wip(media): w2-ingest partial work (handover, unverified)

Stopped mid-implementation for the handover to the project thread.
Not typechecked or tested; do not merge as is.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0138YqDj3ttfayRwuMKKrqVj
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Claude 2026-10-03 18:24:47 +00:00
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commit 55e129cb7e
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import { readFile, rm } from "node:fs/promises";
import type {
AudioFeaturesResult,
DetectScenesResult,
MediaInferenceProvider,
SaliencyResult,
TranscribeResult,
TranscriptWord,
} from "@rakazo/adapter-kit";
import { UnsupportedMediaOperationError } from "@rakazo/adapter-kit";
import type {
MediaAnalysisKind,
MediaCapabilities,
MediaInferenceOperation,
TeaserFeature,
TeaserWeights,
} from "@rakazo/contracts";
import {
BoxKeyframeSchema,
MediaAnalysisKindSchema,
TEASER_LEARNING_MIN_SAMPLES,
} from "@rakazo/contracts";
import type { NewMediaFaceTrack, NewMediaSegment, Prisma } from "@rakazo/db";
import {
cosineSimilarity,
decodeVectors,
defaultTeaserWeights,
encodeVectors,
meanVector,
scoreSegment,
speechHookScore,
} from "@rakazo/media";
import { assertInside, resolveInside } from "@rakazo/media/node";
import { z } from "zod";
import type { MediaServiceDeps } from "./media-context.js";
import { assetDir, writeFileAtomic } from "./media-ingest-files.js";
/*
* Sidecar analyses for one asset and the scored segments built from them.
*
* Biometric rule: face identity embeddings are stored only in
* MediaFaceTrack.embedding. The "faces" analysis row holds track spans and
* counts, never an embedding; box keyframes live in a JSON file per track.
*
* Each analysis is stored under modelVersion "<provider id>:<model>", so a
* model change adds rows instead of overwriting earlier results. An operation
* the provider reports as unsupported is skipped and records nothing.
*/
/** Version of the segment pipeline written to MediaAsset.analysisVersion. */
export const MEDIA_ANALYSIS_VERSION = 1;
const KEYFRAME_LIMIT = 60;
const WINDOW_MS = 3000;
const STILL_SEGMENT_MS = 3000;
const FACE_SAMPLE_FPS = 2;
const CLASSIFIER_SAMPLE_FPS = 1;
const SAME_FACE_SIMILARITY = 0.6;
const EXCERPT_LIMIT = 500;
const ANALYSIS_OPERATION: Record<MediaAnalysisKind, MediaInferenceOperation> = {
scenes: "detectScenes",
transcript: "transcribe",
faces: "trackFaces",
embeddings: "embedFrames",
classifier: "classifyContent",
audio: "audioFeatures",
saliency: "saliency",
};
/** Kinds that need a time axis and audio; stills skip them. */
const VIDEO_ONLY: ReadonlySet<MediaAnalysisKind> = new Set(["scenes", "transcript", "audio"]);
/** Keyframe times: one per second, at most 60 spread evenly; a still is sampled once. */
export function keyframeTimes(durationMs: number | null, still: boolean): number[] {
if (still || !durationMs || durationMs <= 0) return [0];
const seconds = Math.floor(durationMs / 1000);
if (seconds <= 1) return [0];
const count = Math.min(KEYFRAME_LIMIT, seconds);
const step = count === seconds ? 1000 : durationMs / count;
return Array.from({ length: count }, (_, index) => Math.round(index * step));
}
// ---------------------------------------------------------------------------
// Stored analysis shapes (written here, read back for partial re-runs)
// ---------------------------------------------------------------------------
const Span = z.object({ startMs: z.number(), endMs: z.number() });
const ScenesData = z.object({
shots: z.array(Span.extend({ score: z.number() })),
scenes: z.array(Span),
});
const TranscriptData = z.object({
language: z.string().nullable(),
words: z.array(Span.extend({ text: z.string(), confidence: z.number() })),
});
const FacesData = z.object({
sampleFps: z.number(),
trackCount: z.number(),
tracks: z.array(Span.extend({ keyframeCount: z.number() })),
});
const EmbeddingsData = z.object({ dim: z.number().int().positive(), timesMs: z.array(z.number()) });
const AudioData = z.object({
beatsMs: z.array(z.number()),
energy: z.array(z.object({ tMs: z.number(), value: z.number() })),
});
const SaliencyData = z.object({
points: z.array(
z.object({ tMs: z.number(), cx: z.number(), cy: z.number(), strength: z.number() }),
),
});
/** Box keyframes of one face track as written to `faces/<track>.json`. */
export const FaceKeyframesFileSchema = z.object({
sampleFps: z.number().positive(),
keyframes: z.array(BoxKeyframeSchema.extend({ confidence: z.number() })),
});
export type FaceKeyframesFile = z.infer<typeof FaceKeyframesFileSchema>;
/** Read a face track's keyframes file (path relative to the media root). */
export async function readFaceKeyframes(
mediaRoot: string,
keyframesPath: string,
): Promise<FaceKeyframesFile> {
const file = await resolveInside(mediaRoot, keyframesPath);
return FaceKeyframesFileSchema.parse(JSON.parse(await readFile(file, "utf8")));
}
/** Everything segment scoring reads; null where the analysis is missing or unsupported. */
export interface AnalysisBundle {
scenes: DetectScenesResult | null;
transcript: Pick<TranscribeResult, "language" | "words"> | null;
faceSpans: Array<{ startMs: number; endMs: number }> | null;
embeddings: { timesMs: number[]; vectors: Float32Array[] } | null;
audio: Pick<AudioFeaturesResult, "beatsMs" | "energy"> | null;
saliency: SaliencyResult | null;
}
const EMPTY_BUNDLE: AnalysisBundle = {
scenes: null,
transcript: null,
faceSpans: null,
embeddings: null,
audio: null,
saliency: null,
};
// ---------------------------------------------------------------------------
// Segments
// ---------------------------------------------------------------------------
const round3 = (value: number) => Math.round(Math.min(1, Math.max(0, value)) * 1000) / 1000;
function inSpan(tMs: number, span: { startMs: number; endMs: number }): boolean {
return tMs >= span.startMs && tMs < span.endMs;
}
function overlapMs(a: { startMs: number; endMs: number }, b: { startMs: number; endMs: number }) {
return Math.max(0, Math.min(a.endMs, b.endMs) - Math.max(a.startMs, b.startMs));
}
/** Union length of `spans` clipped to `window`. */
function coveredMs(
spans: Array<{ startMs: number; endMs: number }>,
window: { startMs: number; endMs: number },
): number {
const clipped = spans
.map((span) => ({
startMs: Math.max(span.startMs, window.startMs),
endMs: Math.min(span.endMs, window.endMs),
}))
.filter((span) => span.endMs > span.startMs)
.sort((a, b) => a.startMs - b.startMs);
let total = 0;
let end = Number.NEGATIVE_INFINITY;
for (const span of clipped) {
const start = Math.max(span.startMs, end);
if (span.endMs > start) total += span.endMs - start;
end = Math.max(end, span.endMs);
}
return total;
}
function segmentSpans(
durationMs: number | null,
still: boolean,
scenes: DetectScenesResult | null,
): Array<{ startMs: number; endMs: number; kind: "shot" | "scene" }> {
if (still) return [{ startMs: 0, endMs: STILL_SEGMENT_MS, kind: "shot" }];
const total = durationMs && durationMs > 0 ? durationMs : WINDOW_MS;
const shots = (scenes?.shots ?? [])
.map((shot) => ({
startMs: Math.max(0, Math.round(shot.startMs)),
endMs: Math.min(total, Math.round(shot.endMs)),
}))
.filter((shot) => shot.endMs > shot.startMs)
.sort((a, b) => a.startMs - b.startMs);
if (shots.length > 0) return shots.map((shot) => ({ ...shot, kind: "shot" as const }));
const windows: Array<{ startMs: number; endMs: number; kind: "scene" }> = [];
for (let start = 0; start < total; start += WINDOW_MS) {
windows.push({ startMs: start, endMs: Math.min(total, start + WINDOW_MS), kind: "scene" });
}
return windows;
}
/**
* Scored segments: detected shots, else fixed 3 s windows (one span for a still).
* Features are 0..1; a feature without its analysis is omitted (scores as 0).
* motion mean visual change between consecutive keyframe embeddings
* sharpness resolution proxy (shorter side / 1080); no blur measure yet
* faces share of the span covered by face tracks
* audioPeak loudest energy sample in the span relative to the asset maximum
* speechHook speechHookScore of the words inside the span
* novelty embedding distance to the previous span (first span 0.5)
* beatProximity closeness of the span start to a beat (within 500 ms)
* aesthetics saliency strength proxy
* gaze stays unset: no landmarks are computed during ingest.
