3582c17cbc
Models used to live at <profile home>/models (adb2fdbf5c) before the managed runtime moved them to the machine-scoped <root>/models (43e67d872f). GGUFs staged under a named profile's old dir silently stopped being served. adopt_legacy_models() renames them (and their assets/) into the current dirs, so everything downstream keeps reading one directory: listing, presets, delete, the --models-dir fallback. It runs at boot, before the "anything staged?" check, and in the Local Models status route so the pane lists them while the runtime is off. os.rename only: instant within a filesystem, while shutil.move would silently copy tens of GB across devices at session start; a cross-device dir stays put with a warning. An existing destination name is never replaced.
983 lines
45 KiB
Python
983 lines
45 KiB
Python
"""Local-models dashboard routes — the desktop's window into the managed llama.cpp runtime.
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Every payload carries plain-language, pre-formatted facts the UI shows verbatim
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(what will this model do ON THIS MACHINE, how big is the download, what is the
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runtime doing), never raw internals. Long jobs follow the repo's job pattern:
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start-POST -> {job_id} -> GET poll with byte progress.
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"""
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from __future__ import annotations
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import asyncio
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import collections
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import contextlib
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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.web_routers._common import _CONFIG_MUTATION_LOCK, _config_profile_scope
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from hermes_cli.local_runtime import (
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binaries, bootstrap, catalog, context_policy, estimator, growth, hardware, hf_browse,
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load_progress, presets, supervisor,
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)
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from pm.downloader import Download, DownloadPaused, Source
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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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_JOBS: Dict[str, Dict[str, Any]] = {}
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_JOBS_LOCK = threading.Lock()
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_RUNNING: Dict[str, Dict[str, Any]] = {}
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# One quickstart at a time: the job sequences installs, downloads, a server bounce and a config write — two
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# racing runs would interleave all four. Held for the job's lifetime, released in the worker.
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_QUICKSTART_LOCK = threading.Lock()
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_LLAMACPP_PROVIDERS = ("llamacpp", "llama.cpp", "llama-cpp")
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_SPLIT_PART_RE = r"-\d{5}-of-\d{5}"
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_DOWNLOAD_PHASES = frozenset({"starting", "installing-runtime", "downloading-runtime", "downloading"})
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# Trailing window the transfer rate averages over. Long enough that a bursty
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# tick (a chunk flush, a mirror switch) doesn't spike the estimate, short
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# enough that the number tracks what the link is doing NOW.
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_RATE_WINDOW = 8.0
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_RATE_MIN_ELAPSED = 0.5 # below this a two-sample slope is noise, not a rate
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_SERVER_START_FAILED = "The local server could not start — check the runtime is installed"
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class RuntimeInstallBody(BaseModel):
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backend: Optional[str] = None # None/auto -> detect
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class ModelDownloadBody(BaseModel):
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model_id: str
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class JobIdBody(BaseModel):
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job_id: str
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class QuickstartBody(BaseModel):
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model_id: str | None = None # default: the catalog's recommended entry
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class ServerActionBody(BaseModel):
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action: str # "stop" | "start"
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class ModelEjectBody(BaseModel):
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model_id: str
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class ModelActivateBody(BaseModel):
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model_id: str # exact variant id (a staged .gguf stem)
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class BrowsedDownloadBody(BaseModel):
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repo: str
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paths: list[str] # one GGUF, or every part of a split, in order
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class SideloadBody(BaseModel):
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path: str # absolute path to a .gguf on this machine
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def _human_gb(n: int | float) -> str:
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return f"{n / (1 << 30):.1f} GB"
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def _k_label(tokens: int) -> str:
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return f"{tokens // 1024}K"
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@contextlib.contextmanager
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def _http_error(status: int, prefix: str = ""):
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"""Map any exception to ``HTTPException(status, f"{prefix}{exc}")``."""
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try:
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yield
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except Exception as exc: # noqa: BLE001
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raise HTTPException(status_code=status, detail=f"{prefix}{exc}") from exc
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def _quiet(fn: Callable[[], Any], default: Any, *, warn: str | None = None, debug: str | None = None) -> Any:
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"""``fn()`` or ``default`` on any exception — for garnish that must never 500. ``warn`` logs a
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warning with the exception (%s), ``debug`` a debug line with traceback; silent otherwise."""
