mirror of
https://github.com/RooVetGit/Roo-Code.git
synced 2026-08-28 05:27:24 +00:00
feat: migrate Requesty provider to AI SDK (@requesty/ai-sdk) (#11350)
This commit is contained in:
Daniel
GitHub
parent
f51e91ac76
commit
7a38b99232
5 changed files with 586 additions and 364 deletions
19
pnpm-lock.yaml
generated
19
pnpm-lock.yaml
generated
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@ -803,6 +803,9 @@ importers:
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'@qdrant/js-client-rest':
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specifier: ^1.14.0
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version: 1.14.0(typescript@5.8.3)
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'@requesty/ai-sdk':
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specifier: ^3.0.0
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version: 3.0.0(vite@6.3.5(@types/node@20.17.50)(jiti@2.4.2)(lightningcss@1.30.1)(tsx@4.19.4)(yaml@2.8.0))(zod@3.25.76)
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'@roo-code/cloud':
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specifier: workspace:^
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version: link:../packages/cloud
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@ -3774,6 +3777,13 @@ packages:
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peerDependencies:
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'@redis/client': ^5.5.5
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'@requesty/ai-sdk@3.0.0':
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resolution: {integrity: sha512-kGZuOshBx5yjQ3LQKITl/W89Xu8HrektZ6pN0peI64sQD8fpoWionUU+39m0fkdZhOlotebj5zO3emkX7y7O6Q==}
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engines: {node: '>=18'}
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peerDependencies:
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vite: ^7.1.7
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zod: 3.25.76
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'@resvg/resvg-wasm@2.4.0':
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resolution: {integrity: sha512-C7c51Nn4yTxXFKvgh2txJFNweaVcfUPQxwEUFw4aWsCmfiBDJsTSwviIF8EcwjQ6k8bPyMWCl1vw4BdxE569Cg==}
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engines: {node: '>= 10'}
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@ -13808,6 +13818,13 @@ snapshots:
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dependencies:
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'@redis/client': 5.5.5
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'@requesty/ai-sdk@3.0.0(vite@6.3.5(@types/node@20.17.50)(jiti@2.4.2)(lightningcss@1.30.1)(tsx@4.19.4)(yaml@2.8.0))(zod@3.25.76)':
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dependencies:
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'@ai-sdk/provider': 3.0.8
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'@ai-sdk/provider-utils': 3.0.20(zod@3.25.76)
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vite: 6.3.5(@types/node@20.17.50)(jiti@2.4.2)(lightningcss@1.30.1)(tsx@4.19.4)(yaml@2.8.0)
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zod: 3.25.76
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'@resvg/resvg-wasm@2.4.0': {}
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'@rollup/rollup-android-arm-eabi@4.40.2':
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@ -14953,7 +14970,7 @@ snapshots:
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sirv: 3.0.1
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tinyglobby: 0.2.14
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tinyrainbow: 2.0.0
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vitest: 3.2.4(@types/debug@4.1.12)(@types/node@24.2.1)(@vitest/ui@3.2.4)(jiti@2.4.2)(jsdom@26.1.0)(lightningcss@1.30.1)(tsx@4.19.4)(yaml@2.8.0)
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vitest: 3.2.4(@types/debug@4.1.12)(@types/node@20.17.50)(@vitest/ui@3.2.4)(jiti@2.4.2)(jsdom@26.1.0)(lightningcss@1.30.1)(tsx@4.19.4)(yaml@2.8.0)
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'@vitest/utils@3.2.4':
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dependencies:
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@ -1,31 +1,33 @@
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// npx vitest run api/providers/__tests__/requesty.spec.ts
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import { Anthropic } from "@anthropic-ai/sdk"
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import OpenAI from "openai"
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// Use vi.hoisted to define mock functions that can be referenced in hoisted vi.mock() calls
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const { mockStreamText, mockGenerateText } = vi.hoisted(() => ({
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mockStreamText: vi.fn(),
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mockGenerateText: vi.fn(),
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}))
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import { RequestyHandler } from "../requesty"
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import { ApiHandlerOptions } from "../../../shared/api"
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import { Package } from "../../../shared/package"
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import { ApiHandlerCreateMessageMetadata } from "../../index"
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const mockCreate = vitest.fn()
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vitest.mock("openai", () => {
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vi.mock("ai", async (importOriginal) => {
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const actual = await importOriginal<typeof import("ai")>()
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return {
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default: vitest.fn().mockImplementation(() => ({
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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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})),
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...actual,
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streamText: mockStreamText,
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generateText: mockGenerateText,
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}
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})
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vitest.mock("delay", () => ({ default: vitest.fn(() => Promise.resolve()) }))
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vi.mock("@requesty/ai-sdk", () => ({
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createRequesty: vi.fn(() => {
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return vi.fn(() => ({
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modelId: "coding/claude-4-sonnet",
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provider: "requesty",
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}))
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}),
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}))
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vitest.mock("../fetchers/modelCache", () => ({
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getModels: vitest.fn().mockImplementation(() => {
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vi.mock("delay", () => ({ default: vi.fn(() => Promise.resolve()) }))
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vi.mock("../fetchers/modelCache", () => ({
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getModels: vi.fn().mockImplementation(() => {
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return Promise.resolve({
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"coding/claude-4-sonnet": {
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maxTokens: 8192,
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@ -42,41 +44,62 @@ vitest.mock("../fetchers/modelCache", () => ({
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}),
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}))
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import type { Anthropic } from "@anthropic-ai/sdk"
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import { createRequesty } from "@requesty/ai-sdk"
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import { requestyDefaultModelId } from "@roo-code/types"
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import type { ApiHandlerOptions } from "../../../shared/api"
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import type { ApiHandlerCreateMessageMetadata } from "../../index"
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import { RequestyHandler } from "../requesty"
