forked from unom/punktfunk
- new crate::gpu (compiled on all platforms so the OpenAPI doc stays platform-independent): DXGI / sysfs GPU inventory with reboot-stable ids (PCI vendor:device + occurrence — LUIDs are per-boot), persisted auto/manual preference (<config>/gpu-settings.json, atomic temp+rename with in-memory rollback), one selection with precedence console preference > PUNKTFUNK_RENDER_ADAPTER > max VRAM and graceful fallback when the preferred GPU is absent, plus a live "in use" record (RAII session guard wrapped around every encoder open_video returns) - fix: windows_gpu_vendor derived the encoder backend from DXGI adapter 0 instead of the selected render adapter — on a hybrid box (e.g. Intel iGPU at index 0 + NVIDIA dGPU) the backend could disagree with the GPU the capture ring / IddCx render pin sit on. The NVENC 4:4:4 probe now also runs on the selected adapter (was: OS default), the codec/4:4:4 probe caches are keyed per selected GPU (were process-lifetime OnceLocks), and an explicit PUNKTFUNK_ENCODER conflicting with the selected GPU's vendor warns up front - mgmt API: GET /api/v1/gpus (inventory + mode + preferred + next-session selection with reason + in-use GPU/backend/session-count) and PUT /api/v1/gpus/preference (validates mode/gpu_id before writing); openapi.json regenerated; the vdisplay render pin now also engages for a console preference (not just the env pin) - web console: GPU card on the Host page — list with vendor + VRAM, Automatic / Prefer controls, Preferred / Next session / "In use · backend" badges, missing-preferred-GPU warning and env-pin note; en + de messages - Linux: a matched manual preference picks the VAAPI render node and the NVENC-vs-VAAPI auto choice; auto mode is exactly the previous behavior Validated live on the hybrid laptop (RTX 3500 Ada + Intel Arc Pro, which enumerates twice — the occurrence ids disambiguate): enumerate, prefer, bad-id 400, restart persistence, auto-restore keeping the stored pick. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
147 lines
4.6 KiB
TypeScript
147 lines
4.6 KiB
TypeScript
import { useQueryClient } from "@tanstack/react-query";
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import { Button } from "@unom/ui/button";
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import type { FC } from "react";
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import {
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getListGpusQueryKey,
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useListGpus,
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useSetGpuPreference,
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} from "@/api/gen/gpu/gpu";
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import type { GpuState } from "@/api/gen/model";
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import { QueryState } from "@/components/query-state";
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import { Badge } from "@/components/ui/badge";
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import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
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import type { Loadable } from "@/lib/query";
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import { m } from "@/paraglide/messages";
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/**
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* Container: the host's GPU inventory + selection. Polls (a stream starting/stopping moves the
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* "In use" badge; an eGPU can appear) and applies auto/preferred choices via the mgmt API. A
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* preference applies to the NEXT session — the help text says so.
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*/
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export const GpuSection: FC = () => {
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const qc = useQueryClient();
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const gpus = useListGpus({ query: { refetchInterval: 5_000 } });
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const setPref = useSetGpuPreference();
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const apply = (mode: "auto" | "manual", gpuId?: string) =>
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setPref.mutate(
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{ data: { mode, gpu_id: gpuId ?? null } },
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{
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onSuccess: () =>
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qc.invalidateQueries({ queryKey: getListGpusQueryKey() }),
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},
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);
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return <GpuCard state={gpus} onApply={apply} busy={setPref.isPending} />;
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};
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const fmtVram = (mb: number) =>
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mb >= 1024 ? `${Math.round(mb / 1024)} GiB` : `${mb} MiB`;
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/**
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* GPU list in the compositors-card style: per-GPU badges for the manual pick ("Preferred"), what
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* the next session will use ("Next session"), and what live sessions encode on right now
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* ("In use · NVENC"), plus an Automatic/Prefer control pair.
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*/
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export const GpuCard: FC<{
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state: Loadable<GpuState>;
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onApply: (mode: "auto" | "manual", gpuId?: string) => void;
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busy: boolean;
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}> = ({ state, onApply, busy }) => {
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const s = state.data;
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return (
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<Card>
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<CardHeader>
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<CardTitle className="flex items-center justify-between gap-4">
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<span>{m.host_gpus()}</span>
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{s && s.gpus.length > 0 && (
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<Button
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size="sm"
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variant={s.mode === "auto" ? "default" : "outline"}
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disabled={busy || s.mode === "auto"}
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onClick={() => onApply("auto")}
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>
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{m.gpu_automatic()}
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</Button>
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)}
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</CardTitle>
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</CardHeader>
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<CardContent className="space-y-4">
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<p className="text-sm text-muted-foreground">{m.host_gpus_help()}</p>
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<QueryState
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isLoading={state.isLoading}
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error={state.error}
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refetch={state.refetch}
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>
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{s &&
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(s.gpus.length === 0 ? (
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<p className="text-sm text-muted-foreground">{m.gpu_none()}</p>
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) : (
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<ul className="divide-y rounded-md border">
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{s.gpus.map((g) => {
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const isActive = s.active?.id === g.id;
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const isSelected = s.selected?.id === g.id;
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const isPreferred =
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s.mode === "manual" && s.preferred_id === g.id;
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return (
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<li
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key={g.id}
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className="flex items-center justify-between gap-4 px-4 py-3"
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>
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<div className="min-w-0">
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<div className="flex flex-wrap items-center gap-2">
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<span className="font-medium">{g.name}</span>
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{isPreferred && (
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<Badge variant="secondary">
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{m.gpu_preferred()}
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</Badge>
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)}
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{isActive && s.active ? (
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<Badge variant="success">
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{m.gpu_in_use({
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backend: s.active.backend.toUpperCase(),
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})}
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</Badge>
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) : (
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isSelected && (
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<Badge variant="default">
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{m.gpu_next_session()}
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</Badge>
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)
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)}
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</div>
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<code className="text-xs text-muted-foreground">
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{g.vendor}
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{g.vram_mb > 0 ? ` · ${fmtVram(g.vram_mb)}` : ""}
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{` · ${g.id}`}
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</code>
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</div>
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<Button
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size="sm"
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variant="outline"
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disabled={busy || isPreferred}
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onClick={() => onApply("manual", g.id)}
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>
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{m.gpu_prefer()}
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</Button>
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</li>
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);
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})}
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</ul>
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))}
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{s?.selected?.source === "preference_missing" && (
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<p className="text-sm text-amber-600 dark:text-amber-500">
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{m.gpu_missing_warning({ name: s.preferred_name ?? "?" })}
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</p>
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)}
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{s?.env_override && s.mode === "auto" && (
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<p className="text-xs text-muted-foreground">
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{m.gpu_env_note({ value: s.env_override })}
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</p>
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)}
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</QueryState>
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</CardContent>
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</Card>
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);
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};
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