Files
opencode/packages/llm/test/generate-object.test.ts
opencode-agent[bot] ba8c920639 chore: generate
2026-05-08 20:57:36 +00:00

186 lines
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TypeScript

import { describe, expect, test } from "bun:test"
import { Effect, Schema } from "effect"
import { LLM } from "../src"
import * as OpenAIChat from "../src/protocols/openai-chat"
import { Tool, toDefinitions } from "../src/tool"
import { it } from "./lib/effect"
import { dynamicResponse } from "./lib/http"
import { finishChunk, toolCallChunk } from "./lib/openai-chunks"
import { sseEvents } from "./lib/sse"
type OpenAIChatBody = {
readonly tool_choice?: unknown
readonly tools?: ReadonlyArray<{
readonly function: {
readonly parameters: unknown
}
}>
}
const model = OpenAIChat.model({
id: "gpt-4o-mini",
baseURL: "https://api.openai.test/v1/",
headers: { authorization: "Bearer test" },
})
const Json = Schema.fromJsonString(Schema.Unknown)
const decodeJson = Schema.decodeUnknownSync(Json)
const decodeBody = (text: string): OpenAIChatBody => decodeJson(text) as OpenAIChatBody
describe("Tool.make (dynamic JSON Schema)", () => {
test("forwards JSON Schema and description through toDefinitions", () => {
const jsonSchema = {
type: "object" as const,
properties: { city: { type: "string" } },
required: ["city"],
}
const lookup = Tool.make({
description: "Look up something",
jsonSchema,
execute: () => Effect.succeed({ ok: true }),
})
const [definition] = toDefinitions({ lookup })
expect(definition?.name).toBe("lookup")
expect(definition?.description).toBe("Look up something")
expect(definition?.inputSchema).toEqual(jsonSchema)
})
test("execute receives the raw input untouched", async () => {
const seen: unknown[] = []
const tool = Tool.make({
description: "echo",
jsonSchema: { type: "object" },
execute: (params) =>
Effect.sync(() => {
seen.push(params)
return { ok: true }
}),
})
const result = await Effect.runPromise(tool.execute({ hello: "world" }))
expect(seen).toEqual([{ hello: "world" }])
expect(result).toEqual({ ok: true })
})
})
describe("LLM.generateObject", () => {
it.effect("forces a synthetic tool call and decodes the input", () =>
Effect.gen(function* () {
const bodies: OpenAIChatBody[] = []
const layer = dynamicResponse((input) =>
Effect.sync(() => {
bodies.push(decodeBody(input.text))
return input.respond(
sseEvents(
toolCallChunk("call_1", "generate_object", '{"city":"Paris","temp":22}'),
finishChunk("tool_calls"),
),
{ headers: { "content-type": "text/event-stream" } },
)
}),
)
const response = yield* LLM.generateObject({
model,
prompt: "Return a structured weather report.",
schema: Schema.Struct({ city: Schema.String, temp: Schema.Number }),
}).pipe(Effect.provide(layer))
expect(response.object).toEqual({ city: "Paris", temp: 22 })
expect(response.response.toolCalls).toHaveLength(1)
expect(bodies).toHaveLength(1)
expect(bodies[0].tool_choice).toEqual({ type: "function", function: { name: "generate_object" } })
const tool = bodies[0].tools?.[0]
expect(bodies[0].tools).toHaveLength(1)
expect(tool).toMatchObject({
type: "function",
function: { name: "generate_object" },
})
const params = tool?.function.parameters as {
readonly type?: unknown
readonly required?: unknown
readonly properties?: Record<string, unknown>
}
expect(params.type).toBe("object")
expect(params.required).toEqual(["city", "temp"])
expect(params.properties?.city).toMatchObject({ type: "string" })
expect(params.properties?.temp).toBeDefined()
}),
)
it.effect("accepts a raw JSON Schema and returns the input untouched", () =>
Effect.gen(function* () {
const bodies: OpenAIChatBody[] = []
const layer = dynamicResponse((input) =>
Effect.sync(() => {
bodies.push(decodeBody(input.text))
return input.respond(
sseEvents(toolCallChunk("call_1", "generate_object", '{"name":"Ada","age":30}'), finishChunk("tool_calls")),
{ headers: { "content-type": "text/event-stream" } },
)
}),
)
const response = yield* LLM.generateObject({
model,
prompt: "Extract the user.",
jsonSchema: {
type: "object",
properties: { name: { type: "string" }, age: { type: "number" } },
required: ["name", "age"],
},
}).pipe(Effect.provide(layer))
expect(response.object).toEqual({ name: "Ada", age: 30 })
expect(bodies[0].tools?.[0]?.function.parameters).toEqual({
type: "object",
properties: { name: { type: "string" }, age: { type: "number" } },
required: ["name", "age"],
})
}),
)
it.effect("fails when the model does not call the synthetic tool", () =>
Effect.gen(function* () {
const layer = dynamicResponse((input) =>
Effect.sync(() =>
input.respond(sseEvents({ id: "x", choices: [{ delta: { content: "no thanks" }, finish_reason: "stop" }] }), {
headers: { "content-type": "text/event-stream" },
}),
),
)
const exit = yield* LLM.generateObject({
model,
prompt: "Return a structured value.",
schema: Schema.Struct({ value: Schema.Number }),
}).pipe(Effect.provide(layer), Effect.exit)
expect(exit._tag).toBe("Failure")
}),
)
it.effect("fails with a decode error when the tool input does not match the schema", () =>
Effect.gen(function* () {
const layer = dynamicResponse((input) =>
Effect.sync(() =>
input.respond(
sseEvents(
toolCallChunk("call_1", "generate_object", '{"value":"not-a-number"}'),
finishChunk("tool_calls"),
),
{ headers: { "content-type": "text/event-stream" } },
),
),
)
const exit = yield* LLM.generateObject({
model,
prompt: "Return a structured value.",
schema: Schema.Struct({ value: Schema.Number }),
}).pipe(Effect.provide(layer), Effect.exit)
expect(exit._tag).toBe("Failure")
}),
)
})