Roo-Code/src/api/providers/__tests__/openai.spec.ts

// npx vitest run api/providers/__tests__/openai.spec.ts

import { OpenAiHandler, getOpenAiModels } from "../openai"
import { ApiHandlerOptions } from "../../../shared/api"
import { Anthropic } from "@anthropic-ai/sdk"
import OpenAI from "openai"
import { openAiModelInfoSaneDefaults } from "@roo-code/types"
import { Package } from "../../../shared/package"
import axios from "axios"

const mockCreate = vitest.fn()

vitest.mock("openai", () => {
	const mockConstructor = vitest.fn()
	return {
		__esModule: true,
		default: mockConstructor.mockImplementation(() => ({
			chat: {
				completions: {
					create: mockCreate.mockImplementation(async (options) => {
						if (!options.stream) {
							return {
								id: "test-completion",
								choices: [
									{
										message: { role: "assistant", content: "Test response", refusal: null },
										finish_reason: "stop",
										index: 0,
									},
								],
								usage: {
									prompt_tokens: 10,
									completion_tokens: 5,
									total_tokens: 15,
								},
							}
						}

						return {
							[Symbol.asyncIterator]: async function* () {
								yield {
									choices: [
										{
											delta: { content: "Test response" },
											index: 0,
										},
									],
									usage: null,
								}
								yield {
									choices: [
										{
											delta: {},
											index: 0,
										},
									],
									usage: {
										prompt_tokens: 10,
										completion_tokens: 5,
										total_tokens: 15,
									},
								}
							},
						}
					}),
				},
			},
		})),
	}
})

// Mock axios for getOpenAiModels tests
vitest.mock("axios", () => ({
	default: {
		get: vitest.fn(),
	},
}))

describe("OpenAiHandler", () => {
	let handler: OpenAiHandler
	let mockOptions: ApiHandlerOptions

	beforeEach(() => {
		mockOptions = {
			openAiApiKey: "test-api-key",
			openAiModelId: "gpt-4",
			openAiBaseUrl: "https://api.openai.com/v1",
		}
		handler = new OpenAiHandler(mockOptions)
		mockCreate.mockClear()
	})

	describe("constructor", () => {
		it("should initialize with provided options", () => {
			expect(handler).toBeInstanceOf(OpenAiHandler)
			expect(handler.getModel().id).toBe(mockOptions.openAiModelId)
		})

		it("should use custom base URL if provided", () => {
			const customBaseUrl = "https://custom.openai.com/v1"
			const handlerWithCustomUrl = new OpenAiHandler({
				...mockOptions,
				openAiBaseUrl: customBaseUrl,
			})
			expect(handlerWithCustomUrl).toBeInstanceOf(OpenAiHandler)
		})

		it("should set default headers correctly", () => {
			// Check that the OpenAI constructor was called with correct parameters
			expect(vi.mocked(OpenAI)).toHaveBeenCalledWith({
				baseURL: expect.any(String),
				apiKey: expect.any(String),
				defaultHeaders: {
					"HTTP-Referer": "https://github.com/RooVetGit/Roo-Cline",
					"X-Title": "Roo Code",
					"User-Agent": `RooCode/${Package.version}`,
				},
				timeout: expect.any(Number),
			})
		})
	})

	describe("createMessage", () => {
		const systemPrompt = "You are a helpful assistant."
		const messages: Anthropic.Messages.MessageParam[] = [
			{
				role: "user",
				content: [
					{
						type: "text" as const,
						text: "Hello!",
					},
				],
			},
		]

		it("should handle non-streaming mode", async () => {
			const handler = new OpenAiHandler({
				...mockOptions,
				openAiStreamingEnabled: false,
			})

			const stream = handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(chunks.length).toBeGreaterThan(0)
			const textChunk = chunks.find((chunk) => chunk.type === "text")
			const usageChunk = chunks.find((chunk) => chunk.type === "usage")

