fix(huggingface): complete the Inference Providers router migration
Replace the retired api-inference.huggingface.co host with the Inference Providers router (router.huggingface.co): imageConfig.modelMap resolves Hub ids to provider-resolved ids, image-to-image models receive the source image in inputs with the prompt under parameters.prompt, and a new sttConfig wires the hf-inference ASR route. The image catalog grows to 23 models, dead whisper-small is replaced by whisper-large-v3-turbo, the unusable "language" param is dropped, and edit models declare the edit capability so the dashboard offers a source image. Adds unit and end-to-end coverage plus a model-id guard on custom endpoints.
This commit is contained in:
kimono381
144
tests/unit/huggingface-image-end-to-end.test.js
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144
tests/unit/huggingface-image-end-to-end.test.js
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/**
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* HuggingFace image generation — end-to-end through the real core handler.
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*
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* The registry/adapter tests pin the URL and payload in isolation. These tests
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* drive `handleImageGenerationCore` — the same function the `/v1/images/generations`
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* route calls — so the whole seam is exercised: adapter selection, buildUrl /
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* buildBody / buildHeaders, the fetch call, and the binary response parse.
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*
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* The mocked `fetch` asserts on the exact request the router would receive, which
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* is the strongest check available without burning live Inference Providers credits
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* (the router bills before validating the payload, so a live probe can only prove
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* the path exists, never that the body is right).
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*/
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import { describe, it, expect, vi, beforeEach, afterEach } from "vitest";
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import { handleImageGenerationCore } from "../../open-sse/handlers/imageGenerationCore.js";
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const originalFetch = global.fetch;
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const CREDS = { apiKey: "hf_test_token" };
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// A 1x1 transparent PNG — enough to prove the bytes survive the round trip.
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const PNG_1X1 = Buffer.from(
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"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNkYPhfDwAChwGA60e6kgAAAABJRU5ErkJggg==",
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"base64"
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);
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function mockBinaryResponse() {
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return {
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ok: true,
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status: 200,
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arrayBuffer: async () => PNG_1X1.buffer.slice(PNG_1X1.byteOffset, PNG_1X1.byteOffset + PNG_1X1.byteLength),
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};
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}
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async function generate(body, model) {
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return handleImageGenerationCore({
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body,
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modelInfo: { provider: "huggingface", model },
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credentials: CREDS,
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log: null,
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});
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}
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describe("HuggingFace image generation — end to end", () => {
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beforeEach(() => {
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global.fetch = vi.fn().mockResolvedValue(mockBinaryResponse());
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});
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afterEach(() => {
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global.fetch = originalFetch;
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});
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it("posts a text-to-image request to the fal-ai router path", async () => {
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const result = await generate({ prompt: "a lighthouse at dusk" }, "black-forest-labs/FLUX.1-schnell");
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expect(result.success).toBe(true);
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const [url, init] = global.fetch.mock.calls[0];
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expect(url).toBe("https://router.huggingface.co/fal-ai/fal-ai/flux/schnell");
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expect(init.method).toBe("POST");
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expect(JSON.parse(init.body)).toEqual({ inputs: "a lighthouse at dusk" });
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});
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it("authenticates with the connection's API key", async () => {
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await generate({ prompt: "x" }, "black-forest-labs/FLUX.1-schnell");
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const [, init] = global.fetch.mock.calls[0];
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expect(init.headers.Authorization).toBe("Bearer hf_test_token");
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});
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it("never touches the dead api-inference host", async () => {
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await generate({ prompt: "x" }, "black-forest-labs/FLUX.1-schnell");
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expect(global.fetch.mock.calls[0][0]).not.toContain("api-inference.huggingface.co");
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});
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it("posts an image-to-image request with the source image in inputs", async () => {
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const result = await generate(
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{ prompt: "make it snow", image: "data:image/png;base64,AAAB" },
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"Qwen/Qwen-Image-Edit"
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);
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expect(result.success).toBe(true);
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const [url, init] = global.fetch.mock.calls[0];
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expect(url).toBe("https://router.huggingface.co/fal-ai/fal-ai/qwen-image-edit");
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// The router takes raw base64 in inputs and the prompt under parameters —
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// the data-URL prefix must be stripped, not forwarded.
