Preview native LLM runtime stack (#27114)
This commit is contained in:
Kit Langton
@@ -1,15 +1,20 @@
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import { afterAll, beforeAll, beforeEach, describe, expect, test } from "bun:test"
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import path from "path"
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import { tool, type ModelMessage } from "ai"
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import { Cause, Effect, Exit, Stream } from "effect"
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import { Cause, Effect, Exit, Layer, Stream } from "effect"
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import { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
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import z from "zod"
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import { makeRuntime } from "../../src/effect/run-service"
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import { InstanceRef } from "../../src/effect/instance-ref"
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import { LLM } from "../../src/session/llm"
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import type { InstanceContext } from "../../src/project/instance-context"
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import { LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
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import { Auth } from "@/auth"
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import { Config } from "@/config/config"
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import { Provider } from "@/provider/provider"
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import { ProviderTransform } from "@/provider/transform"
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import { ModelsDev } from "@opencode-ai/core/models-dev"
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import { Plugin } from "@/plugin"
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import { ProviderID, ModelID } from "../../src/provider/schema"
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import { Filesystem } from "@/util/filesystem"
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import { tmpdir, withTestInstance } from "../fixture/fixture"
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@@ -17,6 +22,33 @@ import type { Agent } from "../../src/agent/agent"
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import { MessageV2 } from "../../src/session/message-v2"
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import { SessionID, MessageID } from "../../src/session/schema"
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import { AppRuntime } from "../../src/effect/app-runtime"
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import { RuntimeFlags } from "@/effect/runtime-flags"
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import { Permission } from "@/permission"
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import { LLMAISDK } from "@/session/llm/ai-sdk"
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import { Session as SessionNs } from "@/session/session"
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const openAIConfig = (model: ModelsDev.Provider["models"][string], baseURL: string): Partial<Config.Info> => {
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const { experimental: _experimental, ...configModel } = model
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type ConfigModel = NonNullable<NonNullable<Config.Info["provider"]>[string]["models"]>[string]
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return {
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enabled_providers: ["openai"],
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provider: {
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openai: {
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name: "OpenAI",
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env: ["OPENAI_API_KEY"],
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npm: "@ai-sdk/openai",
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api: "https://api.openai.com/v1",
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models: {
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[model.id]: JSON.parse(JSON.stringify(configModel)) as ConfigModel,
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},
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options: {
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apiKey: "test-openai-key",
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baseURL,
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},
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},
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},
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}
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}
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async function getModel(providerID: ProviderID, modelID: ModelID, ctx: InstanceContext) {
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const effect = Effect.gen(function* () {
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@@ -35,6 +67,26 @@ async function drain(input: LLM.StreamInput, ctx: InstanceContext) {
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})
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}
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async function drainWith(layer: Layer.Layer<LLM.Service>, input: LLM.StreamInput, ctx: InstanceContext) {
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return Effect.runPromise(
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LLM.Service.use((svc) => svc.stream(input).pipe(Stream.runDrain)).pipe(
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Effect.provide(layer),
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Effect.provideService(InstanceRef, ctx),
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),
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)
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}
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function llmLayerWithExecutor(executor: Layer.Layer<RequestExecutor.Service>, flags: Partial<RuntimeFlags.Info> = {}) {
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return LLM.layer.pipe(
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Layer.provide(Auth.defaultLayer),
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Layer.provide(Config.defaultLayer),
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Layer.provide(Provider.defaultLayer),
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Layer.provide(Plugin.defaultLayer),
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Layer.provide(LLMClient.layer.pipe(Layer.provide(executor))),
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Layer.provide(RuntimeFlags.layer(flags)),
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)
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}
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describe("session.llm.hasToolCalls", () => {
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test("returns false for empty messages array", () => {
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expect(LLM.hasToolCalls([])).toBe(false)
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@@ -122,6 +174,338 @@ describe("session.llm.hasToolCalls", () => {
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})
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})
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describe("session.llm.ai-sdk adapter", () => {
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type AISDKAdapterEvent = Parameters<typeof LLMAISDK.toLLMEvents>[1]
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const adapt = (events: ReadonlyArray<AISDKAdapterEvent>) => {
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const state = LLMAISDK.adapterState()
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return Effect.runPromise(
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Effect.forEach(events, (event) => LLMAISDK.toLLMEvents(state, event)).pipe(Effect.map((items) => items.flat())),
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)
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}
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// oxlint-disable-next-line typescript-eslint/no-unsafe-type-assertion -- tests defensive adapter branches outside AI SDK's current typed surface
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const uncheckedAdapterEvent = (input: unknown) => input as AISDKAdapterEvent
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test("maps AI SDK stream chunks without losing session-visible fields", async () => {
