(job)
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if out["total_bytes"]:
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out["percent"] = min(100, round(out["done_bytes"] / out["total_bytes"] * 100))
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return out
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def _finish(job: Dict[str, Any], detail: str) -> None:
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job["phase"] = "done"
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job["status"] = "done"
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job["detail"] = detail
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def _spawn_job(job: Dict[str, Any], name: str, body: Callable[[], None], *,
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fail_msg: str | None = None,
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on_exit: Callable[[], None] | None = None) -> None:
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"""Run ``body`` on a daemon thread; any exception marks the job errored
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(optionally warning ``fail_msg`` with the exception). ``on_exit`` always
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runs last (lock release)."""
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def _run():
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try:
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body()
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except Exception as exc: # noqa: BLE001
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if fail_msg:
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logger.warning(fail_msg, exc)
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job["status"] = "error"
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job["error"] = str(exc)
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finally:
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if on_exit is not None:
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on_exit()
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threading.Thread(target=_run, daemon=True, name=name).start()
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def _refresh_runtime(skip_msg: str) -> None:
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"""Bounce a running router so it rescans the models dir; the router only
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scans at spawn, so a new/deleted file is invisible until then. Never
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raises — the file operation already succeeded."""
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try:
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bootstrap.refresh_local_runtime()
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except Exception: # noqa: BLE001
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logger.debug(skip_msg, exc_info=True)
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def _router_request(endpoint: Dict[str, Any], path: str, *, timeout: float,
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payload: dict | None = None) -> Any:
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"""Call the local router (base_url minus ``/v1``) with its bearer key.
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GET (no payload) returns the parsed JSON body; POST returns None."""
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headers = {"Authorization": f"Bearer {endpoint.get('api_key', '')}"}
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data = None
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if payload is not None:
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headers["Content-Type"] = "application/json"
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data = json.dumps(payload).encode()
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req = urllib.request.Request(
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endpoint["base_url"].rsplit("/v1", 1)[0] + path, data=data, headers=headers,
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method="POST" if payload is not None else None)
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with urllib.request.urlopen(req, timeout=timeout) as r:
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return None if payload is not None else json.loads(r.read())
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# ── fast download: ranged parallel streams ───────────────────
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# One TCP stream to a CDN rarely fills a fast line; 8 ranged connections
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# writing into a preallocated file saturate consumer gigabit.
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_DOWNLOAD_CONNECTIONS = 8
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_CHUNK = 4 << 20
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def _probe_range_support(url: str) -> int:
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"""Total size when the server honors Range requests, else 0.
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A 401/403 from the CDN means the repo is gated or the catalog names a
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wrong repo — raise with a plain-language message, not a bare status."""
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req = urllib.request.Request(url, headers={"Range": "bytes=0-0"})
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try:
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with urllib.request.urlopen(req, timeout=60) as r:
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if r.status == 206:
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content_range = r.headers.get("Content-Range", "")
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if "/" in content_range:
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return int(content_range.rsplit("/", 1)[1])
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except urllib.error.HTTPError as exc:
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if exc.code in (401, 403):
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raise RuntimeError(
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"The model host refused the download (gated or moved). "
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"This is a catalog problem, not yours — please report it.") from exc
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raise
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except Exception: # noqa: BLE001
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pass
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return 0
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def _model_id_for(gguf: Path) -> str:
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"""Variant model id for a staged file (strips split-part suffixes)."""
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return re.sub(r"-\d{5}-of-\d{5}$", "", gguf.stem)
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def _variant_files_on_disk(model_id: str) -> "list[Path]":
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"""Every local file belonging to a staged model: all split parts plus
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its catalog-declared assets (mmproj/draft) when present."""
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files = [p for p in _models_dir().glob("*.gguf") if _model_id_for(p) == model_id]
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hit = catalog.find_entry_for_model(model_id)
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if hit is not None:
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for asset in (hit[0].mmproj, hit[0].draft):
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if asset is not None and (bootstrap.assets_dir() / asset.local_name).exists():
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files.append(bootstrap.assets_dir() / asset.local_name)
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return files
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def download_file(url: str, dest: Path, job: Dict[str, Any],
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*,
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base_done: int = 0, keep_totals: bool = False) -> None:
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"""Download url -> dest with byte progress on ``job``.
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Ranged-parallel when the server supports it, single-stream fallback
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otherwise. No integrity check against the CATALOG by design: catalog
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sizes may lag an upstream re-upload, and a newer file must download
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fine. Completeness is checked only against what the SERVER declared for
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this transfer (range-probe total / Content-Length), so a dropped
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connection still errors instead of staging a truncated file. Never
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leaves a .part behind.
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Multi-file variants: ``base_done`` offsets the progress so this file's
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bytes accumulate onto the files before it, and ``keep_totals=True``
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stops the per-file size from overwriting the variant's total.
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"""
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tmp = dest.with_suffix(".part")
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dest.parent.mkdir(parents=True, exist_ok=True)
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file_done = [0]
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progress_lock = threading.Lock()
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def bump(n: int) -> None:
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with progress_lock:
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file_done[0] += n
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job["done_bytes"] = base_done + file_done[0]
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def pump(r, f) -> None:
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while True:
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chunk = r.read(_CHUNK)
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if not chunk:
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break
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f.write(chunk)
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bump(len(chunk))
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try:
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# The probe and the preallocation both take real seconds on a 20+ GB
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# file — narrate them, or the pane shows a dead '— of X GB'.
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job["detail"] = "Connecting"
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total = _probe_range_support(url)
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if total:
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if not keep_totals:
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job["total_bytes"] = total
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# Preallocate so each worker writes at its own offset.