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expect(JSON.parse(init.body)).toEqual({
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inputs: "AAAB",
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parameters: { prompt: "make it snow" },
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});
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});
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it("rejects an image-to-image model that was given no source image", async () => {
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const result = await generate({ prompt: "make it snow" }, "Qwen/Qwen-Image-Edit");
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expect(result.success).toBe(false);
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expect(result.status).toBe(400);
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expect(result.error).toMatch(/requires a source image/i);
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expect(global.fetch).not.toHaveBeenCalled();
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});
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it("rejects a model with no router mapping before calling upstream", async () => {
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const result = await generate({ prompt: "x" }, "some-org/unmapped-model");
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expect(result.success).toBe(false);
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expect(result.status).toBe(400);
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expect(result.error).toMatch(/no HuggingFace router mapping/i);
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expect(global.fetch).not.toHaveBeenCalled();
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});
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it("returns the generated image as base64 to the client", async () => {
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const result = await generate({ prompt: "x" }, "black-forest-labs/FLUX.1-schnell");
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const payload = await result.response.json();
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expect(payload.data[0].b64_json).toBe(PNG_1X1.toString("base64"));
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});
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it("routes a self-hosted connection to its own endpoint", async () => {
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await handleImageGenerationCore({
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body: { prompt: "x" },
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modelInfo: { provider: "huggingface", model: "my-org/my-tgi-model" },
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credentials: { apiKey: "k", providerSpecificData: { baseUrl: "https://tgi.internal" } },
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log: null,
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});
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expect(global.fetch.mock.calls[0][0]).toBe("https://tgi.internal/my-org/my-tgi-model");
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});
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it("surfaces an upstream error instead of a broken image", async () => {
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global.fetch = vi.fn().mockResolvedValue({
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ok: false,
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status: 402,
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text: async () => JSON.stringify({ error: "You have depleted your monthly included credits." }),
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json: async () => ({ error: "You have depleted your monthly included credits." }),
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});
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const result = await generate({ prompt: "x" }, "black-forest-labs/FLUX.1-schnell");
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expect(result.success).toBe(false);
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expect(result.status).toBe(402);
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});
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});
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349
tests/unit/huggingface-router-migration.test.js
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349
tests/unit/huggingface-router-migration.test.js
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/**
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* HuggingFace registry migration to router.huggingface.co
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*
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* The legacy base URL `https://api-inference.huggingface.co` no longer resolves
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* (DNS ENOTFOUND), so every HuggingFace image/STT request failed at the fetch
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* layer. The replacement is `https://router.huggingface.co`, which routes by
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* `<provider>/<providerResolvedModelId>` — the provider-resolved id is NOT the
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* Hub model id and must be resolved from the Hub API's inferenceProviderMapping.
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*
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* Covers:
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* - imageConfig base URL is the live router host, not the dead legacy host
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* - image URL builder emits the provider-resolved id, not the Hub id
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* - image URL builder throws a descriptive error for unmapped models
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* - sttConfig exists and points at the live router host
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* - every registered public model resolves through a provider the router serves
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*/
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import { describe, it, expect } from "vitest";
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import huggingface from "../../open-sse/providers/registry/huggingface.js";
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import imageAdapter from "../../open-sse/handlers/imageProviders/huggingface.js";
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const DEAD_HOST = "api-inference.huggingface.co";
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const LIVE_ROUTER = "router.huggingface.co";
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// Providers the router actually forwards to. replicate/wavespeed/deepinfra appear
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// in the Hub's inferenceProviderMapping but reject every router request with
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// "Model not supported by provider <name>", so they must not be used here.
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const ROUTABLE_PROVIDERS = new Set(["fal-ai", "hf-inference", "nscale", "together", "novita", "hyperbolic"]);
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const imageConfig = huggingface.imageConfig;
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const modelMap = imageConfig.modelMap || {};
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// modelMap values are either a bare path (text-to-image) or
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// { path, task: "image-to-image" } for models that require a source image.
