import { describe, expect, it, vi } from "vitest";
import {
  createDefaultProviderRegistry,
  MockImageProviderAdapter,
  normalizeImageAssets,
  normalizeProviderError,
  OpenAICompatibleImageProviderAdapter,
  SiliconFlowImageProviderAdapter
} from "../index";

describe("provider adapter registry", () => {
  it("creates implemented and reserved adapters", () => {
    const registry = createDefaultProviderRegistry();

    expect(registry.mock.provider).toBe("mock");
    expect(registry["openai-compatible"].provider).toBe("openai-compatible");
    expect(registry.siliconflow.provider).toBe("siliconflow");
    expect(registry.dashscope.provider).toBe("dashscope");
    expect(registry.volcengine.provider).toBe("volcengine");
    expect(registry.zhipu.provider).toBe("zhipu");
    expect(registry["custom-template"].provider).toBe("custom-template");
  });
});

describe("mock provider", () => {
  it("returns deterministic URL assets with mapped dimensions", async () => {
    const adapter = new MockImageProviderAdapter();
    const result = await adapter.generateTextToImage(
      {
        model: "mock-wallpaper",
        prompt: "misty mountain wallpaper",
        size: { aspectRatio: "16:9", resolution: "2k" },
        seed: 42
      },
      {}
    );

    expect(result.assets[0]).toMatchObject({
      kind: "url",
      width: 2560,
      height: 1440,
      seed: 42
    });
    expect(result.usage?.imageCount).toBe(1);
  });

  it("can return base64 assets for local tests", async () => {
    const adapter = new MockImageProviderAdapter();
    const result = await adapter.generateTextToImage(
      {
        model: "mock-wallpaper",
        prompt: "phone wallpaper",
        responseFormat: "base64",
        size: { aspectRatio: "9:16", resolution: "1k" }
      },
      {}
    );

    expect(result.assets[0]?.kind).toBe("base64");
    expect(result.assets[0]?.mimeType).toBe("image/png");
    expect(result.assets[0]?.width).toBe(720);
    expect(result.assets[0]?.height).toBe(1280);
  });
});

describe("OpenAI compatible provider", () => {
  it("posts to configurable image endpoint and normalizes base64 response", async () => {
    const fetch = vi.fn(async (_url: URL | RequestInfo, init?: RequestInit) => {
      expect(_url).toBe("https://new-api.example.com/v1/images/generations");
      expect(JSON.parse(String(init?.body))).toMatchObject({
        model: "gpt-image-1",
        prompt: "desktop wallpaper",
        n: 1,
        size: "1536x1024",
        response_format: "b64_json"
      });
      return jsonResponse({
        data: [{ b64_json: "data:image/png;base64,abc123" }],
        usage: { input_tokens: 12, output_tokens: 0 }
      });
    });
    const adapter = new OpenAICompatibleImageProviderAdapter();

    const result = await adapter.generateTextToImage(
      {
        baseUrl: "https://new-api.example.com",
        model: "gpt-image-1",
        prompt: "desktop wallpaper",
        responseFormat: "base64",
        size: { aspectRatio: "16:9", resolution: "4k" }
      },
      { auth: { apiKey: "test-key" }, fetch }
    );

    expect(result.assets[0]).toMatchObject({
      kind: "base64",
      value: "abc123",
      mimeType: "image/png",
      width: 1536,
      height: 1024
    });
    expect(result.usage?.inputTokens).toBe(12);
  });
});

describe("SiliconFlow provider", () => {
  it("uses image_size and normalizes URL response", async () => {
    const fetch = vi.fn(async (_url: URL | RequestInfo, init?: RequestInit) => {
      expect(_url).toBe("https://api.siliconflow.cn/v1/images/generations");
      expect(JSON.parse(String(init?.body))).toMatchObject({
        model: "black-forest-labs/FLUX.2-pro",
        prompt: "portrait wallpaper",
        image_size: "720x1280",
        batch_size: 1,
        seed: 7
      });
      return jsonResponse({ data: [{ url: "https://cdn.example.com/result.png" }] });
    });
    const adapter = new SiliconFlowImageProviderAdapter();

    const result = await adapter.generateTextToImage(
      {
        model: "black-forest-labs/FLUX.2-pro",
        prompt: "portrait wallpaper",
        size: { aspectRatio: "9:16", resolution: "1k" },
        seed: 7
      },
      { auth: { apiKey: "sf-key" }, fetch }
    );

    expect(result.assets[0]).toMatchObject({
      kind: "url",
      value: "https://cdn.example.com/result.png",
      width: 720,
      height: 1280
    });
  });
});

describe("normalization helpers", () => {
  it("normalizes common provider errors", () => {
    expect(normalizeProviderError("siliconflow", { status: 429, message: "rate limit exceeded" })).toMatchObject({
      category: "rate_limit",
      retryable: true,
      statusCode: 429
    });

    expect(normalizeProviderError("openai-compatible", { status: 401, message: "invalid api key" })).toMatchObject({
      category: "authentication",
      retryable: false
    });

    expect(normalizeProviderError("openai-compatible", { status: 504, message: "gateway timeout" })).toMatchObject({
      category: "timeout",
      retryable: true
    });
  });

  it("normalizes URL and base64 image payloads", () => {
    expect(normalizeImageAssets({ data: [{ url: "https://example.com/a.png" }] })[0]).toMatchObject({
      kind: "url",
      value: "https://example.com/a.png"
    });

    expect(normalizeImageAssets({ images: [{ image_base64: "data:image/jpeg;base64,zzz" }] })[0]).toMatchObject({
      kind: "base64",
      value: "zzz",
      mimeType: "image/jpeg"
    });
  });
});

function jsonResponse(body: unknown, status = 200): Response {
  return new Response(JSON.stringify(body), {
    status,
    headers: { "content-type": "application/json" }
  });
}