			expect(textChunk).toBeDefined()
			expect(textChunk?.text).toBe("Test response")
			expect(usageChunk).toBeDefined()
			expect(usageChunk?.inputTokens).toBe(10)
			expect(usageChunk?.outputTokens).toBe(5)
		})

		it("should handle tool calls in non-streaming mode", async () => {
			mockCreate.mockResolvedValueOnce({
				choices: [
					{
						message: {
							role: "assistant",
							content: null,
							tool_calls: [
								{
									id: "call_1",
									type: "function",
									function: {
										name: "test_tool",
										arguments: '{"arg":"value"}',
									},
								},
							],
						},
						finish_reason: "tool_calls",
					},
				],
				usage: {
					prompt_tokens: 10,
					completion_tokens: 5,
					total_tokens: 15,
				},
			})

			const handler = new OpenAiHandler({
				...mockOptions,
				openAiStreamingEnabled: false,
			})

			const stream = handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			const toolCallChunks = chunks.filter((chunk) => chunk.type === "tool_call")
			expect(toolCallChunks).toHaveLength(1)
			expect(toolCallChunks[0]).toEqual({
				type: "tool_call",
				id: "call_1",
				name: "test_tool",
				arguments: '{"arg":"value"}',
			})
		})

		it("should handle streaming responses", async () => {
			const stream = handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(chunks.length).toBeGreaterThan(0)
			const textChunks = chunks.filter((chunk) => chunk.type === "text")
			expect(textChunks).toHaveLength(1)
			expect(textChunks[0].text).toBe("Test response")
		})

		it("should handle tool calls in streaming responses", async () => {
			mockCreate.mockImplementation(async (options) => {
				return {
					[Symbol.asyncIterator]: async function* () {
						yield {
							choices: [
								{
									delta: {
										tool_calls: [
											{
												index: 0,
												id: "call_1",
												function: { name: "test_tool", arguments: "" },
											},
										],
									},
									finish_reason: null,
								},
							],
						}
						yield {
							choices: [
								{
									delta: {
										tool_calls: [{ index: 0, function: { arguments: '{"arg":' } }],
									},
									finish_reason: null,
								},
							],
						}
						yield {
							choices: [
								{
									delta: {
										tool_calls: [{ index: 0, function: { arguments: '"value"}' } }],
									},
									finish_reason: "tool_calls",
								},
							],
						}
					},
				}
			})

			const stream = handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			// Provider now yields tool_call_partial chunks, NativeToolCallParser handles reassembly
			const toolCallPartialChunks = chunks.filter((chunk) => chunk.type === "tool_call_partial")
			expect(toolCallPartialChunks).toHaveLength(3)
			// First chunk has id and name
			expect(toolCallPartialChunks[0]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: "call_1",
				name: "test_tool",
				arguments: "",
			})
			// Subsequent chunks have arguments
			expect(toolCallPartialChunks[1]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: undefined,
				name: undefined,
				arguments: '{"arg":',
			})
			expect(toolCallPartialChunks[2]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: undefined,
				name: undefined,
				arguments: '"value"}',
			})

			// Verify tool_call_end event is emitted when finish_reason is "tool_calls"
			const toolCallEndChunks = chunks.filter((chunk) => chunk.type === "tool_call_end")
			expect(toolCallEndChunks).toHaveLength(1)
		})

		it("should yield tool calls even when finish_reason is not set (fallback behavior)", async () => {
			mockCreate.mockImplementation(async (options) => {
				return {
					[Symbol.asyncIterator]: async function* () {
						yield {
							choices: [
								{
									delta: {
										tool_calls: [
											{
												index: 0,
												id: "call_fallback",
												function: { name: "fallback_tool", arguments: '{"test":"fallback"}' },
											},
										],
									},
									finish_reason: null,
								},
							],
						}
						// Stream ends without finish_reason being set to "tool_calls"
						yield {
							choices: [
								{
									delta: {},
									finish_reason: "stop", // Different finish reason
								},
							],
						}
					},
				}
			})