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describe("RequestyHandler", () => {
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const mockOptions: ApiHandlerOptions = {
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requestyApiKey: "test-key",
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requestyModelId: "coding/claude-4-sonnet",
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}
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beforeEach(() => vitest.clearAllMocks())
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beforeEach(() => vi.clearAllMocks())
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it("initializes with correct options", () => {
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const handler = new RequestyHandler(mockOptions)
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expect(handler).toBeInstanceOf(RequestyHandler)
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describe("constructor", () => {
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it("initializes with correct options", () => {
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const handler = new RequestyHandler(mockOptions)
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expect(handler).toBeInstanceOf(RequestyHandler)
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expect(OpenAI).toHaveBeenCalledWith({
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baseURL: "https://router.requesty.ai/v1",
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apiKey: mockOptions.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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"User-Agent": `RooCode/${Package.version}`,
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},
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expect(createRequesty).toHaveBeenCalledWith(
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expect.objectContaining({
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baseURL: "https://router.requesty.ai/v1",
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apiKey: mockOptions.requestyApiKey,
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compatibility: "compatible",
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}),
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)
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})
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})
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it("can use a base URL instead of the default", () => {
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const handler = new RequestyHandler({ ...mockOptions, requestyBaseUrl: "https://custom.requesty.ai/v1" })
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expect(handler).toBeInstanceOf(RequestyHandler)
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it("can use a custom base URL", () => {
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const handler = new RequestyHandler({
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...mockOptions,
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requestyBaseUrl: "https://custom.requesty.ai/v1",
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})
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expect(handler).toBeInstanceOf(RequestyHandler)
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expect(OpenAI).toHaveBeenCalledWith({
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baseURL: "https://custom.requesty.ai/v1",
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apiKey: mockOptions.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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"User-Agent": `RooCode/${Package.version}`,
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},
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expect(createRequesty).toHaveBeenCalledWith(
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expect.objectContaining({
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baseURL: "https://custom.requesty.ai/v1",
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apiKey: mockOptions.requestyApiKey,
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}),
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)
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})
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it("uses 'not-provided' when no API key is given", () => {
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const handler = new RequestyHandler({})
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expect(handler).toBeInstanceOf(RequestyHandler)
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expect(createRequesty).toHaveBeenCalledWith(
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expect.objectContaining({
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apiKey: "not-provided",
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}),
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)
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})
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})
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@ -101,66 +124,50 @@ describe("RequestyHandler", () => {
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})
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})
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it("returns default model info when options are not provided", async () => {
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const handler = new RequestyHandler({})
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it("returns default model info when requestyModelId is not provided", async () => {
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const handler = new RequestyHandler({ requestyApiKey: "test-key" })
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const result = await handler.fetchModel()
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expect(result).toMatchObject({
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id: mockOptions.requestyModelId,
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info: {
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maxTokens: 8192,
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contextWindow: 200000,
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supportsImages: true,
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supportsPromptCache: true,
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inputPrice: 3,
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outputPrice: 15,
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cacheWritesPrice: 3.75,
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cacheReadsPrice: 0.3,
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description: "Claude 4 Sonnet",
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},
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})
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expect(result.id).toBe(requestyDefaultModelId)
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})
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})
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describe("createMessage", () => {
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it("generates correct stream chunks", async () => {
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const handler = new RequestyHandler(mockOptions)
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const systemPrompt = "test system prompt"
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const messages: Anthropic.Messages.MessageParam[] = [{ role: "user" as const, content: "test message" }]
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const mockStream = {
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async *[Symbol.asyncIterator]() {
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yield {
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id: mockOptions.requestyModelId,
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choices: [{ delta: { content: "test response" } }],
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}
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yield {
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id: "test-id",
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choices: [{ delta: {} }],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 20,
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prompt_tokens_details: {
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caching_tokens: 5,
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cached_tokens: 2,
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},
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},
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}
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},
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it("generates correct stream chunks", async () => {