*/
export function buildSegments(input: {
durationMs: number | null;
still: boolean;
width: number | null;
height: number | null;
bundle: AnalysisBundle;
weights: TeaserWeights;
}): NewMediaSegment[] {
const { bundle } = input;
const spans = segmentSpans(input.durationMs, input.still, bundle.scenes);
const shortSide = Math.min(input.width ?? 0, input.height ?? 0);
const energyMax = Math.max(0, ...(bundle.audio?.energy.map((sample) => sample.value) ?? []));
const language = bundle.transcript?.language ?? undefined;
let previousMean: Float32Array | null = null;
return spans.map((span, index) => {
const scores: Partial<Record<TeaserFeature, number>> = {};
const embeddings = bundle.embeddings;
const frames = embeddings
? embeddings.timesMs.flatMap((tMs, i) => {
const vector = embeddings.vectors[i];
return vector && (input.still || inSpan(tMs, span)) ? [vector] : [];
})
: [];
if (frames.length >= 2) {
let change = 0;
for (let i = 1; i < frames.length; i++) {
change += 1 - cosineSimilarity(frames[i - 1] as Float32Array, frames[i] as Float32Array);
}
scores.motion = round3((change / (frames.length - 1)) * 4);
} else if (bundle.scenes && !input.still) {
const cuts = bundle.scenes.shots.filter(
(shot) => shot.startMs > span.startMs && shot.startMs < span.endMs,
).length;
scores.motion = round3(cuts / Math.max(1, (span.endMs - span.startMs) / 1000));
}
if (shortSide > 0) scores.sharpness = round3(shortSide / 1080);
if (bundle.faceSpans) {
scores.faces = input.still
? bundle.faceSpans.length > 0
? 1
: 0
: round3(coveredMs(bundle.faceSpans, span) / (span.endMs - span.startMs));
}
if (bundle.audio && energyMax > 0) {
const inside = bundle.audio.energy.filter((sample) => inSpan(sample.tMs, span));
scores.audioPeak = round3(Math.max(0, ...inside.map((sample) => sample.value)) / energyMax);
}
let excerpt: string | null = null;
if (bundle.transcript) {
const words = bundle.transcript.words.filter((word) =>
inSpan((word.startMs + word.endMs) / 2, span),
);
excerpt = words.map((word) => word.text.trim()).filter(Boolean).join(" ") || null;
scores.speechHook = excerpt ? round3(speechHookScore(excerpt, language)) : 0;
}
const mean = frames.length > 0 ? meanVector(frames) : null;
if (mean) {
scores.novelty =
index === 0 || !previousMean || previousMean.length !== mean.length
? 0.5
: round3(1 - cosineSimilarity(previousMean, mean));
previousMean = mean;
}
if (bundle.audio && bundle.audio.beatsMs.length > 0 && !input.still) {
const distance = Math.min(...bundle.audio.beatsMs.map((beat) => Math.abs(beat - span.startMs)));
scores.beatProximity = round3(1 - distance / 500);
}
if (bundle.saliency && bundle.saliency.points.length > 0) {
const inside = bundle.saliency.points.filter((point) => input.still || inSpan(point.tMs, span));
const points = inside.length > 0 ? inside : bundle.saliency.points;
scores.aesthetics = round3(
points.reduce((sum, point) => sum + point.strength, 0) / points.length,
);
}
return {
kind: span.kind,
startMs: span.startMs,
endMs: span.endMs,
scores,
teaserScore: Math.round(scoreSegment(scores, input.weights) * 1000) / 1000,
transcriptExcerpt: excerpt ? excerpt.slice(0, EXCERPT_LIMIT) : null,
labels: [],
};
});
}
// ---------------------------------------------------------------------------
// Running analyses
// ---------------------------------------------------------------------------
type AssetRow = Awaited<ReturnType<MediaServiceDeps["repos"]["getAssetRecord"]>>;
function modelOf(capabilities: MediaCapabilities | null, operation: MediaInferenceOperation) {
const entry = capabilities?.operations[operation];
return { available: entry?.available !== false, model: entry?.model ?? null };
}
/** Run `fn`, or return null when the provider does not support the operation. */
async function unlessUnsupported<T>(fn: () => Promise<T>): Promise<T | null> {
try {
return await fn();
} catch (error) {
if (error instanceof UnsupportedMediaOperationError) return null;
throw error;
}
}
function safeName(value: string): string {
return value.replace(/[^A-Za-z0-9_-]/g, "_").slice(0, 64) || "track";
}
/**
* Re-analysis keeps the person a track was assigned to when the new track of the
* same asset carries the same identity; tracks of other assets are never matched here.
*/
async function previousAssignments(deps: MediaServiceDeps, spaceId: string, assetId: string) {
const rows = await deps.prisma.mediaFaceTrack.findMany({
where: { spaceId, assetId, personId: { not: null }, embedding: { not: null } },
select: { personId: true, embedding: true },
});
return rows.flatMap((row) => {
const bytes = row.embedding as Uint8Array;
if (!row.personId || bytes.byteLength === 0 || bytes.byteLength % 4 !== 0) return [];
const [vector] = decodeVectors(bytes, bytes.byteLength / 4);
return vector ? [{ personId: row.personId, vector }] : [];
});
}
async function storedBundle(
deps: MediaServiceDeps,
spaceId: string,
assetId: string,
kinds: MediaAnalysisKind[],
): Promise<AnalysisBundle> {
const bundle: AnalysisBundle = { ...EMPTY_BUNDLE };
for (const kind of kinds) {
const row = await deps.repos.latestAnalysis(spaceId, assetId, kind);
if (!row) continue;
if (kind === "scenes") {
const parsed = ScenesData.safeParse(row.data);
if (parsed.success) bundle.scenes = parsed.data;
} else if (kind === "transcript") {
const parsed = TranscriptData.safeParse(row.data);
if (parsed.success) bundle.transcript = parsed.data;
} else if (kind === "faces") {
const parsed = FacesData.safeParse(row.data);
if (parsed.success) bundle.faceSpans = parsed.data.tracks;
} else if (kind === "embeddings") {
const parsed = EmbeddingsData.safeParse(row.data);
if (parsed.success && row.vectors) {
bundle.embeddings = {
timesMs: parsed.data.timesMs,
vectors: decodeVectors(row.vectors, parsed.data.dim),
};
}
} else if (kind === "audio") {
const parsed = AudioData.safeParse(row.data);
if (parsed.success) bundle.audio = parsed.data;
} else if (kind === "saliency") {
const parsed = SaliencyData.safeParse(row.data);
if (parsed.success) bundle.saliency = parsed.data;
}
}
return bundle;
}
export interface AnalyzeOutcome {
ran: MediaAnalysisKind[];
skipped: MediaAnalysisKind[];
segments: number;
qualityScore: number | null;
}
/**
* Run the requested analyses (all when omitted) on `inputPath`, store them, and
* rebuild the asset's segments. The caller owns ingest state transitions.
