import { describe, expect, test } from "bun:test" import { LLM, LLMResponse } from "../src" import { LLMRequest, Message, ModelRef, ToolCallPart, ToolChoice, ToolDefinition, ToolResultPart } from "../src/schema" describe("llm constructors", () => { test("builds canonical schema classes from ergonomic input", () => { const request = LLM.request({ id: "req_1", model: LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local" }), system: "You are concise.", prompt: "Say hello.", }) expect(request).toBeInstanceOf(LLMRequest) expect(request.model).toBeInstanceOf(ModelRef) expect(request.messages[0]).toBeInstanceOf(Message) expect(request.system).toEqual([{ type: "text", text: "You are concise." }]) expect(request.messages[0]?.content).toEqual([{ type: "text", text: "Say hello." }]) expect(request.generation).toBeUndefined() expect(request.tools).toEqual([]) }) test("updates requests without spreading schema class instances", () => { const base = LLM.request({ id: "req_1", model: LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local" }), prompt: "Say hello.", }) const updated = LLM.updateRequest(base, { generation: { maxTokens: 20 }, messages: [...base.messages, Message.assistant("Hi.")], }) expect(updated).toBeInstanceOf(LLMRequest) expect(updated.id).toBe("req_1") expect(updated.model).toEqual(base.model) expect(updated.generation).toEqual({ maxTokens: 20 }) expect(updated.messages.map((message) => message.role)).toEqual(["user", "assistant"]) }) test("keeps request options separate from model defaults", () => { const request = LLM.request({ model: LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local", generation: { maxTokens: 100, temperature: 1 }, providerOptions: { openai: { store: false, metadata: { model: true } } }, http: { body: { metadata: { model: true } }, headers: { "x-shared": "model" }, query: { model: "1" } }, }), prompt: "Say hello.", generation: { temperature: 0 }, providerOptions: { openai: { store: true, metadata: { request: true } } }, http: { body: { metadata: { request: true } }, headers: { "x-shared": "request" }, query: { request: "1" } }, }) expect(request.generation).toEqual({ temperature: 0 }) expect(request.providerOptions).toEqual({ openai: { store: true, metadata: { request: true } } }) expect(request.http).toEqual({ body: { metadata: { request: true } }, headers: { "x-shared": "request" }, query: { request: "1" }, }) }) test("updates canonical requests from the request datatype", () => { const base = LLM.request({ id: "req_1", model: LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local" }), prompt: "Say hello.", }) const updated = LLMRequest.update(base, { messages: [...base.messages, Message.assistant("Hi.")] }) expect(updated).toBeInstanceOf(LLMRequest) expect(updated.id).toBe("req_1") expect(LLMRequest.input(updated).id).toBe("req_1") expect(updated.messages.map((message) => message.role)).toEqual(["user", "assistant"]) expect(LLMRequest.update(updated, {})).toBe(updated) }) test("updates canonical models from the model datatype", () => { const base = LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local" }) const updated = ModelRef.update(base, { route: "openai-responses" }) expect(updated).toBeInstanceOf(ModelRef) expect(String(updated.id)).toBe("fake-model") expect(updated.route).toBe("openai-responses") expect(String(ModelRef.input(updated).provider)).toBe("fake") expect(ModelRef.update(updated, {})).toBe(updated) }) test("builds tool choices from names and tools", () => { const tool = ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }) expect(tool).toBeInstanceOf(ToolDefinition) expect(ToolChoice.make("lookup")).toEqual(new ToolChoice({ type: "tool", name: "lookup" })) expect(ToolChoice.named("required")).toEqual(new ToolChoice({ type: "tool", name: "required" })) expect(ToolChoice.make(tool)).toEqual(new ToolChoice({ type: "tool", name: "lookup" })) }) test("builds tool choice modes from reserved strings", () => { expect(ToolChoice.make("auto")).toEqual(new ToolChoice({ type: "auto" })) expect(ToolChoice.make("none")).toEqual(new ToolChoice({ type: "none" })) expect(ToolChoice.make("required")).toEqual(new ToolChoice({ type: "required" })) expect( LLM.request({ model: LLM.model({ id: "fake-model", provider: "fake", route: "openai-chat", baseURL: "https://fake.local" }), prompt: "Use tools if needed.", toolChoice: "required", }).toolChoice, ).toEqual(new ToolChoice({ type: "required" })) }) test("builds assistant tool calls and tool result messages", () => { const call = ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } }) const result = ToolResultPart.make({ id: "call_1", name: "lookup", result: { temperature: 72 } }) expect(Message.assistant([call]).content).toEqual([call]) expect(Message.tool(result).content).toEqual([ { type: "tool-result", id: "call_1", name: "lookup", result: { type: "json", value: { temperature: 72 } } }, ]) }) test("extracts output text from response events", () => { expect( LLMResponse.text({ events: [ { type: "text-delta", id: "text-0", text: "hi" }, { type: "finish", reason: "stop" }, ], }), ).toBe("hi") }) })