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async function* mockFullStream() {
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yield { type: "text-delta", text: "test response" }
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}
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mockCreate.mockResolvedValue(mockStream)
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const mockUsage = Promise.resolve({
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inputTokens: 10,
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outputTokens: 20,
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})
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const systemPrompt = "test system prompt"
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const messages: Anthropic.Messages.MessageParam[] = [{ role: "user" as const, content: "test message" }]
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const mockProviderMetadata = Promise.resolve({
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requesty: {
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usage: {
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cachingTokens: 5,
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cachedTokens: 2,
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},
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},
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})
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const generator = handler.createMessage(systemPrompt, messages)
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const chunks = []
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mockStreamText.mockReturnValue({
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fullStream: mockFullStream(),
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usage: mockUsage,
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providerMetadata: mockProviderMetadata,
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})
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for await (const chunk of generator) {
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const handler = new RequestyHandler(mockOptions)
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const chunks: any[] = []
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for await (const chunk of handler.createMessage(systemPrompt, messages)) {
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chunks.push(chunk)
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}
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// Verify stream chunks
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expect(chunks).toHaveLength(2) // One text chunk and one usage chunk
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expect(chunks).toHaveLength(2)
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expect(chunks[0]).toEqual({ type: "text", text: "test response" })
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expect(chunks[1]).toEqual({
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type: "usage",
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@ -168,181 +175,199 @@ describe("RequestyHandler", () => {
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outputTokens: 20,
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cacheWriteTokens: 5,
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cacheReadTokens: 2,
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reasoningTokens: undefined,
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totalCost: expect.any(Number),
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})
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})
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// Verify OpenAI client was called with correct parameters
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expect(mockCreate).toHaveBeenCalledWith(
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it("calls streamText with correct parameters", async () => {
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async function* mockFullStream() {
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yield { type: "text-delta", text: "test response" }
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}
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mockStreamText.mockReturnValue({
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fullStream: mockFullStream(),
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usage: Promise.resolve({ inputTokens: 10, outputTokens: 5 }),
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providerMetadata: Promise.resolve({}),
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})
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const handler = new RequestyHandler(mockOptions)
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const stream = handler.createMessage(systemPrompt, messages)
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for await (const _chunk of stream) {
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// consume
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}
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expect(mockStreamText).toHaveBeenCalledWith(
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expect.objectContaining({
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max_tokens: 8192,
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messages: [
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{
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role: "system",
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content: "test system prompt",
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},
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{
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role: "user",
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content: "test message",
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},
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],
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model: "coding/claude-4-sonnet",
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stream: true,
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stream_options: { include_usage: true },
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system: "test system prompt",
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temperature: 0,
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maxOutputTokens: 8192,
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}),
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)
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})
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it("passes trace_id and mode via providerOptions", async () => {
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async function* mockFullStream() {
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yield { type: "text-delta", text: "test response" }
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}
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mockStreamText.mockReturnValue({
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fullStream: mockFullStream(),
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usage: Promise.resolve({ inputTokens: 10, outputTokens: 5 }),
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providerMetadata: Promise.resolve({}),
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})
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const metadata: ApiHandlerCreateMessageMetadata = {
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taskId: "test-task",
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mode: "code",
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}
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const handler = new RequestyHandler(mockOptions)
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const stream = handler.createMessage(systemPrompt, messages, metadata)
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for await (const _chunk of stream) {
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// consume
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}
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expect(mockStreamText).toHaveBeenCalledWith(
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expect.objectContaining({
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providerOptions: {
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requesty: expect.objectContaining({
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extraBody: {
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requesty: {
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trace_id: "test-task",
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extra: { mode: "code" },
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},
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},
