77 lines
3.5 KiB
JavaScript
77 lines
3.5 KiB
JavaScript
import { afterEach, describe, expect, it, vi } from "vitest";
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import { getModelsByProviderId, getModelType, isValidModel } from "../../open-sse/config/providerModels.js";
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import { getModelInfoCore } from "../../open-sse/services/model.js";
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import { handleImageGenerationCore } from "../../open-sse/handlers/imageGenerationCore.js";
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const models = ["gpt-5.6-sol", "gpt-5.6-luna", "gpt-5.6-terra"];
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afterEach(() => vi.unstubAllGlobals());
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describe("Codex GPT-5.6 image models", () => {
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it.each(models)("exposes %s-image as an image model while retaining its chat entry", (model) => {
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const catalog = getModelsByProviderId("codex");
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expect(catalog.filter((entry) => entry.id === `${model}-image`)).toHaveLength(1);
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expect(catalog.find((entry) => entry.id === `${model}-image`)).toMatchObject({
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kind: "image",
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capabilities: ["text2img", "edit"],
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params: ["size", "quality", "background", "image_detail", "output_format"],
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});
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expect(isValidModel("cx", `${model}-image`)).toBe(true);
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expect(getModelType("cx", `${model}-image`)).toBe("image");
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expect(catalog.find((entry) => entry.id === model)).toBeDefined();
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expect(getModelType("cx", model)).not.toBe("image");
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});
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it.each(models)("routes %s-image edits and streams image events", async (model) => {
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const events = [
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["response.image_generation_call.partial_image", { partial_image_b64: "cGFydGlhbA==", partial_image_index: 0 }],
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["response.output_item.done", { item: { type: "image_generation_call", result: "ZmluYWw=" } }],
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];
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const fetchMock = vi.fn().mockResolvedValue(new Response(
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events.map(([event, data]) => `event: ${event}\ndata: ${JSON.stringify(data)}\n\n`).join(""),
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{ headers: { "Content-Type": "text/event-stream" } },
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));
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vi.stubGlobal("fetch", fetchMock);
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const onRequestSuccess = vi.fn();
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const modelInfo = await getModelInfoCore(`cx/${model}-image`);
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expect(modelInfo).toEqual({ provider: "codex", model: `${model}-image` });
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expect(await getModelInfoCore(`codex/${model}-image`)).toEqual(modelInfo);
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const result = await handleImageGenerationCore({
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modelInfo,
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body: {
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prompt: "Make the square blue",
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image: "data:image/png;base64,cmVmZXJlbmNl",
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image_detail: "low",
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size: "1024x1024",
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quality: "high",
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background: "transparent",
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output_format: "WEBP",
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},
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credentials: { accessToken: "test-token" },
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streamToClient: true,
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onRequestSuccess,
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});
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expect(result.success).toBe(true);
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expect(result.response.status).toBe(200);
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expect(result.response.headers.get("content-type")).toBe("text/event-stream");
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const [url, options] = fetchMock.mock.calls[0];
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expect(url).toBe("https://chatgpt.com/backend-api/codex/responses");
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const upstreamBody = JSON.parse(options.body);
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expect(upstreamBody.model).toBe(model);
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expect(upstreamBody.tools).toEqual([{
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type: "image_generation", output_format: "webp", size: "1024x1024",
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quality: "high", background: "transparent",
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}]);
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expect(upstreamBody.input[0].content).toContainEqual({
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type: "input_image", image_url: "data:image/png;base64,cmVmZXJlbmNl", detail: "low",
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});
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const stream = await result.response.text();
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expect(stream).toContain('event: partial_image\ndata: {"b64_json":"cGFydGlhbA==","index":0}');
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expect(stream).toContain("event: done\n");
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expect(stream).toContain('"data":[{"b64_json":"ZmluYWw="}]');
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expect(onRequestSuccess).toHaveBeenCalledTimes(1);
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});
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});
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