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const metadata = { openai: { itemID: "item-1" } }
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const events = await adapt([
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{ type: "start" },
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{ type: "start-step", request: {}, warnings: [] },
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{ type: "text-start", id: "text-1", providerMetadata: metadata },
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{ type: "text-delta", id: "text-1", text: "Hel", providerMetadata: { openai: { delta: 1 } } },
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{ type: "text-delta", id: "text-1", text: "lo", providerMetadata: { openai: { delta: 2 } } },
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{ type: "text-end", id: "text-1", providerMetadata: { openai: { done: true } } },
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{ type: "reasoning-start", id: "reasoning-1", providerMetadata: metadata },
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{ type: "reasoning-delta", id: "reasoning-1", text: "Think", providerMetadata: { openai: { delta: 3 } } },
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{ type: "reasoning-end", id: "reasoning-1", providerMetadata: { openai: { done: true } } },
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{ type: "tool-input-start", id: "call-1", toolName: "lookup", providerMetadata: metadata },
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{ type: "tool-input-delta", id: "call-1", delta: '{"query":' },
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{ type: "tool-input-delta", id: "call-1", delta: '"weather"}' },
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{ type: "tool-input-end", id: "call-1", providerMetadata: { openai: { inputDone: true } } },
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{
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type: "tool-call",
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toolCallId: "call-1",
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toolName: "lookup",
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input: { query: "weather" },
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providerExecuted: true,
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providerMetadata: { openai: { called: true } },
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},
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{
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type: "tool-result",
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toolCallId: "call-1",
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toolName: "lookup",
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input: { query: "weather" },
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output: { title: "Lookup", output: "sunny", metadata: { ok: true } },
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providerExecuted: true,
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providerMetadata: { openai: { result: true } },
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},
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{
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type: "finish-step",
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response: { id: "response-1", timestamp: new Date(0), modelId: "gpt-test" },
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finishReason: "other",
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rawFinishReason: "other",
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usage: {
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inputTokens: 10,
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outputTokens: 5,
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totalTokens: 15,
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inputTokenDetails: { noCacheTokens: 5, cacheReadTokens: 3, cacheWriteTokens: 2 },
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outputTokenDetails: { textTokens: 4, reasoningTokens: 1 },
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},
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providerMetadata: { openai: { step: true } },
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},
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{
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type: "finish",
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finishReason: "other",
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rawFinishReason: "other",
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totalUsage: {
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inputTokens: 11,
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outputTokens: 6,
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totalTokens: 17,
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cachedInputTokens: 4,
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reasoningTokens: 2,
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inputTokenDetails: { noCacheTokens: 7, cacheReadTokens: 4, cacheWriteTokens: undefined },
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outputTokenDetails: { textTokens: 4, reasoningTokens: 2 },
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},
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},
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])
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expect(events).toMatchObject([
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{ type: "step-start", index: 0 },
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{ type: "text-start", id: "text-1", providerMetadata: metadata },
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{ type: "text-delta", id: "text-1", text: "Hel", providerMetadata: { openai: { delta: 1 } } },
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{ type: "text-delta", id: "text-1", text: "lo", providerMetadata: { openai: { delta: 2 } } },
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{ type: "text-end", id: "text-1", providerMetadata: { openai: { done: true } } },
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{ type: "reasoning-start", id: "reasoning-1", providerMetadata: metadata },
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{ type: "reasoning-delta", id: "reasoning-1", text: "Think", providerMetadata: { openai: { delta: 3 } } },
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{ type: "reasoning-end", id: "reasoning-1", providerMetadata: { openai: { done: true } } },
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{ type: "tool-input-start", id: "call-1", name: "lookup", providerMetadata: metadata },
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{ type: "tool-input-delta", id: "call-1", name: "lookup", text: '{"query":' },
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{ type: "tool-input-delta", id: "call-1", name: "lookup", text: '"weather"}' },
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{ type: "tool-input-end", id: "call-1", name: "lookup", providerMetadata: { openai: { inputDone: true } } },
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{
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type: "tool-call",
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id: "call-1",
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name: "lookup",
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input: { query: "weather" },
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providerExecuted: true,
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providerMetadata: { openai: { called: true } },
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},
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{
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type: "tool-result",
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id: "call-1",
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name: "lookup",
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result: { type: "json", value: { title: "Lookup", output: "sunny", metadata: { ok: true } } },
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providerExecuted: true,
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providerMetadata: { openai: { result: true } },
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},
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{
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type: "step-finish",
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index: 0,
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reason: "unknown",
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usage: {