*/
export async function analyzeAsset(input: {
deps: MediaServiceDeps;
inference: MediaInferenceProvider;
spaceId: string;
asset: AssetRow;
inputPath: string;
kinds?: MediaAnalysisKind[];
}): Promise<AnalyzeOutcome> {
const { deps, inference, spaceId, asset, inputPath } = input;
const still = asset.kind === "photo" || !asset.durationMs;
const requested = new Set(input.kinds ?? MediaAnalysisKindSchema.options);
const capabilities = await inference.capabilities().catch(() => null);
const times = keyframeTimes(asset.durationMs, still);
const bundle: AnalysisBundle = { ...EMPTY_BUNDLE };
const ran: MediaAnalysisKind[] = [];
const skipped: MediaAnalysisKind[] = [];
const version = (kind: MediaAnalysisKind, resultModel?: string) => {
const model =
modelOf(capabilities, ANALYSIS_OPERATION[kind]).model ?? resultModel ?? "default";
return { modelId: model, modelVersion: `${inference.id}:${model}` };
};
const store = async (
kind: MediaAnalysisKind,
data: Prisma.InputJsonValue,
extra: { vectors?: Uint8Array; resultModel?: string } = {},
) => {
await deps.repos.upsertAnalysis(spaceId, asset.id, {
kind,
...version(kind, extra.resultModel),
data,
vectors: extra.vectors ?? null,
});
ran.push(kind);
};
const runnable = (kind: MediaAnalysisKind) => {
if (!requested.has(kind) || (still && VIDEO_ONLY.has(kind))) return false;
if (!modelOf(capabilities, ANALYSIS_OPERATION[kind]).available) {
skipped.push(kind);
return false;
}
return true;
};
const attempt = async <T>(kind: MediaAnalysisKind, fn: () => Promise<T>) => {
const result = await unlessUnsupported(fn);
if (result === null) skipped.push(kind);
return result;
};
if (runnable("scenes")) {
const scenes = await attempt("scenes", () => inference.detectScenes({ path: inputPath }));
if (scenes) {
bundle.scenes = scenes;
await store("scenes", { shots: scenes.shots, scenes: scenes.scenes });
}
}
if (runnable("transcript")) {
const transcript = await attempt("transcript", () => inference.transcribe({ path: inputPath }));
if (transcript) {
bundle.transcript = transcript;
const words: TranscriptWord[] = transcript.words;
await store("transcript", {
language: transcript.language,
words: words.map((word) => ({ ...word })),
text: words
.map((word) => word.text.trim())
.filter(Boolean)
.join(" "),
});
}
}
if (runnable("faces")) {
const sampleFps = still ? 1 : FACE_SAMPLE_FPS;
const tracked = await attempt("faces", () =>
inference.trackFaces({ path: inputPath, sampleFps }),
);
if (tracked) {
const facesDir = `${assetDir(spaceId, asset.id)}/faces`;
await rm(await resolveInside(deps.mediaRoot, facesDir), { recursive: true, force: true });
const previous = await previousAssignments(deps, spaceId, asset.id);
const stepMs = Math.round(1000 / tracked.sampleFps);
const tracks: NewMediaFaceTrack[] = [];
const spans: Array<{ startMs: number; endMs: number; keyframeCount: number }> = [];
for (const [index, track] of tracked.tracks.entries()) {
const keyframes = [...track.keyframes].sort((a, b) => a.tMs - b.tMs);
const first = keyframes[0];
const last = keyframes.at(-1);
if (!first || !last) continue;
const keyframesPath = `${facesDir}/${index}-${safeName(track.trackId)}.json`;
const file: FaceKeyframesFile = { sampleFps: tracked.sampleFps, keyframes };
await writeFileAtomic(
await resolveInside(deps.mediaRoot, keyframesPath),
JSON.stringify(file),
);
const embedding = track.embedding && track.embedding.length > 0 ? track.embedding : null;
let personId: string | null = null;
if (embedding) {
let best = SAME_FACE_SIMILARITY;
for (const candidate of previous) {
if (candidate.vector.length !== embedding.length) continue;
const similarity = cosineSimilarity(candidate.vector, embedding);
if (similarity >= best) {
best = similarity;
personId = candidate.personId;
}
}
}
const startMs = Math.max(0, Math.round(first.tMs));
const endMs = Math.max(startMs + 1, Math.round(last.tMs) + stepMs);
tracks.push({
startMs,
endMs,
confidenceMin: Math.min(...keyframes.map((keyframe) => keyframe.confidence)),
keyframesPath,
embedding: embedding ? encodeVectors([embedding]) : null,
personId,
});
spans.push({ startMs, endMs, keyframeCount: keyframes.length });
}
const { modelVersion } = version("faces");
await deps.repos.replaceFaceTracks(spaceId, asset.id, modelVersion, tracks);
bundle.faceSpans = spans;
// Spans and counts only: identity embeddings never enter an analysis row.
await store("faces", { sampleFps: tracked.sampleFps, trackCount: spans.length, tracks: spans });
}
}
if (runnable("embeddings")) {
const embedded = await attempt("embeddings", () =>
inference.embedFrames({ path: inputPath, timesMs: times }),
);
if (embedded && embedded.vectors.length > 0) {
const timesMs = times.slice(0, embedded.vectors.length);
bundle.embeddings = {
timesMs,
vectors: embedded.vectors.map((vector) => Float32Array.from(vector)),
};
await store(
"embeddings",
{ model: embedded.model, dim: embedded.dim, timesMs },
{ vectors: encodeVectors(embedded.vectors), resultModel: embedded.model },
);
}
}
if (runnable("classifier")) {
const boundaries = (bundle.scenes?.shots ?? []).map((shot) => shot.startMs).filter((t) => t > 0);
const classified = await attempt("classifier", () =>
inference.classifyContent({
path: inputPath,
sampleFps: CLASSIFIER_SAMPLE_FPS,
...(boundaries.length > 0 ? { extraTimesMs: boundaries } : {}),
}),
);
if (classified) {
await store(
"classifier",
{ model: classified.model, frames: classified.frames },
{ resultModel: classified.model },
);
}
}
if (runnable("audio")) {
const audio = await attempt("audio", () => inference.audioFeatures({ path: inputPath }));
if (audio) {
bundle.audio = audio;
await store("audio", { ...audio });
}
}
if (runnable("saliency")) {
const saliency = await attempt("saliency", () =>
inference.saliency({ path: inputPath, timesMs: times }),
);
if (saliency) {
bundle.saliency = saliency;
await store("saliency", { points: saliency.points });
}
}
// Kinds not run this time come from their latest stored result.
const missing = MediaAnalysisKindSchema.options.filter(
(kind) => !ran.includes(kind) && kind !== "classifier",
);
if (input.kinds && missing.length > 0) {
const stored = await storedBundle(deps, spaceId, asset.id, missing);
bundle.scenes ??= stored.scenes;
bundle.transcript ??= stored.transcript;
bundle.faceSpans ??= stored.faceSpans;
bundle.embeddings ??= stored.embeddings;
bundle.audio ??= stored.audio;
bundle.saliency ??= stored.saliency;
}
const learned = await deps.repos.getTeaserModel(spaceId);
const weights =
learned && learned.sampleCount >= TEASER_LEARNING_MIN_SAMPLES
? learned.weights
: defaultTeaserWeights("teaser");
const segments = buildSegments({
durationMs: asset.durationMs,
still,
width: asset.width,
height: asset.height,
bundle,
weights,
});
await deps.repos.replaceSegments(spaceId, asset.id, MEDIA_ANALYSIS_VERSION, segments);
const teaserScores = segments.flatMap((segment) =>
typeof segment.teaserScore === "number" ? [segment.teaserScore] : [],
);
const qualityScore = teaserScores.length > 0 ? Math.max(...teaserScores) : null;
return { ran, skipped, segments: segments.length, qualityScore };
}
/**
* The file the sidecar analyses. A referenced original inside the media root
* (the sidecar's only mount) is analysed directly; everything else uses the
* proxy, which shares the original's timeline and applies its rotation.
*/
export async function analysisInputPath(input: {
mediaRoot: string;
proxyPath: string;
referencedOriginal: string | null;
}): Promise<string> {
if (input.referencedOriginal) {
try {
return await assertInside(input.mediaRoot, input.referencedOriginal);
} catch {
// Outside the media root: the sidecar cannot read it.
}
}
return resolveInside(input.mediaRoot, input.proxyPath);
}

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import { readFile } from "node:fs/promises";
import type { AgentInputImage } from "@rakazo/adapter-kit";
import type { MediaClusterInput } from "@rakazo/db";
import type { ClusterAsset, VectorItem } from "@rakazo/media";
import {
buildSessions,
clusterFaces,
clusterThemes,
cosineSimilarity,
decodeVectors,
encodeVectors,
meanVector,
ruleLabel,
} from "@rakazo/media";
import { resolveInside } from "@rakazo/media/node";
import { getLogger } from "@rakazo/logging";
import { z } from "zod";
import type { MediaServiceDeps } from "./media-context.js";
import { errorMessage, publishSafe } from "./media-ingest-files.js";
/*
* Sessions, themes, and person suggestions for one space.
*
* Bounds: themes use average-linkage clustering (O(n²) time and memory), so
* each run clusters at most THEME_BATCH_LIMIT of the most recently captured
* analysed assets; older assets keep no theme until they fall into the window.
* Face clustering is bounded the same way per run (FACE_BATCH_LIMIT unassigned
* tracks); the rest are picked up by the next run.
*
* Theme titles come from the model only when the media model client returns
* one (it checks AI consent for the space's library owner); it receives cover
* thumbnails and nothing else. Face embeddings and person data never leave
* this process.
*
* Collections the user edited (labelSource "user") keep their membership when
* it no longer matches the computed cluster (merged or split): their assets are
* withheld from every other computed cluster so re-clustering never re-adds
* them elsewhere. A collection whose stored assets are still a subset of the
* computed cluster (only renamed) keeps updating.