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const mappingPath = (value) => (typeof value === "string" ? value : value.path);
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const mappingTask = (value) => (typeof value === "string" ? "text-to-image" : value.task || "text-to-image");
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describe("HuggingFace registry — legacy host removal", () => {
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it("does not use the dead api-inference host for images", () => {
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expect(imageConfig.baseUrl).not.toContain(DEAD_HOST);
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});
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it("points imageConfig at the live router host", () => {
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expect(imageConfig.baseUrl).toContain(LIVE_ROUTER);
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});
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it("does not use the dead api-inference host for STT", () => {
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expect(huggingface.sttConfig?.baseUrl).not.toContain(DEAD_HOST);
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});
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});
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describe("HuggingFace STT dispatch", () => {
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it("declares an sttConfig so sttCore can dispatch", () => {
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expect(huggingface.sttConfig).toBeDefined();
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});
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it("uses the HuggingFace ASR wire format", () => {
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expect(huggingface.sttConfig.format).toBe("huggingface-asr");
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});
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it("authenticates with a bearer API key", () => {
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expect(huggingface.sttConfig.authType).toBe("apikey");
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expect(huggingface.sttConfig.authHeader).toBe("bearer");
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});
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it("advertises stt in serviceKinds", () => {
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expect(huggingface.serviceKinds).toContain("stt");
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});
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it("points sttConfig at the hf-inference model route", () => {
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expect(huggingface.sttConfig.baseUrl).toBe("https://router.huggingface.co/hf-inference/models");
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});
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});
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describe("HuggingFace image URL builder", () => {
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it("routes FLUX.1-schnell through its fal-ai provider id", () => {
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expect(imageAdapter.buildUrl("black-forest-labs/FLUX.1-schnell")).toBe(
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"https://router.huggingface.co/fal-ai/fal-ai/flux/schnell"
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);
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});
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it("routes SDXL through its fal-ai provider id", () => {
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expect(imageAdapter.buildUrl("stabilityai/stable-diffusion-xl-base-1.0")).toBe(
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"https://router.huggingface.co/fal-ai/fal-ai/fast-sdxl"
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);
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});
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it("never leaks the dead host into a built URL", () => {
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expect(imageAdapter.buildUrl("black-forest-labs/FLUX.1-schnell")).not.toContain(DEAD_HOST);
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});
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it("throws a descriptive error for a model with no provider mapping", () => {
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expect(() => imageAdapter.buildUrl("some-org/not-mapped-model")).toThrow(/no HuggingFace router mapping/i);
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});
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it("lets a connection override the endpoint for a self-hosted model", () => {
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const creds = { providerSpecificData: { baseUrl: "https://tgi.internal/" } };
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expect(imageAdapter.buildUrl("my-org/my-tgi-model", creds)).toBe("https://tgi.internal/my-org/my-tgi-model");
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});
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it("does not apply the router mapping when a custom endpoint is set", () => {
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const creds = { providerSpecificData: { baseUrl: "https://tgi.internal" } };
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// The custom endpoint knows its own model ids — the Hub id passes through verbatim.
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expect(imageAdapter.buildUrl("black-forest-labs/FLUX.1-schnell", creds)).toBe(
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"https://tgi.internal/black-forest-labs/FLUX.1-schnell"
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);
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});
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it("ignores a blank custom endpoint", () => {
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expect(imageAdapter.buildUrl("black-forest-labs/FLUX.1-schnell", { providerSpecificData: { baseUrl: " " } })).toBe(
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"https://router.huggingface.co/fal-ai/fal-ai/flux/schnell"
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);
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});
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it("rejects traversal or query injection in the model id on a custom endpoint", () => {
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const creds = { providerSpecificData: { baseUrl: "https://tgi.internal" } };
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for (const model of ["x/../../admin", "org//model", "model?x=1", "model#f"]) {
