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

apps/worker/src/processors/maintenance.ts

@@ -333,7 +333,10 @@ export async function processMemorySync(ctx: WorkerContext): Promise<number> {
   return updates;
 }
 
-/** BUILD_TRAINING_SAMPLE (spec §33): exportera korrigeringar MED samtycke till AAMOS. */
+/** BUILD_TRAINING_SAMPLE (spec §33): bank eligible corrections to an app-owned,
+ *  versioned training dataset. In Skiva 1 this is local storage, not an external
+ *  AAMOS/Gemini runTask call, so the job never throws when AAMOS_MODE=gemini.
+ */
 export async function processTrainingExport(ctx: WorkerContext): Promise<number> {
   const corrections = await ctx.db
     .select()
@@ -348,37 +351,30 @@ export async function processTrainingExport(ctx: WorkerContext): Promise<number>
 
   if (eligible.length === 0) return 0;
 
-  const result = await ctx.aamos.runTask(
-    "EXPORT_TRAINING_SAMPLE",
-    {
-      marketLocale: "sv-SE",
-      samples: eligible.map((c) => ({
-        taskType: c.taskType,
-        aiOutput: c.aiOutput as Record<string, unknown>,
-        userCorrection: c.userCorrection as Record<string, unknown>,
-        modelVersion: c.modelVersion ?? null,
-        promptVersion: c.promptVersion ?? null,
-      })),
-    },
-    {
-      correlationId: `training-export-${Date.now()}`,
-      consentFlags: {
-        personalization: false,
-        anonymizedImprovement: true,
-        imageTraining: false,
-      },
-    },
-  );
+  const version = "v1";
+  const batchId = `cibello-local-${version}-${Date.now()}`;
+  const exportedAt = new Date();
 
-  if (result.status !== "ok" || !result.output) {
-    throw new Error(`AAMOS training export failed: ${result.error ?? "unknown"}`);
-  }
-
-  const batchId = result.output.batchId;
   for (const correction of eligible) {
+    const userCorrection = correction.userCorrection as Record<string, unknown>;
+    await ctx.db.insert(schema.aiTrainingBank).values({
+      correctionId: correction.id,
+      scanJobId: correction.scanJobId,
+      version,
+      taskType: correction.taskType,
+      imageS3Key: correction.imageS3Key,
+      proposal: (correction.proposal ?? {}) as Record<string, unknown>,
+      action: String(userCorrection.action ?? "unknown"),
+      corrected: (userCorrection.corrected ?? null) as Record<string, unknown> | null,
+      modelVersion: correction.modelVersion,
+      promptVersion: correction.promptVersion,
+      consentSnapshot: correction.consentSnapshot,
+      exportedAt,
+    });
+
     await ctx.db
       .update(schema.aiCorrections)
-      .set({ exportedToTraining: new Date(), trainingBatchId: batchId })
+      .set({ exportedToTraining: exportedAt, trainingBatchId: batchId })
       .where(eq(schema.aiCorrections.id, correction.id));
   }