*/
export const THEME_BATCH_LIMIT = 2000;
export const FACE_BATCH_LIMIT = 2000;
const THEME_MIN_SIZE = 3;
const THEME_SIMILARITY = 0.8;
const FACE_SIMILARITY = 0.6;
const COVER_IMAGES = 9;
const MODEL_LABELS_PER_RUN = 12;
const EMBEDDING_BATCH = 500;
const ThemeTitleSchema = z.object({ title: z.string().trim().min(1).max(80) });
const THEME_INSTRUCTIONS =
'You name groups of photos and videos. Reply with one JSON object {"title": string}: ' +
"a short, neutral title of at most five words for what the images have in common " +
"(place type, activity, or subject). Never name or describe people's identities.";
interface UserCollection {
clusterKey: string | null;
assetIds: string[];
}
/**
* Apply the user-edit rules above to computed clusters of one kind. Clusters
* that lose assets are re-keyed by their first remaining asset (the same rule
* the clustering uses), and dropped when empty or colliding with a kept key.
*/
export function reconcileUserEdits<T extends { key: string; assetIds: string[] }>(
clusters: T[],
userCollections: UserCollection[],
prefix: "session" | "theme",
): T[] {
const splitOff = new Set(
userCollections.flatMap((collection) => (collection.clusterKey ? [] : collection.assetIds)),
);
const computed = new Map(
clusters.map((cluster) => [
cluster.key,
new Set(cluster.assetIds.filter((id) => !splitOff.has(id))),
]),
);
const frozenKeys = new Set<string>();
const frozenAssets = new Set<string>();
for (const collection of userCollections) {
if (!collection.clusterKey) continue;
const members = computed.get(collection.clusterKey);
if (!members || collection.assetIds.some((id) => !members.has(id))) {
frozenKeys.add(collection.clusterKey);
for (const id of collection.assetIds) frozenAssets.add(id);
}
}
const seen = new Set<string>();
const result: T[] = [];
for (const cluster of clusters) {
const assetIds = cluster.assetIds.filter((id) => !splitOff.has(id) && !frozenAssets.has(id));
const first = assetIds[0];
if (!first) continue;
const keep = !frozenKeys.has(cluster.key) && first === cluster.assetIds[0];
const key = keep ? cluster.key : `${prefix}:${first}`;
if (frozenKeys.has(key) || seen.has(key)) continue;
seen.add(key);
result.push({ ...cluster, key, assetIds });
}
return result;
}
type ClusterRow = Awaited<ReturnType<MediaServiceDeps["repos"]["listAssetsForClustering"]>>[number];
/** Mean frame embedding per asset from the latest embeddings analysis, read in batches. */
async function meanEmbeddings(
deps: MediaServiceDeps,
spaceId: string,
assetIds: string[],
): Promise<Map<string, Float32Array>> {
const means = new Map<string, Float32Array>();
for (let offset = 0; offset < assetIds.length; offset += EMBEDDING_BATCH) {
const batch = assetIds.slice(offset, offset + EMBEDDING_BATCH);
const rows = await deps.prisma.mediaAnalysis.findMany({
where: { spaceId, kind: "embeddings", assetId: { in: batch }, vectors: { not: null } },
select: { assetId: true, data: true, vectors: true },
orderBy: [{ createdAt: "desc" }, { id: "desc" }],
});
for (const row of rows) {
if (means.has(row.assetId) || !row.vectors) continue;
const data = row.data as { dim?: unknown } | null;
const dim = typeof data?.dim === "number" ? data.dim : 0;
if (!Number.isInteger(dim) || dim <= 0 || row.vectors.byteLength % (dim * 4) !== 0) continue;
const mean = meanVector(decodeVectors(row.vectors, dim));
if (mean) means.set(row.assetId, mean);
}
}
return means;
}
/** The vectors of the most common dimension (a model change mixes dimensions). */
function sameDimension<T extends { vector: Float32Array }>(items: T[]): T[] {
const counts = new Map<number, number>();
for (const item of items) counts.set(item.vector.length, (counts.get(item.vector.length) ?? 0) + 1);
const dim = [...counts.entries()].sort((a, b) => b[1] - a[1] || b[0] - a[0])[0]?.[0];
return items.filter((item) => item.vector.length === dim);
}
async function userCollections(
deps: MediaServiceDeps,
spaceId: string,
kind: "session" | "theme",
): Promise<UserCollection[]> {
const rows = await deps.prisma.mediaCollection.findMany({
where: { spaceId, kind, labelSource: "user" },
select: { clusterKey: true, items: { select: { assetId: true }, orderBy: { position: "asc" } } },
});
return rows.map((row) => ({
clusterKey: row.clusterKey,
assetIds: row.items.map((item) => item.assetId),
}));
}
/** Whose AI consent governs model labels: the owner of the space's first media source. */
async function libraryOwner(deps: MediaServiceDeps, spaceId: string): Promise<string | null> {
const source = await deps.prisma.mediaSource.findFirst({
where: { spaceId },
orderBy: [{ createdAt: "asc" }, { id: "asc" }],
select: { ownerUserId: true },
});
if (source) return source.ownerUserId;
const space = await deps.prisma.space.findUnique({
where: { id: spaceId },
select: { createdByUserId: true },
});
return space?.createdByUserId ?? null;
}
export interface ClusterOutcome {
sessions: number;
themes: number;
modelLabels: number;
assignedTracks: number;
suggestedPeople: number;
}
export async function clusterSpace(
deps: MediaServiceDeps,
spaceId: string,
options: { signal?: AbortSignal } = {},
): Promise<ClusterOutcome> {
const rows = await deps.repos.listAssetsForClustering(spaceId);
const extras = await deps.prisma.mediaAsset.findMany({
where: { spaceId },
select: { id: true, thumbPath: true, qualityScore: true },
});
const extra = new Map(extras.map((row) => [row.id, row]));
const embeddings = await meanEmbeddings(
deps,
spaceId,
rows.map((row) => row.id),
);
const byId = new Map(rows.map((row) => [row.id, row]));
const cover = (assetIds: string[]): string | null => {
const ranked = assetIds
.map((id) => extra.get(id))
.filter((row) => row?.thumbPath)
.sort((a, b) => (b?.qualityScore ?? 0) - (a?.qualityScore ?? 0));
return ranked[0]?.id ?? assetIds[0] ?? null;
};
const span = (assetIds: string[]) => {
const dates = assetIds
.flatMap((id) => {
const at = byId.get(id)?.capturedAt;
return at ? [at.getTime()] : [];
})
.sort((a, b) => a - b);
return {
startAt: dates.length > 0 ? new Date(dates[0] as number) : null,
endAt: dates.length > 0 ? new Date(dates.at(-1) as number) : null,
};
};
const albums = (assetIds: string[]) => assetIds.flatMap((id) => byId.get(id)?.albumNames ?? []);
// Sessions -----------------------------------------------------------------
const clusterAssets: ClusterAsset[] = rows.map((row: ClusterRow) => ({
id: row.id,
kind: row.kind as ClusterAsset["kind"],
capturedAt: row.capturedAt,
gpsLat: row.gpsLat,
gpsLon: row.gpsLon,
deviceModel: row.deviceModel,
albumNames: row.albumNames,
embedding: embeddings.get(row.id) ?? null,
}));
const computedSessions = buildSessions(clusterAssets);
const centroids = new Map(computedSessions.map((session) => [session.key, session.centroid]));
const sessions: MediaClusterInput[] = reconcileUserEdits(
computedSessions.map((session) => ({ key: session.key, assetIds: session.assetIds })),
await userCollections(deps, spaceId, "session"),
"session",
).map((session) => {
const range = span(session.assetIds);
return {
key: session.key,
title: ruleLabel({ ...range, albumNames: albums(session.assetIds) }),
labelSource: "rule",
...range,
centroid: centroids.get(session.key) ?? null,
coverAssetId: cover(session.assetIds),
assetIds: session.assetIds,
};
});
options.signal?.throwIfAborted();
await deps.repos.replaceClusters(spaceId, "session", sessions);
await publishSafe(deps, spaceId, { type: "media.collections", kind: "session" });
// Themes -------------------------------------------------------------------
const recent = rows
.flatMap((row) => {
const vector = embeddings.get(row.id);
return vector ? [{ id: row.id, vector, at: row.capturedAt?.getTime() ?? 0 }] : [];
})
.sort((a, b) => b.at - a.at || a.id.localeCompare(b.id))
.slice(0, THEME_BATCH_LIMIT);
const items: VectorItem[] = sameDimension(recent).map(({ id, vector }) => ({ id, vector }));
const computedThemes = reconcileUserEdits(
clusterThemes(items, { similarity: THEME_SIMILARITY, minSize: THEME_MIN_SIZE }).map(
(theme) => ({ key: theme.key, assetIds: theme.ids }),
),
await userCollections(deps, spaceId, "theme"),
"theme",
);
const existing = await deps.prisma.mediaCollection.findMany({
where: { spaceId, kind: "theme", clusterKey: { in: computedThemes.map((theme) => theme.key) } },
select: { clusterKey: true, title: true, labelSource: true },
});
const modelTitles = new Map(
existing.flatMap((row) =>
row.labelSource === "model" && row.clusterKey ? [[row.clusterKey, row.title] as const] : [],
),
);
const userId = await libraryOwner(deps, spaceId);
let modelCalls = 0;
let modelLabels = 0;
const themes: MediaClusterInput[] = [];
for (const theme of computedThemes) {
options.signal?.throwIfAborted();
const range = span(theme.assetIds);
const coverAssetId = cover(theme.assetIds);
let title = modelTitles.get(theme.key) ?? null;