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}),
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},
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}),
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)
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})
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it("handles API errors", async () => {
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const handler = new RequestyHandler(mockOptions)
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const mockError = new Error("API Error")
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mockCreate.mockRejectedValue(mockError)
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const generator = handler.createMessage("test", [])
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await expect(generator.next()).rejects.toThrow("API Error")
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async function* errorStream() {
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yield { type: "text-delta", text: "" }
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throw mockError
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}
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mockStreamText.mockReturnValue({
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fullStream: errorStream(),
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usage: Promise.resolve({}),
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providerMetadata: Promise.resolve({}),
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})
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const handler = new RequestyHandler(mockOptions)
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const generator = handler.createMessage(systemPrompt, messages)
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await generator.next()
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await expect(generator.next()).rejects.toThrow()
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})
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describe("native tool support", () => {
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const systemPrompt = "test system prompt"
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const messages: Anthropic.Messages.MessageParam[] = [
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const toolMessages: Anthropic.Messages.MessageParam[] = [
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{ role: "user" as const, content: "What's the weather?" },
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]
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const mockTools: OpenAI.Chat.ChatCompletionTool[] = [
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{
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type: "function",
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function: {
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name: "get_weather",
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description: "Get the current weather",
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parameters: {
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type: "object",
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properties: {
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location: { type: "string" },
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it("should include tools in request when tools are provided", async () => {
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const mockTools = [
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{
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type: "function",
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function: {
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name: "get_weather",
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description: "Get the current weather",
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parameters: {
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type: "object",
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properties: {
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location: { type: "string" },
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},
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required: ["location"],
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},
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required: ["location"],
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},
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},
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},
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]
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]
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beforeEach(() => {
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const mockStream = {
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async *[Symbol.asyncIterator]() {
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yield {
|
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id: "test-id",
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choices: [{ delta: { content: "test response" } }],
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}
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},
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async function* mockFullStream() {
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yield { type: "text-delta", text: "test response" }
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}
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mockCreate.mockResolvedValue(mockStream)
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})
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it("should include tools in request when tools are provided", async () => {
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mockStreamText.mockReturnValue({
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fullStream: mockFullStream(),
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usage: Promise.resolve({ inputTokens: 10, outputTokens: 5 }),
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providerMetadata: Promise.resolve({}),
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})
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const metadata: ApiHandlerCreateMessageMetadata = {
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taskId: "test-task",
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tools: mockTools,
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tools: mockTools as any,
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tool_choice: "auto",
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}
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const handler = new RequestyHandler(mockOptions)
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const iterator = handler.createMessage(systemPrompt, messages, metadata)
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await iterator.next()
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const stream = handler.createMessage(systemPrompt, toolMessages, metadata)
|
||||
for await (const _chunk of stream) {
|
||||
// consume
|
||||
}
|
||||
|
||||
expect(mockCreate).toHaveBeenCalledWith(
|
||||
expect(mockStreamText).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
tools: expect.arrayContaining([
|
||||
expect.objectContaining({
|
||||
type: "function",
|
||||
function: expect.objectContaining({
|
||||
name: "get_weather",
|
||||
description: "Get the current weather",
|
||||
}),
|
||||
}),
|
||||
]),
|
||||
tool_choice: "auto",
|
||||
tools: expect.any(Object),
|
||||
toolChoice: expect.any(String),
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
||||
it("should handle tool_call_partial chunks in streaming response", async () => {
|
||||
const mockStreamWithToolCalls = {
|
||||
async *[Symbol.asyncIterator]() {
|
||||
yield {
|
||||
id: "test-id",
|
||||
choices: [
|
||||
{
|
||||
delta: {
|
||||
tool_calls: [
|
||||
{
|
||||
index: 0,
|
||||
id: "call_123",
|
||||
function: {
|
||||
name: "get_weather",
|
||||
arguments: '{"location":',
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
yield {
|
||||
id: "test-id",
|
||||
choices: [
|
||||
{
|
||||
delta: {
|
||||
tool_calls: [
|
||||
{
|
||||
index: 0,
|
||||
function: {
|
||||
arguments: '"New York"}',
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
yield {
|
||||
id: "test-id",
|
||||
choices: [{ delta: {} }],
|
||||
usage: { prompt_tokens: 10, completion_tokens: 20 },
|
||||
}
|
||||
},
|
||||
it("should handle tool call streaming parts", async () => {
|
||||
async function* mockFullStream() {
|
||||
yield {
|
||||
type: "tool-input-start",
|
||||
id: "call_123",
|
||||
toolName: "get_weather",
|
||||
}
|
||||
yield {
|
||||
type: "tool-input-delta",
|