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inputTokens: 10,
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outputTokens: 5,
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totalTokens: 15,
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reasoningTokens: 1,
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cacheReadInputTokens: 3,
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cacheWriteInputTokens: 2,
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},
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providerMetadata: { openai: { step: true } },
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},
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{
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type: "finish",
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reason: "unknown",
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usage: {
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inputTokens: 11,
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outputTokens: 6,
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totalTokens: 17,
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reasoningTokens: 2,
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cacheReadInputTokens: 4,
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},
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},
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])
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})
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test("creates stable block ids when AI SDK omits them", async () => {
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const events = await adapt([
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uncheckedAdapterEvent({ type: "text-delta", text: "implicit text" }),
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uncheckedAdapterEvent({ type: "text-end" }),
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uncheckedAdapterEvent({ type: "reasoning-delta", text: "implicit reasoning" }),
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uncheckedAdapterEvent({ type: "reasoning-end" }),
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])
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expect(events).toMatchObject([
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{ type: "text-delta", id: "text-0", text: "implicit text" },
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{ type: "text-end", id: "text-0" },
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{ type: "reasoning-delta", id: "reasoning-0", text: "implicit reasoning" },
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{ type: "reasoning-end", id: "reasoning-0" },
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])
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})
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test("explicitly ignores non-session-visible AI SDK chunks", async () => {
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expect(
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await adapt([
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uncheckedAdapterEvent({ type: "abort" }),
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uncheckedAdapterEvent({ type: "source" }),
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uncheckedAdapterEvent({ type: "file" }),
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uncheckedAdapterEvent({ type: "raw" }),
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uncheckedAdapterEvent({ type: "tool-output-denied" }),
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uncheckedAdapterEvent({ type: "tool-approval-request" }),
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]),
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).toEqual([])
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})
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test("preserves tool-error cause", async () => {
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const error = new Permission.RejectedError()
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const events = await Effect.runPromise(
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LLMAISDK.toLLMEvents(LLMAISDK.adapterState(), {
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type: "tool-error",
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toolCallId: "call_123",
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toolName: "bash",
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input: {},
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error,
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}),
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)
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expect(events).toHaveLength(1)
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expect(events[0]).toMatchObject({
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type: "tool-error",
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id: "call_123",
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name: "bash",
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message: error.message,
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error,
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})
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})
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test("emits undefined usage when every AI SDK usage field is missing", async () => {
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// If every numeric field is undefined the translator should signal "no usage info"
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// by emitting undefined, not by polluting the event with usage: {}. Downstream cost
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// telemetry distinguishes "missing" from "zero," so emitting an empty object causes
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// false positives ("usage was tracked, just empty") instead of correct nulls.
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const events = await adapt([
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{
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type: "finish-step",
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response: { id: "response-1", timestamp: new Date(0), modelId: "gpt-test" },
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finishReason: "stop",
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rawFinishReason: "stop",
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providerMetadata: undefined,
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usage: {
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inputTokens: undefined,
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outputTokens: undefined,
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totalTokens: undefined,
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reasoningTokens: undefined,
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cachedInputTokens: undefined,
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inputTokenDetails: { noCacheTokens: undefined, cacheReadTokens: undefined, cacheWriteTokens: undefined },
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outputTokenDetails: { textTokens: undefined, reasoningTokens: undefined },
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},
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},
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])
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expect(events).toHaveLength(1)
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const stepFinish = events[0]
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if (stepFinish.type !== "step-finish") throw new Error("expected step-finish")
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expect(stepFinish.usage).toBeUndefined()
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})
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test("reuses adapter state cleanly across streams once finish has fired", async () => {
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// adapterState() is meant to be per-stream, but the only thing finish currently clears
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// is toolNames — step, text counters, and the current text/reasoning IDs all leak
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// forward. A caller that reuses a state across two streams sees text-1/reasoning-1/
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// step index 1 on the second stream's first events. The test pins the intended
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// contract: after finish, the same state can be reused and starts fresh.