			const stream = handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			// Provider now yields tool_call_partial chunks, NativeToolCallParser handles reassembly
			const toolCallPartialChunks = chunks.filter((chunk) => chunk.type === "tool_call_partial")
			expect(toolCallPartialChunks).toHaveLength(1)
			expect(toolCallPartialChunks[0]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: "call_fallback",
				name: "fallback_tool",
				arguments: '{"test":"fallback"}',
			})
		})

		it("should include reasoning_effort when reasoning effort is enabled", async () => {
			const reasoningOptions: ApiHandlerOptions = {
				...mockOptions,
				enableReasoningEffort: true,
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					supportsPromptCache: false,
					supportsReasoningEffort: true,
					reasoningEffort: "high",
				},
			}
			const reasoningHandler = new OpenAiHandler(reasoningOptions)
			const stream = reasoningHandler.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called with reasoning_effort
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.reasoning_effort).toBe("high")
		})

		it("should not include reasoning_effort when reasoning effort is disabled", async () => {
			const noReasoningOptions: ApiHandlerOptions = {
				...mockOptions,
				enableReasoningEffort: false,
				openAiCustomModelInfo: { contextWindow: 128_000, supportsPromptCache: false },
			}
			const noReasoningHandler = new OpenAiHandler(noReasoningOptions)
			const stream = noReasoningHandler.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called without reasoning_effort
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.reasoning_effort).toBeUndefined()
		})

		it("should include max_tokens when includeMaxTokens is true", async () => {
			const optionsWithMaxTokens: ApiHandlerOptions = {
				...mockOptions,
				includeMaxTokens: true,
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					maxTokens: 4096,
					supportsPromptCache: false,
				},
			}
			const handlerWithMaxTokens = new OpenAiHandler(optionsWithMaxTokens)
			const stream = handlerWithMaxTokens.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called with max_tokens
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.max_completion_tokens).toBe(4096)
		})

		it("should not include max_tokens when includeMaxTokens is false", async () => {
			const optionsWithoutMaxTokens: ApiHandlerOptions = {
				...mockOptions,
				includeMaxTokens: false,
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					maxTokens: 4096,
					supportsPromptCache: false,
				},
			}
			const handlerWithoutMaxTokens = new OpenAiHandler(optionsWithoutMaxTokens)
			const stream = handlerWithoutMaxTokens.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called without max_tokens
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.max_completion_tokens).toBeUndefined()
		})

		it("should not include max_tokens when includeMaxTokens is undefined", async () => {
			const optionsWithUndefinedMaxTokens: ApiHandlerOptions = {
				...mockOptions,
				// includeMaxTokens is not set, should not include max_tokens
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					maxTokens: 4096,
					supportsPromptCache: false,
				},
			}
			const handlerWithDefaultMaxTokens = new OpenAiHandler(optionsWithUndefinedMaxTokens)
			const stream = handlerWithDefaultMaxTokens.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called without max_tokens
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.max_completion_tokens).toBeUndefined()
		})

		it("should use user-configured modelMaxTokens instead of model default maxTokens", async () => {
			const optionsWithUserMaxTokens: ApiHandlerOptions = {
				...mockOptions,
				includeMaxTokens: true,
				modelMaxTokens: 32000, // User-configured value
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					maxTokens: 4096, // Model's default value (should not be used)
					supportsPromptCache: false,
				},
			}
			const handlerWithUserMaxTokens = new OpenAiHandler(optionsWithUserMaxTokens)
			const stream = handlerWithUserMaxTokens.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called with user-configured modelMaxTokens (32000), not model default maxTokens (4096)
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.max_completion_tokens).toBe(32000)
		})