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try:
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return fn()
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except Exception as exc: # noqa: BLE001
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if warn:
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logger.warning(warn, exc)
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if debug:
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logger.debug(debug, exc_info=True)
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return default
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# ── jobs ─────────────────────────────────────────────────────
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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], "kind": kind, "target": target,
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"model_id": model_id, # catalog id for downloads; None otherwise
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"status": "running", # running | paused | done | error
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"phase": "starting", # human-readable step name
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"detail": "", "total_bytes": None, "done_bytes": 0, "started_at": time.time(), "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 _rate_and_eta(samples: "collections.deque[tuple[float, int]]", done: int,
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total: int | None) -> "tuple[float | None, int | None]":
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"""Transfer rate and remaining seconds from a trailing sample window.
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The rate is the slope across the window, not the last two ticks, so a
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burst reads as throughput rather than a spike. Anything that cannot be
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turned into an honest number (one sample, a window too short to divide
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by, a transfer that hasn't moved) reports unknown rather than a guess.
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"""
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first_at, first_done = samples[0]
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elapsed = samples[-1][0] - first_at
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if elapsed < _RATE_MIN_ELAPSED or done <= first_done:
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return None, None
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rate = (done - first_done) / elapsed
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if total:
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return rate, max(0, round(max(0, total - done) / rate))
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return rate, None
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def _record_rate(job: Dict[str, Any], done: int) -> None:
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"""Refresh the job's smoothed rate + ETA from the sample it just reported.
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Samples live on the running entry, not the job, so the wire payload stays
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the derived facts and the history dies with the transfer.
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"""
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running = _RUNNING.get(job["job_id"])
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if running is None:
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return
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now = time.monotonic()
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samples = running.setdefault("samples", collections.deque())
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samples.append((now, done))
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while len(samples) > 1 and now - samples[0][0] > _RATE_WINDOW:
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samples.popleft()
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rate, eta = _rate_and_eta(samples, done, job.get("total_bytes"))
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if rate is None:
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job.pop("bytes_per_sec", None)
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job.pop("eta_seconds", None)
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else:
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job["bytes_per_sec"] = rate
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job["eta_seconds"] = eta
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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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running = _RUNNING.get(job["job_id"], {})
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pause = running.get("pause")
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out["pause_requested"] = bool(pause is not None and pause.is_set() and out["status"] == "running")
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out["can_pause"] = bool(pause is not None and out["status"] == "running"
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and out["phase"] in _DOWNLOAD_PHASES and not out["pause_requested"])
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out["can_resume"] = out["status"] == "paused" and "resume" in running
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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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# A rate and ETA describe a transfer in motion; a parked or settled job
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# would otherwise freeze a stale speed that reads as the live one.
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if out["status"] != "running":
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out.pop("bytes_per_sec", None)
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out.pop("eta_seconds", None)
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return out
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def _check_job_pause(job: Dict[str, Any]) -> None:
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pause = _RUNNING.get(job["job_id"], {}).get("pause")
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if pause is not None and pause.is_set():
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raise DownloadPaused("download paused")
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def _step(job: Dict[str, Any], phase: str, detail: str) -> None:
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with _JOBS_LOCK:
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if job.get("phase") in _DOWNLOAD_PHASES and phase not in _DOWNLOAD_PHASES:
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_check_job_pause(job)
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job["phase"] = phase
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job["detail"] = detail
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def _finish(job: Dict[str, Any], detail: str) -> None:
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# The worker publishes terminal status after releasing its resources.
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_step(job, "done", detail)
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def _spawn_job(job: Dict[str, Any], name: str, body: Callable[[], None], *, fail_msg: str | None = None,
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on_exit: Callable[[], None] | None = None, download_label: str | None = None,
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resumable: bool = False) -> None:
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"""One worker per job. Pauses retain ownership; terminal outcomes release it."""
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guard = threading.Lock()
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pause = threading.Event()
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def _run():
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status = "done"
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try:
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body()
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if download_label is not None:
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_finish(job, f"{download_label} ready")
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_refresh_runtime("post-download runtime refresh skipped")
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except DownloadPaused:
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status = "paused"
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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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status = "error"
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job["error"] = str(exc)
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finally:
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try:
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if status != "paused" and on_exit is not None:
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on_exit()
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finally:
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with _JOBS_LOCK:
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if status != "paused":
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_RUNNING.pop(job["job_id"], None)
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job["status"] = status
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guard.release()
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def start(*, initial: bool = False) -> bool:
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if not guard.acquire(blocking=False):
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return False
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with _JOBS_LOCK:
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if not initial and job["status"] != "paused":
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guard.release()
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return False
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pause.clear()
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# A resume starts a fresh window: the gap parked in the queue
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# would otherwise read as a rate of roughly zero bytes/sec.
