Sven (AAMOS AI)
107 lines
3.6 KiB
TypeScript
107 lines
3.6 KiB
TypeScript
import "./setup-env.js";
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import { describe, it, expect, beforeAll, afterAll } from "vitest";
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import { eq } from "drizzle-orm";
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import { createDatabase, closeDatabase, schema } from "@app/database";
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import { processTrainingExport } from "../src/processors/maintenance.js";
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describe("BUILD_TRAINING_SAMPLE banks locally", () => {
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const testDb = createDatabase(process.env.TEST_DATABASE_URL!);
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const email = "training-export-test@example.invalid";
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async function cleanup() {
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const existing = await testDb.db
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.select({ id: schema.users.id })
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.from(schema.users)
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.where(eq(schema.users.email, email));
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for (const u of existing) {
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await testDb.db.delete(schema.aiCorrections).where(eq(schema.aiCorrections.userId, u.id));
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await testDb.db.delete(schema.userConsents).where(eq(schema.userConsents.userId, u.id));
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await testDb.db.delete(schema.scanJobs).where(eq(schema.scanJobs.userId, u.id));
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await testDb.db.delete(schema.users).where(eq(schema.users.id, u.id));
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}
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}
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beforeAll(async () => {
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await cleanup();
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});
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afterAll(async () => {
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await cleanup();
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await closeDatabase();
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});
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it("banks eligible corrections locally and does not throw in gemini mode", async () => {
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const [user] = await testDb.db
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.insert(schema.users)
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.values({
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email: "training-export-test@example.invalid",
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passwordHash: "not-used",
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displayName: "Training Export Test",
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})
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.returning();
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const userId = user!.id;
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await testDb.db.insert(schema.userConsents).values([
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{ userId, kind: "anonymized_improvement", status: "granted" },
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{ userId, kind: "image_training", status: "granted" },
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]);
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const [job] = await testDb.db
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.insert(schema.scanJobs)
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.values({
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userId,
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scanType: "fridge",
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jobType: "ANALYZE_FRIDGE_IMAGE",
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status: "completed",
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s3Keys: ["fridge-scans/train.jpg"],
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result: { items: [] },
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})
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.returning();
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const [correction] = await testDb.db
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.insert(schema.aiCorrections)
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.values({
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scanJobId: job!.id,
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userId,
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taskType: "ANALYZE_FRIDGE_IMAGE",
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aiOutput: { raw: { items: [] } },
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proposal: { detectedName: "Mellanmjölk", confidence: 0.98 },
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userCorrection: {
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action: "accept",
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corrected: { displayName: "Mellanmjölk", quantity: 1, unit: "LITER" },
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},
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imageS3Key: "fridge-scans/train.jpg",
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modelVersion: "gemini-3.5-flash-lite",
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promptVersion: "gemini-fridge-v1",
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consentSnapshot: { anonymized_improvement: "granted", image_training: "granted" },
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})
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.returning();
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// Force gemini mode in environment so we prove the job does not call AAMOS.
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const previousMode = process.env.AAMOS_MODE;
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process.env.AAMOS_MODE = "gemini";
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const exported = await processTrainingExport({ db: testDb.db } as never);
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process.env.AAMOS_MODE = previousMode;
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expect(exported).toBe(1);
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const banked = await testDb.db
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.select()
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.from(schema.aiTrainingBank)
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.where(eq(schema.aiTrainingBank.correctionId, correction!.id));
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expect(banked).toHaveLength(1);
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expect(banked[0]!.version).toBe("v1");
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expect(banked[0]!.imageS3Key).toBe("fridge-scans/train.jpg");
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expect(banked[0]!.action).toBe("accept");
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const updated = await testDb.db
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.select()
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.from(schema.aiCorrections)
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.where(eq(schema.aiCorrections.id, correction!.id));
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expect(updated[0]!.exportedToTraining).not.toBeNull();
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expect(updated[0]!.trainingBatchId).toMatch(/^cibello-local-v1-/);
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});
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});
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