| 1 | import * as GCP from "@/GCP"; |
| 2 | import * as Test from "@/Test/Alchemy"; |
| 3 | import * as ml from "@distilled.cloud/gcp/ml_v1"; |
| 4 | import { expect } from "alchemy-test"; |
| 5 | import * as Effect from "effect/Effect"; |
| 6 | import * as Schedule from "effect/Schedule"; |
| 7 | import { |
| 8 | logLevel, |
| 9 | currentProject, |
| 10 | region, |
| 11 | runLifecycle, |
| 12 | runVersionLifecycle, |
| 13 | } from "./common.ts"; |
| 14 | |
| 15 | const { test } = Test.make({ providers: GCP.providers() }); |
| 16 | |
| 17 | const waitUntilGone = (name: string) => |
| 18 | ml.getProjectsModelsVersions({ name }).pipe( |
| 19 | Effect.as("found" as const), |
| 20 | Effect.catchTag("NotFound", () => Effect.succeed("gone" as const)), |
| 21 | Effect.repeat({ |
| 22 | schedule: Schedule.spaced("2 seconds"), |
| 23 | until: (status) => status === "gone", |
| 24 | times: 10, |
| 25 | }), |
| 26 | ); |
| 27 | |
| 28 | test.provider( |
| 29 | "getProjectsModelsVersions on a missing version fails with a typed tag", |
| 30 | (stack) => |
| 31 | Effect.gen(function* () { |
| 32 | const project = yield* currentProject; |
| 33 | |
| 34 | yield* stack.destroy(); |
| 35 | |
| 36 | const error = yield* Effect.flip( |
| 37 | ml.getProjectsModelsVersions({ |
| 38 | name: `projects/${project}/models/alchemy-missing-model/versions/v1`, |
| 39 | }), |
| 40 | ); |
| 41 | expect(error._tag).toEqual("NotFound"); |
| 42 | |
| 43 | yield* stack.destroy(); |
| 44 | }).pipe(logLevel), |
| 45 | { tags: ["provider:gcp", "provider:gcp:ml", "live"], timeout: 90_000 }, |
| 46 | ); |
| 47 | |
| 48 | test.provider.skipIf(runLifecycle)( |
| 49 | "createProjectsModelsVersions on a missing model fails with NotFound", |
| 50 | (stack) => |
| 51 | Effect.gen(function* () { |
| 52 | const project = yield* currentProject; |
| 53 | |
| 54 | yield* stack.destroy(); |
| 55 | |
| 56 | const error = yield* Effect.flip( |
| 57 | ml.createProjectsModelsVersions({ |
| 58 | parent: `projects/${project}/models/alchemy-missing-model`, |
| 59 | body: { |
| 60 | name: "v1", |
| 61 | deploymentUri: `gs://${project}-ml-missing/model`, |
| 62 | description: "probe", |
| 63 | }, |
| 64 | }), |
| 65 | ); |
| 66 | expect(error._tag).toEqual("NotFound"); |
| 67 | |
| 68 | yield* stack.destroy(); |
| 69 | }).pipe(logLevel), |
| 70 | { tags: ["provider:gcp", "provider:gcp:ml", "live"], timeout: 90_000 }, |
| 71 | ); |
| 72 | |
| 73 | test.provider.skipIf(!runVersionLifecycle)( |
| 74 | "create, update, and delete a model version", |
| 75 | (stack) => |
| 76 | Effect.gen(function* () { |
| 77 | yield* stack.destroy(); |
| 78 | |
| 79 | const deploymentUri = process.env.GCP_TEST_ML_DEPLOYMENT_URI ?? ""; |
| 80 | |
| 81 | const created = yield* stack.deploy( |
| 82 | Effect.gen(function* () { |
| 83 | const model = yield* GCP.ML.Model("Classifier", { |
| 84 | description: "image classifier", |
| 85 | regions: [region], |
| 86 | }); |
| 87 | const version = yield* GCP.ML.ModelsVersion("V1", { |
| 88 | model: model.name, |
| 89 | deploymentUri, |
| 90 | runtimeVersion: "2.11", |
| 91 | pythonVersion: "3.7", |
| 92 | framework: "TENSORFLOW", |
| 93 | description: "first version", |
| 94 | labels: { env: "test" }, |
| 95 | autoScaling: { minNodes: 0 }, |
| 96 | }); |
| 97 | return { model, version }; |
| 98 | }), |
| 99 | ); |
| 100 | |
| 101 | expect(created.version.name).toContain("/versions/"); |
| 102 | expect(created.version.model).toEqual(created.model.name); |
| 103 | expect(created.version.description).toEqual("first version"); |
| 104 | expect(created.version.deploymentUri).toEqual(deploymentUri); |
| 105 | expect(created.version.labels).toMatchObject({ env: "test" }); |
| 106 | |
| 107 | const fetched = yield* ml.getProjectsModelsVersions({ |
| 108 | name: created.version.name, |
| 109 | }); |
| 110 | expect(fetched.name).toEqual(created.version.name); |
| 111 | expect(fetched.description).toContain("[alchemy "); |
| 112 | expect(fetched.description).toContain("first version"); |
| 113 | |
| 114 | const updated = yield* stack.deploy( |
| 115 | Effect.gen(function* () { |
| 116 | const model = yield* GCP.ML.Model("Classifier", { |
| 117 | modelId: created.model.modelId, |
| 118 | description: "image classifier", |
| 119 | regions: [region], |
| 120 | }); |
| 121 | const version = yield* GCP.ML.ModelsVersion("V1", { |
| 122 | model: model.name, |
| 123 | versionId: created.version.versionId, |
| 124 | deploymentUri, |
| 125 | runtimeVersion: "2.11", |
| 126 | pythonVersion: "3.7", |
| 127 | framework: "TENSORFLOW", |
| 128 | description: "first version v2", |
| 129 | autoScaling: { minNodes: 0 }, |
| 130 | }); |
| 131 | return { model, version }; |
| 132 | }), |
| 133 | ); |
| 134 | |
| 135 | expect(updated.version.name).toEqual(created.version.name); |
| 136 | expect(updated.version.description).toEqual("first version v2"); |
| 137 | |
| 138 | yield* stack.destroy(); |
| 139 | const gone = yield* waitUntilGone(created.version.name); |
| 140 | expect(gone).toEqual("gone"); |
| 141 | }).pipe(logLevel), |
| 142 | { tags: ["provider:gcp", "provider:gcp:ml", "live"], timeout: 120_000 }, |
| 143 | ); |