if (!title && userId && modelCalls < MODEL_LABELS_PER_RUN) {
modelCalls += 1;
title = await themeTitle(deps, spaceId, userId, theme.assetIds, extra, options.signal);
}
if (title) modelLabels += 1;
themes.push({
key: theme.key,
title: title ?? ruleLabel({ ...range, albumNames: albums(theme.assetIds) }),
labelSource: title ? "model" : "rule",
...range,
centroid: null,
coverAssetId,
assetIds: theme.assetIds,
});
}
await deps.repos.replaceClusters(spaceId, "theme", themes);
await publishSafe(deps, spaceId, { type: "media.collections", kind: "theme" });
// People -------------------------------------------------------------------
const people = await suggestPeople(deps, spaceId);
if (people.assignedTracks + people.suggestedPeople > 0) {
await publishSafe(deps, spaceId, { type: "media.people" });
}
return { sessions: sessions.length, themes: themes.length, modelLabels, ...people };
}
/** Ask the model for a theme title from cover thumbnails only; null falls back to rules. */
async function themeTitle(
deps: MediaServiceDeps,
spaceId: string,
userId: string,
assetIds: string[],
extra: Map<string, { id: string; thumbPath: string | null; qualityScore: number | null }>,
signal?: AbortSignal,
): Promise<string | null> {
const covers = assetIds
.flatMap((id) => {
const row = extra.get(id);
return row?.thumbPath ? [row] : [];
})
.sort((a, b) => (b.qualityScore ?? 0) - (a.qualityScore ?? 0) || a.id.localeCompare(b.id))
.slice(0, COVER_IMAGES);
const images: AgentInputImage[] = [];
for (const [index, row] of covers.entries()) {
try {
const file = await resolveInside(deps.mediaRoot, row.thumbPath as string);
images.push({ name: `cover-${index + 1}.jpg`, mimeType: "image/jpeg", data: await readFile(file) });
} catch {
// A missing thumbnail only shrinks the set.
}
}
if (images.length === 0) return null;
try {
const reply = await deps.model.generate({
spaceId,
userId,
instructions: THEME_INSTRUCTIONS,
prompt: `Name what these ${images.length} images have in common.`,
images,
schema: ThemeTitleSchema,
tier: "fast",
...(signal ? { signal } : {}),
});
return reply?.title ?? null;
} catch (error) {
getLogger().warn("media theme label failed", { reason: errorMessage(error) });
return null;
}
}
/**
* Unassigned face tracks join an unconfirmed suggestion with the same identity;
* the rest are clustered into new suggestions. Confirmed people only ever gain
* tracks through the user.
*/
async function suggestPeople(
deps: MediaServiceDeps,
spaceId: string,
): Promise<{ assignedTracks: number; suggestedPeople: number }> {
const unassigned = (await deps.repos.faceTrackEmbeddings(spaceId, { unassignedOnly: true }))
.slice(0, FACE_BATCH_LIMIT)
.flatMap((track) => {
const bytes = track.embedding;
if (bytes.byteLength === 0 || bytes.byteLength % 4 !== 0) return [];
const [vector] = decodeVectors(bytes, bytes.byteLength / 4);
return vector ? [{ id: track.trackId, vector }] : [];
});
if (unassigned.length === 0) return { assignedTracks: 0, suggestedPeople: 0 };
const confirmed = new Set(
(await deps.repos.listPersonRecords(spaceId))
.filter((person) => person.confirmed)
.map((person) => person.id),
);
const suggestions = (await deps.repos.personCentroids(spaceId)).flatMap((person) => {
if (confirmed.has(person.personId)) return [];
const bytes = person.centroid;
if (bytes.byteLength === 0 || bytes.byteLength % 4 !== 0) return [];
const [vector] = decodeVectors(bytes, bytes.byteLength / 4);
return vector ? [{ personId: person.personId, vector }] : [];
});
let assignedTracks = 0;
const remaining: VectorItem[] = [];
for (const track of unassigned) {
let best: string | null = null;
let bestSimilarity = FACE_SIMILARITY;
for (const suggestion of suggestions) {
if (suggestion.vector.length !== track.vector.length) continue;
const similarity = cosineSimilarity(suggestion.vector, track.vector);
if (similarity >= bestSimilarity) {
best = suggestion.personId;
bestSimilarity = similarity;
}
}
if (best) {
await deps.repos.assignTrack(spaceId, track.id, best);
assignedTracks += 1;
} else {
remaining.push(track);
}
}
const groups = clusterFaces(sameDimension(remaining), { similarity: FACE_SIMILARITY });
const created = await deps.repos.createPersonSuggestions(
spaceId,
groups.map((group) => ({ centroid: encodeVectors([group.centroid]), trackIds: group.ids })),
);
return { assignedTracks, suggestedPeople: created.length };
}

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import { createHash, randomUUID } from "node:crypto";
import { createReadStream } from "node:fs";
import { copyFile, mkdir, rename, rm, unlink, writeFile } from "node:fs/promises";
import path from "node:path";
import { pipeline } from "node:stream/promises";
import type { MediaRealtimeEvent, MediaServiceDeps } from "./media-context.js";
import { getLogger } from "@rakazo/logging";
import { resolveInside } from "@rakazo/media/node";
import { FOLDER_MEDIA_EXTENSIONS } from "./media-folder-source.js";
/*
* File helpers for media ingest. Every stored path is relative to the media
* root and resolved through resolveInside; writes go to a temp name in the
* target directory and are renamed into place.
*/
/** Relative directory of one asset's derived files. */
export function assetDir(spaceId: string, assetId: string): string {
return `${spaceId}/assets/${assetId}`;
}
/** Lower-case original extension for an uploaded file name, or null when it is not a media type. */
export function originalExtension(fileName: string): string | null {
const ext = path.extname(fileName).slice(1).toLowerCase();
return Object.hasOwn(FOLDER_MEDIA_EXTENSIONS, ext) ? ext : null;
}
/** Streamed SHA-256 (hex) of a file. */
export async function sha256File(file: string, signal?: AbortSignal): Promise<string> {
const hash = createHash("sha256");
await pipeline(createReadStream(file), hash, { signal });
return hash.digest("hex");
}
/** Delete media-root-relative files or directories; missing ones are fine. */
export async function deleteMediaPaths(mediaRoot: string, paths: Iterable<string>): Promise<void> {
for (const relative of new Set(paths)) {
try {
await rm(await resolveInside(mediaRoot, relative), { recursive: true, force: true });
} catch (error) {
getLogger().warn("media file cleanup failed", {
reason: error instanceof Error ? error.message : String(error),
});
}
}
}
/** A temp path next to `target` that a later rename moves into place atomically. */
export function tempSibling(target: string, ext: string): string {
return path.join(path.dirname(target), `.tmp-${randomUUID()}${ext}`);
}
/** Write bytes atomically: temp file in the same directory, then rename. */
export async function writeFileAtomic(target: string, data: string | Uint8Array): Promise<void> {
await mkdir(path.dirname(target), { recursive: true });
const temp = tempSibling(target, path.extname(target));
try {
await writeFile(temp, data);
await rename(temp, target);
} finally {
await rm(temp, { force: true });
}
}
/** Rename, falling back to copy + unlink across devices. */
export async function moveFile(from: string, to: string): Promise<void> {
await mkdir(path.dirname(to), { recursive: true });
try {
await rename(from, to);
} catch (error) {
if ((error as NodeJS.ErrnoException).code !== "EXDEV") throw error;
const temp = tempSibling(to, path.extname(to));
try {
await copyFile(from, temp);
await rename(temp, to);
} finally {
await rm(temp, { force: true });
}
await unlink(from);
}
}
/** Realtime is best effort: a failed notification never fails ingest work. */
export async function publishSafe(
deps: Pick<MediaServiceDeps, "publish">,
spaceId: string,
event: MediaRealtimeEvent,
): Promise<void> {
try {
await deps.publish(spaceId, event);
} catch (error) {
getLogger().warn("media realtime publish failed", {
type: event.type,
reason: error instanceof Error ? error.message : String(error),
});
}
}
export function errorMessage(error: unknown): string {
return (error instanceof Error ? error.message : String(error)).slice(0, 500);
}
/** A full disk is retried later instead of failing the asset for good. */
export function isDiskFull(error: unknown): boolean {
if ((error as NodeJS.ErrnoException | null)?.code === "ENOSPC") return true;
return error instanceof Error && /No space left on device/i.test(error.message);
}

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import { mkdir, rename, rm, stat } from "node:fs/promises";
import path from "node:path";
import { getLogger } from "@rakazo/logging";
import { resolveInside } from "@rakazo/media/node";
import type { MediaToolPaths, ProbedMedia } from "./media-folder-source-probe.js";
import { parseFfprobe, runMediaTool } from "./media-folder-source-probe.js";
import { assetDir, tempSibling } from "./media-ingest-files.js";
/*
* Proxy, poster and sprite generation with ffmpeg (argv only, never a shell).