		it("should fallback to model default maxTokens when user modelMaxTokens is not set", async () => {
			const optionsWithoutUserMaxTokens: ApiHandlerOptions = {
				...mockOptions,
				includeMaxTokens: true,
				// modelMaxTokens is not set
				openAiCustomModelInfo: {
					contextWindow: 128_000,
					maxTokens: 4096, // Model's default value (should be used as fallback)
					supportsPromptCache: false,
				},
			}
			const handlerWithoutUserMaxTokens = new OpenAiHandler(optionsWithoutUserMaxTokens)
			const stream = handlerWithoutUserMaxTokens.createMessage(systemPrompt, messages)
			// Consume the stream to trigger the API call
			for await (const _chunk of stream) {
			}
			// Assert the mockCreate was called with model default maxTokens (4096) as fallback
			expect(mockCreate).toHaveBeenCalled()
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs.max_completion_tokens).toBe(4096)
		})
	})

	describe("error handling", () => {
		const testMessages: Anthropic.Messages.MessageParam[] = [
			{
				role: "user",
				content: [
					{
						type: "text" as const,
						text: "Hello",
					},
				],
			},
		]

		it("should handle API errors", async () => {
			mockCreate.mockRejectedValueOnce(new Error("API Error"))

			const stream = handler.createMessage("system prompt", testMessages)

			await expect(async () => {
				for await (const _chunk of stream) {
					// Should not reach here
				}
			}).rejects.toThrow("API Error")
		})

		it("should handle rate limiting", async () => {
			const rateLimitError = new Error("Rate limit exceeded")
			rateLimitError.name = "Error"
			;(rateLimitError as any).status = 429
			mockCreate.mockRejectedValueOnce(rateLimitError)

			const stream = handler.createMessage("system prompt", testMessages)

			await expect(async () => {
				for await (const _chunk of stream) {
					// Should not reach here
				}
			}).rejects.toThrow("Rate limit exceeded")
		})
	})

	describe("completePrompt", () => {
		it("should complete prompt successfully", async () => {
			const result = await handler.completePrompt("Test prompt")
			expect(result).toBe("Test response")
			expect(mockCreate).toHaveBeenCalledWith(
				{
					model: mockOptions.openAiModelId,
					messages: [{ role: "user", content: "Test prompt" }],
				},
				{},
			)
		})

		it("should handle API errors", async () => {
			mockCreate.mockRejectedValueOnce(new Error("API Error"))
			await expect(handler.completePrompt("Test prompt")).rejects.toThrow("OpenAI completion error: API Error")
		})

		it("should handle empty response", async () => {
			mockCreate.mockImplementationOnce(() => ({
				choices: [{ message: { content: "" } }],
			}))
			const result = await handler.completePrompt("Test prompt")
			expect(result).toBe("")
		})
	})

	describe("getModel", () => {
		it("should return model info with sane defaults", () => {
			const model = handler.getModel()
			expect(model.id).toBe(mockOptions.openAiModelId)
			expect(model.info).toBeDefined()
			expect(model.info.contextWindow).toBe(128_000)
			expect(model.info.supportsImages).toBe(true)
		})

		it("should handle undefined model ID", () => {
			const handlerWithoutModel = new OpenAiHandler({
				...mockOptions,
				openAiModelId: undefined,
			})
			const model = handlerWithoutModel.getModel()
			expect(model.id).toBe("")
			expect(model.info).toBeDefined()
		})
	})

	describe("Azure AI Inference Service", () => {
		const azureOptions = {
			...mockOptions,
			openAiBaseUrl: "https://test.services.ai.azure.com",
			openAiModelId: "deepseek-v3",
			azureApiVersion: "2024-05-01-preview",
		}

		it("should initialize with Azure AI Inference Service configuration", () => {
			const azureHandler = new OpenAiHandler(azureOptions)
			expect(azureHandler).toBeInstanceOf(OpenAiHandler)
			expect(azureHandler.getModel().id).toBe(azureOptions.openAiModelId)
		})

		it("should handle streaming responses with Azure AI Inference Service", async () => {
			const azureHandler = new OpenAiHandler(azureOptions)
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = azureHandler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(chunks.length).toBeGreaterThan(0)
			const textChunks = chunks.filter((chunk) => chunk.type === "text")
			expect(textChunks).toHaveLength(1)
			expect(textChunks[0].text).toBe("Test response")

