opencode/packages/ai/test/compile.test.ts
2026-08-03 14:50:04 -05:00

296 lines
11 KiB
TypeScript

import { describe, expect, test } from "bun:test"
import { Effect, Ref, Schema } from "effect"
import { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
import { LLM, mergeProviderOptions } from "../src"
import { AnthropicMessages, OpenAIChat } from "../src/protocols"
import { Auth, LLMClient } from "../src/route"
import { compileRequest } from "../src/route/client"
import { it } from "./lib/effect"
import { dynamicResponse } from "./lib/http"
import { deltaChunk } from "./lib/openai-chunks"
import { sseEvents } from "./lib/sse"
const TargetJson = Schema.fromJsonString(Schema.Unknown)
const decodeJson = Schema.decodeUnknownSync(TargetJson)
describe("request option precedence", () => {
test("deep-merges provider option records and replaces arrays, primitives, and null", () => {
const merged = mergeProviderOptions(
{
openai: {
include: ["route"],
metadata: { route: true, shared: "route" },
nullable: "route",
primitive: "route",
},
},
{
openai: {
include: ["model"],
metadata: { model: true, shared: "model" },
nullable: null,
primitive: "model",
},
},
{ openai: { metadata: { request: true }, primitive: false } },
)
expect(merged).toEqual({
openai: {
include: ["model"],
metadata: { route: true, model: true, request: true, shared: "model" },
nullable: null,
primitive: false,
},
})
})
it.effect("compiles bodies with route defaults, model defaults, and call options in order", () =>
Effect.gen(function* () {
const route = OpenAIChat.route.with({
endpoint: { baseURL: "https://api.openai.test/v1/" },
auth: Auth.bearer("test"),
generation: { maxTokens: 10, temperature: 1, stop: ["route"] },
providerOptions: { openai: { store: false, reasoningEffort: "low" } },
})
const model = route.model({
id: "gpt-4o-mini",
defaults: {
generation: { maxTokens: 20, temperature: 0.5, frequencyPenalty: 0.25, stop: ["model"] },
providerOptions: { openai: { reasoningEffort: "medium" } },
},
})
const prepared = yield* compileRequest(
LLM.request({
model,
prompt: "Say hello.",
generation: { maxTokens: 30, topP: 0.9, stop: ["request"] },
providerOptions: { openai: { store: true } },
}),
)
expect(prepared.body).toMatchObject({
model: "gpt-4o-mini",
stream: true,
max_tokens: 30,
temperature: 0.5,
top_p: 0.9,
frequency_penalty: 0.25,
store: true,
reasoning_effort: "medium",
})
expect(prepared.body.stop).toEqual(["request"])
}),
)
it.effect("applies model HTTP defaults before request HTTP overlays", () =>
LLMClient.generate(
LLM.request({
model: OpenAIChat.route
.with({
endpoint: { baseURL: "https://api.openai.test/v1/" },
auth: Auth.bearer("fresh-key"),
http: {
body: { metadata: { route: true, shared: "route" }, value: "route" },
headers: { "x-route": "route", "x-shared": "route" },
query: { route: "1", shared: "route" },
},
})
.model({
id: "gpt-4o-mini",
defaults: {
http: {
body: { metadata: { model: true, shared: "model" }, value: "model" },
headers: { "x-model": "model", "x-shared": "model" },
query: { model: "1", shared: "model" },
},
},
}),
prompt: "Say hello.",
http: {
body: { metadata: { request: true }, value: null },
headers: { "x-request": "request" },
query: { request: "1" },
},
}),
).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
expect(web.url).toBe("https://api.openai.test/v1/chat/completions?route=1&shared=model&model=1&request=1")
expect(web.headers.get("authorization")).toBe("Bearer fresh-key")
expect(web.headers.get("x-route")).toBe("route")
expect(web.headers.get("x-model")).toBe("model")
expect(web.headers.get("x-request")).toBe("request")
expect(web.headers.get("x-shared")).toBe("model")
expect(decodeJson(input.text)).toMatchObject({
metadata: { route: true, model: true, request: true, shared: "model" },
value: null,
})
return input.respond(sseEvents(deltaChunk({}, "stop")), {
headers: { "content-type": "text/event-stream" },
})
}),
),
),
),
)
it.effect("transforms the final HTTP request after serialization and authentication", () =>
LLMClient.generate(
LLM.request({
model: OpenAIChat.route
