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test(opencode): cover native reasoning continuation (#28683)
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1 changed files with 219 additions and 107 deletions
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@ -1,13 +1,14 @@
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import { describe, expect, test } from "bun:test"
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import { ToolFailure } from "@opencode-ai/llm"
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import { LLMClient, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
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import { jsonSchema, tool, type ModelMessage } from "ai"
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import { jsonSchema, tool, type ModelMessage, type Tool } from "ai"
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import { Effect, Layer, Stream } from "effect"
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import { LLMNative } from "@/session/llm/native-request"
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import { LLMNativeRuntime } from "@/session/llm/native-runtime"
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import type { Provider } from "@/provider/provider"
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import { ModelID, ProviderID } from "@/provider/schema"
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import { OAUTH_DUMMY_KEY } from "@/auth"
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import { testEffect } from "../lib/effect"
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const baseModel: Provider.Model = {
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id: ModelID.make("gpt-5-mini"),
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@ -69,6 +70,10 @@ const providerInfo: Provider.Info = {
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models: {},
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}
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const it = testEffect(
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LLMClient.layer.pipe(Layer.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer))),
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)
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function responsesStream(chunks: unknown[]) {
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return new Response(chunks.map((chunk) => `data: ${JSON.stringify(chunk)}`).join("\n\n") + "\n\n", {
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status: 200,
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@ -76,6 +81,72 @@ function responsesStream(chunks: unknown[]) {
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})
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}
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type NativeRequestInput = Parameters<typeof LLMNative.request>[0]
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const sessionText = (text: string) => ({ type: "text" as const, text })
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const sessionOpenAIReasoning = (
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text: string,
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options: {
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readonly storedAs: "providerMetadata" | "providerOptions"
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readonly itemId: string
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readonly encryptedContent: string | null
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},
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) => {
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const metadata = {
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openai: { itemId: options.itemId, reasoningEncryptedContent: options.encryptedContent },
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}
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if (options.storedAs === "providerMetadata")
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return Object.assign({ type: "reasoning" as const, text }, { providerMetadata: metadata })
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return Object.assign({ type: "reasoning" as const, text }, { providerOptions: metadata })
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}
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type SessionAssistantPart = ReturnType<typeof sessionText> | ReturnType<typeof sessionOpenAIReasoning>
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const storedSession = {
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user: (content: string): ModelMessage => ({ role: "user", content }),
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assistant: (content: SessionAssistantPart[]): ModelMessage => ({ role: "assistant", content }),
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text: sessionText,
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openaiReasoning: sessionOpenAIReasoning,
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}
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const openAIResponses = {
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user: (text: string) => ({ role: "user", content: [{ type: "input_text", text }] }),
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assistant: (text: string) => ({ role: "assistant", content: [{ type: "output_text", text }] }),
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openaiReasoning: (text: string, options: { readonly itemId: string; readonly encryptedContent: string }) => ({
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type: "reasoning",
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id: options.itemId,
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encrypted_content: options.encryptedContent,
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summary: [{ type: "summary_text", text }],
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}),
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}
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const prepareNativeRequest = (input: NativeRequestInput) => LLMClient.prepare(LLMNative.request(input))
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const expectOpenAIResponsesRequest = (input: {
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readonly history: NativeRequestInput["messages"]
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readonly providerOptions?: NativeRequestInput["providerOptions"]
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readonly maxOutputTokens?: NativeRequestInput["maxOutputTokens"]
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readonly headers?: NativeRequestInput["headers"]
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readonly expectedBody: unknown
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}) =>
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Effect.gen(function* () {
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expect(
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yield* prepareNativeRequest({
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model: baseModel,
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apiKey: "test-openai-key",
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messages: input.history,
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providerOptions: input.providerOptions,
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maxOutputTokens: input.maxOutputTokens,
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headers: input.headers,
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}),
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).toMatchObject({
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route: "openai-responses",
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protocol: "openai-responses",
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body: input.expectedBody,
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})
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})
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describe("session.llm-native.request", () => {
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test("maps normalized stream inputs to a native LLM request", () => {
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const messages: ModelMessage[] = [
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@ -426,122 +497,163 @@ describe("session.llm-native.request", () => {
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})
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})
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test("native tool wrapper converts thrown errors into typed ToolFailure", async () => {
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const wrapped = LLMNativeRuntime.nativeTools(
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{
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explode: {
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description: "always throws",
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inputSchema: jsonSchema({ type: "object" }),
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execute: async () => {
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throw new Error("boom")
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},
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} as any,
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},
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{ messages: [] as ModelMessage[], abort: new AbortController().signal },
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)
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it.effect("native tool wrapper converts thrown errors into typed ToolFailure", () =>
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Effect.gen(function* () {
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const wrapped = LLMNativeRuntime.nativeTools(
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{
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explode: {
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description: "always throws",
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inputSchema: jsonSchema({ type: "object" }),
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execute: async () => {
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throw new Error("boom")
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},
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} satisfies Tool,
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},
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{ messages: [] as ModelMessage[], abort: new AbortController().signal },
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)
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const failure = await Effect.runPromise(
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Effect.flip(wrapped.explode!.execute!({}, { id: "call-1", name: "explode" })),
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)
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expect(failure).toBeInstanceOf(ToolFailure)
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expect((failure as ToolFailure).message).toBe("boom")
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})
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const failure = yield* Effect.flip(wrapped.explode.execute({}, { id: "call-1", name: "explode" }))
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expect(failure).toBeInstanceOf(ToolFailure)
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expect(failure.message).toBe("boom")
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}),
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)
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test("native tool wrapper raises ToolFailure when the source tool has no execute handler", async () => {
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// The AI SDK Tool shape allows execute to be omitted (e.g., client-side / MCP tools).
