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anomalyco_opencode/packages/opencode/test/session/llm-native.test.ts
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17 KiB
TypeScript

import { describe, expect, test } from "bun:test"
import { ToolFailure } from "@opencode-ai/llm"
import { LLMClient, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
import { jsonSchema, tool, type ModelMessage } from "ai"
import { Effect, Layer, Stream } from "effect"
import { LLMNative } from "@/session/llm/native-request"
import { LLMNativeRuntime } from "@/session/llm/native-runtime"
import type { Provider } from "@/provider/provider"
import { ModelID, ProviderID } from "@/provider/schema"
import { OAUTH_DUMMY_KEY } from "@/auth"
const baseModel: Provider.Model = {
id: ModelID.make("gpt-5-mini"),
providerID: ProviderID.make("openai"),
api: {
id: "gpt-5-mini",
url: "https://api.openai.com/v1",
npm: "@ai-sdk/openai",
},
name: "GPT-5 Mini",
capabilities: {
temperature: true,
reasoning: true,
attachment: true,
toolcall: true,
input: {
text: true,
audio: false,
image: true,
video: false,
pdf: false,
},
output: {
text: true,
audio: false,
image: false,
video: false,
pdf: false,
},
interleaved: false,
},
cost: {
input: 0,
output: 0,
cache: {
read: 0,
write: 0,
},
},
limit: {
context: 128_000,
input: 128_000,
output: 32_000,
},
status: "active",
options: {},
headers: {
"x-model": "model-header",
},
release_date: "2026-01-01",
}
const providerInfo: Provider.Info = {
id: ProviderID.make("openai"),
name: "OpenAI",
source: "config",
env: ["OPENAI_API_KEY"],
options: { apiKey: "test-openai-key" },
models: {},
}
function responsesStream(chunks: unknown[]) {
return new Response(chunks.map((chunk) => `data: ${JSON.stringify(chunk)}`).join("\n\n") + "\n\n", {
status: 200,
headers: { "Content-Type": "text/event-stream" },
})
}
describe("session.llm-native.request", () => {
test("maps normalized stream inputs to a native LLM request", () => {
const messages: ModelMessage[] = [
{
role: "system",
content: "system from messages",
},
{
role: "user",
content: [
{ type: "text", text: "hello", providerOptions: { openai: { cacheControl: { type: "ephemeral" } } } },
{ type: "file", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
],
},
{
role: "assistant",
content: [
{ type: "reasoning", text: "thinking", providerOptions: { openai: { encryptedContent: "secret" } } },
{ type: "text", text: "I'll run it" },
{
type: "tool-call",
toolCallId: "call-1",
toolName: "bash",
input: { command: "ls" },
providerOptions: { openai: { itemId: "item-1" } },
},
],
},
{
role: "tool",
content: [
{
type: "tool-result",
toolCallId: "call-1",
toolName: "bash",
output: { type: "text", value: "ok" },
providerOptions: { openai: { outputId: "output-1" } },
},
],
},
]
const request = LLMNative.request({
model: baseModel,
system: ["agent system"],
messages,
tools: {
bash: tool({
description: "Run a shell command",
inputSchema: jsonSchema({
type: "object",
properties: {
command: { type: "string" },
},
required: ["command"],
}),
}),
},
toolChoice: "required",
temperature: 0.2,
topP: 0.9,
topK: 40,
maxOutputTokens: 1024,
providerOptions: { openai: { store: false } },
headers: { "x-request": "request-header" },
})
expect(request.model).toMatchObject({
id: "gpt-5-mini",
provider: "openai",
route: { id: "openai-responses" },
})
expect(request.model.route.endpoint.baseURL).toBe("https://api.openai.com/v1")
expect(request.model.route.defaults.headers).toEqual({
"x-model": "model-header",
"x-request": "request-header",
})
expect(request.model.route.defaults.limits).toMatchObject({
context: 128_000,
output: 32_000,
})
expect(request.system).toEqual([
{ type: "text", text: "agent system" },
{ type: "text", text: "system from messages" },
])
expect(request.generation).toMatchObject({
temperature: 0.2,
topP: 0.9,
topK: 40,
maxTokens: 1024,
})
expect(request.providerOptions).toEqual({ openai: { store: false } })
expect(request.toolChoice).toMatchObject({ type: "required" })
expect(request.tools).toMatchObject([
{
name: "bash",
description: "Run a shell command",
inputSchema: {
type: "object",
properties: {
command: { type: "string" },
},
required: ["command"],
},
},
])
expect(request.messages).toMatchObject([
{
role: "user",
content: [
{ type: "text", text: "hello", providerMetadata: { openai: { cacheControl: { type: "ephemeral" } } } },
{ type: "media", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
],
},
{
role: "assistant",
content: [
{ type: "reasoning", text: "thinking", providerMetadata: { openai: { encryptedContent: "secret" } } },
{ type: "text", text: "I'll run it" },
{
type: "tool-call",
id: "call-1",
name: "bash",
input: { command: "ls" },
providerMetadata: { openai: { itemId: "item-1" } },
},
],
},
{
role: "tool",
content: [
{
type: "tool-result",
id: "call-1",
name: "bash",