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("fresh-key") })
.model({ id: "gpt-4o-mini" }),
prompt: "Say hello.",
}),
{
http: (request, handler) =>
Effect.gen(function* () {
return yield* handler(
request.pipe(
HttpClientRequest.setUrl("https://proxy.test/v1/chat/completions"),
HttpClientRequest.setMethod("PUT"),
HttpClientRequest.setHeader("x-plugin", "transformed"),
HttpClientRequest.bodyText(JSON.stringify({ transformed: true }), "application/custom+json"),
),
)
}),
},
).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
expect(web.url).toBe("https://proxy.test/v1/chat/completions")
expect(web.method).toBe("PUT")
expect(web.headers.get("x-plugin")).toBe("transformed")
expect(web.headers.get("content-type")).toBe("application/custom+json")
expect(decodeJson(input.text)).toEqual({ transformed: true })
return input.respond(sseEvents(deltaChunk({}, "stop")), {
headers: { "content-type": "text/event-stream" },
})
}),
),
),
),
)
it.effect("transforms the HTTP response before protocol decoding", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: OpenAIChat.route
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
.model({ id: "gpt-4o-mini" }),
prompt: "Say hello.",
}),
{
http: (request, handler) =>
Effect.gen(function* () {
const response = yield* handler(request)
return HttpClientResponse.fromWeb(
response.request,
new Response((yield* response.text).replace("network", "hooked"), {
status: response.status,
headers: response.headers,
}),
)
}),
},
).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.succeed(
input.respond(sseEvents(deltaChunk({ content: "network" }, "stop")), {
headers: { "content-type": "text/event-stream" },
}),
),
),
),
)
expect(response.text).toBe("hooked")
}),
)
it.effect("can inspect an error response and retry the native request", () =>
Effect.gen(function* () {
const attempts = yield* Ref.make(0)
const response = yield* LLMClient.generate(
LLM.request({
model: OpenAIChat.route
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("stale") })
.model({ id: "gpt-4o-mini" }),
prompt: "Say hello.",
}),
{
http: (request, handler) =>
Effect.gen(function* () {
const response = yield* handler(request)
expect(response.status).toBe(401)
return yield* handler(HttpClientRequest.setHeader(request, "authorization", "Bearer refreshed"))
}),
},
).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
yield* Ref.update(attempts, (value) => value + 1)
if (input.request.headers.authorization !== "Bearer refreshed")
return input.respond("unauthorized", { status: 401 })
return input.respond(sseEvents(deltaChunk({ content: "retried" }, "stop")), {
headers: { "content-type": "text/event-stream" },
})
}),
),
),
)
expect(response.text).toBe("retried")
expect(yield* Ref.get(attempts)).toBe(2)
}),
)
it.effect("applies raw body overlays after protocol lowering", () =>
LLMClient.generate(
LLM.request({
model: OpenAIChat.route
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
.model({ id: "gpt-4o-mini" }),
prompt: "Say hello.",
http: { body: { model: "gpt-5", messages: [], tools: [] } },
}),
).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
expect(decodeJson(input.text)).toMatchObject({ model: "gpt-5", messages: [], tools: [] })
return input.respond(sseEvents(deltaChunk({}, "stop")), {
headers: { "content-type": "text/event-stream" },
})
}),
),
),
),
)
it.effect("uses model output limits after route limits and before call maxTokens", () =>
Effect.gen(function* () {
const route = AnthropicMessages.route.with({
endpoint: { baseURL: "https://api.anthropic.test/v1/" },
auth: Auth.header("x-api-key", "test"),
limits: { output: 128 },
})
const model = route.model({ id: "claude-sonnet-4-5", defaults: { limits: { output: 64 } } })
const withoutMaxTokens = yield* compileRequest(LLM.request({ model, prompt: "Say hello.", cache: "none" }))
const withMaxTokens = yield* compileRequest(
LLM.request({ model, prompt: "Say hello.", cache: "none", generation: { maxTokens: 32 } }),
)
expect(withoutMaxTokens.body.max_tokens).toBe(64)
expect(withMaxTokens.body.max_tokens).toBe(32)
}),
)
})