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// The native runtime owns execution, so encountering such a tool here means upstream
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// wiring is wrong; we want a typed failure, not a silent skip or unhandled exception.
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const wrapped = LLMNativeRuntime.nativeTools(
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{ incomplete: { description: "no execute", inputSchema: jsonSchema({ type: "object" }) } as any },
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{ messages: [] as ModelMessage[], abort: new AbortController().signal },
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)
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it.effect("native tool wrapper raises ToolFailure when the source tool has no execute handler", () =>
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Effect.gen(function* () {
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// The AI SDK Tool shape allows execute to be omitted (e.g., client-side / MCP tools).
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// The native runtime owns execution, so encountering such a tool here means upstream
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// wiring is wrong; we want a typed failure, not a silent skip or unhandled exception.
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const wrapped = LLMNativeRuntime.nativeTools(
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{ incomplete: { description: "no execute", inputSchema: jsonSchema({ type: "object" }) } satisfies Tool },
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{ messages: [] as ModelMessage[], abort: new AbortController().signal },
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)
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const failure = await Effect.runPromise(
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Effect.flip(wrapped.incomplete!.execute!({}, { id: "call-1", name: "incomplete" })),
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)
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expect(failure).toBeInstanceOf(ToolFailure)
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expect((failure as ToolFailure).message).toContain("incomplete")
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})
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const failure = yield* Effect.flip(wrapped.incomplete.execute({}, { id: "call-1", name: "incomplete" }))
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expect(failure).toBeInstanceOf(ToolFailure)
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expect(failure.message).toContain("incomplete")
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}),
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)
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test("compiles through the native OpenAI Responses route", async () => {
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const prepared = await Effect.runPromise(
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LLMClient.prepare(
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LLMNative.request({
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model: baseModel,
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apiKey: "test-openai-key",
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messages: [{ role: "user", content: "hello" }],
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providerOptions: { openai: { store: false, instructions: "You are concise." } },
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maxOutputTokens: 512,
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headers: { "x-request": "request-header" },
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}),
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).pipe(
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Effect.provide(LLMClient.layer),
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Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
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),
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)
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expect(prepared).toMatchObject({
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route: "openai-responses",
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protocol: "openai-responses",
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body: {
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it.effect("compiles through the native OpenAI Responses route", () =>
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expectOpenAIResponsesRequest({
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history: [storedSession.user("hello")],
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providerOptions: { openai: { store: false, instructions: "You are concise." } },
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maxOutputTokens: 512,
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headers: { "x-request": "request-header" },
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expectedBody: {
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model: "gpt-5-mini",
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instructions: "You are concise.",
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input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
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input: [openAIResponses.user("hello")],
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max_output_tokens: 512,
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store: false,
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stream: true,
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},
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})
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})
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}),
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)
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test("uses provider fetch override for native OpenAI OAuth requests", async () => {
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const captures: Array<{ url: string; body: unknown }> = []
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const customFetch = (async (input, init) => {
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const request = input instanceof Request ? input : new Request(input, init)
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captures.push({ url: request.url, body: await request.clone().json() })
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return responsesStream([
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{ type: "response.output_text.delta", item_id: "msg_1", delta: "Hello" },
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{ type: "response.completed", response: { usage: { input_tokens: 1, output_tokens: 1 } } },
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])
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}) as typeof fetch
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const events = await Effect.runPromise(
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Effect.gen(function* () {
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const llmClient = yield* LLMClient.Service
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const native = LLMNativeRuntime.stream({
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model: baseModel,
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provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: customFetch } },
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auth: { type: "oauth", refresh: "refresh", access: "access", expires: Date.now() + 60_000 },
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llmClient,
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messages: [{ role: "user", content: "hello" }],
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tools: {},
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providerOptions: { instructions: "You are concise." },
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headers: {},
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abort: new AbortController().signal,
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})
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expect(native.type).toBe("supported")
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if (native.type === "unsupported") return []
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return yield* native.stream.pipe(Stream.runCollect)
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}).pipe(
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Effect.provide(LLMClient.layer),
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Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
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),
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)
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expect(captures).toHaveLength(1)
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expect(captures[0]).toMatchObject({
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url: "https://api.openai.com/v1/responses",
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body: {