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const state = LLMAISDK.adapterState()
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const run = (events: ReadonlyArray<AISDKAdapterEvent>) =>
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Effect.runPromise(
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Effect.forEach(events, (event) => LLMAISDK.toLLMEvents(state, event)).pipe(Effect.map((items) => items.flat())),
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)
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await run([
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{ type: "start-step", request: {}, warnings: [] },
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uncheckedAdapterEvent({ type: "text-delta", text: "first" }),
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uncheckedAdapterEvent({ type: "text-end" }),
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uncheckedAdapterEvent({ type: "reasoning-delta", text: "first reasoning" }),
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uncheckedAdapterEvent({ type: "reasoning-end" }),
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{
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type: "finish-step",
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response: { id: "r1", timestamp: new Date(0), modelId: "gpt-test" },
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finishReason: "stop",
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rawFinishReason: "stop",
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providerMetadata: undefined,
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usage: {
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inputTokens: 1,
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outputTokens: 1,
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totalTokens: 2,
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inputTokenDetails: { noCacheTokens: undefined, cacheReadTokens: undefined, cacheWriteTokens: undefined },
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outputTokenDetails: { textTokens: undefined, reasoningTokens: undefined },
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},
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},
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{
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type: "finish",
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finishReason: "stop",
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rawFinishReason: "stop",
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totalUsage: {
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inputTokens: 1,
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outputTokens: 1,
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totalTokens: 2,
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inputTokenDetails: { noCacheTokens: undefined, cacheReadTokens: undefined, cacheWriteTokens: undefined },
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outputTokenDetails: { textTokens: undefined, reasoningTokens: undefined },
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},
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},
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])
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const secondStream = await run([
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{ type: "start-step", request: {}, warnings: [] },
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uncheckedAdapterEvent({ type: "text-delta", text: "second" }),
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uncheckedAdapterEvent({ type: "text-end" }),
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uncheckedAdapterEvent({ type: "reasoning-delta", text: "second reasoning" }),
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uncheckedAdapterEvent({ type: "reasoning-end" }),
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])
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expect(secondStream).toMatchObject([
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{ type: "step-start", index: 0 },
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{ type: "text-delta", id: "text-0", text: "second" },
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{ type: "text-end", id: "text-0" },
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{ type: "reasoning-delta", id: "reasoning-0", text: "second reasoning" },
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{ type: "reasoning-end", id: "reasoning-0" },
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||||
])
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})
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// Anthropic emits cache write counts in providerMetadata.anthropic.cacheCreationInputTokens
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// rather than usage.inputTokenDetails.cacheWriteTokens. Session.getUsage falls back to the
|
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// metadata path — but only if the adapter preserves providerMetadata on step-finish.
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test("preserves providerMetadata on step-finish so Anthropic cache writes survive getUsage", async () => {
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const events = await adapt([
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||||
{
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type: "finish-step",
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response: { id: "msg_test", timestamp: new Date(0), modelId: "claude-3-5-sonnet" },
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||||
finishReason: "stop",
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rawFinishReason: "stop",
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// Anthropic's AI SDK shape: cacheWriteTokens is NOT in usage, it arrives via providerMetadata.
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usage: {
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inputTokens: 1000,
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||||
outputTokens: 500,
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totalTokens: 1500,
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||||
inputTokenDetails: { noCacheTokens: 800, cacheReadTokens: 200, cacheWriteTokens: undefined },
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||||
outputTokenDetails: { textTokens: 500, reasoningTokens: undefined },
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||||
},
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||||
providerMetadata: { anthropic: { cacheCreationInputTokens: 300 } },
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||||
},
|
||||
])
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expect(events).toHaveLength(1)
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const stepFinish = events[0]
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if (stepFinish.type !== "step-finish") throw new Error("expected step-finish")
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expect(stepFinish.providerMetadata).toEqual({ anthropic: { cacheCreationInputTokens: 300 } })
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expect(stepFinish.usage?.cacheWriteInputTokens).toBeUndefined()
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expect(stepFinish.usage?.cacheReadInputTokens).toBe(200)
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// End-to-end: with the metadata preserved, getUsage extracts cache.write from the fallback path.