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job["detail"] = f"Reserving {_human_gb(total)} of disk space"
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with open(tmp, "wb") as f:
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f.truncate(total)
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job["detail"] = ""
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errors: list[Exception] = []
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bounds = [(i * total // _DOWNLOAD_CONNECTIONS,
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(i + 1) * total // _DOWNLOAD_CONNECTIONS - 1)
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for i in range(_DOWNLOAD_CONNECTIONS)]
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def fetch_range(start: int, end: int) -> None:
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try:
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req = urllib.request.Request(
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url, headers={"Range": f"bytes={start}-{end}"})
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with urllib.request.urlopen(req, timeout=120) as r, \
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open(tmp, "r+b") as f:
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f.seek(start)
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pump(r, f)
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except Exception as exc: # noqa: BLE001
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errors.append(exc)
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threads = [threading.Thread(target=fetch_range, args=b, daemon=True,
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name=f"lm-dl-{i}")
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for i, b in enumerate(bounds)]
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for t in threads:
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t.start()
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for t in threads:
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t.join()
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if errors:
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raise errors[0]
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if file_done[0] != total:
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raise RuntimeError(
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f"download incomplete ({file_done[0]} of {total} bytes)")
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else:
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# No range support: single stream. Completeness is judged by the
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# server's own Content-Length when it sent one — never the catalog.
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with urllib.request.urlopen(url, timeout=120) as r, open(tmp, "wb") as f:
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length = int(r.headers.get("Content-Length") or 0)
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if length and not keep_totals:
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job["total_bytes"] = length
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pump(r, f)
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if length and file_done[0] != length:
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raise RuntimeError(
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f"Download ended at {file_done[0]:,} bytes but the server "
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f"said {length:,} — connection dropped? Removed; try again")
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shutil.move(str(tmp), str(dest))
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except Exception:
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tmp.unlink(missing_ok=True)
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raise
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def _models_dir() -> Path:
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return bootstrap.models_dir()
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def _hf_url(repo: str, path: str) -> str:
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return f"https://huggingface.co/{repo}/resolve/main/{path}"
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def _download_plan(entry, variant) -> list:
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"""Everything a variant needs: split parts + mmproj/draft assets, as
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(url, dest, bytes) tuples."""
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plan = [(_hf_url(entry.repo, a.path), _models_dir() / a.local_name, a.size_bytes)
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for a in variant.files]
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plan += [(_hf_url(entry.repo, a.path), bootstrap.assets_dir() / a.local_name, a.size_bytes)
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for a in (entry.mmproj, entry.draft) if a is not None]
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return plan
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def _run_download_plan(job: Dict[str, Any], plan: list, label: str) -> None:
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"""Download every missing file in ``plan``; already-present files count
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toward progress without a transfer."""
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total = sum(p[2] for p in plan)
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job["phase"] = "downloading"
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job["detail"] = f"{label} — {_human_gb(total)}"
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done_before = 0
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for url, dest, size in plan:
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if not dest.exists():
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download_file(url, dest, job, base_done=done_before, keep_totals=True)
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job["phase"] = "downloading"
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done_before += size
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job["done_bytes"] = done_before
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def _engine_too_old(min_engine: str) -> bool:
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"""True when the installed llama.cpp predates a model's requirement.
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Tags are release numbers (b10362); no engine installed compares as
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too old only when the model states a requirement."""
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if not min_engine:
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return False
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try:
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tags = binaries.installed_tags() or [binaries.default_tag()]
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newest = max(int(t.lstrip("b")) for t in tags if t.lstrip("b").isdigit())
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return newest < int(min_engine.lstrip("b"))
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except Exception: # noqa: BLE001
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return False
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def _load_config() -> dict:
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try:
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return config_mod.load_config()
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except Exception: # noqa: BLE001
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return {}
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def _runtime_section() -> dict:
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return (_load_config() or {}).get("local_runtime") or {}
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def _set_runtime_enabled(enabled: bool) -> dict:
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"""Persist ``local_runtime.enabled`` and return the config written."""
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config = config_mod.load_config()
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config.setdefault("local_runtime", {})["enabled"] = enabled
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config_mod.save_config(config)
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return config
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def _resolve_backend(section: dict, requested: str | None = None) -> str:
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backend = requested or section.get("backend", "auto")
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return binaries.select_backend(bootstrap._detect_gpu_vendor()) if backend == "auto" else backend
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def _eligible_entries():
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"""Catalog entries this engine can activate today (engine-gated ones
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can't be the recommendation either)."""
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return tuple(e for e in catalog.CATALOG if not _engine_too_old(e.min_engine))
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def _ensure_server(job: Dict[str, Any], config: dict, model_id: str, *,
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fail_detail: str, skip_msg: str) -> None:
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"""Start the local server if needed and self-heal a stale router: the
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model list is spawn-only, so a server started before ``model_id``
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finished downloading can't serve it — bounce it when it doesn't know
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the model."""
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job["phase"] = "starting-server"
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job["detail"] = "Starting the local server"
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sup = bootstrap.ensure_local_runtime(config, force=True)
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if sup is None and _state_endpoint() is None:
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raise RuntimeError(fail_detail)
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if sup is not None:
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try:
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if model_id not in sup.models():
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job["detail"] = "Refreshing the local server"
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bootstrap.refresh_local_runtime()
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except Exception: # noqa: BLE001
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logger.debug(skip_msg, exc_info=True)
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def _assign_default(job: Dict[str, Any], model_id: str) -> None:
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"""Make ``model_id`` the main model through the same machinery as
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/api/model/set (late-bound so tests can stub web_deps.late)."""
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job["phase"] = "setting-default"
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job["detail"] = "Making it your default"
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web_deps.late("_apply_model_assignment_sync")("main", "llamacpp", model_id, "", "", "")
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# ── status: the one call the pane opens with ─────────────────
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def _loaded_models(running: Dict[str, Any]) -> "tuple[Dict[str, str], Dict[str, Any]]":
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"""Which staged models are resident right now, plus how each is placed.
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Placement is the granted window from the child itself and the plan's
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spill facts from the preset decision — the difference between 'fast'
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and 'why is my CPU busy', so it must be inspectable, not inferred."""
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data = _router_request(running, "/models", timeout=3)
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# Everything resident or becoming resident: 'loading' renders as its own
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# state in the pane (a 20-GB load in flight is the most important thing
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# the pane can show).
