Roo-Code/src/api/providers/__tests__/requesty.test.ts
2025-03-07 16:41:09 +00:00

257 lines
6.7 KiB
TypeScript

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