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const result = SessionNs.getUsage({
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||||
model: {
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id: "claude-3-5-sonnet",
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providerID: "anthropic",
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||||
name: "Claude",
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||||
limit: { context: 200_000, output: 8_000 },
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||||
cost: { input: 0, output: 0, cache: { read: 0, write: 0 } },
|
||||
capabilities: {
|
||||
toolcall: true,
|
||||
attachment: false,
|
||||
reasoning: false,
|
||||
temperature: true,
|
||||
input: { text: true, image: false, audio: false, video: false },
|
||||
output: { text: true, image: false, audio: false, video: false },
|
||||
},
|
||||
api: { npm: "@ai-sdk/anthropic" },
|
||||
options: {},
|
||||
} as never,
|
||||
usage: stepFinish.usage!,
|
||||
metadata: stepFinish.providerMetadata,
|
||||
})
|
||||
expect(result.tokens.cache.write).toBe(300)
|
||||
expect(result.tokens.cache.read).toBe(200)
|
||||
})
|
||||
})
|
||||
|
||||
type Capture = {
|
||||
url: URL
|
||||
headers: Headers
|
||||
@@ -608,6 +992,18 @@ describe("session.llm.stream", () => {
|
||||
service_tier: null,
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
output_index: 0,
|
||||
item: { type: "message", id: "item-1", status: "in_progress", role: "assistant", content: [] },
|
||||
},
|
||||
{
|
||||
type: "response.content_part.added",
|
||||
item_id: "item-1",
|
||||
output_index: 0,
|
||||
content_index: 0,
|
||||
part: { type: "output_text", text: "", annotations: [] },
|
||||
},
|
||||
{
|
||||
type: "response.output_text.delta",
|
||||
item_id: "item-1",
|
||||
@@ -630,32 +1026,7 @@ describe("session.llm.stream", () => {
|
||||
]
|
||||
const request = waitRequest("/responses", createEventResponse(responseChunks, true))
|
||||
|
||||
await using tmp = await tmpdir({
|
||||
init: async (dir) => {
|
||||
await Bun.write(
|
||||
path.join(dir, "opencode.json"),
|
||||
JSON.stringify({
|
||||
$schema: "https://opencode.ai/config.json",
|
||||
enabled_providers: ["openai"],
|
||||
provider: {
|
||||
openai: {
|
||||
name: "OpenAI",
|
||||
env: ["OPENAI_API_KEY"],
|
||||
npm: "@ai-sdk/openai",
|
||||
api: "https://api.openai.com/v1",
|
||||
models: {
|
||||
[model.id]: configModel(model),
|
||||
},
|
||||
options: {
|
||||
apiKey: "test-openai-key",
|
||||
baseURL: `${server.url.origin}/v1`,
|
||||
},
|
||||
},
|
||||
},
|
||||
}),
|
||||
)
|
||||
},
|
||||
})
|
||||
await using tmp = await tmpdir({ config: openAIConfig(model, `${server.url.origin}/v1`) })
|
||||
|
||||
await withTestInstance({
|
||||
directory: tmp.path,
|
||||
@@ -706,6 +1077,438 @@ describe("session.llm.stream", () => {
|
||||
})
|
||||
})
|
||||
|
||||
test("keeps supported OpenAI models on AI SDK path when native flag is off", async () => {
|
||||
const server = state.server
|
||||
if (!server) {
|
||||
throw new Error("Server not initialized")
|
||||
}
|
||||
|
||||
const source = await loadFixture("openai", "gpt-5.2")
|
||||
const model = source.model
|
||||
const request = waitRequest(
|
||||
"/responses",
|
||||
createEventResponse(
|
||||
[
|
||||
{
|
||||
type: "response.created",
|
||||
response: {
|
||||
id: "resp-flag-off",
|
||||
created_at: Math.floor(Date.now() / 1000),
|
||||
model: model.id,
|
||||
service_tier: null,
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
output_index: 0,
|
||||
item: { type: "message", id: "item-flag-off", status: "in_progress", role: "assistant", content: [] },
|
||||
},
|
||||
{
|
||||
type: "response.content_part.added",
|
||||
item_id: "item-flag-off",
|
||||
output_index: 0,
|
||||
content_index: 0,
|
||||
part: { type: "output_text", text: "", annotations: [] },
|
||||
},
|
||||
{
|
||||
type: "response.output_text.delta",
|
||||
item_id: "item-flag-off",
|
||||
delta: "Flag off",
|
||||
logprobs: null,
|
||||
},
|
||||
{
|
||||
type: "response.completed",
|
||||
response: {
|
||||
incomplete_details: null,
|
||||
usage: {
|
||||
input_tokens: 1,
|
||||
input_tokens_details: null,
|
||||
output_tokens: 1,
|
||||
output_tokens_details: null,
|
||||
},
|
||||
service_tier: null,
|
||||
},
|
||||
},
|
||||
],
|
||||
true,
|
||||
),
|
||||
)
|
||||