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expect(() => imageAdapter.buildUrl(model, creds), model).toThrow(/invalid model ID/i);
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}
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});
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});
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describe("HuggingFace registry model table", () => {
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const modelsById = Object.fromEntries(huggingface.models.map((m) => [m.id, m]));
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const imageModels = huggingface.models.filter((m) => m.kind === "image");
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const sttModels = huggingface.models.filter((m) => m.kind === "stt");
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it("every image model is present in imageConfig.modelMap", () => {
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for (const model of imageModels) {
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expect(modelMap[model.id], `model ${model.id} is missing from imageConfig.modelMap`).toBeTruthy();
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}
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});
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it("every modelMap entry points at a routable provider", () => {
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for (const [hubId, value] of Object.entries(modelMap)) {
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const provider = String(mappingPath(value)).split("/")[0];
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expect(ROUTABLE_PROVIDERS.has(provider), `${hubId} -> unsupported provider ${provider}`).toBe(true);
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}
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});
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it("every modelMap entry has a provider/model path shape", () => {
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for (const [hubId, value] of Object.entries(modelMap)) {
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expect(String(mappingPath(value)), `${hubId} has a malformed target`).toMatch(/^[a-z0-9-]+\/[A-Za-z0-9._/-]+$/);
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}
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});
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it("does not advertise whisper-small, which has no live provider", () => {
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expect(modelsById["openai/whisper-small"]).toBeUndefined();
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});
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it("advertises whisper-large-v3-turbo as its STT replacement", () => {
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expect(modelsById["openai/whisper-large-v3-turbo"]?.kind).toBe("stt");
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});
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it("exposes the FLUX family image models", () => {
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for (const id of [
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"black-forest-labs/FLUX.1-schnell",
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"black-forest-labs/FLUX.1-dev",
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"black-forest-labs/FLUX.1-Krea-dev",
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"black-forest-labs/FLUX.1-Kontext-dev",
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"black-forest-labs/FLUX.2-dev",
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"black-forest-labs/FLUX.2-klein-9B",
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"black-forest-labs/FLUX.2-klein-4B",
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"black-forest-labs/FLUX.2-klein-base-9B",
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"black-forest-labs/FLUX.2-klein-base-4B",
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]) {
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expect(modelsById[id]?.kind, `${id} should be registered as an image model`).toBe("image");
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}
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});
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it("exposes the Qwen-Image family", () => {
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for (const id of [
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"Qwen/Qwen-Image",
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"Qwen/Qwen-Image-2512",
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"Qwen/Qwen-Image-Edit",
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"Qwen/Qwen-Image-Edit-2509",
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"Qwen/Qwen-Image-Edit-2511",
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]) {
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expect(modelsById[id]?.kind, `${id} should be registered as an image model`).toBe("image");
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}
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});
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it("exposes the Stable Diffusion family", () => {
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for (const id of [
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"stabilityai/stable-diffusion-xl-base-1.0",
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"stabilityai/stable-diffusion-3.5-large",
|
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"stabilityai/stable-diffusion-3.5-large-turbo",
|
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]) {
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expect(modelsById[id]?.kind, `${id} should be registered as an image model`).toBe("image");
|
||||
}
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||||
});
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||||
|
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it("exposes the HuggingFace ASR models", () => {
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for (const id of ["openai/whisper-large-v3", "openai/whisper-large-v3-turbo"]) {
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expect(modelsById[id]?.kind, `${id} should be registered as an stt model`).toBe("stt");
|
||||
}
|
||||
});
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||||
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it("exposes the remaining third-party image models", () => {
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for (const id of [
|
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"tencent/HunyuanImage-3.0",
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"Tongyi-MAI/Z-Image-Turbo",
|
||||