result: { type: "text", value: "ok" },
providerMetadata: { openai: { outputId: "output-1" } },
},
],
},
])
})
test("maps stored provider metadata to native content metadata", () => {
const reasoning = Object.assign(
{ type: "reasoning" as const, text: "thinking" },
{
providerMetadata: {
openai: {
itemId: "rs_1",
reasoningEncryptedContent: "encrypted-state",
},
},
},
)
const request = LLMNative.request({
model: baseModel,
messages: [
{
role: "assistant",
content: [reasoning],
},
],
})
expect(request.messages).toMatchObject([
{
role: "assistant",
content: [
{
type: "reasoning",
text: "thinking",
providerMetadata: { openai: { itemId: "rs_1", reasoningEncryptedContent: "encrypted-state" } },
},
],
},
])
})
test("selects native request routes for provider packages", () => {
const openai = LLMNative.model({
model: { ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/openai" } },
apiKey: "test-key",
messages: [],
})
expect(openai.route.id).toBe("openai-responses")
expect(openai.route.endpoint.baseURL).toBe("https://api.openai.com/v1")
const anthropic = LLMNative.model({
model: { ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/anthropic" } },
apiKey: "test-key",
messages: [],
})
expect(anthropic.route.id).toBe("anthropic-messages")
expect(anthropic.route.endpoint.baseURL).toBe("https://api.anthropic.com/v1")
const google = LLMNative.model({
model: { ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/google" } },
apiKey: "test-key",
messages: [],
})
expect(google.route.id).toBe("gemini")
expect(google.route.endpoint.baseURL).toBe("https://generativelanguage.googleapis.com/v1beta")
const compatible = LLMNative.model({
model: {
...baseModel,
providerID: ProviderID.make("opencode"),
api: { ...baseModel.api, url: "https://ai.example.test/v1", npm: "@ai-sdk/openai-compatible" },
},
apiKey: "test-key",
messages: [],
})
expect(compatible.route.id).toBe("openai-compatible-chat")
expect(compatible.route.endpoint.baseURL).toBe("https://ai.example.test/v1")
const openrouter = LLMNative.model({
model: { ...baseModel, api: { ...baseModel.api, url: "", npm: "@openrouter/ai-sdk-provider" } },
apiKey: "test-key",
messages: [],
})
expect(openrouter.route.id).toBe("openrouter")
expect(openrouter.route.endpoint.baseURL).toBe("https://openrouter.ai/api/v1")
})
test("fails fast for unsupported provider packages", () => {
expect(() =>
LLMNative.request({
model: { ...baseModel, api: { ...baseModel.api, npm: "unknown-provider" } },
messages: [],
}),
).toThrow("Native LLM request adapter does not support provider package unknown-provider")
})
test("only enables native runtime for supported OpenAI API-key models", () => {
expect(LLMNativeRuntime.status({ model: baseModel, provider: providerInfo, auth: undefined })).toMatchObject({
type: "supported",
apiKey: "test-openai-key",
})
expect(
LLMNativeRuntime.status({
model: { ...baseModel, providerID: ProviderID.make("opencode") },
provider: { ...providerInfo, id: ProviderID.make("opencode") },
auth: undefined,
}),
).toMatchObject({
type: "supported",
apiKey: "test-openai-key",
})
expect(
LLMNativeRuntime.status({
model: {
...baseModel,
providerID: ProviderID.make("opencode"),
api: { ...baseModel.api, npm: "@ai-sdk/openai-compatible" },
},
provider: { ...providerInfo, id: ProviderID.make("opencode") },
auth: undefined,
}),
).toMatchObject({
type: "supported",
apiKey: "test-openai-key",
})
expect(
LLMNativeRuntime.status({
model: { ...baseModel, providerID: ProviderID.make("google") },
provider: { ...providerInfo, id: ProviderID.make("google") },
auth: undefined,
}),
).toEqual({ type: "unsupported", reason: "provider is not openai, opencode, or anthropic" })
expect(
LLMNativeRuntime.status({
model: baseModel,
provider: providerInfo,
auth: { type: "oauth", refresh: "refresh", access: "access", expires: 1 },
}),
).toEqual({ type: "unsupported", reason: "OAuth auth requires a provider fetch override" })
expect(
LLMNativeRuntime.status({
model: baseModel,
provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: async () => new Response() } },
auth: { type: "oauth", refresh: "refresh", access: "access", expires: 1 },
}),
).toMatchObject({ type: "supported", apiKey: OAUTH_DUMMY_KEY })
expect(
LLMNativeRuntime.status({
model: { ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/google" } },
provider: providerInfo,
auth: undefined,
}),
).toEqual({ type: "unsupported", reason: "provider package is not OpenAI, OpenAI-compatible, or Anthropic" })
expect(
LLMNativeRuntime.status({
model: baseModel,
provider: { ...providerInfo, options: {} },
auth: undefined,
}),
).toEqual({ type: "unsupported", reason: "API key is not configured" })
})
test("enables native runtime for Anthropic API-key models", () => {
expect(
LLMNativeRuntime.status({
model: {
...baseModel,
providerID: ProviderID.make("anthropic"),
