690615:1449 237 #01
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// File: backend/tests/integration/ai/sandbox-runtime-params.spec.ts
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// Change Log:
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// - 2026-06-15: Created integration test for runtime parameters application to sandbox (T043)
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import { Test, TestingModule } from '@nestjs/testing';
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import { TypeOrmModule } from '@nestjs/typeorm';
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import { Queue } from 'bullmq';
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import { AiBatchProcessor } from '../../../src/modules/ai/processors/ai-batch.processor';
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import { AiPolicyService } from '../../../src/modules/ai/services/ai-policy.service';
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import { AiPromptsService } from '../../../src/modules/ai/prompts/ai-prompts.service';
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import { AiExecutionProfile } from '../../../src/modules/ai/entities/ai-execution-profile.entity';
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import { AiSandboxProfile } from '../../../src/modules/ai/entities/ai-sandbox-profile.entity';
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import { AiPrompt } from '../../../src/modules/ai/prompts/ai-prompts.entity';
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import { DataSource } from 'typeorm';
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import IORedis from 'ioredis';
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describe('Sandbox Runtime Parameters Integration Tests (T043)', () => {
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let _processor: AiBatchProcessor;
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let aiPolicyService: AiPolicyService;
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let aiPromptsService: AiPromptsService;
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let aiBatchQueue: Queue;
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let dataSource: DataSource;
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let redis: IORedis;
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beforeAll(async () => {
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redis = new IORedis({
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host: process.env.REDIS_HOST || 'localhost',
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port: Number(process.env.REDIS_PORT || '6379'),
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});
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aiBatchQueue = new Queue('ai-batch', {
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connection: redis,
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});
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const module: TestingModule = await Test.createTestingModule({
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imports: [
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TypeOrmModule.forRoot({
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type: 'mariadb',
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host: process.env.DB_HOST || 'localhost',
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port: Number(process.env.DB_PORT || '3306'),
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username: process.env.DB_USER || 'root',
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password: process.env.DB_PASSWORD || '',
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database: process.env.DB_NAME || 'lcbp3_test',
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entities: [AiExecutionProfile, AiSandboxProfile, AiPrompt],
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synchronize: false,
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}),
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TypeOrmModule.forFeature([
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AiExecutionProfile,
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AiSandboxProfile,
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AiPrompt,
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]),
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],
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providers: [AiBatchProcessor, AiPolicyService, AiPromptsService],
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}).compile();
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_processor = module.get<AiBatchProcessor>(AiBatchProcessor);
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aiPolicyService = module.get<AiPolicyService>(AiPolicyService);
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aiPromptsService = module.get<AiPromptsService>(AiPromptsService);
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dataSource = module.get<DataSource>(DataSource);
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});
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afterAll(async () => {
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await aiBatchQueue.close();
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await redis.quit();
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await dataSource.destroy();
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});
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describe('Runtime Parameters Application', () => {
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it('ควรใช้ custom profile parameters เมื่อระบุ profileId ใน sandbox-rag-prep job', async () => {
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// สร้าง custom execution profile
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const profileRepo = dataSource.getRepository(AiExecutionProfile);
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const customProfile = profileRepo.create({
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profileName: 'custom-rag-profile',
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canonicalModel: 'np-dms-ai',
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temperature: 0.2,
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topP: 0.7,
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maxTokens: 2048,
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numCtx: 4096,
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repeatPenalty: 1.2,
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keepAliveSeconds: 30,
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isActive: true,
