| import { describe, expect, test } from "bun:test" |
| import { Effect } from "effect" |
| import { LLM } from "../src" |
| import { OpenAIChat } from "../src/protocols" |
| import { ToolSchemaProjection } from "../src/protocols/utils/tool-schema" |
| import { Auth, LLMClient } from "../src/route" |
| import { it } from "./lib/effect" |
|
|
| describe("tool schema projections", () => { |
| test("moonshot strips $ref siblings and converts tuple arrays to a schema object", () => { |
| expect( |
| ToolSchemaProjection.moonshot({ |
| type: "object", |
| properties: { |
| linked: { $ref: "#/$defs/Linked", description: "drop me" }, |
| tuple: { type: "array", items: [{ type: "string" }, { type: "number" }] }, |
| prefixTuple: { type: "array", prefixItems: [{ type: "boolean" }, { type: "string" }] }, |
| }, |
| }), |
| ).toEqual({ |
| type: "object", |
| properties: { |
| linked: { $ref: "#/$defs/Linked" }, |
| tuple: { type: "array", items: { anyOf: [{ type: "string" }, { type: "number" }] } }, |
| prefixTuple: { type: "array", items: { anyOf: [{ type: "boolean" }, { type: "string" }] } }, |
| }, |
| }) |
| }) |
|
|
| test("gemini handles numeric enums, dangling required fields, untyped arrays, and scalar object keys", () => { |
| expect( |
| ToolSchemaProjection.gemini({ |
| type: "object", |
| required: ["status", "missing"], |
| properties: { |
| status: { type: "integer", enum: [1, 2] }, |
| tags: { type: "array" }, |
| name: { type: "string", properties: { ignored: { type: "string" } }, required: ["ignored"] }, |
| }, |
| }), |
| ).toEqual({ |
| type: "object", |
| required: ["status"], |
| properties: { |
| status: { type: "string", enum: ["1", "2"] }, |
| tags: { type: "array", items: { type: "string" } }, |
| name: { type: "string" }, |
| }, |
| }) |
| }) |
|
|
| test("openai keeps one flat object top-level schema", () => { |
| expect( |
| ToolSchemaProjection.openAI({ |
| anyOf: [ |
| { |
| type: "object", |
| properties: { |
| path: { type: "string" }, |
| maybe: { anyOf: [{ type: "string" }, { type: "null" }] }, |
| }, |
| }, |
| { type: "object", properties: { resource: { type: "string" } } }, |
| ], |
| }), |
| ).toEqual({ |
| type: "object", |
| properties: { |
| path: { type: "string" }, |
| maybe: { type: "string" }, |
| resource: { type: "string" }, |
| }, |
| additionalProperties: false, |
| }) |
| }) |
|
|
| it.effect("applies model compatibility before protocol projection", () => |
| Effect.gen(function* () { |
| const model = OpenAIChat.route |
| .with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") }) |
| .model({ id: "kimi-k2", compatibility: { toolSchema: "moonshot" } }) |
| const prepared = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>( |
| LLM.request({ |
| model, |
| prompt: "Use the tool.", |
| tools: [ |
| { |
| name: "lookup", |
| description: "Lookup data.", |
| inputSchema: { |
| type: "object", |
| anyOf: [ |
| { |
| type: "object", |
| properties: { |
| tuple: { type: "array", items: [{ type: "string" }, { type: "number" }] }, |
| linked: { $ref: "#/$defs/Linked", description: "drop me" }, |
| }, |
| }, |
| ], |
| }, |
| }, |
| ], |
| }), |
| ) |
|
|
| expect(prepared.body.tools?.[0]?.function.parameters).toEqual({ |
| type: "object", |
| properties: { |
| tuple: { type: "array", items: { anyOf: [{ type: "string" }, { type: "number" }] } }, |
| linked: { $ref: "#/$defs/Linked" }, |
| }, |
| additionalProperties: false, |
| }) |
| }), |
| ) |
| }) |
|
|