const failingNativeClient = Layer.succeed(
|
||||
LLMClient.Service,
|
||||
LLMClient.Service.of({
|
||||
prepare: () => Effect.die(new Error("native LLM client should not be used when the flag is off")),
|
||||
stream: () => Stream.die(new Error("native LLM client should not be used when the flag is off")),
|
||||
generate: () => Effect.die(new Error("native LLM client should not be used when the flag is off")),
|
||||
}),
|
||||
)
|
||||
|
||||
await using tmp = await tmpdir({ config: openAIConfig(model, `${server.url.origin}/v1`) })
|
||||
|
||||
await withTestInstance({
|
||||
directory: tmp.path,
|
||||
fn: async (ctx) => {
|
||||
const resolved = await getModel(ProviderID.openai, ModelID.make(model.id), ctx)
|
||||
const sessionID = SessionID.make("session-test-native-flag-off")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
} satisfies Agent.Info
|
||||
|
||||
await drainWith(
|
||||
LLM.layer.pipe(
|
||||
Layer.provide(Auth.defaultLayer),
|
||||
Layer.provide(Config.defaultLayer),
|
||||
Layer.provide(Provider.defaultLayer),
|
||||
Layer.provide(Plugin.defaultLayer),
|
||||
Layer.provide(failingNativeClient),
|
||||
Layer.provide(RuntimeFlags.layer({ experimentalNativeLlm: false })),
|
||||
),
|
||||
{
|
||||
user: {
|
||||
id: MessageID.make("msg_user-native-flag-off"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: Date.now() },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.make("openai"), modelID: resolved.id, variant: "high" },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: ["You are a helpful assistant."],
|
||||
messages: [{ role: "user", content: "Hello" }],
|
||||
tools: {},
|
||||
},
|
||||
ctx,
|
||||
)
|
||||
|
||||
const capture = await request
|
||||
expect(capture.url.pathname.endsWith("/responses")).toBe(true)
|
||||
expect(capture.body.model).toBe(resolved.api.id)
|
||||
},
|
||||
})
|
||||
})
|
||||
|
||||
test("streams OpenAI through native runtime when opted in", async () => {
|
||||
const server = state.server
|
||||
if (!server) {
|
||||
throw new Error("Server not initialized")
|
||||
}
|
||||
|
||||
const source = await loadFixture("openai", "gpt-5.2")
|
||||
const model = source.model
|
||||
const chunks = [
|
||||
{
|
||||
type: "response.created",
|
||||
response: {
|
||||
id: "resp-native",
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
item: { type: "message", id: "item-native", status: "in_progress" },
|
||||
},
|
||||
{
|
||||
type: "response.output_text.delta",
|
||||
item_id: "item-native",
|
||||
delta: "Hello native",
|
||||
},
|
||||
{
|
||||
type: "response.completed",
|
||||
response: {
|
||||
incomplete_details: null,
|
||||
usage: {
|
||||
input_tokens: 1,
|
||||
input_tokens_details: null,
|
||||
output_tokens: 1,
|
||||
output_tokens_details: null,
|
||||
},
|
||||
},
|
||||
},
|
||||
]
|
||||
const request = waitRequest("/responses", createEventResponse(chunks, true))
|
||||
|
||||
await using tmp = await tmpdir({ config: openAIConfig(model, `${server.url.origin}/v1`) })
|
||||
|
||||
await withTestInstance({
|
||||
directory: tmp.path,
|
||||
fn: async (ctx) => {
|
||||
const resolved = await getModel(ProviderID.openai, ModelID.make(model.id), ctx)
|
||||
const sessionID = SessionID.make("session-test-native")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
temperature: 0.2,
|
||||
} satisfies Agent.Info
|
||||
|
||||
await drainWith(
|
||||
llmLayerWithExecutor(RequestExecutor.defaultLayer, { experimentalNativeLlm: true }),
|
||||
{
|
||||
user: {
|
||||
id: MessageID.make("msg_user-native"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: Date.now() },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.make("openai"), modelID: resolved.id, variant: "high" },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: ["You are a helpful assistant."],
|
||||
messages: [{ role: "user", content: "Hello" }],
|
||||
tools: {},
|
||||
},
|
||||
ctx,
|
||||
)
|
||||
|
||||
const capture = await request
|
||||
expect(capture.url.pathname.endsWith("/responses")).toBe(true)
|
||||
expect(capture.headers.get("Authorization")).toBe("Bearer test-openai-key")
|
||||
expect(capture.body.model).toBe(model.id)
|
||||
expect(capture.body.stream).toBe(true)
|
||||
expect((capture.body.reasoning as { effort?: string } | undefined)?.effort).toBe("high")
|
||||
expect(JSON.stringify(capture.body.input)).toContain("You are a helpful assistant.")
