import { mkdir, mkdtemp, readFile, rm, writeFile } from 'node:fs/promises';
import { tmpdir } from 'node:os';
import path from 'node:path';
import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';

import { generateMedia } from '../src/media.js';

const PNG_BASE64 = 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mP8/x8AAwMCAO+X2uoAAAAASUVORK5CYII=';
const VIDEO_BASE64 = Buffer.from([0, 0, 0, 24, 102, 116, 121, 112]).toString('base64');

describe('OpenAI-compatible media providers', () => {
  let root: string;
  let projectRoot: string;
  let projectsRoot: string;
  const realFetch = globalThis.fetch;
  const originalImageRouterKey = process.env.OD_IMAGEROUTER_API_KEY;
  const originalCustomImageKey = process.env.OD_CUSTOM_IMAGE_API_KEY;
  const originalMediaConfigDir = process.env.OD_MEDIA_CONFIG_DIR;
  const originalDataDir = process.env.OD_DATA_DIR;

  beforeEach(async () => {
    root = await mkdtemp(path.join(tmpdir(), 'od-openai-compatible-media-'));
    projectRoot = path.join(root, 'project-root');
    projectsRoot = path.join(projectRoot, '.od', 'projects');
    await mkdir(projectsRoot, { recursive: true });
    delete process.env.OD_IMAGEROUTER_API_KEY;
    delete process.env.OD_CUSTOM_IMAGE_API_KEY;
    delete process.env.OD_MEDIA_CONFIG_DIR;
    delete process.env.OD_DATA_DIR;
  });

  afterEach(async () => {
    globalThis.fetch = realFetch;
    vi.unstubAllGlobals();
    if (originalImageRouterKey == null) {
      delete process.env.OD_IMAGEROUTER_API_KEY;
    } else {
      process.env.OD_IMAGEROUTER_API_KEY = originalImageRouterKey;
    }
    if (originalCustomImageKey == null) {
      delete process.env.OD_CUSTOM_IMAGE_API_KEY;
    } else {
      process.env.OD_CUSTOM_IMAGE_API_KEY = originalCustomImageKey;
    }
    if (originalMediaConfigDir == null) {
      delete process.env.OD_MEDIA_CONFIG_DIR;
    } else {
      process.env.OD_MEDIA_CONFIG_DIR = originalMediaConfigDir;
    }
    if (originalDataDir == null) {
      delete process.env.OD_DATA_DIR;
    } else {
      process.env.OD_DATA_DIR = originalDataDir;
    }
    await rm(root, { recursive: true, force: true });
  });

  async function writeConfig(data: unknown) {
    const file = path.join(projectRoot, '.od', 'media-config.json');
    await mkdir(path.dirname(file), { recursive: true });
    await writeFile(file, JSON.stringify(data), 'utf8');
  }

  it('renders custom /v1/images/generations providers with configured base URL and model', async () => {
    await writeConfig({
      providers: {
        'custom-image': {
          baseUrl: 'https://images.example.test/v1',
          model: 'acme-image-model',
        },
      },
    });

    const fetchMock = vi.fn(async (input: unknown, init?: RequestInit) => {
      expect(String(input)).toBe('https://images.example.test/v1/images/generations');
      expect(init?.method).toBe('POST');
      expect(init?.headers).toMatchObject({
        'content-type': 'application/json',
      });
      expect(init?.headers).not.toHaveProperty('authorization');
      expect(JSON.parse(String(init?.body))).toEqual({
        prompt: 'A product render on white seamless paper',
        model: 'acme-image-model',
        n: 1,
        size: '1024x1024',
      });
      return new Response(JSON.stringify({
        data: [{ b64_json: PNG_BASE64 }],
      }), {
        status: 200,
        headers: { 'content-type': 'application/json' },
      });
    });
    vi.stubGlobal('fetch', fetchMock);

    const result = await generateMedia({
      projectRoot,
      projectsRoot,
      projectId: 'project-1',
      surface: 'image',
      model: 'custom-image',
      prompt: 'A product render on white seamless paper',
      output: 'custom.png',
    });

