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| 1 | +// npx vitest run src/api/providers/__tests__/kenari.spec.ts |
| 2 | + |
| 3 | +// Mock vscode first to avoid import errors |
| 4 | +vitest.mock("vscode", () => ({ |
| 5 | + workspace: { |
| 6 | + getConfiguration: () => ({ |
| 7 | + get: (_key: string, defaultValue?: unknown) => defaultValue, |
| 8 | + }), |
| 9 | + }, |
| 10 | +})) |
| 11 | + |
| 12 | +import { Anthropic } from "@anthropic-ai/sdk" |
| 13 | +import OpenAI from "openai" |
| 14 | + |
| 15 | +import { kenariDefaultModelId } from "@roo-code/types" |
| 16 | + |
| 17 | +import { KenariHandler } from "../kenari" |
| 18 | +import { ApiHandlerOptions } from "../../../shared/api" |
| 19 | + |
| 20 | +vitest.mock("openai") |
| 21 | +vitest.mock("delay", () => ({ default: vitest.fn(() => Promise.resolve()) })) |
| 22 | +vitest.mock("../fetchers/modelCache", () => ({ |
| 23 | + getModels: vitest.fn().mockImplementation(() => |
| 24 | + Promise.resolve({ |
| 25 | + "glm-5-2": { |
| 26 | + maxTokens: 32768, |
| 27 | + contextWindow: 1048576, |
| 28 | + supportsImages: false, |
| 29 | + supportsPromptCache: false, |
| 30 | + description: "GLM 5.2", |
| 31 | + }, |
| 32 | + }), |
| 33 | + ), |
| 34 | + getModelsFromCache: vitest.fn().mockReturnValue(undefined), |
| 35 | +})) |
| 36 | + |
| 37 | +const mockCreate = vitest.fn() |
| 38 | + |
| 39 | +;(OpenAI as any).mockImplementation(function () { |
| 40 | + return { |
| 41 | + chat: { completions: { create: mockCreate } }, |
| 42 | + } |
| 43 | +}) |
| 44 | + |
| 45 | +describe("KenariHandler", () => { |
| 46 | + const mockOptions: ApiHandlerOptions = { |
| 47 | + kenariApiKey: "test-key", |
| 48 | + kenariModelId: "glm-5-2", |
| 49 | + } |
| 50 | + |
| 51 | + beforeEach(() => { |
| 52 | + vitest.clearAllMocks() |
| 53 | + mockCreate.mockClear() |
| 54 | + }) |
| 55 | + |
| 56 | + it("initializes the OpenAI client with the Kenari base URL and key", () => { |
| 57 | + const handler = new KenariHandler(mockOptions) |
| 58 | + expect(handler).toBeInstanceOf(KenariHandler) |
| 59 | + expect(OpenAI).toHaveBeenCalledWith( |
| 60 | + expect.objectContaining({ |
| 61 | + baseURL: "https://kenari.id/v1", |
| 62 | + apiKey: "test-key", |
| 63 | + }), |
| 64 | + ) |
| 65 | + }) |
| 66 | + |
| 67 | + describe("fetchModel", () => { |
| 68 | + it("returns the configured model info", async () => { |
| 69 | + const handler = new KenariHandler(mockOptions) |
| 70 | + const result = await handler.fetchModel() |
| 71 | + expect(result.id).toBe("glm-5-2") |
| 72 | + expect(result.info.maxTokens).toBe(32768) |
| 73 | + expect(result.info.contextWindow).toBe(1048576) |
| 74 | + expect(result.info.supportsPromptCache).toBe(false) |
| 75 | + }) |
| 76 | + |
| 77 | + it("falls back to the default model id when none is configured", async () => { |
| 78 | + const handler = new KenariHandler({ kenariApiKey: "test-key" }) |
| 79 | + const result = await handler.fetchModel() |
| 80 | + expect(result.id).toBe(kenariDefaultModelId) |
| 81 | + }) |
| 82 | + }) |
| 83 | + |
| 84 | + describe("createMessage", () => { |
| 85 | + beforeEach(() => { |
| 86 | + mockCreate.mockImplementation(async () => ({ |
| 87 | + [Symbol.asyncIterator]: async function* () { |
| 88 | + yield { |
| 89 | + choices: [ |
| 90 | + { |
| 91 | + delta: { |
| 92 | + content: "Hello", |
| 93 | + reasoning_content: "thinking…", |