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loaded = {
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m["id"]: m.get("status", {}).get("value", "unknown")
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for m in data.get("data", [])
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if m.get("status", {}).get("value") in ("loaded", "ready", "loading")
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}
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placement: Dict[str, Any] = {}
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decisions = presets.read_preset_decisions()
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for model_id, state in loaded.items():
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facts: Dict[str, Any] = {}
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plan = decisions.get(model_id)
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if plan is not None:
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facts["window"] = plan.window
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facts["window_label"] = f"{plan.window // 1024}K"
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facts["spilled"] = plan.spilled
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if state in ("loaded", "ready"):
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try:
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props = _router_request(running, f"/props?model={model_id}", timeout=3)
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n_ctx = props.get("default_generation_settings", {}).get("n_ctx")
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if n_ctx:
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facts["granted_window"] = int(n_ctx)
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facts["granted_window_label"] = f"{int(n_ctx) // 1024}K"
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except Exception: # noqa: BLE001
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pass
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if facts:
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placement[model_id] = facts
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return loaded, placement
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@router.get("/api/local-models/status")
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def local_models_status():
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"""Cheap, immediate, never blocks on probes: config state + installed
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runtime + staged models + supervisor state. GPU facts come from
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/api/local-models/hardware (slower, polled).
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Sync def on purpose: blocking urlopen/scans run in FastAPI's threadpool
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instead of stalling the event loop."""
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section = _runtime_section()
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configured_tag = section.get("tag") or binaries.default_tag()
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have = binaries.installed_tags()
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# The tag actually serving (boot ladder: configured if installed, else
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# newest installed).
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tag = configured_tag if configured_tag in have else (have[0] if have else configured_tag)
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# A pending engine update exists when the user runs the local engine
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# (enabled + something installed) and the configured tag — pinned or the
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# Hermes-release default — is newer than anything on disk. The download
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# is a button click, never automatic.
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update_available = bool(
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section.get("enabled") and have and configured_tag not in have)
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runtime_installed = False
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runtime_backend = None
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root = binaries.runtimes_root() / tag
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if root.exists():
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for backend_dir in sorted(p for p in root.iterdir() if p.is_dir()):
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try:
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binaries.server_binary(backend_dir)
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runtime_installed = True
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runtime_backend = backend_dir.name
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break
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except Exception: # noqa: BLE001
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continue
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staged = []
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mdir = _models_dir()
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if mdir.exists():
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for gguf in bootstrap.staged_models():
|
|
model_id = _model_id_for(gguf)
|
|
# Split models: report the whole variant's bytes, not one part's.
|
|
hit = catalog.find_entry_for_model(model_id)
|
|
size = hit[1].size_bytes if hit is not None else gguf.stat().st_size
|
|
staged.append({"id": model_id, "size_bytes": size, "size_label": _human_gb(size)})
|
|
|
|
running = _state_endpoint()
|
|
|
|
# Resident models from the live router; {} when down. Feeds the pane's
|
|
# Loaded pills and eject buttons.
|
|
loaded: Dict[str, str] = {}
|
|
placement: Dict[str, Any] = {}
|
|
if running is not None:
|
|
try:
|
|
loaded, placement = _loaded_models(running)
|
|
except Exception as exc: # noqa: BLE001
|
|
# Never silent: an empty dict here renders as 'Not in memory'
|
|
# on a machine whose VRAM is visibly full.
|
|
logger.warning("loaded-models read failed: %r", exc)
|
|
loaded = {}
|
|
|
|
# The active main model, when it is one of ours (config authority: the
|
|
# same model.provider + model.default that /api/model/set writes).
|
|
active_model_id = None
|
|
try:
|
|
model_section = (_load_config() or {}).get("model") or {}
|
|
if str(model_section.get("provider", "")).strip().lower() in _LLAMACPP_PROVIDERS:
|
|
active_model_id = str(
|
|
model_section.get("default") or model_section.get("name") or ""
|
|
).strip() or None
|
|
except Exception: # noqa: BLE001
|
|
pass
|
|
|
|
return {
|
|
"enabled": bool(section.get("enabled")),
|
|
"tag": tag,
|
|
"configured_tag": configured_tag,
|
|
"update_available": update_available,
|
|
"runtime_installed": runtime_installed,
|
|
"runtime_backend": runtime_backend,
|
|
"server_running": running is not None,
|
|
"server_base_url": (running or {}).get("base_url"),
|
|
"active_model_id": active_model_id,
|
|
"loaded_models": loaded,
|
|
# Live load progress per model (SSE-fed): {model_id: {stage, value,
|
|
# percent}}. The chat's loading bar and the picker rows poll this.
|
|
"loading": _loading_progress(),
|
|
"placement": placement,
|
|
"models": staged,
|
|
"models_dir": str(mdir),
|
|
}
|
|
|
|
|
|
def _loading_progress() -> Dict[str, Any]:
|
|
try:
|
|
|
|
return load_progress.get_loading_progress()
|
|
except Exception: # noqa: BLE001 — progress is garnish, never a 500
|
|
return {}
|
|
|
|
|
|
# ── hardware: what this machine can do ───────────────────────
|
|
|
|
|
|
@router.get("/api/local-models/hardware")
|
|
def local_models_hardware():
|
|
"""The budget as plain facts. Polled by the pane and the statusbar
|
|
resource item (throttled client-side). Sync def on purpose: shells out
|
|
to nvidia-smi and probes budgets — threadpool, not loop."""
|
|
|
|
budget = hardware.probe_budget()
|
|
ram_total, ram_avail = hardware._ram_bytes()