			// Verify the API call was made with correct Azure AI Inference Service path
			expect(mockCreate).toHaveBeenCalledWith(
				{
					model: azureOptions.openAiModelId,
					messages: [
						{ role: "system", content: systemPrompt },
						{ role: "user", content: "Hello!" },
					],
					stream: true,
					stream_options: { include_usage: true },
					temperature: undefined,
					tools: undefined,
					tool_choice: undefined,
					parallel_tool_calls: true,
				},
				{ path: "/models/chat/completions" },
			)

			// Verify max_tokens is NOT included when not explicitly set
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("max_completion_tokens")
		})

		it("should handle non-streaming responses with Azure AI Inference Service", async () => {
			const azureHandler = new OpenAiHandler({
				...azureOptions,
				openAiStreamingEnabled: false,
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = azureHandler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(chunks.length).toBeGreaterThan(0)
			const textChunk = chunks.find((chunk) => chunk.type === "text")
			const usageChunk = chunks.find((chunk) => chunk.type === "usage")

			expect(textChunk).toBeDefined()
			expect(textChunk?.text).toBe("Test response")
			expect(usageChunk).toBeDefined()
			expect(usageChunk?.inputTokens).toBe(10)
			expect(usageChunk?.outputTokens).toBe(5)

			// Verify the API call was made with correct Azure AI Inference Service path
			expect(mockCreate).toHaveBeenCalledWith(
				{
					model: azureOptions.openAiModelId,
					messages: [
						{ role: "system", content: systemPrompt },
						{ role: "user", content: "Hello!" },
					],
					tools: undefined,
					tool_choice: undefined,
					parallel_tool_calls: true,
				},
				{ path: "/models/chat/completions" },
			)

			// Verify max_tokens is NOT included when not explicitly set
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("max_completion_tokens")
		})

		it("should handle completePrompt with Azure AI Inference Service", async () => {
			const azureHandler = new OpenAiHandler(azureOptions)
			const result = await azureHandler.completePrompt("Test prompt")
			expect(result).toBe("Test response")
			expect(mockCreate).toHaveBeenCalledWith(
				{
					model: azureOptions.openAiModelId,
					messages: [{ role: "user", content: "Test prompt" }],
				},
				{ path: "/models/chat/completions" },
			)

			// Verify max_tokens is NOT included when includeMaxTokens is not set
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("max_completion_tokens")
		})
	})

	describe("Grok xAI Provider", () => {
		const grokOptions = {
			...mockOptions,
			openAiBaseUrl: "https://api.x.ai/v1",
			openAiModelId: "grok-1",
		}

		it("should initialize with Grok xAI configuration", () => {
			const grokHandler = new OpenAiHandler(grokOptions)
			expect(grokHandler).toBeInstanceOf(OpenAiHandler)
			expect(grokHandler.getModel().id).toBe(grokOptions.openAiModelId)
		})

		it("should exclude stream_options when streaming with Grok xAI", async () => {
			const grokHandler = new OpenAiHandler(grokOptions)
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = grokHandler.createMessage(systemPrompt, messages)
			await stream.next()

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: grokOptions.openAiModelId,
					stream: true,
				}),
				{},
			)

			const mockCalls = mockCreate.mock.calls
			const lastCall = mockCalls[mockCalls.length - 1]
			expect(lastCall[0]).not.toHaveProperty("stream_options")
		})
	})

	describe("O3 Family Models", () => {
		const o3Options = {
			...mockOptions,
			openAiModelId: "o3-mini",
			openAiCustomModelInfo: {
				contextWindow: 128_000,
				maxTokens: 65536,
				supportsPromptCache: false,
				reasoningEffort: "medium" as "low" | "medium" | "high",
			},
		}

