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https://github.com/decolua/9router.git
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feat: add OpenCode Go provider and support for custom models
- Introduced OpenCode Go provider with relevant configurations. - Enhanced model management by allowing users to add and delete custom models. - Updated UI components to support model selection for image types. - Adjusted sidebar visibility to include image media kinds.
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decolua
320
tests/unit/image-generation.test.js
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320
tests/unit/image-generation.test.js
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/**
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* Unit tests for image generation handler
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*
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* Covers:
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* - OpenAI-compatible format (openai, minimax, openrouter)
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* - Gemini format (generateContent API)
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* - Provider-specific formats (nanobanana, sdwebui)
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* - Response normalization to OpenAI format
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* - Error handling (missing prompt, invalid model)
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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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describe("handleImageGenerationCore", () => {
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beforeEach(() => {
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global.fetch = vi.fn();
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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("validates required prompt field", async () => {
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const result = await handleImageGenerationCore({
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body: { model: "openai/dall-e-3" },
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modelInfo: { provider: "openai", model: "dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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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).toContain("Missing required field: prompt");
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});
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it("rejects unsupported provider", async () => {
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const result = await handleImageGenerationCore({
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body: { prompt: "test" },
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modelInfo: { provider: "unknown-provider", model: "test" },
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credentials: null,
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log: null,
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});
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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).toContain("does not support image generation");
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});
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it("generates image with OpenAI format", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({
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created: 1234567890,
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data: [{ url: "https://example.com/image.png" }],
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}),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A cute cat", n: 1, size: "1024x1024" },
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modelInfo: { provider: "openai", model: "dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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expect(global.fetch).toHaveBeenCalledWith(
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"https://api.openai.com/v1/images/generations",
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expect.objectContaining({
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method: "POST",
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headers: expect.objectContaining({
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"Content-Type": "application/json",
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Authorization: "Bearer test-key",
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}),
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body: expect.stringContaining('"prompt":"A cute cat"'),
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})
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);
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const responseBody = await result.response.json();
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expect(responseBody.data).toHaveLength(1);
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expect(responseBody.data[0].url).toBe("https://example.com/image.png");
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});
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it("generates image with Gemini format", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({
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candidates: [
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{
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content: {
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parts: [
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{ text: "Generated image" },
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{ inlineData: { data: "base64imagedata" } },
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],
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},
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},
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],
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}),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A sunset" },
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modelInfo: { provider: "gemini", model: "gemini-image-preview" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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expect(global.fetch).toHaveBeenCalledWith(
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expect.stringContaining("generativelanguage.googleapis.com"),
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expect.objectContaining({
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method: "POST",
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body: expect.stringContaining('"responseModalities":["TEXT","IMAGE"]'),
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})
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);
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const responseBody = await result.response.json();
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expect(responseBody.data).toHaveLength(1);
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expect(responseBody.data[0].b64_json).toBe("base64imagedata");
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});
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it("generates image with Minimax format", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({
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created: 1234567890,
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data: [{ url: "https://example.com/minimax.png" }],
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}),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A mountain", size: "1024x1024" },
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modelInfo: { provider: "minimax", model: "minimax-image-01" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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expect(global.fetch).toHaveBeenCalledWith(
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"https://api.minimaxi.com/v1/images/generations",
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expect.objectContaining({
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method: "POST",
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headers: expect.objectContaining({
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Authorization: "Bearer test-key",
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}),
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})
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);
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});
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it("generates image with NanoBanana format", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({ image: "base64nanobanana" }),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A robot", n: 2, size: "1024x1792" },
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modelInfo: { provider: "nanobanana", model: "nanobanana-flash" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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const fetchCall = global.fetch.mock.calls[0];
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const requestBody = JSON.parse(fetchCall[1].body);
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expect(requestBody.type).toBe("TEXTTOIAMGE");
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expect(requestBody.numImages).toBe(2);
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expect(requestBody.image_size).toBe("9:16");
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const responseBody = await result.response.json();
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expect(responseBody.data[0].b64_json).toBe("base64nanobanana");
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});
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it("generates image with SD WebUI format", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({ images: ["base64sdwebui1", "base64sdwebui2"] }),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A forest", size: "768x768", n: 2 },
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modelInfo: { provider: "sdwebui", model: "sdxl-base-1.0" },
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credentials: null,
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log: null,
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});
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expect(result.success).toBe(true);
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const fetchCall = global.fetch.mock.calls[0];
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const requestBody = JSON.parse(fetchCall[1].body);
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expect(requestBody.width).toBe(768);
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expect(requestBody.height).toBe(768);
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expect(requestBody.batch_size).toBe(2);
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const responseBody = await result.response.json();
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expect(responseBody.data).toHaveLength(2);
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});
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it("handles OpenRouter with HTTP-Referer header", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({
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created: 1234567890,
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data: [{ url: "https://example.com/or.png" }],
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}),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A city" },
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modelInfo: { provider: "openrouter", model: "openai/dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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expect(global.fetch).toHaveBeenCalledWith(
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"https://openrouter.ai/api/v1/images/generations",
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expect.objectContaining({
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headers: expect.objectContaining({
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"HTTP-Referer": "https://endpoint-proxy.local",
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"X-Title": "Endpoint Proxy",
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}),
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})
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);
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});
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it("handles HuggingFace binary response", async () => {
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const imageBuffer = new Uint8Array([0x89, 0x50, 0x4e, 0x47]); // PNG header
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global.fetch.mockResolvedValueOnce(
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new Response(imageBuffer, {
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status: 200,
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headers: { "Content-Type": "image/png" },
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})
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "A tree" },
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modelInfo: { provider: "huggingface", model: "black-forest-labs/FLUX.1-schnell" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(true);
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const responseBody = await result.response.json();
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expect(responseBody.data[0].b64_json).toBeTruthy();
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});
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it("handles provider error responses", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({ error: { message: "Rate limit exceeded" } }),
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{ status: 429, headers: { "Content-Type": "application/json" } }
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)
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);
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const result = await handleImageGenerationCore({
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body: { prompt: "test" },
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modelInfo: { provider: "openai", model: "dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(false);
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expect(result.status).toBe(429);
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expect(result.error).toContain("Rate limit exceeded");
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});
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it("handles network errors", async () => {
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global.fetch.mockRejectedValueOnce(new Error("Network timeout"));
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const result = await handleImageGenerationCore({
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body: { prompt: "test" },
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modelInfo: { provider: "openai", model: "dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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});
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expect(result.success).toBe(false);
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expect(result.status).toBe(502);
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expect(result.error).toContain("Network timeout");
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});
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it("calls onRequestSuccess callback on success", async () => {
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global.fetch.mockResolvedValueOnce(
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new Response(
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JSON.stringify({
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created: 1234567890,
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data: [{ url: "https://example.com/success.png" }],
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}),
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{ status: 200, headers: { "Content-Type": "application/json" } }
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)
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);
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const onRequestSuccess = vi.fn();
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const result = await handleImageGenerationCore({
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body: { prompt: "test" },
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modelInfo: { provider: "openai", model: "dall-e-3" },
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credentials: { apiKey: "test-key" },
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log: null,
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onRequestSuccess,
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});
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expect(result.success).toBe(true);
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expect(onRequestSuccess).toHaveBeenCalledTimes(1);
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});
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});
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