|
||||
expect(capture.body.input).toContainEqual({ role: "user", content: [{ type: "input_text", text: "Hello" }] })
|
||||
},
|
||||
})
|
||||
})
|
||||
|
||||
test("uses injected native request executor for tool calls", async () => {
|
||||
const source = await loadFixture("openai", "gpt-5.2")
|
||||
const model = source.model
|
||||
const chunks = [
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
item: { type: "function_call", id: "item-injected-tool", call_id: "call-injected-tool", name: "lookup" },
|
||||
},
|
||||
{
|
||||
type: "response.function_call_arguments.delta",
|
||||
item_id: "item-injected-tool",
|
||||
delta: '{"query":"weather"}',
|
||||
},
|
||||
{
|
||||
type: "response.output_item.done",
|
||||
item: {
|
||||
type: "function_call",
|
||||
id: "item-injected-tool",
|
||||
call_id: "call-injected-tool",
|
||||
name: "lookup",
|
||||
arguments: '{"query":"weather"}',
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.completed",
|
||||
response: { incomplete_details: null, usage: { input_tokens: 1, output_tokens: 1 } },
|
||||
},
|
||||
]
|
||||
let captured: Record<string, unknown> | undefined
|
||||
let executed: unknown
|
||||
const executor = Layer.succeed(
|
||||
RequestExecutor.Service,
|
||||
RequestExecutor.Service.of({
|
||||
execute: (request) =>
|
||||
Effect.gen(function* () {
|
||||
const web = yield* HttpClientRequest.toWeb(request).pipe(Effect.orDie)
|
||||
captured = (yield* Effect.promise(() => web.json())) as Record<string, unknown>
|
||||
return HttpClientResponse.fromWeb(request, createEventResponse(chunks, true))
|
||||
}),
|
||||
}),
|
||||
)
|
||||
|
||||
await using tmp = await tmpdir({ config: openAIConfig(model, "https://injected-openai.test/v1") })
|
||||
|
||||
await withTestInstance({
|
||||
directory: tmp.path,
|
||||
fn: async (ctx) => {
|
||||
const resolved = await getModel(ProviderID.openai, ModelID.make(model.id), ctx)
|
||||
const sessionID = SessionID.make("session-test-native-injected-tool")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
} satisfies Agent.Info
|
||||
|
||||
await drainWith(
|
||||
llmLayerWithExecutor(executor, { experimentalNativeLlm: true }),
|
||||
{
|
||||
user: {
|
||||
id: MessageID.make("msg_user-native-injected-tool"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: Date.now() },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.make("openai"), modelID: resolved.id },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: [],
|
||||
messages: [{ role: "user", content: "Use lookup" }],
|
||||
tools: {
|
||||
lookup: tool({
|
||||
description: "Lookup data",
|
||||
inputSchema: z.object({ query: z.string() }),
|
||||
execute: async (args, options) => {
|
||||
executed = { args, toolCallId: options.toolCallId }
|
||||
return { output: "looked up" }
|
||||
},
|
||||
}),
|
||||
},
|
||||
},
|
||||
ctx,
|
||||
)
|
||||
|
||||
expect(captured?.model).toBe(model.id)
|
||||
expect(captured?.tools).toEqual([
|
||||
{
|
||||
type: "function",
|
||||
name: "lookup",
|
||||
description: "Lookup data",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: { query: { type: "string" } },
|
||||
required: ["query"],
|
||||
additionalProperties: false,
|
||||
$schema: "http://json-schema.org/draft-07/schema#",
|
||||
},
|
||||
},
|
||||
])
|
||||
expect(executed).toEqual({ args: { query: "weather" }, toolCallId: "call-injected-tool" })
|
||||
},
|
||||
})
|
||||
})
|
||||
|
||||
test("executes OpenAI tool calls through native runtime", async () => {
|
||||
const server = state.server
|
||||
if (!server) {
|
||||
throw new Error("Server not initialized")
|
||||
}
|
||||
|
||||
const source = await loadFixture("openai", "gpt-5.2")
|
||||
const model = source.model
|
||||
const chunks = [
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