		it("should handle O3 model with streaming and include max_completion_tokens when includeMaxTokens is true", async () => {
			const o3Handler = new OpenAiHandler({
				...o3Options,
				includeMaxTokens: true,
				modelMaxTokens: 32000,
				modelTemperature: 0.5,
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3Handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: "o3-mini",
					messages: [
						{
							role: "developer",
							content: "Formatting re-enabled\nYou are a helpful assistant.",
						},
						{ role: "user", content: "Hello!" },
					],
					stream: true,
					stream_options: { include_usage: true },
					reasoning_effort: "medium",
					temperature: undefined,
					// O3 models do not support deprecated max_tokens but do support max_completion_tokens
					max_completion_tokens: 32000,
				}),
				{},
			)
		})

		it("should handle tool calls with O3 model in streaming mode", async () => {
			const o3Handler = new OpenAiHandler(o3Options)

			mockCreate.mockImplementation(async (options) => {
				return {
					[Symbol.asyncIterator]: async function* () {
						yield {
							choices: [
								{
									delta: {
										tool_calls: [
											{
												index: 0,
												id: "call_1",
												function: { name: "test_tool", arguments: "" },
											},
										],
									},
									finish_reason: null,
								},
							],
						}
						yield {
							choices: [
								{
									delta: {
										tool_calls: [{ index: 0, function: { arguments: "{}" } }],
									},
									finish_reason: "tool_calls",
								},
							],
						}
					},
				}
			})

			const stream = o3Handler.createMessage("system", [])
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			// Provider now yields tool_call_partial chunks, NativeToolCallParser handles reassembly
			const toolCallPartialChunks = chunks.filter((chunk) => chunk.type === "tool_call_partial")
			expect(toolCallPartialChunks).toHaveLength(2)
			expect(toolCallPartialChunks[0]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: "call_1",
				name: "test_tool",
				arguments: "",
			})
			expect(toolCallPartialChunks[1]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: undefined,
				name: undefined,
				arguments: "{}",
			})

			// Verify tool_call_end event is emitted when finish_reason is "tool_calls"
			const toolCallEndChunks = chunks.filter((chunk) => chunk.type === "tool_call_end")
			expect(toolCallEndChunks).toHaveLength(1)
		})

		it("should yield tool calls for O3 model even when finish_reason is not set (fallback behavior)", async () => {
			const o3Handler = new OpenAiHandler(o3Options)

			mockCreate.mockImplementation(async (options) => {
				return {
					[Symbol.asyncIterator]: async function* () {
						yield {
							choices: [
								{
									delta: {
										tool_calls: [
											{
												index: 0,
												id: "call_o3_fallback",
												function: { name: "o3_fallback_tool", arguments: '{"o3":"test"}' },
											},
										],
									},
									finish_reason: null,
								},
							],
						}
						// Stream ends with different finish reason
						yield {
							choices: [
								{
									delta: {},
									finish_reason: "length", // Different finish reason
								},
							],
						}
					},
				}
			})

			const stream = o3Handler.createMessage("system", [])
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			// Provider now yields tool_call_partial chunks, NativeToolCallParser handles reassembly
			const toolCallPartialChunks = chunks.filter((chunk) => chunk.type === "tool_call_partial")
			expect(toolCallPartialChunks).toHaveLength(1)
			expect(toolCallPartialChunks[0]).toEqual({
				type: "tool_call_partial",
				index: 0,
				id: "call_o3_fallback",
				name: "o3_fallback_tool",
				arguments: '{"o3":"test"}',
			})
		})

		it("should handle O3 model with streaming and exclude max_tokens when includeMaxTokens is false", async () => {
			const o3Handler = new OpenAiHandler({
				...o3Options,
				includeMaxTokens: false,
				modelTemperature: 0.7,
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3Handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: "o3-mini",
					messages: [
						{
							role: "developer",
							content: "Formatting re-enabled\nYou are a helpful assistant.",
						},
						{ role: "user", content: "Hello!" },
					],
					stream: true,
					stream_options: { include_usage: true },
					reasoning_effort: "medium",
					temperature: undefined,
				}),
				{},
			)