*
* Videos: 720p (shorter side) H.264 with a keyframe every second, constant
* frame rate (variable-rate sources are normalized for frame-accurate cuts),
* stereo AAC, display rotation applied by ffmpeg's autorotate, HDR (PQ/HLG)
* tone-mapped to SDR BT.709 when zscale and tonemap are available. Photos get
* a resized JPEG proxy. Posters and sprites are JPEGs written with
* `-map_metadata -1`, so no capture date, GPS, or device tags survive.
* Every output is written to a temp name and renamed into place.
*/
const PROXY_SHORT_SIDE = 720;
const THUMB_WIDTH = 480;
const SPRITE_TILES = 10;
const SPRITE_TILE_WIDTH = 160;
const MAX_PROXY_FPS = 60;
const HDR_TRANSFERS = new Set(["smpte2084", "arib-std-b67"]);
export interface ProxyOutputs {
proxyPath: string;
thumbPath: string;
spritePath: string | null;
probe: ProbedMedia;
hdr: boolean;
tonemapped: boolean;
}
interface ProbeStream {
codec_type?: string;
color_transfer?: string;
}
/** Even-dimension scale so the shorter side is at most 720 px, never upscaled. */
const SCALE_720 =
`scale=w='if(gte(iw,ih),-2,trunc(min(${PROXY_SHORT_SIDE},iw)/2)*2)'` +
`:h='if(gte(iw,ih),trunc(min(${PROXY_SHORT_SIDE},ih)/2)*2,-2)'`;
const TONEMAP =
"zscale=t=linear:npl=100,format=gbrpf32le,zscale=p=bt709," +
"tonemap=tonemap=hable:desat=0,zscale=t=bt709:m=bt709:r=tv";
let tonemapSupport: Promise<boolean> | null = null;
/** Whether this ffmpeg build has zscale and tonemap (cached per process). */
function hasTonemapFilters(ffmpeg: string): Promise<boolean> {
tonemapSupport ??= runMediaTool(ffmpeg, ["-hide_banner", "-filters"])
.then(({ stdout }) => {
const text = stdout.toString("utf8");
return /\szscale\s/.test(text) && /\stonemap\s/.test(text);
})
.catch(() => false);
return tonemapSupport;
}
export async function probeOriginal(
file: string,
tools: MediaToolPaths,
signal?: AbortSignal,
): Promise<{ probe: ProbedMedia; hdr: boolean }> {
const { stdout } = await runMediaTool(
tools.ffprobePath ?? "ffprobe",
["-v", "error", "-print_format", "json", "-show_format", "-show_streams", "--", file],
{ signal },
);
const json = JSON.parse(stdout.toString("utf8")) as { streams?: ProbeStream[] };
const video = json.streams?.find((stream) => stream.codec_type === "video");
return {
probe: parseFfprobe(json as Parameters<typeof parseFfprobe>[0]),
hdr: HDR_TRANSFERS.has(video?.color_transfer ?? ""),
};
}
async function ffmpegTo(
target: string,
ext: string,
build: (out: string) => string[],
tools: MediaToolPaths,
signal?: AbortSignal,
): Promise<void> {
await mkdir(path.dirname(target), { recursive: true });
const temp = tempSibling(target, ext);
try {
await runMediaTool(tools.ffmpegPath ?? "ffmpeg", build(temp), { signal });
if ((await stat(temp)).size === 0) throw new Error("ffmpeg produced an empty file");
await rename(temp, target);
} finally {
await rm(temp, { force: true });
}
}
function proxyFps(probe: ProbedMedia): number {
const fps = probe.fps && probe.fps > 0 ? probe.fps : 30;
return Math.min(MAX_PROXY_FPS, Math.max(1, Math.round(fps)));
}
/** Build proxy, poster, and sprite for one original. Returns media-root-relative paths. */
export async function buildProxy(input: {
mediaRoot: string;
spaceId: string;
assetId: string;
original: string;
still: boolean;
tools?: MediaToolPaths;
signal?: AbortSignal;
}): Promise<ProxyOutputs> {
const tools = input.tools ?? {};
const signal = input.signal;
const dir = assetDir(input.spaceId, input.assetId);
const { probe, hdr } = await probeOriginal(input.original, tools, signal);
const still = input.still || !probe.hasVideo || !probe.durationMs;
const ffmpeg = tools.ffmpegPath ?? "ffmpeg";
let tonemapped = false;
const filters: string[] = [];
if (hdr) {
if (await hasTonemapFilters(ffmpeg)) {
filters.push(TONEMAP);
tonemapped = true;
} else {
getLogger().warn("media proxy: HDR source kept without tone mapping", {
reason: "ffmpeg lacks zscale or tonemap",
});
}
}
filters.push(SCALE_720);
const thumbRel = `${dir}/thumb.jpg`;
const thumb = await resolveInside(input.mediaRoot, thumbRel);
if (still) {
const proxyRel = `${dir}/proxy.jpg`;
const proxy = await resolveInside(input.mediaRoot, proxyRel);
await ffmpegTo(
proxy,
".jpg",
(out) => [
...["-v", "error", "-y", "-i", input.original, "-map", "0:v:0"],
...["-map_metadata", "-1", "-frames:v", "1", "-update", "1"],
...["-vf", [...filters, "format=yuvj420p"].join(","), "-q:v", "3", out],
],
tools,
signal,
);
await writeThumb(proxy, thumb, 0, tools, signal);
return { proxyPath: proxyRel, thumbPath: thumbRel, spritePath: null, probe, hdr, tonemapped };
}
const proxyRel = `${dir}/proxy.mp4`;
const proxy = await resolveInside(input.mediaRoot, proxyRel);
filters.push(`fps=${proxyFps(probe)}`, "format=yuv420p");
await ffmpegTo(
proxy,
".mp4",
(out) => [
...["-v", "error", "-y", "-i", input.original],
...["-map", "0:v:0", "-map", "0:a:0?", "-map_metadata", "-1", "-map_chapters", "-1"],
...["-vf", filters.join(",")],
...["-c:v", "libx264", "-preset", "veryfast", "-crf", "23", "-profile:v", "high"],
...["-force_key_frames", "expr:gte(t,n_forced*1)", "-sc_threshold", "0"],
...["-c:a", "aac", "-b:a", "128k", "-ac", "2", "-ar", "48000"],
...["-movflags", "+faststart", "-f", "mp4", out],
],
tools,
signal,
);
const durationMs = probe.durationMs ?? 1000;
await writeThumb(proxy, thumb, Math.min(1000, Math.floor(durationMs / 2)), tools, signal);
const spriteRel = `${dir}/sprite.jpg`;
const sprite = await resolveInside(input.mediaRoot, spriteRel);
const sampleFps = (SPRITE_TILES / Math.max(0.1, durationMs / 1000)).toFixed(6);
await ffmpegTo(
sprite,
".jpg",
(out) => [
...["-v", "error", "-y", "-i", proxy, "-map", "0:v:0", "-map_metadata", "-1"],
...["-vf", `fps=${sampleFps},scale=${SPRITE_TILE_WIDTH}:-2,tile=${SPRITE_TILES}x1`],
...["-frames:v", "1", "-update", "1", "-q:v", "4", out],
],
tools,
signal,
);
return { proxyPath: proxyRel, thumbPath: thumbRel, spritePath: spriteRel, probe, hdr, tonemapped };
}
async function writeThumb(
source: string,
target: string,
atMs: number,
tools: MediaToolPaths,
signal?: AbortSignal,
): Promise<void> {
await ffmpegTo(
target,
".jpg",
(out) => [
...["-v", "error", "-y", "-ss", (atMs / 1000).toFixed(3), "-i", source],
...["-map", "0:v:0", "-map_metadata", "-1", "-frames:v", "1", "-update", "1"],
...["-vf", `scale='min(${THUMB_WIDTH},iw)':-2`, "-q:v", "3", out],
],
tools,
signal,
);
}

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@ -0,0 +1,452 @@
import { rename } from "node:fs/promises";
import path from "node:path";
import type { MediaJobHandlers, MediaSourceProvider } from "@rakazo/adapter-kit";
import {
mediaAnalyzeJob,
mediaClusterJob,
mediaProxyJob,
mediaSyncJob,
} from "@rakazo/adapter-kit";
import type { MediaSourceKind } from "@rakazo/contracts";
import { CLIENT_PUSHED_MEDIA_SOURCES } from "@rakazo/contracts";
import type { MediaSourceRecord } from "@rakazo/db";
import { clientMediaItemToSourceItem, InvalidMediaInputError } from "@rakazo/db";
import { getLogger } from "@rakazo/logging";
import { assertInside, resolveInside } from "@rakazo/media/node";
import type { MediaIngestService, MediaServiceDeps } from "./media-context.js";
import type { MediaToolPaths } from "./media-folder-source-probe.js";
import { analysisInputPath, analyzeAsset, MEDIA_ANALYSIS_VERSION } from "./media-ingest-analyze.js";
import { clusterSpace } from "./media-ingest-cluster.js";
import {
assetDir,
deleteMediaPaths,
errorMessage,
isDiskFull,
moveFile,
originalExtension,
publishSafe,
sha256File,
} from "./media-ingest-files.js";
import { buildProxy } from "./media-ingest-proxy.js";
/*
* Media ingest: client pushes, uploads, and the sync → proxy → analyze →
* cluster job chain. Jobs carry only record ids; every step re-reads its
* record, scopes by the owning space, and is safe to repeat.