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running = _RUNNING.get(job["job_id"])
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if running is not None:
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running.pop("samples", None)
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job["status"] = "running"
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job["error"] = None
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try:
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threading.Thread(target=_run, daemon=True, name=name).start()
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except Exception:
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_RUNNING.pop(job["job_id"], None)
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if on_exit is not None:
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on_exit()
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job["status"] = "error"
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guard.release()
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raise
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return True
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if resumable:
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_RUNNING[job["job_id"]] = {"resume": start, "pause": pause}
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start(initial=True)
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# ── runtime / router plumbing ────────────────────────────────
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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 (it only scans at spawn).
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Never raises — the file operation already succeeded."""
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_quiet(bootstrap.refresh_local_runtime, None, debug=skip_msg)
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def _router_request(endpoint: Dict[str, Any], path: str, *, timeout: float, payload: dict | None = None) -> Any:
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"""Call the local router (base_url minus ``/v1``) with its bearer key; GET (no payload) -> parsed JSON, POST -> 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(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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def _load_config() -> dict:
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"""Read-only config for status/garnish paths that must render degraded, never 500."""
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return _quiet(config_mod.load_config_readonly, {})
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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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# Runs on quickstart/activate/stop job threads; the RMW span races the dashboard's
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# debounced PUT /api/config autosave without the lock.
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with _CONFIG_MUTATION_LOCK:
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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 _runtime_target(requested: str | None = None) -> tuple[str, str]:
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"""Resolve only reviewed PM artifacts; hardware work stays off the event loop."""
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section = _runtime_section()
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backend = requested or section.get("backend", "auto")
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with _http_error(400):
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backend = binaries.resolve_backend(backend)
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return binaries.pinned_tag(backend), backend
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def _engine_too_old(min_engine: str) -> bool:
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if not min_engine:
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return False
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requested = _runtime_section().get("backend", "auto")
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engine = binaries.installed_engine(requested)
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tag = engine.tag if engine is not None else _runtime_target()[0]
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return int(tag.removeprefix("b")) < int(min_engine.removeprefix("b"))
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def _eligible_entries():
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"""Catalog entries this engine can activate today (engine-gated ones 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 _entry_or_404(model_id: str):
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entry = catalog.catalog_by_id().get(model_id)
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if entry is None:
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raise HTTPException(status_code=404, detail=f"unknown model {model_id}")
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return entry
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def _start_local_server(config: dict, fail_detail: str):
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"""Force-start the local server; raise ``fail_detail`` when neither we nor another process ended up serving."""
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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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return sup
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def _ensure_server(job: Dict[str, Any], config: dict, model_id: str, *, fail_detail: str, skip_msg: str) -> None:
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"""Start the local server if needed and self-heal a stale router: the model list is spawn-only, so a
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server started before ``model_id`` finished downloading can't serve it — bounce it when it doesn't know it."""
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_step(job, "starting-server", "Starting the local server")
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sup = _start_local_server(config, fail_detail)
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def rescan_if_unknown(known: Dict[str, Any]) -> None:
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if model_id not in known:
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job["detail"] = "Refreshing the local server"
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bootstrap.refresh_local_runtime()
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if sup is not None:
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_quiet(lambda: rescan_if_unknown(sup.models()), None, debug=skip_msg)
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return
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# A server owned by another process: ensure_local_runtime returned None, so the supervisor
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# path above never ran — but the same spawn-only listing gap applies. Probe the live
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# listing through the persisted endpoint and bounce when it lacks the model.
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endpoint = _state_endpoint()
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if endpoint is not None:
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def _known_models() -> Dict[str, Any]:
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data = (_router_request(endpoint, "/models", timeout=10) or {}).get("data", [])
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return {m.get("id"): m for m in data}
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_quiet(lambda: rescan_if_unknown(_known_models()), None, debug=skip_msg)
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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 via the same machinery as /api/model/set."""
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_step(job, "setting-default", "Making it your default")
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web_deps.late("_apply_model_assignment_sync", "hermes_cli.web_server_config")("main", "llamacpp", model_id, "", "", "")
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# ── downloads: ranged parallel streams ───────────────────────
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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 _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(_SPLIT_PART_RE + "$", "", gguf.stem)
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|
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def _variant_files_on_disk(model_id: str) -> "list[Path]":
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"""Every local file of a staged model: all split parts plus catalog-declared assets (mmproj/draft) when present."""
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files = [p for p in bootstrap.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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assets = (hit[0].mmproj, hit[0].draft) if hit is not None else ()
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files += [bootstrap.assets_dir() / a.local_name for a in assets
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if a is not None and (bootstrap.assets_dir() / a.local_name).exists()]
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return files
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def _download_plan(entry, variant) -> list:
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"""Everything a variant needs: split parts + mmproj/draft assets, as (url, dest, bytes) tuples."""
