mirror of
https://github.com/RooVetGit/Roo-Code.git
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257 lines
6.7 KiB
TypeScript
257 lines
6.7 KiB
TypeScript
import { Anthropic } from "@anthropic-ai/sdk"
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import OpenAI from "openai"
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import { ApiHandlerOptions, ModelInfo, requestyModelInfoSaneDefaults } from "../../../shared/api"
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import { RequestyHandler } from "../requesty"
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import { convertToOpenAiMessages } from "../../transform/openai-format"
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import { convertToR1Format } from "../../transform/r1-format"
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// Mock OpenAI and transform functions
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jest.mock("openai")
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jest.mock("../../transform/openai-format")
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jest.mock("../../transform/r1-format")
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describe("RequestyHandler", () => {
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let handler: RequestyHandler
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let mockCreate: jest.Mock
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const defaultOptions: ApiHandlerOptions = {
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requestyApiKey: "test-key",
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requestyModelId: "test-model",
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requestyModelInfo: {
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maxTokens: 1000,
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contextWindow: 4000,
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supportsPromptCache: false,
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supportsImages: true,
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inputPrice: 1,
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outputPrice: 10,
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cacheReadsPrice: 0.1,
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cacheWritesPrice: 1.5,
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},
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openAiStreamingEnabled: true,
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includeMaxTokens: true, // Add this to match the implementation
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}
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beforeEach(() => {
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// Clear mocks
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jest.clearAllMocks()
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// Setup mock create function
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mockCreate = jest.fn()
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// Mock OpenAI constructor
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;(OpenAI as jest.MockedClass<typeof OpenAI>).mockImplementation(
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() =>
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({
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chat: {
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completions: {
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create: mockCreate,
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},
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},
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}) as unknown as OpenAI,
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)
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// Mock transform functions
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;(convertToOpenAiMessages as jest.Mock).mockImplementation((messages) => messages)
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;(convertToR1Format as jest.Mock).mockImplementation((messages) => messages)
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// Create handler instance
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handler = new RequestyHandler(defaultOptions)
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})
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describe("constructor", () => {
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it("should initialize with correct options", () => {
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expect(OpenAI).toHaveBeenCalledWith({
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baseURL: "https://router.requesty.ai/v1",
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apiKey: defaultOptions.requestyApiKey,
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defaultHeaders: {
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"HTTP-Referer": "https://github.com/RooVetGit/Roo-Cline",
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"X-Title": "Roo Code",
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},
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})
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})
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})
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describe("createMessage", () => {
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const systemPrompt = "You are a helpful assistant"
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const messages: Anthropic.Messages.MessageParam[] = [{ role: "user", content: "Hello" }]
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describe("with streaming enabled", () => {
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beforeEach(() => {
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const stream = {
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[Symbol.asyncIterator]: async function* () {
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yield {
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choices: [{ delta: { content: "Hello" } }],
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}
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yield {
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choices: [{ delta: { content: " world" } }],
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usage: {
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prompt_tokens: 30,
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completion_tokens: 10,
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prompt_tokens_details: {
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cached_tokens: 15,
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caching_tokens: 5,
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},
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},
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}
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},
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}
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mockCreate.mockResolvedValue(stream)
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})
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it("should handle streaming response correctly", async () => {
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const stream = handler.createMessage(systemPrompt, messages)
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const results = []
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for await (const chunk of stream) {
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results.push(chunk)
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}
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expect(results).toEqual([
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{ type: "text", text: "Hello" },
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{ type: "text", text: " world" },
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{
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type: "usage",
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inputTokens: 30,
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outputTokens: 10,
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cacheWriteTokens: 5,
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cacheReadTokens: 15,
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totalCost: 0.000119, // (10 * 1 / 1,000,000) + (5 * 1.5 / 1,000,000) + (15 * 0.1 / 1,000,000) + (10 * 10 / 1,000,000)
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},
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])
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expect(mockCreate).toHaveBeenCalledWith({
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model: defaultOptions.requestyModelId,
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temperature: 0,
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messages: [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: "Hello" },
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],
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stream: true,
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stream_options: { include_usage: true },
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max_tokens: defaultOptions.requestyModelInfo?.maxTokens,
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})
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})
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it("should not include max_tokens when includeMaxTokens is false", async () => {
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handler = new RequestyHandler({
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...defaultOptions,
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includeMaxTokens: false,
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})
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await handler.createMessage(systemPrompt, messages).next()
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expect(mockCreate).toHaveBeenCalledWith(
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expect.not.objectContaining({
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max_tokens: expect.any(Number),
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}),
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)
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})
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it("should handle deepseek-reasoner model format", async () => {
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handler = new RequestyHandler({
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...defaultOptions,
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requestyModelId: "deepseek-reasoner",
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})
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await handler.createMessage(systemPrompt, messages).next()
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expect(convertToR1Format).toHaveBeenCalledWith([{ role: "user", content: systemPrompt }, ...messages])
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})
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})
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describe("with streaming disabled", () => {
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beforeEach(() => {
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handler = new RequestyHandler({
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...defaultOptions,
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openAiStreamingEnabled: false,
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})
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mockCreate.mockResolvedValue({
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choices: [{ message: { content: "Hello world" } }],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 5,
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},
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})
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})
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it("should handle non-streaming response correctly", async () => {
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const stream = handler.createMessage(systemPrompt, messages)
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const results = []
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for await (const chunk of stream) {
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results.push(chunk)
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}
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expect(results).toEqual([
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{ type: "text", text: "Hello world" },
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{
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type: "usage",
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inputTokens: 10,
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outputTokens: 5,
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cacheWriteTokens: 0,
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cacheReadTokens: 0,
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totalCost: 0.00006, // (10 * 1 / 1,000,000) + (5 * 10 / 1,000,000)
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},
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])
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expect(mockCreate).toHaveBeenCalledWith({
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model: defaultOptions.requestyModelId,
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messages: [
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{ role: "user", content: systemPrompt },
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{ role: "user", content: "Hello" },
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],
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})
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})
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})
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})
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describe("getModel", () => {
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it("should return correct model information", () => {
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const result = handler.getModel()
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expect(result).toEqual({
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id: defaultOptions.requestyModelId,
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info: defaultOptions.requestyModelInfo,
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})
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})
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it("should use sane defaults when no model info provided", () => {
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handler = new RequestyHandler({
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...defaultOptions,
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requestyModelInfo: undefined,
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})
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const result = handler.getModel()
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expect(result).toEqual({
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id: defaultOptions.requestyModelId,
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info: requestyModelInfoSaneDefaults,
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})
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})
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})
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describe("completePrompt", () => {
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beforeEach(() => {
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mockCreate.mockResolvedValue({
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choices: [{ message: { content: "Completed response" } }],
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})
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})
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it("should complete prompt successfully", async () => {
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const result = await handler.completePrompt("Test prompt")
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expect(result).toBe("Completed response")
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expect(mockCreate).toHaveBeenCalledWith({
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model: defaultOptions.requestyModelId,
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messages: [{ role: "user", content: "Test prompt" }],
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})
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})
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it("should handle errors correctly", async () => {
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const errorMessage = "API error"
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mockCreate.mockRejectedValue(new Error(errorMessage))
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await expect(handler.completePrompt("Test prompt")).rejects.toThrow(
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`OpenAI completion error: ${errorMessage}`,
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)
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})
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})
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})
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