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model: "gpt-5-mini",
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instructions: "You are concise.",
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input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
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it.effect("omits non-persisted OpenAI reasoning ids without encrypted state", () =>
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expectOpenAIResponsesRequest({
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history: [
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storedSession.user("What changed?"),
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storedSession.assistant([
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storedSession.openaiReasoning("Checked the previous diff.", {
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storedAs: "providerOptions",
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itemId: "rs_1",
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encryptedContent: null,
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}),
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storedSession.text("The parser changed."),
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]),
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storedSession.user("Summarize it."),
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],
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providerOptions: { openai: { store: false } },
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expectedBody: {
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input: [
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openAIResponses.user("What changed?"),
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openAIResponses.assistant("The parser changed."),
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openAIResponses.user("Summarize it."),
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],
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store: false,
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},
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})
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expect(events).toEqual(
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expect.arrayContaining([
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expect.objectContaining({ type: "text-delta", text: "Hello" }),
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expect.objectContaining({ type: "finish" }),
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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.effect("preserves encrypted OpenAI reasoning state through native request lowering", () =>
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expectOpenAIResponsesRequest({
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history: [
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storedSession.user("What changed?"),
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storedSession.assistant([
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storedSession.openaiReasoning("Checked the previous diff.", {
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storedAs: "providerMetadata",
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itemId: "rs_1",
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encryptedContent: "encrypted-state",
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}),
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storedSession.text("The parser changed."),
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]),
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storedSession.user("Summarize it."),
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],
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providerOptions: { openai: { store: false, includeEncryptedReasoning: true } },
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expectedBody: {
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input: [
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openAIResponses.user("What changed?"),
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openAIResponses.openaiReasoning("Checked the previous diff.", {
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itemId: "rs_1",
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encryptedContent: "encrypted-state",
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}),
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openAIResponses.assistant("The parser changed."),
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openAIResponses.user("Summarize it."),
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],
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include: ["reasoning.encrypted_content"],
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store: false,
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},
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}),
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)
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it.effect("uses provider fetch override for native OpenAI OAuth requests", () =>
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Effect.gen(function* () {
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const captures: Array<{ url: string; body: unknown }> = []
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const customFetch = Object.assign(
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async (input: Parameters<typeof fetch>[0], init: Parameters<typeof fetch>[1]) => {
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const request = input instanceof Request ? input : new Request(input, init)
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captures.push({ url: request.url, body: await request.clone().json() })
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return responsesStream([
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{ type: "response.output_text.delta", item_id: "msg_1", delta: "Hello" },
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{ type: "response.completed", response: { usage: { input_tokens: 1, output_tokens: 1 } } },
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])
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},
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{ preconnect: () => undefined },
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) satisfies typeof fetch
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const llmClient = yield* LLMClient.Service
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const native = LLMNativeRuntime.stream({
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model: baseModel,
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provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: customFetch } },
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auth: { type: "oauth", refresh: "refresh", access: "access", expires: Date.now() + 60_000 },
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llmClient,
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messages: [{ role: "user", content: "hello" }],
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tools: {},
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providerOptions: { instructions: "You are concise." },
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headers: {},
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abort: new AbortController().signal,
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})
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expect(native.type).toBe("supported")
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if (native.type === "unsupported") throw new Error(native.reason)
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const events = Array.from(yield* native.stream.pipe(Stream.runCollect))
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expect(captures).toHaveLength(1)
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expect(captures[0]).toMatchObject({
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url: "https://api.openai.com/v1/responses",
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body: {
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model: "gpt-5-mini",
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instructions: "You are concise.",
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input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
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},
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})
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expect(events).toEqual(
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expect.arrayContaining([
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expect.objectContaining({ type: "text-delta", text: "Hello" }),
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expect.objectContaining({ type: "finish" }),
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]),
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)
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}),
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)
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})
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