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plan = [(_hf_url(entry.repo, a.path), bootstrap.models_dir() / a.local_name, a.size_bytes) 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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|
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def _run_download_plan(job: Dict[str, Any], plan: list, label: str) -> None:
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"""The downloader counts completed files and every part of this plan."""
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_step(job, "downloading", f"Downloading {label}")
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_download_job(job, plan)
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|
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|
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def _download_progress_hook(job: Dict[str, Any]):
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def tick(done: int, total: int, ranges: dict) -> None:
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with _JOBS_LOCK:
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job.update(done_bytes=done, total_bytes=total or None, ranges=ranges)
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_record_rate(job, done)
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return tick
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def _download_job(job: Dict[str, Any], plan) -> None:
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"""Model bytes use the same resumable transfer as pinned PM archives."""
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running = _RUNNING.get(job["job_id"], {})
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dl = Download([Source(url, dest) for url, dest, _ in plan], pause_event=running.get("pause"))
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dl.run(progress=_download_progress_hook(job))
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def _loaded_models(running: Dict[str, Any]) -> "tuple[Dict[str, str], Dict[str, Any]]":
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|
"""Resident models right now, plus how each is placed (granted window from the child, spill facts from
|
|
the preset decision) — the difference between 'fast' and 'why is my CPU busy', so it must be inspectable.
|
|
'loading' is its own state (a 20-GB load in flight is the most important thing the pane can show)."""
|
|
data = _router_request(running, "/models", timeout=3)
|
|
loaded = {m["id"]: m.get("status", {}).get("value", "unknown") for m in data.get("data", [])
|
|
if m.get("status", {}).get("value") in ("loaded", "ready", "loading")}
|
|
placement: Dict[str, Any] = {}
|
|
decisions = presets.read_preset_decisions()
|
|
for model_id, state in loaded.items():
|
|
facts: Dict[str, Any] = {}
|
|
plan = decisions.get(model_id)
|
|
if plan is not None:
|
|
facts.update(window=plan.window, window_label=_k_label(plan.window), spilled=plan.spilled)
|
|
n_ctx = state in ("loaded", "ready") and _quiet(
|
|
lambda: _router_request(running, f"/props?model={model_id}", timeout=3)
|
|
.get("default_generation_settings", {}).get("n_ctx"), None)
|
|
if n_ctx:
|
|
facts.update(granted_window=int(n_ctx), granted_window_label=_k_label(int(n_ctx)))
|
|
if facts:
|
|
placement[model_id] = facts
|
|
return loaded, placement
|
|
|
|
|
|
def _staged_row(gguf: Path) -> Dict[str, Any]:
|
|
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
|
|
return {"id": model_id, "size_bytes": size, "size_label": _human_gb(size)}
|
|
|
|
|
|
def _active_llamacpp_model_id() -> str | None:
|
|
"""The active main model when it is one of ours (config authority: the model.provider + model.default
|
|
that /api/model/set writes)."""
|
|
def read() -> str | None:
|
|
model_section = (_load_config() or {}).get("model") or {}
|
|
if str(model_section.get("provider", "")).strip().lower() in _LLAMACPP_PROVIDERS:
|
|
return str(model_section.get("default") or model_section.get("name") or "").strip() or None
|
|
return None
|
|
|
|
return _quiet(read, None)
|
|
|
|
|
|
@router.get("/api/local-models/status")
|
|
def local_models_status():
|
|
"""Cheap, immediate: config state + installed runtime + staged models + supervisor state (GPU facts live
|
|
in /hardware). Sync def on purpose: blocking urlopen/scans run in the threadpool."""
|
|
section = _runtime_section()
|
|
engine = binaries.installed_engine(section.get("backend", "auto"))
|
|
runtime_backend = engine.backend if engine is not None else None
|
|
configured_tag = binaries.pinned_tag(runtime_backend) if runtime_backend else _runtime_target()[0]
|
|
tag = engine.tag if engine is not None else configured_tag
|
|
import pm
|
|
|
|
current = pm.installed_package(binaries.BACKEND_PACKAGES[runtime_backend]) if runtime_backend else None
|
|
# The pane must list models from the old per-profile layout even while the runtime is off.
|
|
_quiet(bootstrap.adopt_legacy_models, [], warn="legacy model adoption failed: %r")
|
|
mdir = bootstrap.models_dir()
|
|
running = _state_endpoint()