			// Verify max_tokens is NOT included
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("max_completion_tokens")
		})

		it("should handle O3 model non-streaming with reasoning_effort and max_completion_tokens when includeMaxTokens is true", async () => {
			const o3Handler = new OpenAiHandler({
				...o3Options,
				openAiStreamingEnabled: false,
				includeMaxTokens: true,
				modelTemperature: 0.3,
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3Handler.createMessage(systemPrompt, messages)
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: "o3-mini",
					messages: [
						{
							role: "developer",
							content: "Formatting re-enabled\nYou are a helpful assistant.",
						},
						{ role: "user", content: "Hello!" },
					],
					reasoning_effort: "medium",
					temperature: undefined,
					// O3 models do not support deprecated max_tokens but do support max_completion_tokens
					max_completion_tokens: 65536, // Using default maxTokens from o3Options
				}),
				{},
			)

			// Verify stream is not set
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("stream")
		})

		it("should handle tool calls with O3 model in non-streaming mode", async () => {
			const o3Handler = new OpenAiHandler({
				...o3Options,
				openAiStreamingEnabled: false,
			})

			mockCreate.mockResolvedValueOnce({
				choices: [
					{
						message: {
							role: "assistant",
							content: null,
							tool_calls: [
								{
									id: "call_1",
									type: "function",
									function: {
										name: "test_tool",
										arguments: "{}",
									},
								},
							],
						},
						finish_reason: "tool_calls",
					},
				],
				usage: {
					prompt_tokens: 10,
					completion_tokens: 5,
					total_tokens: 15,
				},
			})

			const stream = o3Handler.createMessage("system", [])
			const chunks: any[] = []
			for await (const chunk of stream) {
				chunks.push(chunk)
			}

			const toolCallChunks = chunks.filter((chunk) => chunk.type === "tool_call")
			expect(toolCallChunks).toHaveLength(1)
			expect(toolCallChunks[0]).toEqual({
				type: "tool_call",
				id: "call_1",
				name: "test_tool",
				arguments: "{}",
			})
		})

		it("should use default temperature of 0 when not specified for O3 models", async () => {
			const o3Handler = new OpenAiHandler({
				...o3Options,
				// No modelTemperature specified
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3Handler.createMessage(systemPrompt, messages)
			await stream.next()

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					temperature: undefined, // Temperature is not supported for O3 models
				}),
				{},
			)
		})

		it("should handle O3 model with Azure AI Inference Service respecting includeMaxTokens", async () => {
			const o3AzureHandler = new OpenAiHandler({
				...o3Options,
				openAiBaseUrl: "https://test.services.ai.azure.com",
				includeMaxTokens: false, // Should NOT include max_tokens
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3AzureHandler.createMessage(systemPrompt, messages)
			await stream.next()

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: "o3-mini",
				}),
				{ path: "/models/chat/completions" },
			)

			// Verify max_tokens is NOT included when includeMaxTokens is false
			const callArgs = mockCreate.mock.calls[0][0]
			expect(callArgs).not.toHaveProperty("max_completion_tokens")
		})

		it("should NOT include max_tokens for O3 model with Azure AI Inference Service even when includeMaxTokens is true", async () => {
			const o3AzureHandler = new OpenAiHandler({
				...o3Options,
				openAiBaseUrl: "https://test.services.ai.azure.com",
				includeMaxTokens: true, // Should include max_tokens
			})
			const systemPrompt = "You are a helpful assistant."
			const messages: Anthropic.Messages.MessageParam[] = [
				{
					role: "user",
					content: "Hello!",
				},
			]

			const stream = o3AzureHandler.createMessage(systemPrompt, messages)
			await stream.next()

