fix: add foundation model endpoint

src/ai/AkamaiAgentCR.test.ts

@@ -60,7 +60,6 @@ describe('AkamaiAgentCR', () => {
           name: 'test-kb',
           description:
             'Search the test-kb knowledge base for relevant information. Use this when you need factual information, documentation, or specific details stored in the knowledge base.',
-          endpoint: undefined,
         },
       ])
     })
@@ -111,7 +110,6 @@ describe('AkamaiAgentCR', () => {
           type: 'knowledgeBase',
           name: 'test-kb',
           description: 'Custom description for the knowledge base',
-          endpoint: undefined,
         },
       ])
     })
@@ -154,7 +152,6 @@ describe('AkamaiAgentCR', () => {
               name: 'test-kb',
               description:
                 'Search the test-kb knowledge base for relevant information. Use this when you need factual information, documentation, or specific details stored in the knowledge base.',
-              endpoint: undefined,
             },
           ],
         },
@@ -186,7 +183,7 @@ describe('AkamaiAgentCR', () => {
       expect(response.spec.tools).toBeUndefined()
     })
 
-    test('should preserve custom description and endpoint in response', () => {
+    test('should preserve custom description and apiUrl in response', () => {
       const requestWithDetails = {
         ...mockAgentRequest,
         spec: {
@@ -196,7 +193,7 @@ describe('AkamaiAgentCR', () => {
               type: 'knowledgeBase',
               name: 'test-kb',
               description: 'Custom KB description',
-              endpoint: 'https://api.example.com/kb',
+              apiUrl: 'https://api.example.com/kb',
             },
           ],
         },
@@ -210,7 +207,7 @@ describe('AkamaiAgentCR', () => {
           type: 'knowledgeBase',
           name: 'test-kb',
           description: 'Custom KB description',
-          endpoint: 'https://api.example.com/kb',
+          apiUrl: 'https://api.example.com/kb',
         },
       ])
     })

src/ai/AkamaiAgentCR.ts

@@ -18,12 +18,20 @@ export class AkamaiAgentCR {
   }
   public spec: {
     foundationModel: string
+    foundationModelEndpoint?: string
     agentInstructions: string
+    routes?: Array<{
+      agent: string
+      condition: string
+      apiUrl: string
+      apiKey?: string
+    }>
     tools?: Array<{
       type: string
       name: string
       description?: string
-      endpoint?: string
+      apiUrl?: string
+      apiKey?: string
     }>
   }
 
@@ -42,17 +50,29 @@ export class AkamaiAgentCR {
     }
     this.spec = {
       foundationModel: request.spec.foundationModel,
+      ...(request.spec.foundationModelEndpoint && { foundationModelEndpoint: request.spec.foundationModelEndpoint }),
       agentInstructions: request.spec.agentInstructions,
-      tools: request.spec.tools?.map((tool) => ({
-        type: tool.type,
-        name: tool.name,
-        description:
-          tool.description ||
-          (tool.type === 'knowledgeBase'
-            ? `Search the ${tool.name} knowledge base for relevant information. Use this when you need factual information, documentation, or specific details stored in the knowledge base.`
-            : undefined),
-        endpoint: tool.endpoint,
-      })),
+      ...(request.spec.routes && {
+        routes: request.spec.routes.map((route) => ({
+          agent: route.agent,
+          condition: route.condition,
+          apiUrl: route.apiUrl,
+          ...(route.apiKey && { apiKey: route.apiKey }),
+        })),
+      }),
+      ...(request.spec.tools && {
+        tools: request.spec.tools.map((tool) => ({
+          type: tool.type,
+          name: tool.name,
+          description:
+            tool.description ||
+            (tool.type === 'knowledgeBase'
+              ? `Search the ${tool.name} knowledge base for relevant information. Use this when you need factual information, documentation, or specific details stored in the knowledge base.`
+              : undefined),
+          ...(tool.apiUrl && { apiUrl: tool.apiUrl }),
+          ...(tool.apiKey && { apiKey: tool.apiKey }),
+        })),
+      }),
     }
   }
 
