fix(skiva-1): spara accept, bildref, lokal träningsbank, lärande-loop-dok

- confirm-loop sparar nu även action=accept som positivt exempel i ai_corrections
- imageS3Key sparas vid image_training-samtycke, annars null
- ai_corrections.proposal lagrar det specifika AI-förslaget per item
- BUILD_TRAINING_SAMPLE bankar lokalt till ai_training_bank (ej externt runTask)
- Jobbet kastar aldrig i AAMOS_MODE=gemini
- Migration 0020: ai_corrections.image_s3_key/proposal + ai_training_bank
- docs/28-lärande-loop.md: datakontrakt, samtycke, retention, GDPR-radering
- Tester: accept + bildref (ja/nej) + lokal bank i gemini-läge
- REQUIRE_REAL=1 är AI-fokuserat i gemini-läge; staging mail/S3 får vara mock
This commit is contained in:
Sven (AAMOS AI)
2026-08-08 04:00:49 +07:00
parent 050c958285
commit c2cc3878dd
10 changed files with 646 additions and 43 deletions
+72 -15
View File
@@ -129,17 +129,12 @@ export async function scanRoutes(app: FastifyInstance) {
input.storageLocationId ?? (await defaultLocation(app, householdId, job.scanType));
const created: string[] = [];
const proposals = extractProposals(job);
for (const item of input.items) {
if (item.action === "reject") {
await recordCorrection(app, job, item.tempId ?? null, { action: "reject" });
continue;
}
if (item.action === "edit" || item.action === "add") {
await recordCorrection(app, job, item.tempId ?? null, {
action: item.action,
corrected: { name: item.displayName, quantity: item.quantity, unit: item.unit },
});
}
const proposal = findProposal(proposals, item.tempId);
await recordCorrection(app, job, item, proposal);
if (item.action === "reject") continue;
const locationId = item.storageLocationId ?? fallbackLocation;
if (!locationId)
throw errors.badRequest("storageLocationId saknas och ingen standardplats finns.");
@@ -334,6 +329,39 @@ async function defaultLocation(app: FastifyInstance, householdId: string, scanTy
return loc?.id ?? null;
}
type ProposalItem = {
tempId?: string;
detectedName?: string;
canonicalIngredientId?: string | null;
brand?: string | null;
estimatedQuantity?: number | null;
unit?: string | null;
bestBeforeDate?: string | null;
confidence?: number;
requiresConfirmation?: boolean;
};
function extractProposals(job: { result: unknown }): ProposalItem[] {
const result = job.result as Record<string, unknown> | null;
if (!result || !Array.isArray(result.items)) return [];
return result.items.map((it, idx) => ({
tempId: String(it.tempId ?? idx),
detectedName: String(it.detectedName ?? ""),
canonicalIngredientId: it.canonicalIngredientId ?? null,
brand: it.brand ?? null,
estimatedQuantity: it.estimatedQuantity ?? null,
unit: it.unit ?? null,
bestBeforeDate: it.bestBeforeDate ?? null,
confidence: typeof it.confidence === "number" ? it.confidence : null,
requiresConfirmation: typeof it.requiresConfirmation === "boolean" ? it.requiresConfirmation : null,
}));
}
function findProposal(proposals: ProposalItem[], tempId: string | undefined): ProposalItem | null {
if (tempId == null) return null;
return proposals.find((p) => p.tempId === tempId) ?? null;
}
async function recordCorrection(
app: FastifyInstance,
job: {
@@ -341,33 +369,62 @@ async function recordCorrection(
userId: string;
jobType: string;
result: unknown;
s3Keys: string[];
modelVersion: string | null;
promptVersion: string | null;
},
tempId: string | null,
correction: Record<string, unknown>,
item: {
tempId?: string;
action: "accept" | "edit" | "reject" | "add";
displayName: string;
quantity: number;
unit: string;
brand?: string;
canonicalIngredientId?: string;
bestBeforeDate?: string;
useByDate?: string;
},
proposal: ProposalItem | null,
) {
const consents = await app.db
.select()
.from(schema.userConsents)
.where(eq(schema.userConsents.userId, job.userId));
const snapshot = Object.fromEntries(consents.map((c) => [c.kind, c.status]));
const hasImageConsent = snapshot.image_training === "granted";
const userCorrection: Record<string, unknown> = { action: item.action };
if (item.action !== "reject") {
userCorrection.corrected = {
displayName: item.displayName,
canonicalIngredientId: item.canonicalIngredientId ?? null,
brand: item.brand ?? null,
quantity: item.quantity,
unit: item.unit,
bestBeforeDate: item.bestBeforeDate ?? null,
useByDate: item.useByDate ?? null,
};
}
await app.db.insert(schema.aiCorrections).values({
scanJobId: job.id,
userId: job.userId,
taskType: job.jobType,
aiOutput: { tempId, raw: job.result },
userCorrection: correction,
aiOutput: { raw: job.result },
proposal: proposal,
userCorrection,
imageS3Key: hasImageConsent && job.s3Keys.length > 0 ? job.s3Keys[0] : null,
modelVersion: job.modelVersion,
promptVersion: job.promptVersion,
consentSnapshot: snapshot,
});
await emitEvent(app.db, {
type: "AI_CORRECTED",
payload: {
scanJobId: job.id,
taskType: job.jobType,
field: String(correction.action ?? "unknown"),
field: item.action,
},
userId: job.userId,
});