||||
id: "call_123",
|
||||
delta: '{"location":"New York"}',
|
||||
}
|
||||
yield {
|
||||
type: "tool-input-end",
|
||||
id: "call_123",
|
||||
}
|
||||
}
|
||||
mockCreate.mockResolvedValue(mockStreamWithToolCalls)
|
||||
|
||||
const metadata: ApiHandlerCreateMessageMetadata = {
|
||||
taskId: "test-task",
|
||||
tools: mockTools,
|
||||
}
|
||||
mockStreamText.mockReturnValue({
|
||||
fullStream: mockFullStream(),
|
||||
usage: Promise.resolve({ inputTokens: 10, outputTokens: 5 }),
|
||||
providerMetadata: Promise.resolve({}),
|
||||
})
|
||||
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
const chunks = []
|
||||
for await (const chunk of handler.createMessage(systemPrompt, messages, metadata)) {
|
||||
const chunks: any[] = []
|
||||
for await (const chunk of handler.createMessage(systemPrompt, toolMessages)) {
|
||||
chunks.push(chunk)
|
||||
}
|
||||
|
||||
// Expect two tool_call_partial chunks and one usage chunk
|
||||
expect(chunks).toHaveLength(3)
|
||||
expect(chunks[0]).toEqual({
|
||||
type: "tool_call_partial",
|
||||
index: 0,
|
||||
const startChunks = chunks.filter((c) => c.type === "tool_call_start")
|
||||
expect(startChunks).toHaveLength(1)
|
||||
expect(startChunks[0]).toEqual({
|
||||
type: "tool_call_start",
|
||||
id: "call_123",
|
||||
name: "get_weather",
|
||||
arguments: '{"location":',
|
||||
})
|
||||
expect(chunks[1]).toEqual({
|
||||
type: "tool_call_partial",
|
||||
index: 0,
|
||||
id: undefined,
|
||||
name: undefined,
|
||||
arguments: '"New York"}',
|
||||
|
||||
const deltaChunks = chunks.filter((c) => c.type === "tool_call_delta")
|
||||
expect(deltaChunks).toHaveLength(1)
|
||||
expect(deltaChunks[0]).toEqual({
|
||||
type: "tool_call_delta",
|
||||
id: "call_123",
|
||||
delta: '{"location":"New York"}',
|
||||
})
|
||||
expect(chunks[2]).toMatchObject({
|
||||
type: "usage",
|
||||
inputTokens: 10,
|
||||
outputTokens: 20,
|
||||
|
||||
const endChunks = chunks.filter((c) => c.type === "tool_call_end")
|
||||
expect(endChunks).toHaveLength(1)
|
||||
expect(endChunks[0]).toEqual({
|
||||
type: "tool_call_end",
|
||||
id: "call_123",
|
||||
})
|
||||
})
|
||||
})
|
||||
|
|
@ -350,36 +375,134 @@ describe("RequestyHandler", () => {
|
|||
|
||||
describe("completePrompt", () => {
|
||||
it("returns correct response", async () => {
|
||||
mockGenerateText.mockResolvedValue({
|
||||
text: "test completion",
|
||||
})
|
||||
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
const mockResponse = { choices: [{ message: { content: "test completion" } }] }
|
||||
|
||||
mockCreate.mockResolvedValue(mockResponse)
|
||||
|
||||
const result = await handler.completePrompt("test prompt")
|
||||
|
||||
expect(result).toBe("test completion")
|
||||
|
||||
expect(mockCreate).toHaveBeenCalledWith({
|
||||
model: mockOptions.requestyModelId,
|
||||
max_tokens: 8192,
|
||||
messages: [{ role: "system", content: "test prompt" }],
|
||||
temperature: 0,
|
||||
})
|
||||
expect(mockGenerateText).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
prompt: "test prompt",
|
||||
maxOutputTokens: 8192,
|
||||
temperature: 0,
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
||||
it("handles API errors", async () => {
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
const mockError = new Error("API Error")
|
||||
mockCreate.mockRejectedValue(mockError)
|
||||
mockGenerateText.mockRejectedValue(mockError)
|
||||
|
||||
await expect(handler.completePrompt("test prompt")).rejects.toThrow("API Error")
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
await expect(handler.completePrompt("test prompt")).rejects.toThrow()
|
||||
})
|
||||
})
|
||||
|
||||
describe("processUsageMetrics", () => {
|
||||
it("should correctly process usage metrics with Requesty provider metadata", () => {
|
||||
class TestRequestyHandler extends RequestyHandler {
|
||||
public testProcessUsageMetrics(usage: any, modelInfo?: any, providerMetadata?: any) {
|
||||
return this.processUsageMetrics(usage, modelInfo, providerMetadata)
|
||||
}
|
||||
}
|
||||
|
||||
const testHandler = new TestRequestyHandler(mockOptions)
|
||||
|
||||
const usage = {
|
||||
inputTokens: 100,
|
||||
outputTokens: 50,
|
||||
}
|
||||
|
||||
const providerMetadata = {
|
||||
requesty: {
|
||||
usage: {
|
||||
cachingTokens: 10,
|
||||
cachedTokens: 20,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
const modelInfo = {
|
||||
maxTokens: 8192,
|
||||
contextWindow: 200000,
|
||||
supportsImages: true,
|
||||
supportsPromptCache: true,
|
||||
inputPrice: 3,
|
||||
outputPrice: 15,
|
||||
cacheWritesPrice: 3.75,
|
||||
cacheReadsPrice: 0.3,
|
||||
}
|
||||
|
||||
const result = testHandler.testProcessUsageMetrics(usage, modelInfo, providerMetadata)
|
||||
|
||||
expect(result.type).toBe("usage")
|
||||
expect(result.inputTokens).toBe(100)
|
||||
expect(result.outputTokens).toBe(50)
|
||||
expect(result.cacheWriteTokens).toBe(10)
|
||||
expect(result.cacheReadTokens).toBe(20)
|
||||
expect(result.totalCost).toBeGreaterThan(0)
|
||||
})
|
||||
|
||||
it("handles unexpected errors", async () => {
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
mockCreate.mockRejectedValue(new Error("Unexpected error"))
|
||||
it("should fall back to usage.details when providerMetadata is absent", () => {
|
||||
class TestRequestyHandler extends RequestyHandler {
|
||||
public testProcessUsageMetrics(usage: any, modelInfo?: any, providerMetadata?: any) {
|
||||
return this.processUsageMetrics(usage, modelInfo, providerMetadata)
|
||||
}
|
||||
}
|
||||
|
||||
await expect(handler.completePrompt("test prompt")).rejects.toThrow("Unexpected error")
|
||||
const testHandler = new TestRequestyHandler(mockOptions)
|
||||
|
||||
const usage = {
|
||||
inputTokens: 100,
|
||||
outputTokens: 50,
|
||||
details: {
|
||||
cachedInputTokens: 15,
|
||||
reasoningTokens: 25,
|
||||
},
|
||||
}
|
||||
|
||||
const result = testHandler.testProcessUsageMetrics(usage)
|
||||
|
||||
expect(result.type).toBe("usage")
|
||||
expect(result.inputTokens).toBe(100)
|
||||
expect(result.outputTokens).toBe(50)
|
||||
expect(result.cacheWriteTokens).toBe(0)
|
||||
expect(result.cacheReadTokens).toBe(15)
|
||||
expect(result.reasoningTokens).toBe(25)
|
||||
})
|
||||
|
||||
it("should handle missing cache metrics gracefully", () => {
|
||||
class TestRequestyHandler extends RequestyHandler {
|
||||
public testProcessUsageMetrics(usage: any, modelInfo?: any, providerMetadata?: any) {
|
||||
return this.processUsageMetrics(usage, modelInfo, providerMetadata)
|
||||
}
|
||||
}
|
||||
|
||||
const testHandler = new TestRequestyHandler(mockOptions)
|
||||
|
||||
const usage = {
|
||||
inputTokens: 100,
|
||||
outputTokens: 50,
|
||||
}
|
||||
|
||||
const result = testHandler.testProcessUsageMetrics(usage)
|
||||
|
||||
expect(result.type).toBe("usage")
|
||||
expect(result.inputTokens).toBe(100)
|
||||
expect(result.outputTokens).toBe(50)
|
||||
expect(result.cacheWriteTokens).toBe(0)
|
||||
expect(result.cacheReadTokens).toBe(0)
|
||||
expect(result.totalCost).toBe(0)
|
||||
})
|
||||
})
|
||||
|
||||
describe("isAiSdkProvider", () => {
|
||||
it("returns true", () => {
|
||||
const handler = new RequestyHandler(mockOptions)
|
||||
expect(handler.isAiSdkProvider()).toBe(true)
|
||||
})
|
||||
})
|
||||
})
|
||||
|
|
|
|||
|
|
@ -1,60 +1,39 @@
|
|||
import { Anthropic } from "@anthropic-ai/sdk"
|
||||
import OpenAI from "openai"
|
||||
import { createRequesty, type RequestyProviderMetadata } from "@requesty/ai-sdk"
|
||||
import { streamText, generateText, ToolSet } from "ai"
|
||||
|
||||
import { type ModelInfo, type ModelRecord, requestyDefaultModelId, requestyDefaultModelInfo } from "@roo-code/types"
|
||||
|
||||
import type { ApiHandlerOptions } from "../../shared/api"
|
||||
import { calculateApiCostOpenAI } from "../../shared/cost"
|
||||
|
||||
import { convertToOpenAiMessages } from "../transform/openai-format"
|
||||
import {
|
||||
convertToAiSdkMessages,
|
||||
convertToolsForAiSdk,
|
||||
processAiSdkStreamPart,
|
||||
mapToolChoice,
|
||||
handleAiSdkError,
|
||||
} from "../transform/ai-sdk"
|
||||
import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
|
||||
import { getModelParams } from "../transform/model-params"
|
||||
import { AnthropicReasoningParams } from "../transform/reasoning"
|
||||
|
||||
import { DEFAULT_HEADERS } from "./constants"
|
||||
import { getModels } from "./fetchers/modelCache"
|
||||
import { BaseProvider } from "./base-provider"
|
||||
import type { SingleCompletionHandler, ApiHandlerCreateMessageMetadata } from "../index"
|
||||
import { toRequestyServiceUrl } from "../../shared/utils/requesty"
|
||||
import { handleOpenAIError } from "./utils/openai-error-handler"
|
||||
import { applyRouterToolPreferences } from "./utils/router-tool-preferences"
|
||||
|
||||
// Requesty usage includes an extra field for Anthropic use cases.