|
|
# Resident models from the live router ({} when down): Loaded pills + eject. A failed read is never
|
|
# silent: an empty dict here renders as 'Not in memory' on a machine whose VRAM is visibly full.
|
|
loaded, placement = ({}, {}) if running is None else _quiet(
|
|
lambda: _loaded_models(running), ({}, {}), warn="loaded-models read failed: %r")
|
|
return {
|
|
"enabled": bool(section.get("enabled")), "tag": tag, "configured_tag": configured_tag,
|
|
"update_available": bool(section.get("enabled") and engine is not None and current is None),
|
|
"runtime_installed": runtime_backend is not None, "runtime_backend": runtime_backend,
|
|
"server_running": running is not None, "server_base_url": (running or {}).get("base_url"),
|
|
"active_model_id": _active_llamacpp_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; garnish, never a 500.
|
|
"loading": _quiet(load_progress.get_loading_progress, {}),
|
|
"placement": placement,
|
|
"models": [_staged_row(gguf) for gguf in bootstrap.staged_models()] if mdir.exists() else [],
|
|
"models_dir": str(mdir),
|
|
}
|
|
|
|
|
|
# ── hardware: what this machine can do ───────────────────────
|
|
def _nvidia_smi_facts() -> dict:
|
|
"""GPU identity + live utilization (NVIDIA only; other vendors degrade to {} and the UI hides those readouts)."""
|
|
smi_exe = hardware._nvidia_smi_path()
|
|
if not smi_exe:
|
|
return {}
|
|
smi = subprocess.run([smi_exe, "--query-gpu=name,utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
|
|
capture_output=True, text=True, encoding="utf-8", errors="replace", timeout=5)
|
|
if smi.returncode != 0 or not smi.stdout.strip():
|
|
return {}
|
|
name, util, used_mib = (x.strip() for x in smi.stdout.strip().splitlines()[0].split(","))
|
|
return dict(gpu_name=name, gpu_util_percent=int(util), vram_used_bytes=int(used_mib) << 20)
|
|
|
|
|
|
@router.get("/api/local-models/hardware")
|
|
def local_models_hardware():
|
|
"""The budget as plain facts, polled by the pane and statusbar. Sync def: shells out to nvidia-smi — threadpool."""
|
|
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,
|
|
}
|
|
out.update(_quiet(_nvidia_smi_facts, {}))
|
|
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"
|
|
|
|
|
|
def _catalog_row(entry, budget, recommended, recommended_reason, staged_ids) -> Dict[str, Any]:
|
|
choice = catalog.select_variant(entry, budget)
|
|
# Any variant of this family on disk counts as downloaded.
|
|
dl = next((v for v in entry.variants if v.model_id in staged_ids
|
|
and all(dest.is_file() for _, dest, _ in _download_plan(entry, v))), 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": _k_label(entry.n_ctx_train),
|
|
"recommended": entry.id == recommended,
|
|
"recommended_reason": recommended_reason if entry.id == recommended else None,
|
|
"downloaded": dl is not None, "downloaded_model_id": dl.model_id if dl else None,
|
|
"downloaded_quant": dl.quant if dl 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 until the engine updates, but 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}, {_human_gb(smallest_total)}) "
|
|
"exceeds GPU + system memory"),
|
|
})
|
|
return row
|
|
|
|
variant = choice.variant
|
|
decision = entry.launch_plan(variant, budget).decision
|
|
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 isinstance(decision, estimator.PhysicsRefusal):
|
|
row["fit_summary"] = row["quant_reason"]
|
|
return row
|
|
row.update(start_window=decision.window, start_window_label=_k_label(decision.window), 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 {row['native_context_label']} as you use it"
|
|
row["fit_summary"] = shape + (" (larger than your GPU memory — runs slower)" if decision.spilled else "")
|
|
return row
|
|
|
|
|
|
@router.get("/api/local-models/catalog")
|
|
def local_models_catalog():
|
|
"""Every entry answers up front: how big is the download, will it fit, what context/speed shape will I
|
|
get. The row advertises the BEST build for this machine (highest quality fully on GPU at the 64K floor;
|
|
else the smallest that works, spilled and priced). No entry is hidden; unaffordable models show WHY.
|
|
Sync def: blocking I/O -> threadpool."""
|
|
# Serve the in-memory catalog; 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: machine capacity, not live-free VRAM — a loaded model must not make every row unaffordable.