*
* A full sync walks every page from the start on each run: positional cursors
* (folder paths) cannot express "changed since", and per-item revisions make
* repeated pages cheap. Unchanged items enqueue nothing. Memory stays bounded
* by the page size plus the set of external ids seen.
*/
export const MEDIA_SYNC_PAGE = 500;
/** Clustering waits for a quiet period so a burst of ingest work clusters once. */
export const MEDIA_CLUSTER_DEBOUNCE_MS = 30_000;
const SERVER_SOURCES = ["folder", "emulator"] as const;
const REMOVE_BATCH = 500;
type ServerSourceKind = (typeof SERVER_SOURCES)[number];
function isServerSource(kind: MediaSourceKind): kind is ServerSourceKind {
return (SERVER_SOURCES as readonly string[]).includes(kind);
}
function isClientPushed(kind: MediaSourceKind): boolean {
return (CLIENT_PUSHED_MEDIA_SOURCES as readonly string[]).includes(kind);
}
async function scheduleCluster(deps: MediaServiceDeps, spaceId: string): Promise<void> {
await deps.jobs.enqueue(
mediaClusterJob(spaceId, new Date(deps.now().getTime() + MEDIA_CLUSTER_DEBOUNCE_MS)),
);
}
/** Every derived file of a source's assets lives in their asset directories. */
async function sourceAssetDirs(
deps: MediaServiceDeps,
spaceId: string,
sourceId: string,
externalIds?: string[],
): Promise<string[]> {
const rows = await deps.prisma.mediaAsset.findMany({
where: { spaceId, sourceId, ...(externalIds ? { externalId: { in: externalIds } } : {}) },
select: { id: true },
});
return rows.map((row) => assetDir(spaceId, row.id));
}
/** Delete assets by external id along with every file derived from them. */
async function removeItems(
deps: MediaServiceDeps,
spaceId: string,
sourceId: string,
externalIds: string[],
): Promise<number> {
let deleted = 0;
for (let offset = 0; offset < externalIds.length; offset += REMOVE_BATCH) {
const batch = externalIds.slice(offset, offset + REMOVE_BATCH);
const dirs = await sourceAssetDirs(deps, spaceId, sourceId, batch);
const removed = await deps.repos.removeSourceItems(spaceId, sourceId, batch);
await deleteMediaPaths(deps.mediaRoot, [...removed.paths, ...dirs]);
deleted += removed.deleted;
}
return deleted;
}
export function createMediaIngestService(deps: MediaServiceDeps): MediaIngestService {
return {
async pushItems(actor, input) {
const source = await deps.repos.getSource(actor.spaceId, input.sourceId);
if (!isClientPushed(source.kind)) {
throw new InvalidMediaInputError("Only device sources accept pushed items");
}
const upserted = await deps.repos.upsertSourceItems(
actor.spaceId,
source.id,
input.items.map(clientMediaItemToSourceItem),
);
const deleted = await removeItems(deps, actor.spaceId, source.id, [
...new Set(input.deletedExternalIds),
]);
const updated = await deps.repos.updateSourceSync(
actor.spaceId,
source.id,
input.complete
? {
status: "idle",
lastSyncCursor: input.syncToken,
lastSyncedAt: deps.now(),
error: null,
}
: { status: "syncing", error: null },
);
await publishSafe(deps, actor.spaceId, {
type: "media.source",
sourceId: source.id,
status: updated.status,
error: null,
});
// Pushed assets wait for an upload; proxy work starts in uploadCompleted.
if (input.complete) await scheduleCluster(deps, actor.spaceId);
return {
created: upserted.created,
updated: upserted.updated,
unchanged: upserted.unchanged,
deleted,
};
},
async requestSync(actor, sourceId) {
const source = await deps.repos.getSource(actor.spaceId, sourceId);
if (!isServerSource(source.kind)) {
throw new InvalidMediaInputError("This source syncs from its device");
}
await deps.jobs.enqueue(mediaSyncJob(source.id));
},
async uploadCompleted(actor, input) {
const ext = originalExtension(input.fileName);
if (!ext) throw new InvalidMediaInputError("Unsupported media file type");
if (!/^[0-9a-f]{64}$/.test(input.sha256)) {
throw new InvalidMediaInputError("Invalid content hash");
}
const asset = await deps.repos.getAssetRecord(actor.spaceId, input.assetId);
if (asset.storage === "referenced") {
throw new InvalidMediaInputError("This asset is read from its source");
}
const temp = await assertInside(deps.mediaRoot, input.tempPath);
const uploads = await resolveInside(deps.mediaRoot, `${actor.spaceId}/uploads`);
const relative = path.relative(uploads, temp);
if (!relative || relative.startsWith("..") || path.isAbsolute(relative)) {
throw new InvalidMediaInputError("Upload is outside this space's upload area");
}
const actual = await sha256File(temp);
if (actual !== input.sha256) throw new InvalidMediaInputError("Content hash mismatch");
const storagePath = `${assetDir(actor.spaceId, asset.id)}/original.${ext}`;
const target = await resolveInside(deps.mediaRoot, storagePath);
await moveFile(temp, target);
try {
const upload = await deps.prisma.mediaUpload.findFirst({
where: { spaceId: actor.spaceId, assetId: asset.id, status: "open", sha256: actual },
orderBy: [{ createdAt: "desc" }, { id: "desc" }],
select: { id: true },
});
if (upload) {
// Closes the upload and points the asset at the stored original in one transaction.
