feat(playground): image & video generation tabs + real chat metrics

The infosave collection now ships media models (Lumina-Image-2.0, MiniMax-H3
Turbo) that cortiq runs via `imagine`/`animate` CLI, not `cortiq serve`. The
gateway grows a media API: local .cmf files are classified by `cortiq info`
(chat/image/video, cached), generations run as tracked jobs with step progress
parsed from stdout, one at a time, cancellable, outputs under <data>/media.

The playground becomes three tabs. Image: width/height/steps/CFG/seed, live
progress, result rendered from P6 PPM to a canvas in the browser (PNG export
via toBlob). Video: frames/steps/quality/seed plus optional first/last
keyframes (rasterized to PPM client-side); the MJPEG+PCM AVI is decoded in JS
and played on a canvas synced to the wav — no ffmpeg on either side (mp4 remux
happens opportunistically when ffmpeg exists). A metrics card shows resolution,
steps, seed, total time, time per step/frame and file size.

Chat metrics: the local cortiq server sends no usage chunk in streams, so
token counts showed 0/0. tap_stream now injects one OpenAI-shaped usage event
ahead of [DONE] with the gateway's ~4-chars/token estimate, flagged
`cortiq_estimated`; the UI renders it as "≈ N / M" and adds tok/s and
time-to-first-token. Registration skips media packs (a `cortiq serve` entry
for a diffusion model would only fail) in both Register and the wizard's
Finish.

36 new UI strings translated across all 7 languages.
This commit is contained in:
infosave2007
2026-08-07 15:55:06 +03:00
parent 32ce2f7ed7
commit a77beeabab
16 changed files with 1814 additions and 30 deletions
+38
View File
@@ -468,4 +468,42 @@ export default {
"onboarding.deleteFile": "Die .cmf-Datei von der Festplatte löschen",
"onboarding.confirmDelete": "„{id}“ löschen? Die .cmf-Datei wird von der Festplatte entfernt.",
"onboarding.unregistered": "Ebenfalls abgemeldet: {ids}",
// playground: media generation + streaming metrics
"pg.tab.chat": "Chat",
"pg.tab.image": "Bild",
"pg.tab.video": "Video",
"pg.generate": "Generieren",
"pg.generating": "Wird generiert…",
"pg.genFailed": "Generierung fehlgeschlagen — siehe Log.",
"pg.result": "Ergebnis",
"pg.genMetrics": "Generierungsmetriken",
"pg.imagePromptPlaceholder": "ein Rotfuchs im Schnee bei Sonnenuntergang, fotorealistisch, detailliertes Fell",
"pg.videoPromptPlaceholder": "ein Corgi mit Kochmütze wirft einen Pfannkuchen, Brutzeln und ein fröhliches Bellen",
"pg.imageEmpty": "Das generierte Bild erscheint hier.",
"pg.videoEmpty": "Der generierte Clip (mit Ton) erscheint hier.",
"pg.width": "Breite",
"pg.height": "Höhe",
"pg.steps": "Schritte",
"pg.seed": "Seed",
"pg.randomSeed": "Zufälliger Seed",
"pg.cfgHint": "Guidance-Stärke; ≤ 1 schaltet CFG ab und halbiert die Arbeit.",
"pg.frames": "Frames",
"pg.framesHint": "Bei 24 fps; auf das Raster des Modells gerundet.",
"pg.quality": "JPEG-Qualität",
"pg.videoSizeHint": "Vielfache von 32; die trainierte kurze Kante ist 768.",
"pg.videoStepsHint": "Die Turbo-LoRA ist auf 4 Schritte trainiert.",
"pg.firstFrame": "Erstes Frame (optional)",
"pg.lastFrame": "Letztes Frame (optional)",
"pg.keyframeHint": "Macht den Lauf zu Keyframe-to-Video.",
"pg.resolution": "Auflösung",
"pg.genTime": "Generierungszeit",
"pg.timePerStep": "Pro Schritt",
"pg.timePerFrame": "Pro Frame",
"pg.fileSize": "Dateigröße",
"pg.duration": "Dauer",
"pg.play": "Abspielen",
"pg.noMediaModels": "Noch kein lokales {kind}-Modell. Lade eines (z. B. aus der infosave-Sammlung) unter Import herunter:",
"pg.tokSpeed": "Geschwindigkeit",
"pg.ttft": "Erstes Token",
};