|
|
budget = hardware.probe_budget(planning=True)
|
|
# 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.
|
|
recommended, recommended_reason = catalog.recommended_entry(budget, _eligible_entries()) or (None, None)
|
|
recommended_id = recommended.id if recommended 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())
|
|
return {"models": [_catalog_row(e, budget, recommended_id, recommended_reason, staged_ids) for e in catalog.CATALOG]}
|
|
|
|
|
|
# ── runtime install (job) ────────────────────────────────────
|
|
def _runtime_progress_hook(job: Dict[str, Any]):
|
|
"""PM owns byte accounting; stages describe work without resetting it."""
|
|
phases = {
|
|
"download": ("downloading-runtime", "Downloading the local engine"),
|
|
"unpack": ("unpacking-runtime", "Unpacking the local engine"),
|
|
"verify": ("verifying-runtime", "Verifying the local engine"),
|
|
}
|
|
|
|
def hook(stage: str, done: int, total: int, label: str) -> None:
|
|
phase, detail = phases[stage]
|
|
_step(job, phase, detail + (f" ({label})" if label else ""))
|
|
return hook
|
|
|
|
|
|
def _install_engine_job(job: Dict[str, Any], backend: str):
|
|
_step(job, "installing-runtime", "Preparing the pinned local engine")
|
|
return binaries.ensure_engine(
|
|
backend, progress=_runtime_progress_hook(job),
|
|
download_progress=_download_progress_hook(job),
|
|
pause_event=_RUNNING[job["job_id"]]["pause"],
|
|
)
|
|
|
|
|
|
@router.post("/api/local-models/runtime/install")
|
|
def local_models_runtime_install(body: RuntimeInstallBody, profile: Optional[str] = None):
|
|
tag, backend = _runtime_target(body.backend)
|
|
job = _job("runtime-install", f"llama.cpp {tag} ({backend})")
|
|
|
|
def run():
|
|
with _config_profile_scope(profile):
|
|
previous = binaries.installed_engine(backend)
|
|
engine = _install_engine_job(job, backend)
|
|
running = bootstrap.get_supervisor()
|
|
if running is not None and previous != engine:
|
|
_step(job, "restarting", "Switching the running server to the pinned build")
|
|
bootstrap.refresh_local_runtime()
|
|
_finish(job, f"llama.cpp {tag} ready ({backend})")
|
|
|
|
_spawn_job(job, "lr-runtime-install", run, fail_msg="runtime install failed: %s", resumable=True)
|
|
return {"job_id": job["job_id"], "backend": backend, "tag": tag}
|
|
|
|
|
|
# ── model download (job with byte progress) ──────────────────
|
|
def _download_target(model_id: str):
|
|
"""(entry, variant) for a family id (this machine's selected variant — the same planning budget as the
|
|
catalog, so the user downloads exactly the build the row advertised) or an exact variant model_id."""
|
|
entry = catalog.catalog_by_id().get(model_id)
|
|
if entry is None: # exact variant id, or nothing we know (404)
|
|
return catalog.find_entry_for_model(model_id) or _entry_or_404(model_id)
|
|
if _engine_too_old(entry.min_engine):
|
|
raise HTTPException(status_code=409, detail=(
|
|
f"{entry.display_name} needs llama.cpp {entry.min_engine} or newer — update the engine first"))
|
|
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")
|
|
return entry, choice.variant
|
|
|
|
|
|
@router.post("/api/local-models/download")
|
|
def local_models_download(body: ModelDownloadBody):
|
|
"""Accepts either a family id (downloads this machine's selected variant) or an exact variant model_id."""
|
|
entry, variant = _download_target(body.model_id)
|
|
plan = _download_plan(entry, variant)
|
|
if plan and all(dest.is_file() for _, dest, _ in plan):
|
|
return {"job_id": None, "already_downloaded": True, "model_id": variant.model_id}
|
|
job = _job("model-download", f"{entry.display_name} ({variant.quant})", model_id=entry.id)
|
|
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", resumable=True)
|
|
return {"job_id": job["job_id"], "model_id": variant.model_id}
|
|
|
|
|
|
@router.post("/api/local-models/download/pause")
|
|
async def local_models_download_pause(body: JobIdBody):
|
|
"""Pause the download phase of a model, component or quickstart job."""
|
|
job = _JOBS.get(body.job_id)
|
|
if job is None:
|
|
raise HTTPException(status_code=404, detail="unknown download job")
|
|
with _JOBS_LOCK:
|
|
if not _job_view(job)["can_pause"]:
|
|
return {"ok": True, "paused": False}
|
|
_RUNNING[body.job_id]["pause"].set()
|
|
return {"ok": True, "paused": True}
|
|
|
|
|
|
@router.post("/api/local-models/download/resume")
|
|
async def local_models_download_resume(body: JobIdBody):
|
|
"""Restart the same job; PM reuses verified files and durable ranges."""