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createdBy: 1,
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});
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await profileRepo.save(customProfile);
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// สร้าง active prompt สำหรับ rag_prep_prompt
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const prompt = await aiPromptsService.create(
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'rag_prep_prompt',
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{ template: 'Chunk this text: {{text}}' },
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1
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);
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await aiPromptsService.activate(
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'rag_prep_prompt',
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prompt.versionNumber,
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1
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);
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const idempotencyKey = 'test-runtime-params-001';
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await aiBatchQueue.add('sandbox-rag-prep', {
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jobType: 'sandbox-rag-prep',
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documentPublicId: 'test-doc-001',
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projectPublicId: 'default',
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payload: {
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text: 'Test text for runtime parameters',
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profileId: 'custom-rag-profile',
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},
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idempotencyKey,
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});
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// Poll Redis for result
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let result = null;
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for (let i = 0; i < 30; i++) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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const cached = await redis.get(`ai:rag:result:${idempotencyKey}`);
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if (cached) {
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result = JSON.parse(cached);
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break;
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}
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}
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expect(result).toBeDefined();
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expect((result as { status: string }).status).toBe('completed');
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// ลบข้อมูลทดสอบ
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await aiPromptsService.delete('rag_prep_prompt', prompt.versionNumber, 1);
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await profileRepo.delete(customProfile.id);
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}, 60000);
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it('ควร fallback ไป standard profile เมื่อ profileId ไม่มีอยู่', async () => {
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const prompt = await aiPromptsService.create(
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'rag_prep_prompt',
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{ template: 'Chunk this text: {{text}}' },
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1
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);
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await aiPromptsService.activate(
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'rag_prep_prompt',
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prompt.versionNumber,
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1
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);
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const idempotencyKey = 'test-runtime-params-fallback';
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await aiBatchQueue.add('sandbox-rag-prep', {
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jobType: 'sandbox-rag-prep',
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documentPublicId: 'test-doc-002',
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projectPublicId: 'default',
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payload: {
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text: 'Test text for fallback',
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profileId: 'non-existent-profile',
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},
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idempotencyKey,
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});
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// Poll Redis for result
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let result = null;
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for (let i = 0; i < 30; i++) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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const cached = await redis.get(`ai:rag:result:${idempotencyKey}`);
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if (cached) {
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result = JSON.parse(cached);
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break;
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}
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}
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expect(result).toBeDefined();
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expect((result as { status: string }).status).toBe('completed');
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// ลบข้อมูลทดสอบ
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await aiPromptsService.delete('rag_prep_prompt', prompt.versionNumber, 1);
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}, 60000);
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it('ควรใช้ sandbox draft parameters เมื่อระบุใน sandbox-ai-extract job', async () => {
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const sandboxRepo = dataSource.getRepository(AiSandboxProfile);
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const sandboxDraft = sandboxRepo.create({
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profileName: 'standard',
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canonicalModel: 'np-dms-ai',
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temperature: 0.3,