|
||||
// Safely cast the prompt token details section to the appropriate structure.
|
||||
interface RequestyUsage extends OpenAI.CompletionUsage {
|
||||
prompt_tokens_details?: {
|
||||
caching_tokens?: number
|
||||
cached_tokens?: number
|
||||
}
|
||||
total_cost?: number
|
||||
}
|
||||
|
||||
type RequestyChatCompletionParamsStreaming = OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming & {
|
||||
requesty?: {
|
||||
trace_id?: string
|
||||
extra?: {
|
||||
mode?: string
|
||||
}
|
||||
}
|
||||
thinking?: AnthropicReasoningParams
|
||||
}
|
||||
|
||||
type RequestyChatCompletionParams = OpenAI.Chat.ChatCompletionCreateParams & {
|
||||
requesty?: {
|
||||
trace_id?: string
|
||||
extra?: {
|
||||
mode?: string
|
||||
}
|
||||
}
|
||||
thinking?: AnthropicReasoningParams
|
||||
}
|
||||
|
||||
/**
|
||||
* Requesty provider using the dedicated @requesty/ai-sdk package.
|
||||
* Requesty is a unified LLM gateway providing access to 300+ models.
|
||||
* This handler uses the Vercel AI SDK for streaming and tool support.
|
||||
*/
|
||||
export class RequestyHandler extends BaseProvider implements SingleCompletionHandler {
|
||||
protected options: ApiHandlerOptions
|
||||
protected models: ModelRecord = {}
|
||||
private client: OpenAI
|
||||
protected provider: ReturnType<typeof createRequesty>
|
||||
private baseURL: string
|
||||
private readonly providerName = "Requesty"
|
||||
|
||||
constructor(options: ApiHandlerOptions) {
|
||||
super()
|
||||
|
|
@ -64,10 +43,11 @@ export class RequestyHandler extends BaseProvider implements SingleCompletionHan
|
|||
|
||||
const apiKey = this.options.requestyApiKey ?? "not-provided"
|
||||
|
||||
this.client = new OpenAI({
|
||||
this.provider = createRequesty({
|
||||
baseURL: this.baseURL,
|
||||
apiKey: apiKey,
|
||||
defaultHeaders: DEFAULT_HEADERS,
|
||||
headers: DEFAULT_HEADERS,
|
||||
compatibility: "compatible",
|
||||
})
|
||||
}
|
||||
|
||||
|
|
@ -81,11 +61,10 @@ export class RequestyHandler extends BaseProvider implements SingleCompletionHan
|
|||
const cachedInfo = this.models[id] ?? requestyDefaultModelInfo
|
||||
let info: ModelInfo = cachedInfo
|
||||
|
||||
// Apply tool preferences for models accessed through routers (OpenAI, Gemini)
|
||||
info = applyRouterToolPreferences(id, info)
|
||||
|
||||
const params = getModelParams({
|
||||
format: "anthropic",
|
||||
format: "openai",
|
||||
modelId: id,
|
||||
model: info,
|
||||
settings: this.options,
|
||||
|
|
@ -95,125 +74,169 @@ export class RequestyHandler extends BaseProvider implements SingleCompletionHan
|
|||
return { id, info, ...params }
|
||||
}
|
||||
|
||||
protected processUsageMetrics(usage: any, modelInfo?: ModelInfo): ApiStreamUsageChunk {
|
||||
const requestyUsage = usage as RequestyUsage
|
||||
const inputTokens = requestyUsage?.prompt_tokens || 0
|
||||
const outputTokens = requestyUsage?.completion_tokens || 0
|
||||
const cacheWriteTokens = requestyUsage?.prompt_tokens_details?.caching_tokens || 0
|
||||
const cacheReadTokens = requestyUsage?.prompt_tokens_details?.cached_tokens || 0
|
||||
/**
|
||||
* Get the language model for the configured model ID, including reasoning settings.
|
||||
*
|
||||
* Reasoning settings (includeReasoning, reasoningEffort) must be passed as model
|
||||
* settings — NOT as providerOptions — because the SDK reads them from this.settings
|
||||
* to populate the top-level `include_reasoning` and `reasoning_effort` request fields.
|
||||
*/
|
||||
protected getLanguageModel() {
|
||||
const { id, reasoningEffort, reasoningBudget } = this.getModel()
|
||||
|
||||
let resolvedEffort: string | undefined
|
||||
if (reasoningBudget) {
|
||||
resolvedEffort = String(reasoningBudget)
|
||||
} else if (reasoningEffort) {
|
||||
resolvedEffort = reasoningEffort
|
||||
}
|
||||
|
||||
const needsReasoning = !!resolvedEffort
|
||||
|
||||
return this.provider(id, {
|
||||
...(needsReasoning ? { includeReasoning: true, reasoningEffort: resolvedEffort } : {}),
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the max output tokens parameter to include in the request.
|
||||
*/
|
||||
protected getMaxOutputTokens(): number | undefined {
|
||||
const { info } = this.getModel()
|
||||
return this.options.modelMaxTokens || info.maxTokens || undefined
|
||||
}
|
||||
|
||||
/**
|
||||
* Build the Requesty provider options for tracing metadata.
|
||||
*
|
||||
* Note: providerOptions.requesty gets placed into body.requesty (the Requesty
|
||||
* metadata field), NOT into top-level body fields. Only tracing/metadata should
|
||||
* go here — reasoning settings go through model settings in getLanguageModel().