|
|
if body.job_id not in _JOBS:
|
|
raise HTTPException(status_code=404, detail="unknown download job")
|
|
resume = _RUNNING.get(body.job_id, {}).get("resume")
|
|
return {"ok": True, "resumed": bool(resume and resume())}
|
|
|
|
|
|
@router.delete("/api/local-models/models/{model_id}")
|
|
async def local_models_delete(model_id: str):
|
|
"""Remove every split part plus 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, not a stale grown one.
|
|
_quiet(lambda: growth.clear_window_override(model_id), None, debug="window-override clear skipped")
|
|
threading.Thread(target=_refresh_runtime, args=("post-delete runtime refresh skipped",), daemon=True,
|
|
name="lr-post-delete").start()
|
|
return {"ok": True}
|
|
|
|
|
|
# ── quickstart: one click from nothing to a working default ──
|
|
|
|
|
|
def _quickstart_target(body: QuickstartBody, budget):
|
|
"""Resolve an explicit model, or start with the machine's automatic recommendation.
|
|
|
|
With no recommendation, require an explicit choice before starting setup.
|
|
"""
|
|
if body.model_id:
|
|
candidates = [_entry_or_404(body.model_id)]
|
|
else:
|
|
picked = catalog.recommended_entry(budget, _eligible_entries())
|
|
if picked is None:
|
|
raise HTTPException(
|
|
status_code=409,
|
|
detail="No automatic recommendation for this machine — open Local Models to browse or choose a model explicitly",
|
|
)
|
|
candidates = [picked[0]] + [e for e in catalog.CATALOG if e.id != picked[0].id]
|
|
for candidate in candidates:
|
|
choice = catalog.select_variant(candidate, budget)
|
|
if choice is not None and not _engine_too_old(candidate.min_engine):
|
|
return candidate, choice.variant
|
|
raise HTTPException(status_code=409, detail=(
|
|
"no catalog model fits this machine — open Local Models to browse for a smaller build"))
|
|
|
|
|
|
@router.post("/api/local-models/quickstart")
|
|
def local_models_quickstart(body: QuickstartBody, profile: Optional[str] = None):
|
|
"""One job: install the runtime (if missing), download this machine's build of the recommended model (if
|
|
missing), make it the default. Each leg uses the same code as the individual setup routes.
|
|
Preflight rejects (no automatic recommendation or no servable choice) fail the POST
|
|
synchronously so the button can explain itself; everything slow runs in the job with phase/byte progress."""
|
|
entry, variant = _quickstart_target(body, hardware.probe_budget(planning=True))
|
|
tag, backend = _runtime_target()
|
|
need_runtime = binaries.installed_engine(backend) is None
|
|
download_plan = _download_plan(entry, variant)
|
|
need_download = any(not dest.is_file() for _, dest, _ in download_plan)
|
|
if not need_download:
|
|
download_plan = []
|
|
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)
|
|
def _run():
|
|
if need_runtime and binaries.installed_engine(backend) is None:
|
|
_install_engine_job(job, backend)
|
|
if need_download:
|
|
# Each phase has its own complete download plan. Resume within a
|
|
# phase retains counters until PM reports the durable bytes.
|
|
if job["phase"] != "downloading":
|
|
with _JOBS_LOCK:
|
|
job.update(done_bytes=0, total_bytes=None, ranges={})
|
|
_run_download_plan(job, download_plan, entry.display_name)
|
|
_step(job, "starting-server", "Starting the local server")
|
|
with _config_profile_scope(profile):
|
|
_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, resumable=True)
|
|
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}
|
|
|
|
|
|
# ── server lifecycle: turn the engine on/off ─────────────────
|
|
def _terminate_state_pid() -> None:
|
|
"""Explicit recovery, never raw-PID termination of another live owner."""
|
|
from hermes_cli.local_runtime.recovery import stop_recorded_orphan
|
|
|
|
if not stop_recorded_orphan():
|
|
raise HTTPException(status_code=409, detail=(
|
|
"Another Hermes process owns this server, or its ownership could not be verified"))
|
|
|
|
|
|
def _stop_server() -> None:
|
|
if bootstrap.get_supervisor() is not None:
|
|
bootstrap.shutdown_local_runtime()
|
|
else:
|
|
_terminate_state_pid()
|
|
_set_runtime_enabled(False)
|
|
|
|
|
|
def _start_server() -> None:
|
|
_start_local_server(_set_runtime_enabled(True), _SERVER_START_FAILED)
|
|
|
|
|
|
_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, disable auto-start) or back on. Unlike
|
|
per-model eject the off switch 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 HTTPException:
|
|
raise
|
|
except Exception as exc:
|
|
raise HTTPException(status_code=502, detail=str(exc)) from exc
|
|
return {"ok": True, "action": action}
|
|
|
|
|
|
# ── eject / activate ─────────────────────────────────────────
|
|
@router.post("/api/local-models/eject")
|
|
def local_models_eject(body: ModelEjectBody):
|
|
"""Free a loaded model's GPU memory now; only demand (the next message) reloads it — residency v2 has no
|
|
automatic loading anywhere. Sync def: the fallback path blocks on a 120s urlopen — threadpool, never the loop."""