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topP: 0.6,
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maxTokens: 2048,
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numCtx: 4096,
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repeatPenalty: 1.1,
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keepAliveSeconds: 30,
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updatedBy: 1,
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});
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await sandboxRepo.save(sandboxDraft);
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const prompt = await aiPromptsService.create(
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'ocr_extraction',
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{ template: 'Extract from {{ocr_text}}' },
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1
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);
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await aiPromptsService.activate(
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'ocr_extraction',
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prompt.versionNumber,
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1
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);
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const idempotencyKey = 'test-sandbox-draft-params';
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await aiBatchQueue.add('sandbox-ai-extract', {
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jobType: 'sandbox-ai-extract',
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documentPublicId: 'test-doc-003',
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projectPublicId: 'default',
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payload: {
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promptVersion: prompt.versionNumber,
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projectPublicId: 'default',
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},
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idempotencyKey,
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});
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// Poll Redis for result
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let result = null;
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for (let i = 0; i < 30; i++) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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const cached = await redis.get(`ai:rag:result:${idempotencyKey}`);
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if (cached) {
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result = JSON.parse(cached);
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break;
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}
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}
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expect(result).toBeDefined();
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expect((result as { status: string }).status).toBe('completed');
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// ลบข้อมูลทดสอบ
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await aiPromptsService.delete('ocr_extraction', prompt.versionNumber, 1);
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await sandboxRepo.delete(sandboxDraft.id);
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}, 60000);
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it('ควร apply runtime parameters จาก AiPolicyService.getSandboxParameters', async () => {
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const profileRepo = dataSource.getRepository(AiExecutionProfile);
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const testProfile = profileRepo.create({
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profileName: 'runtime-test-profile',
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canonicalModel: 'np-dms-ai',
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temperature: 0.15,
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topP: 0.65,
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maxTokens: 1024,
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numCtx: 2048,
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repeatPenalty: 1.05,
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keepAliveSeconds: 15,
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isActive: true,
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createdBy: 1,
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});
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await profileRepo.save(testProfile);
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// ทดสอบ getSandboxParameters
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const params = await aiPolicyService.getSandboxParameters(
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'runtime-test-profile'
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);
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expect(params).toBeDefined();
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expect(params.temperature).toBe(0.15);
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expect(params.topP).toBe(0.65);
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expect(params.maxTokens).toBe(1024);
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expect(params.numCtx).toBe(2048);
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expect(params.repeatPenalty).toBe(1.05);
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expect(params.keepAliveSeconds).toBe(15);
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// ลบข้อมูลทดสอบ
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await profileRepo.delete(testProfile.id);
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});
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it('ควร cache sandbox parameters ใน Redis เพื่อ performance', async () => {
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const profileRepo = dataSource.getRepository(AiExecutionProfile);
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const cacheTestProfile = profileRepo.create({
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profileName: 'cache-test-profile',
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canonicalModel: 'np-dms-ai',
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temperature: 0.25,
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topP: 0.75,
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maxTokens: 3072,
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numCtx: 6144,