| 94 | + tool_calls: [ |
| 95 | + { |
| 96 | + index: 0, |
| 97 | + id: "call_1", |
| 98 | + function: { name: "read_file", arguments: '{"path":' }, |
| 99 | + }, |
| 100 | + ], |
| 101 | + }, |
| 102 | + index: 0, |
| 103 | + }, |
| 104 | + ], |
| 105 | + usage: null, |
| 106 | + } |
| 107 | + yield { |
| 108 | + choices: [{ delta: {}, index: 0 }], |
| 109 | + usage: { |
| 110 | + prompt_tokens: 12, |
| 111 | + completion_tokens: 7, |
| 112 | + total_tokens: 19, |
| 113 | + prompt_tokens_details: { cached_tokens: 4 }, |
| 114 | + }, |
| 115 | + } |
| 116 | + }, |
| 117 | + })) |
| 118 | + }) |
| 119 | + |
| 120 | + it("streams text, reasoning, tool-call and usage chunks", async () => { |
| 121 | + const handler = new KenariHandler(mockOptions) |
| 122 | + const messages: Anthropic.Messages.MessageParam[] = [{ role: "user", content: "Hi" }] |
| 123 | + |
| 124 | + const chunks = [] |
| 125 | + for await (const chunk of handler.createMessage("You are helpful.", messages)) { |
| 126 | + chunks.push(chunk) |
| 127 | + } |
| 128 | + |
| 129 | + expect(chunks).toContainEqual({ type: "text", text: "Hello" }) |
| 130 | + expect(chunks).toContainEqual({ type: "reasoning", text: "thinking…" }) |
| 131 | + expect(chunks).toContainEqual({ |
| 132 | + type: "tool_call_partial", |
| 133 | + index: 0, |
| 134 | + id: "call_1", |
| 135 | + name: "read_file", |
| 136 | + arguments: '{"path":', |
| 137 | + }) |
| 138 | + expect(chunks).toContainEqual({ |
| 139 | + type: "usage", |
| 140 | + inputTokens: 12, |
| 141 | + outputTokens: 7, |
| 142 | + cacheReadTokens: 4, |
| 143 | + }) |
| 144 | + }) |
| 145 | + |
| 146 | + it("requests a streaming completion with usage included", async () => { |
| 147 | + const handler = new KenariHandler(mockOptions) |
| 148 | + const messages: Anthropic.Messages.MessageParam[] = [{ role: "user", content: "Hi" }] |
| 149 | + for await (const _chunk of handler.createMessage("sys", messages)) { |
| 150 | + void _chunk // drain |
| 151 | + } |
| 152 | + |
| 153 | + expect(mockCreate).toHaveBeenCalledWith( |
| 154 | + expect.objectContaining({ |
| 155 | + model: "glm-5-2", |
| 156 | + stream: true, |
| 157 | + stream_options: { include_usage: true }, |
| 158 | + max_completion_tokens: 32768, |
| 159 | + temperature: expect.any(Number), |
| 160 | + }), |
| 161 | + ) |
| 162 | + }) |
| 163 | + }) |
| 164 | + |
| 165 | + describe("completePrompt", () => { |
| 166 | + it("returns the message content for a non-streaming completion", async () => { |
| 167 | + mockCreate.mockResolvedValue({ choices: [{ message: { content: "the answer" } }] }) |
| 168 | + const handler = new KenariHandler(mockOptions) |
| 169 | + expect(await handler.completePrompt("ping")).toBe("the answer") |
| 170 | + expect(mockCreate).toHaveBeenCalledWith( |
| 171 | + expect.objectContaining({ |
| 172 | + model: "glm-5-2", |
| 173 | + stream: false, |
| 174 | + max_completion_tokens: 32768, |
| 175 | + }), |
| 176 | + ) |
| 177 | + }) |
| 178 | + |
| 179 | + it("wraps errors with a Kenari-specific message", async () => { |
| 180 | + mockCreate.mockRejectedValue(new Error("boom")) |
| 181 | + const handler = new KenariHandler(mockOptions) |
| 182 | + await expect(handler.completePrompt("ping")).rejects.toThrow("Kenari completion error: boom") |
| 183 | + }) |
| 184 | + }) |
| 185 | +}) |
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