|
|
out = {
|
|
"uma": budget.uma,
|
|
"vram_total_bytes": budget.total_device_bytes,
|
|
"vram_usable_bytes": budget.usable_vram_bytes,
|
|
"ram_total_bytes": ram_total,
|
|
"ram_available_bytes": ram_avail,
|
|
"vram_label": _human_gb(budget.total_device_bytes),
|
|
"gpu_name": None,
|
|
"gpu_util_percent": None,
|
|
"vram_used_bytes": None,
|
|
}
|
|
# GPU identity + live utilization (NVIDIA; other vendors degrade to None
|
|
# and the UI hides those readouts).
|
|
try:
|
|
|
|
smi_exe = hardware._nvidia_smi_path()
|
|
smi = subprocess.run(
|
|
[smi_exe, "--query-gpu=name,utilization.gpu,memory.used",
|
|
"--format=csv,noheader,nounits"],
|
|
capture_output=True, text=True, timeout=5) if smi_exe else None
|
|
if smi and smi.returncode == 0 and smi.stdout.strip():
|
|
name, util, used_mib = (x.strip() for x in smi.stdout.strip().splitlines()[0].split(","))
|
|
out["gpu_name"] = name
|
|
out["gpu_util_percent"] = int(util)
|
|
out["vram_used_bytes"] = int(used_mib) << 20
|
|
except Exception: # noqa: BLE001
|
|
pass
|
|
return out
|
|
|
|
|
|
# ── catalog: priced for THIS machine before download ─────────
|
|
|
|
_QUANT_REASONS = {
|
|
"best-large-window": ("Recommended build ({quant}) — the quant class this "
|
|
"engine is optimized for; runs fully on your GPU with a "
|
|
"large context window"),
|
|
"best-fits": ("Recommended build ({quant}) — the quant class this "
|
|
"engine is optimized for; runs fully on your GPU"),
|
|
}
|
|
_QUANT_REASON_COMPACT = ("Compact build sized for this machine ({quant}) — "
|
|
"larger than GPU memory, runs slower")
|
|
|
|
|
|
@router.get("/api/local-models/catalog")
|
|
def local_models_catalog():
|
|
"""Every entry answers the user's three questions up front: how big is
|
|
the download, will it fit, and what context/speed shape will I get —
|
|
from the catalog's measured numbers + this machine's budget. The row
|
|
advertises the BEST build for this machine (highest quality that runs
|
|
fully on the GPU at the 64K floor; else the smallest that works, spilled
|
|
and priced). No entry is hidden; unaffordable models show WHY. Sync def
|
|
on purpose: probe_budget + catalog I/O block — threadpool, not loop."""
|
|
|
|
# Serve the catalog already in memory; a TTL-gated background fetch lands
|
|
# new entries for the next call (day-0 models without an app release).
|
|
catalog.refresh_catalog_soon()
|
|
|
|
# Planning budget: price against machine capacity, not live-free VRAM —
|
|
# a loaded model must not make every row unaffordable.
|
|
budget = hardware.probe_budget(planning=True)
|
|
# The default pick for THIS machine: quality-ranked, fit- and speed-gated.
|
|
# The reason key ships with the row so the Recommended badge's tooltip is
|
|
# the branch that actually fired, not a re-derivation that can drift.
|
|
picked = catalog.recommended_entry(budget, _eligible_entries())
|
|
recommended = picked[0].id if picked is not None else None
|
|
recommended_reason = picked[1] if picked is not None else None
|
|
# Completeness-checked staging (split parts all present) — same answer the
|
|
# picker and router see, so a mid-download model never reads as downloaded.
|
|
staged_ids = set(bootstrap.staged_model_ids())
|
|
entries = []
|
|
for entry in catalog.CATALOG:
|
|
choice = catalog.select_variant(entry, budget)
|
|
# Any variant of this family on disk counts as downloaded.
|
|
downloaded_variant = next(
|
|
(v for v in entry.variants if v.model_id in staged_ids), None)
|
|
row: Dict[str, Any] = {
|
|
"id": entry.id,
|
|
"display_name": entry.display_name,
|
|
"description": entry.description,
|
|
"native_context": entry.n_ctx_train,
|
|
"native_context_label": f"{entry.n_ctx_train // 1024}K",
|
|
"recommended": entry.id == recommended,
|
|
"recommended_reason": recommended_reason if entry.id == recommended else None,
|
|
"downloaded": downloaded_variant is not None,
|
|
"downloaded_model_id": downloaded_variant.model_id if downloaded_variant else None,
|
|
"downloaded_quant": downloaded_variant.quant if downloaded_variant else None,
|
|
"mtp": entry.mtp,
|
|
"vision": entry.mmproj is not None,
|
|
# Day-0 architectures need the llama.cpp release where their support
|
|
# landed. True gates download/activate in the pane until the engine
|
|
# updates; the row still renders (visible + explained beats hidden).
|
|
"needs_engine": _engine_too_old(entry.min_engine),
|
|
"min_engine": entry.min_engine or None,
|
|
}
|
|
if choice is None:
|
|
smallest = min(entry.variants, key=lambda v: v.size_bytes)
|
|
smallest_total = entry.download_bytes(smallest)
|
|
row.update({
|
|
"fits": False,
|
|
"size_bytes": smallest_total,
|
|
"size_label": _human_gb(smallest_total),
|
|
"fit_summary": "Needs more memory than this machine has",
|
|
"fit_detail": (f"even the most compact build ({smallest.quant}, "
|
|
f"{_human_gb(smallest_total)}) exceeds GPU + system memory"),
|
|
})
|
|
entries.append(row)
|
|
continue
|
|
|
|
variant = choice.variant
|
|
# Same overhead the launch decision prices (runtime buffers + vision
|
|
# projector + microbatch/MTP logits): the row must advertise the window
|
|
# the model will actually get, not a paper number.
|
|
overhead = (context_policy.RUNTIME_OVERHEAD_BYTES
|
|
+ (entry.mmproj.size_bytes if entry.mmproj else 0)
|
|
+ context_policy.ub_logits_bytes(entry.n_vocab, mtp_capable=entry.mtp))
|
|
decision = context_policy.initial_window(entry.profile(variant), budget, overhead_bytes=overhead)
|
|
download_total = entry.download_bytes(variant)
|
|
row.update({
|
|
"fits": True,
|
|
"model_id": variant.model_id,
|
|
"quant": variant.quant,
|
|
"quant_validated": variant.validated,
|
|
"size_bytes": download_total,
|
|
"size_label": _human_gb(download_total),
|
|
"variant_count": len(entry.variants),
|
|
"quant_reason": _QUANT_REASONS.get(
|
|
choice.reason_key, _QUANT_REASON_COMPACT).format(quant=variant.quant),
|
|
})
|
|
if not isinstance(decision, estimator.PhysicsRefusal):
|
|
row["start_window"] = decision.window
|
|
row["start_window_label"] = f"{decision.window // 1024}K"
|
|
row["spilled"] = decision.spilled
|
|
if decision.window >= entry.n_ctx_train:
|
|
shape = f"runs at its full {row['native_context_label']} context"
|
|
else:
|
|
shape = (f"starts at {row['start_window_label']} and grows toward "
|
|
f"{row['native_context_label']} as you use it")
|
|
if decision.spilled:
|
|
shape += " (larger than your GPU memory — runs slower)"
|
|
row["fit_summary"] = shape
|
|
else:
|
|
row["fit_summary"] = row["quant_reason"]
|
|
entries.append(row)
|
|
return {"models": entries}
|
|
|
|
|
|
# ── runtime install (job) ────────────────────────────────────
|
|
|
|
|
|
class RuntimeInstallBody(BaseModel):
|
|
backend: Optional[str] = None # None/auto -> detect
|
|
|
|
|
|
def _runtime_progress_hook(job: Dict[str, Any]):
|
|
"""Adapter: ensure_runtime_installed's progress stream -> job fields.