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repeatPenalty: 1.15,
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keepAliveSeconds: 45,
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isActive: true,
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createdBy: 1,
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});
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await profileRepo.save(cacheTestProfile);
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// First call - should fetch from DB and cache
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const params1 =
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await aiPolicyService.getSandboxParameters('cache-test-profile');
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expect(params1.temperature).toBe(0.25);
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// Second call - should fetch from Redis cache
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const params2 =
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await aiPolicyService.getSandboxParameters('cache-test-profile');
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expect(params2.temperature).toBe(0.25);
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// Verify cache exists in Redis
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const cached = await redis.get('ai:policy:cache-test-profile');
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expect(cached).toBeDefined();
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// ลบข้อมูลทดสอบ
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await profileRepo.delete(cacheTestProfile.id);
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await redis.del('ai:policy:cache-test-profile');
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});
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});
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});
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@@ -0,0 +1,332 @@
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// File: backend/tests/integration/ai/sandbox-workflow.spec.ts
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// Change Log:
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// - 2026-06-15: Created integration test for 3-step sandbox workflow (T032)
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import { Test, TestingModule } from '@nestjs/testing';
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import { TypeOrmModule } from '@nestjs/typeorm';
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import { Queue } from 'bullmq';
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import { AiBatchProcessor } from '../../../src/modules/ai/processors/ai-batch.processor';
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import { AiPromptsService } from '../../../src/modules/ai/prompts/ai-prompts.service';
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import { AiPolicyService } from '../../../src/modules/ai/services/ai-policy.service';
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import { OcrService } from '../../../src/modules/ai/services/ocr.service';
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import { OllamaService } from '../../../src/modules/ai/services/ollama.service';
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import { SandboxOcrEngineService } from '../../../src/modules/ai/services/sandbox-ocr-engine.service';
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import { EmbeddingService } from '../../../src/modules/ai/services/embedding.service';
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import { AiRagService } from '../../../src/modules/ai/ai-rag.service';
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import { Attachment } from '../../../src/common/file-storage/entities/attachment.entity';
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import { Project } from '../../../src/modules/project/entities/project.entity';
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import { AiPrompt } from '../../../src/modules/ai/prompts/ai-prompts.entity';
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import { DataSource } from 'typeorm';
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import IORedis from 'ioredis';
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describe('3-Step Sandbox Workflow Integration Tests (T032)', () => {
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let _processor: AiBatchProcessor;
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let aiBatchQueue: Queue;
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let aiPromptsService: AiPromptsService;
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let dataSource: DataSource;
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let redis: IORedis;
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beforeAll(async () => {
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redis = new IORedis({
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host: process.env.REDIS_HOST || 'localhost',
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port: Number(process.env.REDIS_PORT || '6379'),
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});
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aiBatchQueue = new Queue('ai-batch', {
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connection: redis,
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});
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const module: TestingModule = await Test.createTestingModule({
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imports: [
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TypeOrmModule.forRoot({
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type: 'mariadb',
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host: process.env.DB_HOST || 'localhost',
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port: Number(process.env.DB_PORT || '3306'),
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username: process.env.DB_USER || 'root',
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password: process.env.DB_PASSWORD || '',
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database: process.env.DB_NAME || 'lcbp3_test',
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entities: [Attachment, Project, AiPrompt],
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synchronize: false,
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}),
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TypeOrmModule.forFeature([Attachment, Project, AiPrompt]),
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],
