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feat: add knowledge base apis (#802)
* feat: added API spec for agent inference platform * feat: add agent crud api and fix comments * feat: add ai model get api * feat: add authz tests * feat: add knowledgebase apis * feat: update prettier * feat: create classes for CR * feat: rename dir to knowledgebases * feat: add agent api * feat: add agent api * feat: add validation and tests * feat: update pipelineParameters to snake_case * fix: api authz test --------- Co-authored-by: Matthias Erll <merll@akamai.com> Co-authored-by: svcAPLBot <174728082+svcAPLBot@users.noreply.github.com>
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‎src/ai/AkamaiAgentCR.test.ts‎

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import { AkamaiAgentCR } from './AkamaiAgentCR'
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import { AplAgentRequest } from 'src/otomi-models'
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import { K8sResourceNotFound } from '../error'
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import * as aiModelHandler from './aiModelHandler'
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// Mock the aiModelHandler module
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jest.mock('./aiModelHandler')
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const mockedGetAIModels = aiModelHandler.getAIModels as jest.MockedFunction<typeof aiModelHandler.getAIModels>
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describe('AkamaiAgentCR', () => {
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const mockFoundationModel = {
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kind: 'AplAIModel',
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metadata: { name: 'gpt-4' },
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spec: {
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displayName: 'GPT-4',
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modelEndpoint: 'http://gpt-4.ai.svc.cluster.local',
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modelType: 'foundation' as const,
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},
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status: {
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conditions: [],
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phase: 'Ready' as const,
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},
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}
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const mockAgentRequest: AplAgentRequest = {
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kind: 'AkamaiAgent',
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metadata: {
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name: 'test-agent',
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},
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spec: {
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foundationModel: 'gpt-4',
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agentInstructions: 'You are a helpful assistant',
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knowledgeBase: 'test-kb',
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},
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}
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beforeEach(() => {
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jest.clearAllMocks()
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})
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describe('constructor', () => {
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test('should create AkamaiAgentCR with all properties', () => {
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', mockAgentRequest)
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expect(agentCR.apiVersion).toBeDefined()
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expect(agentCR.kind).toBeDefined()
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expect(agentCR.metadata.name).toBe('test-agent')
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expect(agentCR.metadata.namespace).toBe('team-team-123')
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expect(agentCR.metadata.labels?.['apl.io/teamId']).toBe('team-123')
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expect(agentCR.spec.foundationModel).toBe('gpt-4')
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expect(agentCR.spec.systemPrompt).toBe('You are a helpful assistant')
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expect(agentCR.spec.knowledgeBase).toBe('test-kb')
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})
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test('should set teamId label and not merge custom labels', () => {
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', mockAgentRequest)
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expect(agentCR.metadata.labels).toEqual({
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'apl.io/teamId': 'team-123',
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})
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// Custom labels from request are not merged in constructor
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expect(agentCR.metadata.labels?.['custom-label']).toBeUndefined()
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})
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test('should handle request without knowledgeBase', () => {
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const requestWithoutKB = {
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...mockAgentRequest,
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spec: {
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...mockAgentRequest.spec,
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knowledgeBase: undefined,
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},
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}
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', requestWithoutKB)
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expect(agentCR.spec.knowledgeBase).toBeUndefined()
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})
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})
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describe('toRecord', () => {
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test('should return serializable record', () => {
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', mockAgentRequest)
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const record = agentCR.toRecord()
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expect(record).toEqual({
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apiVersion: agentCR.apiVersion,
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kind: agentCR.kind,
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metadata: agentCR.metadata,
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spec: agentCR.spec,
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})
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})
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})
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describe('toApiResponse', () => {
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test('should transform to API response format', () => {
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', mockAgentRequest)
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const response = agentCR.toApiResponse('team-123')
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expect(response).toEqual({
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kind: 'AkamaiAgent',
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metadata: {
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name: 'test-agent',
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namespace: 'team-team-123',
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labels: {
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'apl.io/teamId': 'team-123',
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},
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},
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spec: {
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foundationModel: 'gpt-4',
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agentInstructions: 'You are a helpful assistant',
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knowledgeBase: 'test-kb',
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},
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status: {
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conditions: [
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{
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type: 'AgentDeployed',
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status: true,
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reason: 'Scheduled',
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message: 'Successfully deployed the Agent',
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},
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],
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},
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})
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})
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test('should handle empty knowledgeBase in response', () => {
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const requestWithoutKB = {
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...mockAgentRequest,
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spec: {
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...mockAgentRequest.spec,
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knowledgeBase: undefined,
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},
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}
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const agentCR = new AkamaiAgentCR('team-123', 'test-agent', requestWithoutKB)
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const response = agentCR.toApiResponse('team-123')
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expect(response.spec.knowledgeBase).toBe('')
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})
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})
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describe('create', () => {
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test('should create AkamaiAgentCR when foundation model exists', async () => {
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mockedGetAIModels.mockResolvedValue([mockFoundationModel as any])
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const result = await AkamaiAgentCR.create('team-123', 'test-agent', mockAgentRequest)
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expect(result).toBeInstanceOf(AkamaiAgentCR)
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expect(result.metadata.name).toBe('test-agent')
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expect(mockedGetAIModels).toHaveBeenCalledTimes(1)
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})
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test('should throw K8sResourceNotFound when foundation model does not exist', async () => {
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mockedGetAIModels.mockResolvedValue([])
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await expect(AkamaiAgentCR.create('team-123', 'test-agent', mockAgentRequest)).rejects.toThrow(
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K8sResourceNotFound,
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)
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await expect(AkamaiAgentCR.create('team-123', 'test-agent', mockAgentRequest)).rejects.toThrow(
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"Foundation model 'gpt-4' not found",
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)
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})
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test('should throw K8sResourceNotFound when foundation model has wrong type', async () => {
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const embeddingModel = {
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...mockFoundationModel,
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spec: {
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...mockFoundationModel.spec,
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modelType: 'embedding' as const,
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},
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}
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mockedGetAIModels.mockResolvedValue([embeddingModel as any])
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await expect(AkamaiAgentCR.create('team-123', 'test-agent', mockAgentRequest)).rejects.toThrow(
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K8sResourceNotFound,
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)
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})
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test('should throw error when foundationModel is undefined', async () => {
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const requestWithoutModel = {
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...mockAgentRequest,
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spec: {
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...mockAgentRequest.spec,
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foundationModel: undefined,
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},
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}
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mockedGetAIModels.mockResolvedValue([mockFoundationModel as any])
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await expect(AkamaiAgentCR.create('team-123', 'test-agent', requestWithoutModel as any)).rejects.toThrow(
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K8sResourceNotFound,
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)
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await expect(AkamaiAgentCR.create('team-123', 'test-agent', requestWithoutModel as any)).rejects.toThrow(
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"Foundation model 'undefined' not found",
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)
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})
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})
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describe('fromCR', () => {
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test('should create instance from existing CR object', () => {
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const crObject = {
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apiVersion: 'akamai.com/v1',
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kind: 'Agent',
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metadata: { name: 'existing-agent', namespace: 'team-456' },
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spec: { foundationModel: 'gpt-3.5', systemPrompt: 'Test prompt' },
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}
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const result = AkamaiAgentCR.fromCR(crObject)
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expect(result).toBeInstanceOf(AkamaiAgentCR)
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expect(result.metadata.name).toBe('existing-agent')
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expect(result.spec.foundationModel).toBe('gpt-3.5')
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})
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})
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})