|
|
|
|
Throttled to ~4 updates/s. Byte counters are CUMULATIVE across the plan:
|
|
a multi-asset engine (CUDA zip + cudart zip) reads as one growing
|
|
download, not a bar that restarts per asset; the total grows as each
|
|
asset's size becomes known. Unpack/verify keep the download's counters —
|
|
a bar bouncing back to zero after the bytes finished reads as failure."""
|
|
state = {"last": 0.0, "banked": 0, "asset": None, "asset_total": 0}
|
|
|
|
def hook(stage: str, done: int, total: int, label: str) -> None:
|
|
now = time.monotonic()
|
|
if now - state["last"] < 0.25 and done < total:
|
|
return
|
|
state["last"] = now
|
|
suffix = f" ({label})" if label else ""
|
|
if stage == "download":
|
|
if label != state["asset"]:
|
|
# Previous asset finished: bank its bytes so the counters keep
|
|
# climbing instead of restarting for the next asset.
|
|
state["banked"] += state["asset_total"]
|
|
state["asset"] = label
|
|
state["asset_total"] = total or done
|
|
plan_done = state["banked"] + done
|
|
plan_total = state["banked"] + (total or 0)
|
|
job["phase"] = "downloading-runtime"
|
|
job["detail"] = f"Downloading the local engine{suffix} — {_human_gb(plan_done)}"
|
|
if total:
|
|
job["detail"] += f" of {_human_gb(plan_total)}"
|
|
job["done_bytes"] = plan_done
|
|
job["total_bytes"] = plan_total or None
|
|
elif stage == "extract":
|
|
job["phase"] = "unpacking-runtime"
|
|
pct = f" — {min(100, round(done / total * 100))}%" if total else ""
|
|
job["detail"] = f"Unpacking the engine{suffix}{pct}"
|
|
else: # verify
|
|
job["phase"] = "verifying-runtime"
|
|
job["detail"] = f"Verifying the engine{suffix}"
|
|
|
|
return hook
|
|
|
|
|
|
@router.post("/api/local-models/runtime/install")
|
|
async def local_models_runtime_install(body: RuntimeInstallBody):
|
|
|
|
section = _runtime_section()
|
|
tag = section.get("tag") or binaries.default_tag()
|
|
backend = _resolve_backend(section, body.backend)
|
|
# Resolve first so an impossible combination fails the POST, not the job.
|
|
try:
|
|
plan = binaries.resolve_assets(tag, backend)
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=400, detail=str(exc))
|
|
|
|
job = _job("runtime-install", f"llama.cpp {tag} ({backend})")
|
|
|
|
def _run():
|
|
|
|
previous = binaries.installed_tags()
|
|
job["phase"] = "downloading"
|
|
job["detail"] = f"Fetching {len(plan.assets)} package(s) for {backend}"
|
|
binaries.ensure_runtime_installed(tag, backend, progress=_runtime_progress_hook(job))
|
|
|
|
# Engine update path: a server already running on an older tag moves
|
|
# to the new one now — the click was the consent. Fresh installs (no
|
|
# server) skip this; Use/boot handles their start.
|
|
restarted = False
|
|
try:
|
|
|
|
if bootstrap.get_supervisor() is not None and previous and tag not in previous:
|
|
job["phase"] = "restarting"
|
|
job["detail"] = "Switching the running server to the new build"
|
|
bootstrap.shutdown_local_runtime()
|
|
bootstrap.ensure_local_runtime(_load_config(), force=True)
|
|
restarted = True
|
|
except Exception as exc: # noqa: BLE001
|
|
# The new build is installed either way; the next boot serves it.
|
|
logger.warning("post-update restart skipped: %s", exc)
|
|
|
|
# N-1 retention, only after the new tag verified: keep it and the
|
|
# newest previous build as the rollback pin target.
|
|
try:
|
|
binaries.prune_old_tags([tag] + [t for t in previous if t != tag][:1])
|
|
except Exception as exc: # noqa: BLE001
|
|
logger.warning("runtime prune skipped: %s", exc)
|
|
|
|
_finish(job, f"llama.cpp {tag} ready ({backend})"
|
|
+ (" — server restarted on the new build" if restarted else ""))
|
|
|
|
_spawn_job(job, "lr-runtime-install", _run, fail_msg="runtime install failed: %s")
|
|
return {"job_id": job["job_id"], "backend": backend, "tag": tag}
|
|
|
|
|
|
# ── model download (job with byte progress) ──────────────────
|
|
|
|
|
|
class ModelDownloadBody(BaseModel):
|
|
model_id: str
|
|
|
|
|
|
@router.post("/api/local-models/download")
|
|
async def local_models_download(body: ModelDownloadBody):
|
|
"""Accepts either a family id (downloads this machine's selected
|
|
variant) or an exact variant model_id."""