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providers: [
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AiBatchProcessor,
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AiPromptsService,
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AiPolicyService,
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OcrService,
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OllamaService,
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SandboxOcrEngineService,
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EmbeddingService,
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AiRagService,
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],
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}).compile();
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processor = module.get<AiBatchProcessor>(AiBatchProcessor);
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aiPromptsService = module.get<AiPromptsService>(AiPromptsService);
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dataSource = module.get<DataSource>(DataSource);
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});
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afterAll(async () => {
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await aiBatchQueue.close();
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await redis.quit();
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await dataSource.destroy();
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});
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describe('Step 1: OCR Extraction', () => {
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it('ควรส่งงาน sandbox-ocr และรับผลลัพธ์ OCR text จาก Redis', async () => {
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const idempotencyKey = 'test-sandbox-ocr-001';
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await aiBatchQueue.add('sandbox-ocr', {
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jobType: 'sandbox-ocr',
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documentPublicId: 'test-doc-001',
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projectPublicId: 'default',
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payload: {
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pdfPath: '/test/sample.pdf',
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engine: 'auto',
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},
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idempotencyKey,
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});
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// Poll Redis for result
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let result = null;
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for (let i = 0; i < 30; i++) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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const cached = await redis.get(`ai:ocr:result:${idempotencyKey}`);
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if (cached) {
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result = JSON.parse(cached);
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break;
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||||
}
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}
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expect(result).toBeDefined();
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expect((result as { status: string }).status).toBe('completed');
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expect((result as { ocrText: string }).ocrText).toBeDefined();
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expect(typeof (result as { ocrText: string }).ocrText).toBe('string');
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}, 60000);
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});
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describe('Step 2: AI Metadata Extraction', () => {
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it('ควรส่งงาน sandbox-ai-extract และรับผลลัพธ์ JSON metadata จาก Redis', async () => {
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// สร้าง active prompt สำหรับ ocr_extraction
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const prompt = await aiPromptsService.create(
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'ocr_extraction',
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{ template: 'Extract metadata from {{ocr_text}}' },
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||||
1
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);
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await aiPromptsService.activate(
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'ocr_extraction',
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prompt.versionNumber,
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1
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);
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const idempotencyKey = 'test-sandbox-extract-001';
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await aiBatchQueue.add('sandbox-ai-extract', {
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jobType: 'sandbox-ai-extract',
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documentPublicId: 'test-doc-002',
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projectPublicId: 'default',
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payload: {
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promptVersion: prompt.versionNumber,
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projectPublicId: 'default',
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||||
},
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||||
idempotencyKey,
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||||
});
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||||
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||||
// Poll Redis for result
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||||
let result = null;
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||||
for (let i = 0; i < 30; i++) {
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await new Promise((resolve) => setTimeout(resolve, 1000));
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||||
const cached = await redis.get(`ai:rag:result:${idempotencyKey}`);
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||||
if (cached) {
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||||
result = JSON.parse(cached);
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||||
break;
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||||
}
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||||