await deps.repos.completeUpload(actor.spaceId, upload.id, { storagePath });
} else {
const result = await deps.prisma.mediaAsset.updateMany({
where: { id: asset.id, spaceId: actor.spaceId },
data: {
storage: "uploaded",
storagePath,
contentHash: actual,
ingestState: "indexed",
ingestError: null,
},
});
if (result.count !== 1) throw new InvalidMediaInputError("Asset no longer exists");
}
} catch (error) {
await rename(target, temp).catch(() => undefined);
throw error;
}
if (asset.storagePath && asset.storagePath !== storagePath) {
await deleteMediaPaths(deps.mediaRoot, [asset.storagePath]);
}
await publishSafe(deps, actor.spaceId, {
type: "media.asset",
assetId: asset.id,
ingestState: "indexed",
});
await deps.jobs.enqueue(mediaProxyJob(asset.id));
},
async recluster(actor) {
await deps.jobs.enqueue(mediaClusterJob(actor.spaceId));
},
async removeSource(actor, sourceId) {
const source = await deps.repos.getSource(actor.spaceId, sourceId);
await deps.jobs.cancel(mediaSyncJob(source.id).replaceKey as string);
await deleteMediaPaths(deps.mediaRoot, await sourceAssetDirs(deps, actor.spaceId, source.id));
await deps.repos.removeSource(actor.spaceId, source.id);
await scheduleCluster(deps, actor.spaceId);
},
};
}
// ---------------------------------------------------------------------------
// Job handlers
// ---------------------------------------------------------------------------
export interface MediaIngestHandlerOptions extends MediaToolPaths {
/** Aborts long-running ingest work when the worker shuts down. */
signal?: AbortSignal;
}
async function syncSource(
deps: MediaServiceDeps,
source: MediaSourceRecord,
provider: MediaSourceProvider,
signal?: AbortSignal,
): Promise<{ changed: number; deleted: number }> {
const seen = new Set<string>();
let cursor: string | null = null;
let changed = 0;
do {
signal?.throwIfAborted();
const page = await provider.list({
config: source.config,
cursor,
limit: MEDIA_SYNC_PAGE,
...(signal ? { signal } : {}),
});
for (const item of page.items) seen.add(item.externalId);
const result = await deps.repos.upsertSourceItems(source.spaceId, source.id, page.items);
for (const assetId of result.changedAssetIds) await deps.jobs.enqueue(mediaProxyJob(assetId));
changed += result.changedAssetIds.length;
cursor = page.nextCursor;
} while (cursor);
// Items gone from the source. An empty listing of a non-empty library is
// treated as an unavailable source (unmounted disk), never as mass deletion.
const known = await deps.prisma.mediaAsset.findMany({
where: { spaceId: source.spaceId, sourceId: source.id },
select: { externalId: true },
});
if (seen.size === 0 && known.length > 0) {
throw new Error("The source listed no files; check that it is reachable");
}
const gone = known.map((row) => row.externalId).filter((id) => !seen.has(id));
const deleted = await removeItems(deps, source.spaceId, source.id, gone);
return { changed, deleted };
}
export function createMediaIngestHandlers(
deps: MediaServiceDeps,
options: MediaIngestHandlerOptions = {},
): Pick<MediaJobHandlers, "media.sync" | "media.proxy" | "media.analyze" | "media.cluster"> {
const { signal } = options;
const tools: MediaToolPaths = {
...(options.ffmpegPath ? { ffmpegPath: options.ffmpegPath } : {}),
...(options.ffprobePath ? { ffprobePath: options.ffprobePath } : {}),
};
const setAssetState = async (
spaceId: string,
assetId: string,
from: Parameters<MediaServiceDeps["repos"]["transitionIngestState"]>[2]["from"],
to: Parameters<MediaServiceDeps["repos"]["transitionIngestState"]>[2]["to"],
error?: string,
) => {
const applied = await deps.repos.transitionIngestState(spaceId, assetId, {
from,
to,
...(error !== undefined ? { error } : {}),
});
if (applied) await publishSafe(deps, spaceId, { type: "media.asset", assetId, ingestState: to });
return applied;
};
/** Absolute path of the original, or null for a device asset that has not been uploaded. */
const originalOf = async (
spaceId: string,
asset: Awaited<ReturnType<MediaServiceDeps["repos"]["getAssetRecord"]>>,
): Promise<{ path: string; referenced: boolean } | null> => {
if (asset.storage === "uploaded" && asset.storagePath) {
return { path: await resolveInside(deps.mediaRoot, asset.storagePath), referenced: false };
}
if (asset.storage !== "referenced") return null;
const source = await deps.repos.getSource(spaceId, asset.sourceId);
const provider = isServerSource(source.kind) ? deps.sources[source.kind] : undefined;
if (!provider) throw new Error(`No ${source.kind} source provider is configured`);
return { path: await provider.resolve(source.config, asset.externalId), referenced: true };
};
return {
async "media.sync"({ sourceId }) {
const spaceId = await deps.repos.mediaSpaceOf("source", sourceId);
if (!spaceId) return;
const source = await deps.repos.getSource(spaceId, sourceId);
const provider = isServerSource(source.kind) ? deps.sources[source.kind] : undefined;
if (!provider) {
const error = `No ${source.kind} source provider is configured`;
await deps.repos.updateSourceSync(spaceId, sourceId, { status: "unavailable", error });
await publishSafe(deps, spaceId, {
type: "media.source",
sourceId,
status: "unavailable",
error,
});
return;
}
await deps.repos.updateSourceSync(spaceId, sourceId, { status: "syncing", error: null });
await publishSafe(deps, spaceId, { type: "media.source", sourceId, status: "syncing" });
try {
const { changed, deleted } = await syncSource(deps, source, provider, signal);
await deps.repos.updateSourceSync(spaceId, sourceId, {
status: "idle",
lastSyncedAt: deps.now(),
error: null,
});
await publishSafe(deps, spaceId, { type: "media.source", sourceId, status: "idle" });
if (changed + deleted > 0) await scheduleCluster(deps, spaceId);
} catch (error) {
if (signal?.aborted) throw error;
const message = errorMessage(error);
getLogger().error("media sync failed", error, { sourceId });
await deps.repos.updateSourceSync(spaceId, sourceId, { status: "error", error: message });
await publishSafe(deps, spaceId, {
type: "media.source",
sourceId,
status: "error",
error: message,
});
}
},
async "media.proxy"({ assetId }) {
const spaceId = await deps.repos.mediaSpaceOf("asset", assetId);
if (!spaceId) return;
const asset = await deps.repos.getAssetRecord(spaceId, assetId);
if (asset.storage === "remote") return;
const started = await setAssetState(
spaceId,
assetId,
["indexed", "proxying", "proxied", "analyzing", "analyzed", "failed"],
"proxying",
);
if (!started) return;
try {
const original = await originalOf(spaceId, asset);
if (!original) throw new Error("The original has not been uploaded");
const contentHash = await sha256File(original.path, signal);
const outputs = await buildProxy({
mediaRoot: deps.mediaRoot,
spaceId,
assetId,
original: original.path,
still: asset.kind === "photo",
tools,
...(signal ? { signal } : {}),
});
const still = outputs.spritePath === null;
await deps.repos.recordProxy(spaceId, assetId, {
contentHash,
proxyPath: outputs.proxyPath,
thumbPath: outputs.thumbPath,
spritePath: outputs.spritePath,
durationMs: still ? asset.durationMs : outputs.probe.durationMs,
width: outputs.probe.width,
height: outputs.probe.height,
fps: still ? asset.fps : outputs.probe.fps,
codec: outputs.probe.codec,
orientation: outputs.probe.rotation,
});
await publishSafe(deps, spaceId, { type: "media.asset", assetId, ingestState: "proxied" });
await deps.jobs.enqueue(mediaAnalyzeJob(assetId));
} catch (error) {
if (signal?.aborted) throw error;
getLogger().error("media proxy failed", error, { assetId });
if (isDiskFull(error)) {
await setAssetState(spaceId, assetId, ["proxying"], "failed", "Disk is full; retrying");
throw error;
}
await setAssetState(spaceId, assetId, ["proxying"], "failed", errorMessage(error));
}
},
async "media.analyze"({ assetId, kinds }) {
const inference = deps.inference;
if (!inference) return;
const spaceId = await deps.repos.mediaSpaceOf("asset", assetId);
if (!spaceId) return;
const asset = await deps.repos.getAssetRecord(spaceId, assetId);
if (!asset.proxyPath) return;
const started = await setAssetState(
spaceId,
assetId,
["proxied", "analyzing", "analyzed", "failed"],
"analyzing",
);
if (!started) return;
try {
const original = asset.storage === "referenced" ? await originalOf(spaceId, asset) : null;
const inputPath = await analysisInputPath({
mediaRoot: deps.mediaRoot,
proxyPath: asset.proxyPath,
referencedOriginal: original?.path ?? null,
});
const outcome = await analyzeAsset({
deps,
inference,
spaceId,
asset,
inputPath,
...(kinds ? { kinds } : {}),
});
await deps.repos.recordAnalysisVersion(
spaceId,
assetId,
MEDIA_ANALYSIS_VERSION,
outcome.qualityScore,
);
await publishSafe(deps, spaceId, { type: "media.asset", assetId, ingestState: "analyzed" });
await scheduleCluster(deps, spaceId);
} catch (error) {
if (signal?.aborted) throw error;
getLogger().error("media analysis failed", error, { assetId });
await setAssetState(spaceId, assetId, ["analyzing"], "failed", errorMessage(error));
if (isDiskFull(error)) throw error;
}
},
async "media.cluster"({ spaceId }) {
await clusterSpace(deps, spaceId, signal ? { signal } : {});
},
};
}