item: { type: "function_call", id: "item-native-tool", call_id: "call-native-tool", name: "lookup" },
|
||||
},
|
||||
{
|
||||
type: "response.function_call_arguments.delta",
|
||||
item_id: "item-native-tool",
|
||||
delta: '{"query":"weather"}',
|
||||
},
|
||||
{
|
||||
type: "response.output_item.done",
|
||||
item: {
|
||||
type: "function_call",
|
||||
id: "item-native-tool",
|
||||
call_id: "call-native-tool",
|
||||
name: "lookup",
|
||||
arguments: '{"query":"weather"}',
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.completed",
|
||||
response: { incomplete_details: null, usage: { input_tokens: 1, output_tokens: 1 } },
|
||||
},
|
||||
]
|
||||
const request = waitRequest("/responses", createEventResponse(chunks, true))
|
||||
let executed: unknown
|
||||
|
||||
await using tmp = await tmpdir({
|
||||
init: async (dir) => {
|
||||
await Bun.write(
|
||||
path.join(dir, "opencode.json"),
|
||||
JSON.stringify({
|
||||
$schema: "https://opencode.ai/config.json",
|
||||
enabled_providers: ["openai"],
|
||||
provider: {
|
||||
openai: {
|
||||
name: "OpenAI",
|
||||
env: ["OPENAI_API_KEY"],
|
||||
npm: "@ai-sdk/openai",
|
||||
api: "https://api.openai.com/v1",
|
||||
models: {
|
||||
[model.id]: model,
|
||||
},
|
||||
options: {
|
||||
apiKey: "test-openai-key",
|
||||
baseURL: `${server.url.origin}/v1`,
|
||||
},
|
||||
},
|
||||
},
|
||||
}),
|
||||
)
|
||||
},
|
||||
})
|
||||
|
||||
await withTestInstance({
|
||||
directory: tmp.path,
|
||||
fn: async (ctx) => {
|
||||
const resolved = await getModel(ProviderID.openai, ModelID.make(model.id), ctx)
|
||||
const sessionID = SessionID.make("session-test-native-tool")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
} satisfies Agent.Info
|
||||
|
||||
await drainWith(
|
||||
llmLayerWithExecutor(RequestExecutor.defaultLayer, { experimentalNativeLlm: true }),
|
||||
{
|
||||
user: {
|
||||
id: MessageID.make("msg_user-native-tool"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: Date.now() },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.make("openai"), modelID: resolved.id },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: [],
|
||||
messages: [{ role: "user", content: "Use lookup" }],
|
||||
tools: {
|
||||
lookup: tool({
|
||||
description: "Lookup data",
|
||||
inputSchema: z.object({ query: z.string() }),
|
||||
execute: async (args, options) => {
|
||||
executed = { args, toolCallId: options.toolCallId }
|
||||
return { output: "looked up" }
|
||||
},
|
||||
}),
|
||||
},
|
||||
},
|
||||
ctx,
|
||||
)
|
||||
|
||||
const capture = await request
|
||||
expect(capture.body.tools).toEqual([
|
||||
{
|
||||
type: "function",
|
||||
name: "lookup",
|
||||
description: "Lookup data",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: { query: { type: "string" } },
|
||||
required: ["query"],
|
||||
additionalProperties: false,
|
||||
$schema: "http://json-schema.org/draft-07/schema#",
|
||||
},
|
||||
},
|
||||
])
|
||||
expect(executed).toEqual({ args: { query: "weather" }, toolCallId: "call-native-tool" })
|
||||
},
|
||||
})
|
||||
})
|
||||
|
||||
test("accepts user image attachments as data URLs for OpenAI models", async () => {
|
||||
const server = state.server
|
||||
if (!server) {
|
||||
@@ -724,6 +1527,18 @@ describe("session.llm.stream", () => {
|
||||
service_tier: null,
|
||||
},
|
||||
},
|
||||
{
|
||||
type: "response.output_item.added",
|
||||
output_index: 0,
|
||||
item: { type: "message", id: "item-data-url", status: "in_progress", role: "assistant", content: [] },
|
||||
},
|
||||
{
|
||||
type: "response.content_part.added",
|
||||
item_id: "item-data-url",
|
||||
output_index: 0,
|
||||
content_index: 0,
|
||||
part: { type: "output_text", text: "", annotations: [] },
|
||||
},
|
||||
{
|
||||
type: "response.output_text.delta",
|
||||
item_id: "item-data-url",
|
||||
|
||||
Reference in New Issue
Block a user