}
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||||
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||||
expect(result).toBeDefined();
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||||
expect((result as { status: string }).status).toBe('completed');
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||||
expect((result as { answer: unknown }).answer).toBeDefined();
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||||
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||||
// ลบข้อมูลทดสอบ
|
||||
await aiPromptsService.delete('ocr_extraction', prompt.versionNumber, 1);
|
||||
}, 60000);
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||||
});
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||||
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||||
describe('Step 3: RAG Prep', () => {
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||||
it('ควรส่งงาน sandbox-rag-prep และรับผลลัพธ์ chunks และ vectors จาก Redis', async () => {
|
||||
// สร้าง active prompt สำหรับ rag_prep_prompt
|
||||
const prompt = await aiPromptsService.create(
|
||||
'rag_prep_prompt',
|
||||
|
||||
{ template: 'Chunk this text: {{text}}' },
|
||||
1
|
||||
);
|
||||
await aiPromptsService.activate(
|
||||
'rag_prep_prompt',
|
||||
prompt.versionNumber,
|
||||
1
|
||||
);
|
||||
|
||||
const idempotencyKey = 'test-sandbox-rag-prep-001';
|
||||
await aiBatchQueue.add('sandbox-rag-prep', {
|
||||
jobType: 'sandbox-rag-prep',
|
||||
documentPublicId: 'test-doc-003',
|
||||
projectPublicId: 'default',
|
||||
payload: {
|
||||
text: 'This is a test document for RAG preparation. It contains multiple sections that should be chunked semantically.',
|
||||
profileId: 'standard',
|
||||
},
|
||||
idempotencyKey,
|
||||
});
|
||||
|
||||
// Poll Redis for result
|
||||
let result = null;
|
||||
for (let i = 0; i < 30; i++) {
|
||||
await new Promise((resolve) => setTimeout(resolve, 1000));
|
||||
const cached = await redis.get(`ai:rag:result:${idempotencyKey}`);
|
||||
if (cached) {
|
||||
result = JSON.parse(cached);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
expect(result).toBeDefined();
|
||||
expect((result as { status: string }).status).toBe('completed');
|
||||
expect((result as { ragChunks: unknown[] }).ragChunks).toBeDefined();
|
||||
expect(
|
||||
Array.isArray((result as { ragChunks: unknown[] }).ragChunks)
|
||||
).toBe(true);
|
||||
expect(
|
||||
(result as { ragChunks: unknown[] }).ragChunks.length
|
||||
).toBeGreaterThan(0);
|
||||
expect((result as { ragVectors: unknown[] }).ragVectors).toBeDefined();
|
||||
expect(
|
||||
Array.isArray((result as { ragVectors: unknown[] }).ragVectors)
|
||||
).toBe(true);
|
||||
|
||||
// ลบข้อมูลทดสอบ
|
||||
await aiPromptsService.delete('rag_prep_prompt', prompt.versionNumber, 1);
|
||||
}, 60000);
|
||||
});
|
||||
|
||||
describe('Full 3-Step Workflow Integration', () => {
|
||||
it('ควรรัน 3 steps ต่อเนื่องกัน OCR → AI Extract → RAG Prep', async () => {
|
||||
// สร้าง prompts ที่จำเป็น
|
||||
const ocrPrompt = await aiPromptsService.create(
|
||||
'ocr_extraction',
|
||||
{ template: 'Extract metadata from {{ocr_text}}' },
|
||||
1
|
||||
);
|
||||
|
||||
await aiPromptsService.activate(
|
||||
'ocr_extraction',
|
||||
ocrPrompt.versionNumber,
|
||||
1
|
||||
);
|
||||
|
||||
const ragPrompt = await aiPromptsService.create(
|
||||
'rag_prep_prompt',
|
||||
{ template: 'Chunk this text: {{text}}' },
|
||||
1
|
||||
);
|
||||
await aiPromptsService.activate(
|
||||
'rag_prep_prompt',
|
||||
ragPrompt.versionNumber,
|
||||
1
|
||||
);
|
||||
|
||||
const workflowId = 'test-full-workflow-001';
|
||||
|
||||
// Step 1: OCR
|
||||
await aiBatchQueue.add('sandbox-ocr', {
|
||||
jobType: 'sandbox-ocr',
|
||||
documentPublicId: workflowId,
|
||||
projectPublicId: 'default',
|
||||
payload: {
|
||||
pdfPath: '/test/sample.pdf',
|
||||
engine: 'auto',
|
||||
},
|
||||
idempotencyKey: `${workflowId}-ocr`,
|
||||
});
|
||||
|
||||
let ocrResult = null;
|
||||
for (let i = 0; i < 30; i++) {
|
||||
await new Promise((resolve) => setTimeout(resolve, 1000));
|
||||
const cached = await redis.get(`ai:ocr:result:${workflowId}-ocr`);
|
||||
if (cached) {
|
||||
ocrResult = JSON.parse(cached);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
expect(ocrResult).toBeDefined();
|
||||
expect((ocrResult as { status: string }).status).toBe('completed');
|
||||
const ocrText = (ocrResult as { ocrText: string }).ocrText;
|
||||
|
||||
// Step 2: AI Extract
|
||||
await aiBatchQueue.add('sandbox-ai-extract', {
|
||||
jobType: 'sandbox-ai-extract',
|
||||
documentPublicId: workflowId,
|
||||
projectPublicId: 'default',
|
||||
payload: {
|
||||
promptVersion: ocrPrompt.versionNumber,
|
||||
projectPublicId: 'default',
|
||||
},
|
||||
idempotencyKey: `${workflowId}-extract`,
|
||||
});
|
||||
|
||||
let extractResult = null;
|
||||
for (let i = 0; i < 30; i++) {
|
||||
await new Promise((resolve) => setTimeout(resolve, 1000));
|
||||
const cached = await redis.get(`ai:rag:result:${workflowId}-extract`);
|
||||
if (cached) {
|
||||
extractResult = JSON.parse(cached);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
expect(extractResult).toBeDefined();
|
||||
expect((extractResult as { status: string }).status).toBe('completed');
|
||||
expect((extractResult as { answer: unknown }).answer).toBeDefined();
|
||||
|
||||
// Step 3: RAG Prep
|
||||
await aiBatchQueue.add('sandbox-rag-prep', {
|
||||
jobType: 'sandbox-rag-prep',
|
||||
documentPublicId: workflowId,
|
||||
projectPublicId: 'default',
|
||||
payload: {
|
||||
text: ocrText || 'Fallback text for RAG prep',
|
||||
profileId: 'standard',
|
||||
},
|
||||
idempotencyKey: `${workflowId}-rag-prep`,
|
||||
});
|
||||
|
||||
let ragResult = null;
|
||||
|
||||
for (let i = 0; i < 30; i++) {
|
||||
await new Promise((resolve) => setTimeout(resolve, 1000));
|
||||
const cached = await redis.get(`ai:rag:result:${workflowId}-rag-prep`);
|
||||
if (cached) {
|
||||
ragResult = JSON.parse(cached);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
expect(ragResult).toBeDefined();
|
||||
expect((ragResult as { status: string }).status).toBe('completed');
|
||||
expect((ragResult as { ragChunks: unknown[] }).ragChunks).toBeDefined();
|
||||
expect((ragResult as { ragVectors: unknown[] }).ragVectors).toBeDefined();
|
||||
|
||||
// ลบข้อมูลทดสอบ
|
||||
await aiPromptsService.delete(
|
||||
'ocr_extraction',
|
||||
ocrPrompt.versionNumber,
|
||||
1
|
||||
);
|
||||
await aiPromptsService.delete(
|
||||
'rag_prep_prompt',
|
||||
ragPrompt.versionNumber,
|
||||
1
|
||||
);
|
||||
}, 180000);
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user