api: { ...baseModel.api, npm: "@ai-sdk/anthropic", url: "https://api.anthropic.com/v1" },
},
provider: {
...providerInfo,
id: ProviderID.make("anthropic"),
name: "Anthropic",
env: ["ANTHROPIC_API_KEY"],
options: { apiKey: "test-anthropic-key" },
},
auth: undefined,
}),
).toMatchObject({ type: "supported", apiKey: "test-anthropic-key" })
})
test("prefers console provider api key over stored opencode auth", () => {
expect(
LLMNativeRuntime.status({
model: { ...baseModel, providerID: ProviderID.make("opencode") },
provider: {
...providerInfo,
id: ProviderID.make("opencode"),
options: { apiKey: "console-token" },
key: "zen-token",
},
auth: { type: "api", key: "zen-token" },
}),
).toMatchObject({
type: "supported",
apiKey: "console-token",
})
expect(
LLMNativeRuntime.status({
model: baseModel,
provider: { ...providerInfo, options: {}, key: "provider-key" },
auth: undefined,
}),
).toMatchObject({
type: "supported",
apiKey: "provider-key",
})
})
test("native tool wrapper converts thrown errors into typed ToolFailure", async () => {
const wrapped = LLMNativeRuntime.nativeTools(
{
explode: {
description: "always throws",
inputSchema: jsonSchema({ type: "object" }),
execute: async () => {
throw new Error("boom")
},
} as any,
},
{ messages: [] as ModelMessage[], abort: new AbortController().signal },
)
const failure = await Effect.runPromise(
Effect.flip(wrapped.explode!.execute!({}, { id: "call-1", name: "explode" })),
)
expect(failure).toBeInstanceOf(ToolFailure)
expect((failure as ToolFailure).message).toBe("boom")
})
test("native tool wrapper raises ToolFailure when the source tool has no execute handler", async () => {
// The AI SDK Tool shape allows execute to be omitted (e.g., client-side / MCP tools).
// The native runtime owns execution, so encountering such a tool here means upstream
// wiring is wrong; we want a typed failure, not a silent skip or unhandled exception.
const wrapped = LLMNativeRuntime.nativeTools(
{ incomplete: { description: "no execute", inputSchema: jsonSchema({ type: "object" }) } as any },
{ messages: [] as ModelMessage[], abort: new AbortController().signal },
)
const failure = await Effect.runPromise(
Effect.flip(wrapped.incomplete!.execute!({}, { id: "call-1", name: "incomplete" })),
)
expect(failure).toBeInstanceOf(ToolFailure)
expect((failure as ToolFailure).message).toContain("incomplete")
})
test("compiles through the native OpenAI Responses route", async () => {
const prepared = await Effect.runPromise(
LLMClient.prepare(
LLMNative.request({
model: baseModel,
apiKey: "test-openai-key",
messages: [{ role: "user", content: "hello" }],
providerOptions: { openai: { store: false, instructions: "You are concise." } },
maxOutputTokens: 512,
headers: { "x-request": "request-header" },
}),
).pipe(
Effect.provide(LLMClient.layer),
Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
),
)
expect(prepared).toMatchObject({
route: "openai-responses",
protocol: "openai-responses",
body: {
model: "gpt-5-mini",
instructions: "You are concise.",
input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
max_output_tokens: 512,
store: false,
stream: true,
},
})
})
test("uses provider fetch override for native OpenAI OAuth requests", async () => {
const captures: Array<{ url: string; body: unknown }> = []
const customFetch = (async (input, init) => {
const request = input instanceof Request ? input : new Request(input, init)
captures.push({ url: request.url, body: await request.clone().json() })
return responsesStream([
{ type: "response.output_text.delta", item_id: "msg_1", delta: "Hello" },
{ type: "response.completed", response: { usage: { input_tokens: 1, output_tokens: 1 } } },
])
}) as typeof fetch
const events = await Effect.runPromise(
Effect.gen(function* () {
const llmClient = yield* LLMClient.Service
const native = LLMNativeRuntime.stream({
model: baseModel,
provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: customFetch } },
auth: { type: "oauth", refresh: "refresh", access: "access", expires: Date.now() + 60_000 },
llmClient,
messages: [{ role: "user", content: "hello" }],
tools: {},
providerOptions: { instructions: "You are concise." },
headers: {},
abort: new AbortController().signal,
})
expect(native.type).toBe("supported")
if (native.type === "unsupported") return []
return yield* native.stream.pipe(Stream.runCollect)
}).pipe(
Effect.provide(LLMClient.layer),
Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
),
)
expect(captures).toHaveLength(1)
expect(captures[0]).toMatchObject({
url: "https://api.openai.com/v1/responses",
body: {
model: "gpt-5-mini",
instructions: "You are concise.",
input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
},
})
expect(events).toEqual(
expect.arrayContaining([
expect.objectContaining({ type: "text-delta", text: "Hello" }),
expect.objectContaining({ type: "finish" }),
]),
)
})
})