|
|
sup = bootstrap.get_supervisor()
|
|
if sup is not None:
|
|
with _http_error(502):
|
|
sup.unload_model(body.model_id)
|
|
return {"ok": True}
|
|
# 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")
|
|
with _http_error(502):
|
|
_router_request(endpoint, "/models/unload", timeout=120, payload={"model": body.model_id})
|
|
return {"ok": True}
|
|
|
|
|
|
@router.post("/api/local-models/activate")
|
|
async def local_models_activate(body: ModelActivateBody, profile: Optional[str] = None):
|
|
"""Make a downloaded model the default for new chats: a config write via the same machinery as
|
|
/api/model/set plus making sure the server is up. NO model loading (residency v2: models load on first
|
|
inference; an empty router costs nothing). Kept as a job for UI continuity."""
|
|
# Split variants stage under their first part — resolve like the other routes.
|
|
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():
|
|
# The llama runtime is one host-wide process, but "my default model" is a
|
|
# config.yaml write — scope it to the profile the request names, inside the job
|
|
# thread (the contextvar override must be set where the write happens).
|
|
with _config_profile_scope(profile):
|
|
_ensure_server(job, config_mod.load_config(), body.model_id,
|
|
fail_detail=_SERVER_START_FAILED, skip_msg="activate rescan check skipped")
|
|
_step(job, "setting-default", "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 app-level poller rediscover in-flight work here after a remount."""
|
|
with _JOBS_LOCK:
|
|
jobs = sorted(_JOBS.values(), key=lambda job: -job["started_at"])
|
|
active = [job for job in jobs if job["status"] in ("running", "paused")]
|
|
recent = [job for job in jobs if job["status"] in ("done", "error")][:20]
|
|
return {"jobs": [_job_view(job) for job in [*active, *recent]]}
|
|
|
|
|
|
@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; fit pills come from /search/files."""
|
|
if not q.strip():
|
|
return {"hits": []}
|
|
with _http_error(502, "Hugging Face search unavailable: "):
|
|
return {"hits": [h.__dict__ for h in await run_in_threadpool(hf_browse.search_models, q, limit)]}
|
|
|
|
|
|
@router.get("/api/local-models/search/files")
|
|
async def local_models_search_files(repo: str):
|
|
"""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)."""
|
|
with _http_error(502, f"Could not list {repo}: "):
|
|
groups = await run_in_threadpool(hf_browse.priced_repo_files, repo, hardware.probe_budget(planning=True))
|
|
return {"files": [dict(g.__dict__, paths=list(g.paths)) for g in groups]}
|
|
|
|
|
|
@router.post("/api/local-models/download-browsed")
|
|
async def local_models_download_browsed(body: BrowsedDownloadBody):
|
|
"""Download an arbitrary HF GGUF into the managed models dir. Once landed it is a normal staged model (the
|
|
post-download bounce regenerates presets from its real header); with 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")
|
|
model_id = re.sub(rf"(?:{_SPLIT_PART_RE})?\.gguf$", "", paths[0].rsplit("/", 1)[-1], flags=re.IGNORECASE)
|
|
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)
|
|
|
|
plan = [(_hf_url(body.repo, urllib.parse.quote(path)),
|
|
bootstrap.models_dir() / path.rsplit("/", 1)[-1], 0) for path in paths]
|
|
|
|
def _fetch():
|
|
_run_download_plan(job, plan, model_id)
|
|
|
|
_spawn_job(job, "lm-download-browsed", _fetch, download_label=model_id, resumable=True)
|
|
return {"job_id": job["job_id"], "model_id": model_id}
|
|
|
|
|
|
@router.post("/api/local-models/sideload")
|
|
async def local_models_sideload(body: SideloadBody):
|
|
"""Register a GGUF already on this machine: link it into the managed models dir (copy only when linking is
|
|
impossible) and bounce the router. The original stays put; 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 = bootstrap.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}
|