@@ -79,13 +99,25 @@ export class AkamaiAgentCR {
       },
       spec: {
         foundationModel: this.spec.foundationModel,
+        ...(this.spec.foundationModelEndpoint && { foundationModelEndpoint: this.spec.foundationModelEndpoint }),
         agentInstructions: this.spec.agentInstructions,
-        tools: this.spec.tools?.map((tool) => ({
-          type: tool.type,
-          name: tool.name,
-          ...(tool.description && { description: tool.description }),
-          ...(tool.endpoint && { endpoint: tool.endpoint }),
-        })),
+        ...(this.spec.routes && {
+          routes: this.spec.routes.map((route) => ({
+            agent: route.agent,
+            condition: route.condition,
+            apiUrl: route.apiUrl,
+            ...(route.apiKey && { apiKey: route.apiKey }),
+          })),
+        }),
+        ...(this.spec.tools && {
+          tools: this.spec.tools.map((tool) => ({
+            type: tool.type,
+            name: tool.name,
+            ...(tool.description && { description: tool.description }),
+            ...(tool.apiUrl && { apiUrl: tool.apiUrl }),
+            ...(tool.apiKey && { apiKey: tool.apiKey }),
+          })),
+        }),
       },
       status: {
         conditions: [
@@ -103,15 +135,24 @@ export class AkamaiAgentCR {
   // Static factory method
   static async create(teamId: string, agentName: string, request: AplAgentRequest): Promise<AkamaiAgentCR> {
     const aiModels = await getAIModels()
-    const embeddingModel = aiModels.find(
+    const foundationModel = aiModels.find(
       (model) => model.metadata.name === request.spec.foundationModel && model.spec.modelType === 'foundation',
     )
 
-    if (!embeddingModel) {
+    if (!foundationModel) {
       throw new K8sResourceNotFound('Foundation model', `Foundation model '${request.spec.foundationModel}' not found`)
     }
 
-    return new AkamaiAgentCR(teamId, agentName, request)
+    // Create enriched request with foundationModelEndpoint from the model
+    const enrichedRequest: AplAgentRequest = {
+      ...request,
+      spec: {
+        ...request.spec,
+        foundationModelEndpoint: foundationModel.spec.modelEndpoint,
+      },
+    }
+
+    return new AkamaiAgentCR(teamId, agentName, enrichedRequest)
   }
 
   // Static method to create from existing CR (for transformation)

src/ai/aiModelHandler.test.ts

@@ -1,12 +1,15 @@
 import { V1Deployment } from '@kubernetes/client-node'
-import { getAIModels, transformK8sDeploymentToAplAIModel } from './aiModelHandler'
+import { getAIModels, transformK8sWorkloadToAplAIModel } from './aiModelHandler'
 import * as k8s from './k8s'
 
 // Mock the k8s module
 jest.mock('./k8s')
 const mockedGetDeploymentsWithAIModelLabels = k8s.getDeploymentsWithAIModelLabels as jest.MockedFunction<
   typeof k8s.getDeploymentsWithAIModelLabels
 >
+const mockedGetStatefulSetsWithAIModelLabels = k8s.getStatefulSetsWithAIModelLabels as jest.MockedFunction<
+  typeof k8s.getStatefulSetsWithAIModelLabels
+>
 
 describe('aiModelHandler', () => {
   const mockDeployment: V1Deployment = {
@@ -19,6 +22,7 @@ describe('aiModelHandler', () => {
         modelNameTitle: 'GPT-4o-mini',
         modelType: 'foundation',
         modelDimension: '1536',
+        'serving.knative.dev/service': 'gpt-4-deployment',
       },
     },
     status: {
@@ -47,18 +51,18 @@ describe('aiModelHandler', () => {
     jest.clearAllMocks()
   })
 
-  describe('transformK8sDeploymentToAplAIModel', () => {
+  describe('transformK8sWorkloadToAplAIModel', () => {
     test('should transform K8s deployment to AplAIModel with all fields', () => {
-      const result = transformK8sDeploymentToAplAIModel(mockDeployment)
+      const result = transformK8sWorkloadToAplAIModel(mockDeployment)
 
       expect(result).toEqual({
         kind: 'AplAIModel',
         metadata: {
           name: 'gpt-4',
         },
         spec: {
-          displayName: 'GPT-4o-mini',
-          modelEndpoint: 'http://gpt-4.ai-models.svc.cluster.local/openai/v1',
+          displayName: 'gpt-4',
+          modelEndpoint: 'http://gpt-4-deployment.ai-models.svc.cluster.local/openai/v1',
           modelType: 'foundation',
           modelDimension: 1536,
         },
@@ -97,10 +101,10 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithModelName)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithModelName)
 
       expect(result.metadata.name).toBe('custom-model-name')
-      expect(result.spec.displayName).toBe('GPT-4o-mini')
+      expect(result.spec.displayName).toBe('custom-model-name')
     })
 
     test('should use modelName from labels when deployment name is missing', () => {
@@ -116,10 +120,10 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutName)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutName)
 
       expect(result.metadata.name).toBe('custom-model-name')
-      expect(result.spec.displayName).toBe('GPT-4o-mini')
+      expect(result.spec.displayName).toBe('custom-model-name')
     })
 
     test('should handle deployment without labels', () => {
@@ -131,7 +135,7 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutLabels)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutLabels)
 
       expect(result.metadata.name).toBe('test-deployment')
       expect(result.spec.modelType).toBeUndefined()
@@ -150,7 +154,7 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutDimension)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutDimension)
 
       expect(result.spec.modelDimension).toBeUndefined()
     })
@@ -164,9 +168,9 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutNamespace)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutNamespace)
 