|
|
|
|
entry = catalog.catalog_by_id().get(body.model_id)
|
|
variant = None
|
|
if entry is not None:
|
|
if _engine_too_old(entry.min_engine):
|
|
raise HTTPException(
|
|
status_code=409,
|
|
detail=(f"{entry.display_name} needs llama.cpp {entry.min_engine} "
|
|
f"or newer — update the engine first"))
|
|
# Same planning budget as the catalog — the user downloads exactly
|
|
# the build the row advertised.
|
|
choice = catalog.select_variant(entry, hardware.probe_budget(planning=True))
|
|
if choice is None:
|
|
raise HTTPException(status_code=409,
|
|
detail=f"no variant of {entry.id} fits this machine")
|
|
variant = choice.variant
|
|
else:
|
|
hit = catalog.find_entry_for_model(body.model_id)
|
|
if hit is not None:
|
|
entry, variant = hit
|
|
if entry is None or variant is None:
|
|
raise HTTPException(status_code=404, detail=f"unknown model {body.model_id}")
|
|
|
|
if variant.model_id in bootstrap.staged_model_ids():
|
|
return {"job_id": None, "already_downloaded": True, "model_id": variant.model_id}
|
|
|
|
plan = _download_plan(entry, variant)
|
|
job = _job("model-download", f"{entry.display_name} ({variant.quant})",
|
|
model_id=entry.id)
|
|
job["total_bytes"] = sum(p[2] for p in plan)
|
|
|
|
def _run():
|
|
_run_download_plan(job, plan, entry.display_name)
|
|
_finish(job, f"{entry.display_name} ready")
|
|
_refresh_runtime("post-download runtime refresh skipped")
|
|
|
|
_spawn_job(job, "lr-model-download", _run, fail_msg="model download failed: %s")
|
|
return {"job_id": job["job_id"], "model_id": variant.model_id}
|
|
|
|
|
|
@router.delete("/api/local-models/models/{model_id}")
|
|
async def local_models_delete(model_id: str):
|
|
"""Remove a staged model: every split part plus its private assets, then
|
|
bounce the router off the request thread (deleting the active file
|
|
mid-serve is exactly the stale state the refresh exists for)."""
|
|
files = _variant_files_on_disk(model_id)
|
|
if not files:
|
|
raise HTTPException(status_code=404, detail="model not found")
|
|
for path in files:
|
|
path.unlink(missing_ok=True)
|
|
# Growth state dies with the model: a re-download starts back at its
|
|
# zero-spill window instead of inheriting a stale grown one.
|
|
try:
|
|
|
|
growth.clear_window_override(model_id)
|
|
except Exception: # noqa: BLE001
|
|
logger.debug("window-override clear skipped", exc_info=True)
|
|
|
|
threading.Thread(target=_refresh_runtime, args=("post-delete runtime refresh skipped",),
|
|
daemon=True, name="lr-post-delete").start()
|
|
return {"ok": True}
|
|
|
|
|
|
# ── server lifecycle: turn the engine on/off ─────────────────
|
|
|
|
|
|
class ServerActionBody(BaseModel):
|
|
action: str # "stop" | "start"
|
|
|
|
|
|
# ── quickstart: one click from nothing to a working default ──
|
|
|
|
|
|
class QuickstartBody(BaseModel):
|
|
model_id: str | None = None # default: the catalog's recommended entry
|
|
|
|
|
|
# One quickstart at a time: the job sequences installs, downloads, a
|
|
# server bounce, and a config write — two racing runs would interleave
|
|
# all four. Held for the job's lifetime, released in the worker.
|
|
_QUICKSTART_LOCK = threading.Lock()
|
|
|
|
|
|
@router.post("/api/local-models/quickstart")
|
|
async def local_models_quickstart(body: QuickstartBody):
|
|
"""The dummy-proof path: one job that installs the runtime (if missing),
|
|
downloads this machine's build of the recommended model (if missing),
|
|
and makes it the default for new chats. Each leg is the same code the
|
|
individual routes run — this route only sequences them, so 'Configure'
|
|
and quickstart can never disagree about what gets installed.
|
|
|
|
Preflight rejects (no servable entry, engine too old) fail the POST
|
|
synchronously so the button can explain itself; everything slow runs in
|
|
the job with the usual phase/byte progress.
|
|
"""
|
|
|
|
# Resolve the target entry: explicit id, else this machine's
|
|
# recommendation, else the first catalog entry this machine can serve.
|
|
budget = hardware.probe_budget(planning=True)
|
|
if body.model_id:
|
|
entry = catalog.catalog_by_id().get(body.model_id)
|
|
if entry is None:
|
|
raise HTTPException(status_code=404,
|
|
detail=f"unknown model {body.model_id}")
|
|
candidates = [entry]
|
|
else:
|
|
picked = catalog.recommended_entry(budget, _eligible_entries())
|
|
best = picked[0] if picked is not None else None
|
|
candidates = ([best] if best is not None else []) + [
|
|
e for e in catalog.CATALOG if best is None or e.id != best.id]
|
|
chosen = None
|
|
for candidate in candidates:
|
|
choice = catalog.select_variant(candidate, budget)
|
|
if choice is not None and not _engine_too_old(candidate.min_engine):
|
|
chosen = (candidate, choice.variant)
|
|
break
|
|
if chosen is None:
|
|
raise HTTPException(
|
|
status_code=409,
|
|
detail="no catalog model fits this machine — open Local Models "
|
|
"to browse for a smaller build")
|
|
entry, variant = chosen
|
|
|
|
section = _runtime_section()
|
|
tag = section.get("tag") or binaries.default_tag()
|
|
backend = _resolve_backend(section)
|
|
need_runtime = not binaries.installed_tags()
|
|
if need_runtime:
|
|
# Same preflight as /runtime/install: impossible combos fail the POST.
|
|
try:
|
|
binaries.resolve_assets(tag, backend)
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=400, detail=str(exc))
|
|
|
|
need_download = variant.model_id not in bootstrap.staged_model_ids()
|
|
download_plan = _download_plan(entry, variant) if need_download else []
|
|
download_bytes = sum(p[2] for p in download_plan)
|
|
|
|
if not _QUICKSTART_LOCK.acquire(blocking=False):
|
|
raise HTTPException(status_code=409,
|
|
detail="Setup is already running")
|
|
|
|
job = _job("quickstart", entry.display_name, model_id=entry.id)
|
|
job["total_bytes"] = download_bytes or None
|
|
|
|
def _run():
|
|
if need_runtime:
|
|
|
|
job["phase"] = "installing-runtime"
|
|
job["detail"] = "Installing the local engine"
|
|
binaries.ensure_runtime_installed(tag, backend, progress=_runtime_progress_hook(job))
|
|
|
|
if need_download:
|
|
# The runtime leg repurposed the byte counters for its own
|
|
# stages — reset them to the model plan before download.
|
|
job["done_bytes"] = 0
|
|
job["total_bytes"] = download_bytes
|
|
_run_download_plan(job, download_plan, entry.display_name)
|
|
|
|
# Activate: same sequence as /activate's job body.
|
|
_ensure_server(
|
|
job, _set_runtime_enabled(True), variant.model_id,
|
|
fail_detail="The local server could not start — open Local Models for details",
|
|
skip_msg="quickstart rescan check skipped")
|
|
_assign_default(job, variant.model_id)
|
|
_finish(job, f"{entry.display_name} is ready — new chats use it")
|
|
|
|
_spawn_job(job, "lr-quickstart", _run, fail_msg="quickstart failed: %s",
|
|
on_exit=_QUICKSTART_LOCK.release)
|
|
return {
|
|
"job_id": job["job_id"],
|
|
"model_id": entry.id,
|
|
"display_name": entry.display_name,
|
|
"needs_runtime": need_runtime,
|
|
"needs_download": need_download,
|
|
"download_bytes": download_bytes,
|
|
}
|
|
|
|
|
|
def _stop_server() -> None:
|
|
|
|
if bootstrap.get_supervisor() is not None:
|
|
bootstrap.shutdown_local_runtime()
|
|
elif _state_endpoint() is not None:
|
|
# Server owned by another process (or an orphan): best-effort
|
|
# terminate via the state file's pid, then clear the state.
|
|
try:
|
|
import psutil # type: ignore
|
|
|
|
|
|
state = json.loads(supervisor.state_path().read_text(encoding="utf-8"))
|
|
pid = int(state.get("pid") or 0)
|
|
if pid > 0 and psutil.pid_exists(pid):
|
|
psutil.Process(pid).terminate()
|
|
supervisor.state_path().unlink(missing_ok=True)
|
|
except Exception: # noqa: BLE001
|
|
pass
|
|
_set_runtime_enabled(False)
|
|
|
|
|
|
def _start_server() -> None:
|
|
|
|
sup = bootstrap.ensure_local_runtime(_set_runtime_enabled(True), force=True)
|
|
if sup is None and _state_endpoint() is None:
|
|
raise RuntimeError("The local server could not start — check the "
|
|
"runtime is installed")
|
|
|
|
|
|
_SERVER_ACTIONS = {"stop": _stop_server, "start": _start_server}
|
|
|
|
|
|
@router.post("/api/local-models/server")
|
|
async def local_models_server(body: ServerActionBody):
|
|
"""Turn the local engine off (stop the server, free ALL GPU memory, and
|
|
disable auto-start) or back on. The off switch is the whole-engine
|
|
counterpart of per-model eject — and unlike eject it IS durable: the
|
|
user said off, so boots stay off until they say on."""
|
|
action = (body.action or "").strip().lower()
|
|
if action not in _SERVER_ACTIONS:
|
|
raise HTTPException(status_code=400, detail="action must be 'stop' or 'start'")
|
|
try:
|
|
await asyncio.to_thread(_SERVER_ACTIONS[action])
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=502, detail=str(exc)) from exc
|
|
return {"ok": True, "action": action}
|
|
|
|
|
|
# ── activate: make a downloaded model THE model ──────────────
|
|
|
|
|
|
class ModelEjectBody(BaseModel):
|
|
model_id: str
|
|
|
|
|
|
@router.post("/api/local-models/eject")
|
|
def local_models_eject(body: ModelEjectBody):
|
|
"""Free a loaded model's GPU memory now. Nothing reloads it except
|
|
demand — the next message to it (residency v2: no automatic loading
|
|
exists anywhere). Sync def on purpose: the fallback path blocks on a
|
|
urlopen with a 120s timeout — threadpool, never the event loop."""
|
|
|
|
sup = bootstrap.get_supervisor()
|
|
if sup is not None:
|
|
try:
|
|
sup.unload_model(body.model_id)
|
|
return {"ok": True}
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=502, detail=str(exc)) from exc
|
|
|
|
# Server owned by another process (or state-file only): drive the
|
|
# router directly with the persisted endpoint.
|
|
endpoint = _state_endpoint()
|
|
if endpoint is None:
|
|
raise HTTPException(status_code=409, detail="local server is not running")
|
|
try:
|
|
_router_request(endpoint, "/models/unload", timeout=120,
|
|
payload={"model": body.model_id})
|
|
return {"ok": True}
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=502, detail=str(exc)) from exc
|
|
|
|
|
|
class ModelActivateBody(BaseModel):
|
|
model_id: str # exact variant id (a staged .gguf stem)
|
|
|
|
|
|
@router.post("/api/local-models/activate")
|
|
async def local_models_activate(body: ModelActivateBody):
|
|
"""Make a downloaded model the default for new chats. Pure selection
|
|
(residency v2): a config write through the same machinery as
|
|
/api/model/set, plus making sure the server is up. NO model loading —
|
|
models load on first inference, always; an empty router costs nothing.
|
|
Kept as a job for UI continuity."""
|
|
# Split variants stage under their first part — resolve like the rest
|
|
# of the routes instead of assuming a single flat file.
|
|
|
|
if body.model_id not in bootstrap.staged_model_ids():
|
|
raise HTTPException(status_code=404, detail=f"{body.model_id} is not downloaded")
|
|
|
|
job = _job("model-activate", body.model_id, model_id=body.model_id)
|
|
|
|
def _run():
|
|
|
|
_ensure_server(
|
|
job, config_mod.load_config(), body.model_id,
|
|
fail_detail="The local server could not start — check the runtime is installed",
|
|
skip_msg="activate rescan check skipped")
|
|
job["phase"] = "setting-default"
|
|
job["detail"] = "Making it your default"
|
|
_set_runtime_enabled(True)
|
|
_assign_default(job, body.model_id)
|
|
_finish(job, f"{body.model_id} is the default for new chats")
|
|
|
|
_spawn_job(job, "lr-model-activate", _run, fail_msg="model activate failed: %s")
|
|
return {"job_id": job["job_id"]}
|
|
|
|
|
|
# ── job polling ──────────────────────────────────────────────
|
|
|
|
|
|
@router.get("/api/local-models/jobs")
|
|
async def local_models_jobs():
|
|
"""All recent jobs, running first — the pane and the app-level poller
|
|
rediscover in-flight work here after a remount or app restart."""