			expect(mockCreate).toHaveBeenCalledWith(
				expect.objectContaining({
					model: "o3-mini",
					// O3 models do not support max_tokens
				}),
				{ path: "/models/chat/completions" },
			)
		})
	})
})

describe("getOpenAiModels", () => {
	beforeEach(() => {
		vi.mocked(axios.get).mockClear()
	})

	it("should return empty array when baseUrl is not provided", async () => {
		const result = await getOpenAiModels(undefined, "test-key")
		expect(result).toEqual([])
		expect(axios.get).not.toHaveBeenCalled()
	})

	it("should return empty array when baseUrl is empty string", async () => {
		const result = await getOpenAiModels("", "test-key")
		expect(result).toEqual([])
		expect(axios.get).not.toHaveBeenCalled()
	})

	it("should trim whitespace from baseUrl", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "gpt-4" }, { id: "gpt-3.5-turbo" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		const result = await getOpenAiModels("  https://api.openai.com/v1  ", "test-key")

		expect(axios.get).toHaveBeenCalledWith("https://api.openai.com/v1/models", expect.any(Object))
		expect(result).toEqual(["gpt-4", "gpt-3.5-turbo"])
	})

	it("should handle baseUrl with trailing spaces", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "model-1" }, { id: "model-2" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		const result = await getOpenAiModels("https://api.example.com/v1 ", "test-key")

		expect(axios.get).toHaveBeenCalledWith("https://api.example.com/v1/models", expect.any(Object))
		expect(result).toEqual(["model-1", "model-2"])
	})

	it("should handle baseUrl with leading spaces", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "model-1" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		const result = await getOpenAiModels(" https://api.example.com/v1", "test-key")

		expect(axios.get).toHaveBeenCalledWith("https://api.example.com/v1/models", expect.any(Object))
		expect(result).toEqual(["model-1"])
	})

	it("should return empty array for invalid URL after trimming", async () => {
		const result = await getOpenAiModels("   not-a-valid-url   ", "test-key")
		expect(result).toEqual([])
		expect(axios.get).not.toHaveBeenCalled()
	})

	it("should include authorization header when apiKey is provided", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "model-1" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		await getOpenAiModels("https://api.example.com/v1", "test-api-key")

		expect(axios.get).toHaveBeenCalledWith(
			"https://api.example.com/v1/models",
			expect.objectContaining({
				headers: expect.objectContaining({
					Authorization: "Bearer test-api-key",
				}),
			}),
		)
	})

	it("should include custom headers when provided", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "model-1" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		const customHeaders = {
			"X-Custom-Header": "custom-value",
		}

		await getOpenAiModels("https://api.example.com/v1", "test-key", customHeaders)

		expect(axios.get).toHaveBeenCalledWith(
			"https://api.example.com/v1/models",
			expect.objectContaining({
				headers: expect.objectContaining({
					"X-Custom-Header": "custom-value",
					Authorization: "Bearer test-key",
				}),
			}),
		)
	})

	it("should handle API errors gracefully", async () => {
		vi.mocked(axios.get).mockRejectedValueOnce(new Error("Network error"))

		const result = await getOpenAiModels("https://api.example.com/v1", "test-key")

		expect(result).toEqual([])
	})

	it("should handle malformed response data", async () => {
		vi.mocked(axios.get).mockResolvedValueOnce({ data: null })

		const result = await getOpenAiModels("https://api.example.com/v1", "test-key")

		expect(result).toEqual([])
	})

	it("should deduplicate model IDs", async () => {
		const mockResponse = {
			data: {
				data: [{ id: "gpt-4" }, { id: "gpt-4" }, { id: "gpt-3.5-turbo" }, { id: "gpt-4" }],
			},
		}
		vi.mocked(axios.get).mockResolvedValueOnce(mockResponse)

		const result = await getOpenAiModels("https://api.example.com/v1", "test-key")

		expect(result).toEqual(["gpt-4", "gpt-3.5-turbo"])
	})
})