‎src/ai/AkamaiAgentCR.ts‎

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import { AplAgentRequest, AplAgentResponse } from 'src/otomi-models'
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import { AGENT_API_VERSION, AGENT_KIND, cleanEnv } from '../validators'
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import { K8sResourceNotFound } from '../error'
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import { getAIModels } from './aiModelHandler'
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const env = cleanEnv({
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AGENT_API_VERSION,
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AGENT_KIND,
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})
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export class AkamaiAgentCR {
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public apiVersion: string
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public kind: string
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public metadata: {
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name: string
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namespace: string
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labels?: Record<string, string>
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}
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public spec: {
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foundationModel: string
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systemPrompt: string
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knowledgeBase?: string
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}
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constructor(teamId: string, agentName: string, request: AplAgentRequest) {
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const namespace = `team-${teamId}`
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this.apiVersion = env.AGENT_API_VERSION
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this.kind = env.AGENT_KIND
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this.metadata = {
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...request.metadata,
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name: agentName,
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namespace,
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labels: {
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'apl.io/teamId': teamId,
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},
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}
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this.spec = {
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foundationModel: request.spec.foundationModel,
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systemPrompt: request.spec.agentInstructions,
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knowledgeBase: request.spec.knowledgeBase,
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}
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}
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// Convert to plain object for serialization
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toRecord(): Record<string, any> {
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return {
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apiVersion: this.apiVersion,
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kind: this.kind,
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metadata: this.metadata,
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spec: this.spec,
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}
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}
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// Transform to API response format
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toApiResponse(teamId: string): AplAgentResponse {
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return {
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kind: 'AkamaiAgent',
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metadata: {
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...this.metadata,
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labels: {
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'apl.io/teamId': teamId,
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...(this.metadata.labels || {}),
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},
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},
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spec: {
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foundationModel: this.spec.foundationModel,
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agentInstructions: this.spec.systemPrompt,
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knowledgeBase: this.spec.knowledgeBase || '',
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},
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status: {
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conditions: [
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{
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type: 'AgentDeployed',
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status: true,
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reason: 'Scheduled',
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message: 'Successfully deployed the Agent',
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},
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],
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},
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}
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}
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// Static factory method
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static async create(teamId: string, agentName: string, request: AplAgentRequest): Promise<AkamaiAgentCR> {
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const aiModels = await getAIModels()
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const embeddingModel = aiModels.find(
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(model) => model.metadata.name === request.spec.foundationModel && model.spec.modelType === 'foundation',
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)
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if (!embeddingModel) {
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throw new K8sResourceNotFound('Foundation model', `Foundation model '${request.spec.foundationModel}' not found`)
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}
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return new AkamaiAgentCR(teamId, agentName, request)
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}
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// Static method to create from existing CR (for transformation)
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static fromCR(cr: any): AkamaiAgentCR {
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const instance = Object.create(AkamaiAgentCR.prototype)
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return Object.assign(instance, cr)
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}
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}

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