|
|
with _JOBS_LOCK:
|
|
jobs = sorted(_JOBS.values(),
|
|
key=lambda j: (j["status"] != "running", -j["started_at"]))
|
|
return {"jobs": [_job_view(job) for job in jobs[:20]]}
|
|
|
|
|
|
@router.get("/api/local-models/jobs/{job_id}")
|
|
async def local_models_job(job_id: str):
|
|
with _JOBS_LOCK:
|
|
job = _JOBS.get(job_id)
|
|
if job is None:
|
|
raise HTTPException(status_code=404, detail="job not found")
|
|
return _job_view(job)
|
|
|
|
|
|
# ── Hugging Face browser: search, repo files, arbitrary download ─
|
|
|
|
|
|
@router.get("/api/local-models/search")
|
|
async def local_models_search(q: str, limit: int = 20):
|
|
"""Full-text HF search over GGUF models — the firehose behind the
|
|
curated catalog. Per-quant fit pills come from the repo-files call once
|
|
the user opens a hit."""
|
|
|
|
|
|
if not q.strip():
|
|
return {"hits": []}
|
|
try:
|
|
hits = await run_in_threadpool(hf_browse.search_models, q, limit)
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=502,
|
|
detail=f"Hugging Face search unavailable: {exc}") from exc
|
|
return {"hits": [h.__dict__ for h in hits]}
|
|
|
|
|
|
@router.get("/api/local-models/search/files")
|
|
async def local_models_search_files(repo: str):
|
|
"""The servable GGUFs in one HF repo with a rough pre-download fit
|
|
verdict per quant (file size + conservative fill-ins — the GGUF header
|
|
refines it after download)."""
|
|
|
|
|
|
try:
|
|
groups = await run_in_threadpool(
|
|
hf_browse.priced_repo_files, repo, hardware.probe_budget(planning=True))
|
|
except Exception as exc: # noqa: BLE001
|
|
raise HTTPException(status_code=502,
|
|
detail=f"Could not list {repo}: {exc}") from exc
|
|
return {"files": [dict(g.__dict__, paths=list(g.paths)) for g in groups]}
|
|
|
|
|
|
class BrowsedDownloadBody(BaseModel):
|
|
repo: str
|
|
paths: list[str] # one GGUF, or every part of a split, in order
|
|
|
|
|
|
@router.post("/api/local-models/download-browsed")
|
|
async def local_models_download_browsed(body: BrowsedDownloadBody):
|
|
"""Download an arbitrary HF GGUF (browsed or pasted) into the managed
|
|
models dir. From the moment it lands it is a normal staged model: the
|
|
post-download bounce regenerates presets from its real header and the
|
|
fit policy owns its launch. No catalog entry — it serves 'unverified',
|
|
capabilities answered from the live server only."""
|
|
|
|
paths = [p for p in (body.paths or []) if p.lower().endswith(".gguf")]
|
|
if not paths:
|
|
raise HTTPException(status_code=422, detail="no .gguf files given")
|
|
first = paths[0].rsplit("/", 1)[-1]
|
|
model_id = re.sub(r"-\d{5}-of-\d{5}\.gguf$", "", first, flags=re.IGNORECASE)
|
|
model_id = model_id[:-5] if model_id.lower().endswith(".gguf") else model_id
|
|
if model_id in bootstrap.staged_model_ids():
|
|
return {"job_id": None, "already_downloaded": True, "model_id": model_id}
|
|
|
|
job = _job("model-download", f"{model_id} (from {body.repo})",
|
|
model_id=model_id)
|
|
|
|
def _run():
|
|
job["phase"] = "downloading"
|
|
for p in paths:
|
|
dest = _models_dir() / p.rsplit("/", 1)[-1]
|
|
if dest.exists():
|
|
continue
|
|
download_file(_hf_url(body.repo, urllib.parse.quote(p)), dest, job,
|
|
base_done=int(job.get("done_bytes") or 0),
|
|
keep_totals=bool(job.get("total_bytes")))
|
|
job["phase"] = "downloading"
|
|
_finish(job, f"{model_id} ready")
|
|
_refresh_runtime("post-download runtime refresh skipped")
|
|
|
|
_spawn_job(job, "lm-download-browsed", _run)
|
|
return {"job_id": job["job_id"], "model_id": model_id}
|
|
|
|
|
|
class SideloadBody(BaseModel):
|
|
path: str # absolute path to a .gguf on this machine
|
|
|
|
|
|
@router.post("/api/local-models/sideload")
|
|
async def local_models_sideload(body: SideloadBody):
|
|
"""Register a GGUF that already exists on this machine: link it into
|
|
the managed models dir (copy only when linking is impossible) and
|
|
bounce the router so it serves immediately. The original stays where
|
|
it is; delete-from-Hermes removes only our link."""
|
|
|
|
src = Path(body.path)
|
|
if not src.is_file() or src.suffix.lower() != ".gguf":
|
|
raise HTTPException(status_code=422, detail="Pick a .gguf model file")
|
|
dest = _models_dir() / src.name
|
|
if dest.exists():
|
|
return {"ok": True, "model_id": dest.stem, "already_present": True}
|
|
dest.parent.mkdir(parents=True, exist_ok=True)
|
|
try:
|
|
os.link(src, dest) # hardlink: instant, no extra disk
|
|
except OSError:
|
|
try:
|
|
os.symlink(src, dest) # cross-volume fallback
|
|
except OSError:
|
|
await run_in_threadpool(shutil.copyfile, src, dest)
|
|
_refresh_runtime("post-sideload runtime refresh skipped")
|
|
return {"ok": True, "model_id": dest.stem}
|