|
||||
*/
|
||||
private getRequestyProviderOptions(metadata?: ApiHandlerCreateMessageMetadata) {
|
||||
if (!metadata?.taskId && !metadata?.mode) {
|
||||
return undefined
|
||||
}
|
||||
|
||||
return {
|
||||
extraBody: {
|
||||
requesty: {
|
||||
trace_id: metadata?.taskId ?? null,
|
||||
extra: { mode: metadata?.mode ?? null },
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Process usage metrics from the AI SDK response, including Requesty's cache metrics.
|
||||
*
|
||||
* Requesty provides cache hit/miss info via providerMetadata, but only when both
|
||||
* cachingTokens and cachedTokens are non-zero (SDK limitation). We fall back to
|
||||
* usage.details.cachedInputTokens when providerMetadata is empty.
|
||||
*/
|
||||
protected processUsageMetrics(
|
||||
usage: {
|
||||
inputTokens?: number
|
||||
outputTokens?: number
|
||||
details?: {
|
||||
cachedInputTokens?: number
|
||||
reasoningTokens?: number
|
||||
}
|
||||
},
|
||||
modelInfo?: ModelInfo,
|
||||
providerMetadata?: RequestyProviderMetadata,
|
||||
): ApiStreamUsageChunk {
|
||||
const inputTokens = usage.inputTokens || 0
|
||||
const outputTokens = usage.outputTokens || 0
|
||||
const cacheWriteTokens = providerMetadata?.requesty?.usage?.cachingTokens ?? 0
|
||||
const cacheReadTokens = providerMetadata?.requesty?.usage?.cachedTokens ?? usage.details?.cachedInputTokens ?? 0
|
||||
|
||||
const { totalCost } = modelInfo
|
||||
? calculateApiCostOpenAI(modelInfo, inputTokens, outputTokens, cacheWriteTokens, cacheReadTokens)
|
||||
: { totalCost: 0 }
|
||||
|
||||
return {
|
||||
type: "usage",
|
||||
inputTokens: inputTokens,
|
||||
outputTokens: outputTokens,
|
||||
cacheWriteTokens: cacheWriteTokens,
|
||||
cacheReadTokens: cacheReadTokens,
|
||||
totalCost: totalCost,
|
||||
inputTokens,
|
||||
outputTokens,
|
||||
cacheWriteTokens,
|
||||
cacheReadTokens,
|
||||
reasoningTokens: usage.details?.reasoningTokens,
|
||||
totalCost,
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a message stream using the AI SDK.
|
||||
*/
|
||||
override async *createMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): ApiStream {
|
||||
const {
|
||||
id: model,
|
||||
info,
|
||||
maxTokens: max_tokens,
|
||||
temperature,
|
||||
reasoningEffort: reasoning_effort,
|
||||
reasoning: thinking,
|
||||
} = await this.fetchModel()
|
||||
const { info, temperature } = await this.fetchModel()
|
||||
const languageModel = this.getLanguageModel()
|
||||
|
||||
const openAiMessages: OpenAI.Chat.ChatCompletionMessageParam[] = [
|
||||
{ role: "system", content: systemPrompt },
|
||||
...convertToOpenAiMessages(messages),
|
||||
]
|
||||
const aiSdkMessages = convertToAiSdkMessages(messages)
|
||||
|
||||
// Map extended efforts to OpenAI Chat Completions-accepted values (omit unsupported)
|
||||
const allowedEffort = (["low", "medium", "high"] as const).includes(reasoning_effort as any)
|
||||
? (reasoning_effort as OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming["reasoning_effort"])
|
||||
: undefined
|
||||
const openAiTools = this.convertToolsForOpenAI(metadata?.tools)
|
||||
const aiSdkTools = convertToolsForAiSdk(openAiTools) as ToolSet | undefined
|
||||
|
||||
const completionParams: RequestyChatCompletionParamsStreaming = {
|
||||
messages: openAiMessages,
|
||||
model,
|
||||
max_tokens,
|
||||
temperature,
|
||||
...(allowedEffort && { reasoning_effort: allowedEffort }),
|
||||
...(thinking && { thinking }),
|
||||
stream: true,
|
||||
stream_options: { include_usage: true },
|
||||
requesty: { trace_id: metadata?.taskId, extra: { mode: metadata?.mode } },
|
||||
tools: this.convertToolsForOpenAI(metadata?.tools),
|
||||
tool_choice: metadata?.tool_choice,
|
||||
const requestyOptions = this.getRequestyProviderOptions(metadata)
|
||||
|
||||
const requestOptions: Parameters<typeof streamText>[0] = {
|
||||
model: languageModel,
|
||||
system: systemPrompt,
|
||||
messages: aiSdkMessages,
|
||||
temperature: this.options.modelTemperature ?? temperature ?? 0,
|
||||
maxOutputTokens: this.getMaxOutputTokens(),
|
||||
tools: aiSdkTools,
|
||||
toolChoice: mapToolChoice(metadata?.tool_choice),
|
||||
...(requestyOptions ? { providerOptions: { requesty: requestyOptions } } : {}),
|
||||
}
|
||||
|
||||
let stream
|
||||
const result = streamText(requestOptions)
|
||||
|
||||
try {
|
||||
// With streaming params type, SDK returns an async iterable stream
|
||||
stream = await this.client.chat.completions.create(completionParams)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
let lastUsage: any = undefined
|
||||
|
||||
for await (const chunk of stream) {
|
||||
const delta = chunk.choices[0]?.delta
|
||||
|
||||
if (delta?.content) {
|
||||
yield { type: "text", text: delta.content }
|
||||
}
|
||||
|
||||
if (delta && "reasoning_content" in delta && delta.reasoning_content) {
|
||||
yield { type: "reasoning", text: (delta.reasoning_content as string | undefined) || "" }
|
||||
}
|
||||
|
||||
// Handle native tool calls
|
||||
if (delta && "tool_calls" in delta && Array.isArray(delta.tool_calls)) {
|
||||
for (const toolCall of delta.tool_calls) {
|
||||
yield {
|
||||
type: "tool_call_partial",
|
||||
index: toolCall.index,
|
||||
id: toolCall.id,
|
||||
name: toolCall.function?.name,
|
||||
arguments: toolCall.function?.arguments,
|
||||
}
|
||||
for await (const part of result.fullStream) {
|
||||
for (const chunk of processAiSdkStreamPart(part)) {
|
||||
yield chunk
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.usage) {
|
||||
lastUsage = chunk.usage
|
||||
const usage = await result.usage
|
||||
const providerMetadata = await result.providerMetadata
|
||||
if (usage) {
|
||||
yield this.processUsageMetrics(usage, info, providerMetadata as RequestyProviderMetadata)
|
||||
}
|
||||
}
|
||||
|
||||
if (lastUsage) {
|
||||
yield this.processUsageMetrics(lastUsage, info)
|
||||
} catch (error) {
|
||||
throw handleAiSdkError(error, "Requesty")
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Complete a prompt using the AI SDK generateText.