"krea/Krea-2-Turbo",
|
||||
"HiDream-ai/HiDream-I1-Fast",
|
||||
"playgroundai/playground-v2.5-1024px-aesthetic",
|
||||
"ideogram-ai/ideogram-4-fp8",
|
||||
]) {
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||||
expect(modelsById[id]?.kind, `${id} should be registered as an image model`).toBe("image");
|
||||
}
|
||||
});
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||||
|
||||
it("keeps the model table free of duplicates", () => {
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||||
const ids = huggingface.models.map((m) => m.id);
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expect(new Set(ids).size).toBe(ids.length);
|
||||
});
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||||
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||||
it("keeps STT models free of image-only router mappings", () => {
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||||
for (const model of sttModels) {
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||||
expect(modelMap[model.id], `STT model ${model.id} should not be in the image model map`).toBeUndefined();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// The router is a switchboard in front of many providers; every Hub model that is
|
||||
// `pipeline_tag: image-to-image` needs a source image, and the request shape differs
|
||||
// from text-to-image: `inputs` carries the base64 source image and the prompt moves
|
||||
// under `parameters.prompt`. Verified against
|
||||
// https://huggingface.co/docs/inference-providers/tasks/image-to-image
|
||||
describe("HuggingFace image-to-image models", () => {
|
||||
const IMAGE_TO_IMAGE = [
|
||||
"black-forest-labs/FLUX.2-dev",
|
||||
"black-forest-labs/FLUX.1-Kontext-dev",
|
||||
"black-forest-labs/FLUX.2-klein-9B",
|
||||
"black-forest-labs/FLUX.2-klein-4B",
|
||||
"black-forest-labs/FLUX.2-klein-base-9B",
|
||||
"black-forest-labs/FLUX.2-klein-base-4B",
|
||||
"Qwen/Qwen-Image-Edit",
|
||||
"Qwen/Qwen-Image-Edit-2509",
|
||||
"Qwen/Qwen-Image-Edit-2511",
|
||||
];
|
||||
|
||||
it("marks every image-to-image model as such in modelMap", () => {
|
||||
for (const hubId of IMAGE_TO_IMAGE) {
|
||||
expect(mappingTask(modelMap[hubId]), `${hubId} must be declared image-to-image`).toBe("image-to-image");
|
||||
}
|
||||
});
|
||||
|
||||
it("declares text-to-image as the default for the remaining image models", () => {
|
||||
for (const [hubId, value] of Object.entries(modelMap)) {
|
||||
if (IMAGE_TO_IMAGE.includes(hubId)) continue;
|
||||
expect(mappingTask(value), `${hubId} should default to text-to-image`).toBe("text-to-image");
|
||||
}
|
||||
});
|
||||
|
||||
it("sends the source image as inputs and the prompt under parameters", async () => {
|
||||
const body = await imageAdapter.buildBody("Qwen/Qwen-Image-Edit", {
|
||||
prompt: "make it snow",
|
||||
image: "data:image/png;base64,AAAA",
|
||||
});
|
||||
|
||||
expect(body.inputs).toBe("AAAA");
|
||||
expect(body.parameters).toEqual({ prompt: "make it snow" });
|
||||
});
|
||||
|
||||
it("accepts a source image given as a bare base64 payload", async () => {
|
||||
const body = await imageAdapter.buildBody("black-forest-labs/FLUX.2-dev", {
|
||||
prompt: "winter",
|
||||
image: "AAAA",
|
||||
});
|
||||
|
||||
expect(body.inputs).toBe("AAAA");
|
||||
});
|
||||
|
||||
it("accepts a source image given as an array", async () => {
|
||||
const body = await imageAdapter.buildBody("Qwen/Qwen-Image-Edit-2509", {
|
||||
prompt: "winter",
|
||||
images: ["data:image/png;base64,BBBB"],
|
||||
});
|
||||
|
||||
expect(body.inputs).toBe("BBBB");
|
||||
});
|
||||
|
||||
it("throws a descriptive error when an image-to-image model gets no source image", async () => {
|
||||
await expect(
|
||||
imageAdapter.buildBody("black-forest-labs/FLUX.1-Kontext-dev", { prompt: "winter" })
|
||||
).rejects.toThrow(/requires a source image/i);
|
||||
});
|
||||
|
||||
it("keeps the text-to-image shape prompt-only", async () => {
|
||||
const body = await imageAdapter.buildBody("black-forest-labs/FLUX.1-schnell", {
|
||||
prompt: "a lighthouse",
|
||||
image: "data:image/png;base64,AAAA",
|
||||
});
|
||||
|
||||
expect(body).toEqual({ inputs: "a lighthouse" });
|
||||
});
|
||||
|
||||
it("still throws for a model with no router mapping", () => {
|
||||
expect(() => imageAdapter.buildUrl("some-org/unknown")).toThrow(/no HuggingFace router mapping/i);
|
||||
});
|
||||
});
|
||||
|
||||
// The dashboard's GenericExampleCard only renders the source-image field when the
|
||||
// selected model declares capabilities: ["edit"] (GenericExampleCard.js:47), and it
|
||||
// then sends the value as `image`. Without the flag the edit models are unusable
|
||||
// from the UI even though the adapter supports them.
|
||||
describe("HuggingFace edit models reach the dashboard", () => {
|
||||
const IMAGE_TO_IMAGE = ["black-forest-labs/FLUX.2-dev", "Qwen/Qwen-Image-Edit"];
|
||||
|
||||
it("declares the edit capability on image-to-image models", () => {
|
||||
const modelsById = Object.fromEntries(huggingface.models.map((m) => [m.id, m]));
|
||||
|
||||
for (const hubId of IMAGE_TO_IMAGE) {
|
||||
expect(modelsById[hubId]?.capabilities, `${hubId} must declare the edit capability`).toContain("edit");
|
||||
}
|
||||
});
|
||||
|
||||
it("keeps the capability on text-to-image models that do not take a source image", () => {
|
||||
const modelsById = Object.fromEntries(huggingface.models.map((m) => [m.id, m]));
|
||||
|
||||
expect(modelsById["black-forest-labs/FLUX.1-schnell"]?.capabilities || []).not.toContain("edit");
|
||||
});
|
||||
});
|
||||
|
||||
describe("HuggingFace registry prototype safety", () => {
|
||||
it("does not resolve inherited object keys as models", () => {
|
||||
// A plain-object map returns a truthy inherited value for these, which would
|
||||
// build a URL like `<base>/function Object() { [native code] }`.
|
||||
for (const key of ["toString", "constructor", "__proto__", "hasOwnProperty"]) {
|
||||
expect(() => imageAdapter.buildUrl(key)).toThrow(/no HuggingFace router mapping/i);
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
describe("HuggingFace STT model parameters", () => {
|
||||
const sttModels = huggingface.models.filter((m) => m.kind === "stt");
|
||||
|
||||
it("does not advertise a language parameter the ASR route cannot carry", () => {
|
||||
// transcribeHuggingFace posts raw audio bytes and never reads formData, and the
|
||||
// router's ASR payload has no `language` field — so a UI-declared "language"
|
||||
// param is silently dropped. Declaring it lies to the dashboard.
|
||||
for (const model of sttModels) {
|
||||
expect(model.params, `${model.id} advertises an unusable language param`).toEqual([]);
|
||||
}
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user