-      expect(result.spec.modelEndpoint).toBe('http://gpt-4.undefined.svc.cluster.local/openai/v1')
+      expect(result.spec.modelEndpoint).toBe('http://gpt-4-deployment.undefined.svc.cluster.local/openai/v1')
     })
 
     test('should handle deployment without status conditions', () => {
@@ -178,7 +182,7 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutConditions)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutConditions)
 
       expect(result.status.conditions).toEqual([])
       expect(result.status.phase).toBe('NotReady')
@@ -193,13 +197,13 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(notReadyDeployment)
+      const result = transformK8sWorkloadToAplAIModel(notReadyDeployment)
 
       expect(result.status.phase).toBe('NotReady')
     })
 
     test('should set phase to Ready when has ready replicas', () => {
-      const result = transformK8sDeploymentToAplAIModel(mockDeployment)
+      const result = transformK8sWorkloadToAplAIModel(mockDeployment)
 
       expect(result.status.phase).toBe('Ready')
     })
@@ -221,7 +225,7 @@ describe('aiModelHandler', () => {
         },
       }
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithFalseCondition)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithFalseCondition)
 
       expect(result.status.conditions?.[0]?.status).toBe(false)
     })
@@ -231,35 +235,39 @@ describe('aiModelHandler', () => {
         status: mockDeployment.status,
       } as V1Deployment
 
-      const result = transformK8sDeploymentToAplAIModel(deploymentWithoutMetadata)
+      const result = transformK8sWorkloadToAplAIModel(deploymentWithoutMetadata)
 
       expect(result.metadata.name).toBe('')
-      expect(result.spec.modelEndpoint).toBe('http://.undefined.svc.cluster.local/openai/v1')
+      expect(result.spec.modelEndpoint).toBe('http://.undefined.svc.cluster.local/v1')
     })
   })
 
   describe('getAIModels', () => {
     test('should return transformed AI models from deployments', async () => {
       mockedGetDeploymentsWithAIModelLabels.mockResolvedValue([mockDeployment])
+      mockedGetStatefulSetsWithAIModelLabels.mockResolvedValue([])
 
       const result = await getAIModels()
 
       expect(result).toHaveLength(1)
       expect(result[0].kind).toBe('AplAIModel')
       expect(result[0].metadata.name).toBe('gpt-4')
       expect(mockedGetDeploymentsWithAIModelLabels).toHaveBeenCalledTimes(1)
+      expect(mockedGetStatefulSetsWithAIModelLabels).toHaveBeenCalledTimes(1)
     })
 
-    test('should return empty array when no deployments found', async () => {
+    test('should return empty array when no deployments or statefulsets found', async () => {
       mockedGetDeploymentsWithAIModelLabels.mockResolvedValue([])
+      mockedGetStatefulSetsWithAIModelLabels.mockResolvedValue([])
 
       const result = await getAIModels()
 
       expect(result).toEqual([])
       expect(mockedGetDeploymentsWithAIModelLabels).toHaveBeenCalledTimes(1)
+      expect(mockedGetStatefulSetsWithAIModelLabels).toHaveBeenCalledTimes(1)
     })
 
-    test('should handle multiple deployments', async () => {
+    test('should handle multiple deployments and statefulsets', async () => {
       const secondDeployment = {
         ...mockDeployment,
         metadata: {
@@ -274,6 +282,7 @@ describe('aiModelHandler', () => {
       }
 
       mockedGetDeploymentsWithAIModelLabels.mockResolvedValue([mockDeployment, secondDeployment])
+      mockedGetStatefulSetsWithAIModelLabels.mockResolvedValue([])
 
       const result = await getAIModels()
 
@@ -285,6 +294,7 @@ describe('aiModelHandler', () => {
     test('should propagate errors from k8s module', async () => {
       const error = new Error('K8s API error')
       mockedGetDeploymentsWithAIModelLabels.mockRejectedValue(error)
+      mockedGetStatefulSetsWithAIModelLabels.mockResolvedValue([])
 
       await expect(getAIModels()).rejects.toThrow('K8s API error')
     })