|
||||
*/
|
||||
async completePrompt(prompt: string): Promise<string> {
|
||||
const { id: model, maxTokens: max_tokens, temperature } = await this.fetchModel()
|
||||
const { temperature } = await this.fetchModel()
|
||||
const languageModel = this.getLanguageModel()
|
||||
|
||||
let openAiMessages: OpenAI.Chat.ChatCompletionMessageParam[] = [{ role: "system", content: prompt }]
|
||||
|
||||
const completionParams: RequestyChatCompletionParams = {
|
||||
model,
|
||||
max_tokens,
|
||||
messages: openAiMessages,
|
||||
temperature: temperature,
|
||||
}
|
||||
|
||||
let response: OpenAI.Chat.ChatCompletion
|
||||
try {
|
||||
response = await this.client.chat.completions.create(completionParams)
|
||||
const { text } = await generateText({
|
||||
model: languageModel,
|
||||
prompt,
|
||||
maxOutputTokens: this.getMaxOutputTokens(),
|
||||
temperature: this.options.modelTemperature ?? temperature ?? 0,
|
||||
})
|
||||
|
||||
return text
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
throw handleAiSdkError(error, "Requesty")
|
||||
}
|
||||
return response.choices[0]?.message.content || ""
|
||||
}
|
||||
|
||||
override isAiSdkProvider(): boolean {
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -469,6 +469,7 @@
|
|||
"@mistralai/mistralai": "^1.9.18",
|
||||
"@modelcontextprotocol/sdk": "1.12.0",
|
||||
"@qdrant/js-client-rest": "^1.14.0",
|
||||
"@requesty/ai-sdk": "^3.0.0",
|
||||
"@roo-code/cloud": "workspace:^",
|
||||
"@roo-code/core": "workspace:^",
|
||||
"@roo-code/ipc": "workspace:^",
|
||||
|
|
|
|||
58
src/types/requesty-ai-sdk.d.ts
vendored
Normal file
58
src/types/requesty-ai-sdk.d.ts
vendored
Normal file
|
|
@ -0,0 +1,58 @@
|
|||
declare module "@requesty/ai-sdk" {
|
||||
import type { LanguageModelV2 } from "@ai-sdk/provider"
|
||||
|
||||
type RequestyLanguageModel = LanguageModelV2
|
||||
|
||||
interface RequestyProviderMetadata {
|
||||
requesty?: {
|
||||
usage?: {
|
||||
cachingTokens?: number
|
||||
cachedTokens?: number
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
type RequestyChatModelId = string
|
||||
|
||||
type RequestyChatSettings = {
|
||||
logitBias?: Record<number, number>
|
||||
logprobs?: boolean | number
|
||||
parallelToolCalls?: boolean
|
||||
user?: string
|
||||
includeReasoning?: boolean
|
||||
reasoningEffort?: "low" | "medium" | "high" | "max" | string
|
||||
extraBody?: Record<string, any>
|
||||
models?: string[]
|
||||
}
|
||||
|
||||
interface RequestyProvider {
|
||||
(modelId: RequestyChatModelId, settings?: RequestyChatSettings): RequestyLanguageModel
|
||||
languageModel(modelId: RequestyChatModelId, settings?: RequestyChatSettings): RequestyLanguageModel
|
||||
chat(modelId: RequestyChatModelId, settings?: RequestyChatSettings): RequestyLanguageModel
|
||||
}
|
||||
|
||||
interface RequestyProviderSettings {
|
||||
baseURL?: string
|
||||
baseUrl?: string
|
||||
apiKey?: string
|
||||
headers?: Record<string, string>
|
||||
compatibility?: "strict" | "compatible"
|
||||
fetch?: typeof fetch
|
||||
extraBody?: Record<string, unknown>
|
||||
}
|
||||
|
||||
function createRequesty(options?: RequestyProviderSettings): RequestyProvider
|
||||
|
||||
const requesty: RequestyProvider
|
||||
|
||||
export {
|
||||
type RequestyChatModelId,
|
||||
type RequestyChatSettings,
|
||||
type RequestyLanguageModel,
|
||||
type RequestyProvider,
|
||||
type RequestyProviderMetadata,
|
||||
type RequestyProviderSettings,
|
||||
createRequesty,
|
||||
requesty,
|
||||
}
|
||||
}
|
||||
Loading…
Add table
Reference in a new issue