    expect(result.providerId).toBe('custom-image');
    expect(result.providerNote).toContain('custom-image/acme-image-model');
    expect(fetchMock).toHaveBeenCalledTimes(1);
    const bytes = await readFile(path.join(projectsRoot, 'project-1', 'custom.png'));
    expect(bytes.length).toBeGreaterThan(0);
  });

  it('routes matching OpenAI image catalog ids through the configured custom provider', async () => {
    await writeConfig({
      providers: {
        'custom-image': {
          apiKey: 'proxy-test-key',
          baseUrl: 'https://proxy.example.test/v1/images/generations',
          model: 'gpt-image-2',
        },
      },
    });

    const fetchMock = vi.fn(async (input: unknown, init?: RequestInit) => {
      expect(String(input)).toBe('https://proxy.example.test/v1/images/generations');
      expect(init?.method).toBe('POST');
      expect(init?.headers).toMatchObject({
        authorization: 'Bearer proxy-test-key',
        'content-type': 'application/json',
      });
      expect(JSON.parse(String(init?.body))).toEqual({
        prompt: 'A clean app icon with glass material',
        model: 'gpt-image-2',
        n: 1,
        size: '1024x1024',
      });
      return new Response(JSON.stringify({
        data: [{ b64_json: PNG_BASE64 }],
      }), {
        status: 200,
        headers: { 'content-type': 'application/json' },
      });
    });
    vi.stubGlobal('fetch', fetchMock);

    const result = await generateMedia({
      projectRoot,
      projectsRoot,
      projectId: 'project-1',
      surface: 'image',
      model: 'gpt-image-2',
      prompt: 'A clean app icon with glass material',
      output: 'proxy.png',
    });

    expect(result.providerId).toBe('custom-image');
    expect(result.providerNote).toContain('custom-image/gpt-image-2');
    expect(fetchMock).toHaveBeenCalledTimes(1);
  });

  it('renders ImageRouter images through the OpenAI-compatible JSON endpoint', async () => {
    process.env.OD_IMAGEROUTER_API_KEY = 'ir-test-key';

    const fetchMock = vi.fn(async (input: unknown, init?: RequestInit) => {
      expect(String(input)).toBe('https://api.imagerouter.io/v1/openai/images/generations');
      expect(init?.method).toBe('POST');
      expect(init?.headers).toMatchObject({
        authorization: 'Bearer ir-test-key',
        'content-type': 'application/json',
      });
      expect(JSON.parse(String(init?.body))).toEqual({
        prompt: 'A cinematic vertical poster',
        model: 'openai/gpt-image-2',
        quality: 'auto',
        size: '576x1024',
        response_format: 'b64_json',
        output_format: 'png',
      });
      return new Response(JSON.stringify({
        data: [{ b64_json: PNG_BASE64 }],
      }), {
        status: 200,
        headers: { 'content-type': 'application/json' },
      });
    });
    vi.stubGlobal('fetch', fetchMock);

    const result = await generateMedia({
      projectRoot,
      projectsRoot,
      projectId: 'project-1',
      surface: 'image',
      model: 'openai/gpt-image-2',
      prompt: 'A cinematic vertical poster',
      aspect: '9:16',
      output: 'imagerouter.png',
    });

    expect(result.providerId).toBe('imagerouter');
    expect(result.providerNote).toContain('imagerouter/openai/gpt-image-2');
  });

  it('renders ImageRouter videos through the OpenAI-compatible JSON endpoint', async () => {
    process.env.OD_IMAGEROUTER_API_KEY = 'ir-test-key';

    const fetchMock = vi.fn(async (input: unknown, init?: RequestInit) => {
      expect(String(input)).toBe('https://api.imagerouter.io/v1/openai/videos/generations');
      expect(init?.method).toBe('POST');
      expect(init?.headers).toMatchObject({
        authorization: 'Bearer ir-test-key',
        'content-type': 'application/json',
      });
      expect(JSON.parse(String(init?.body))).toEqual({
        prompt: 'A short cinematic camera push through a neon market',
        model: 'xAI/grok-imagine-video',
        size: '1024x576',
        seconds: 8,
        response_format: 'b64_json',
      });
      return new Response(JSON.stringify({
        data: [{ b64_json: VIDEO_BASE64 }],
      }), {
        status: 200,
        headers: { 'content-type': 'application/json' },
      });
    });
    vi.stubGlobal('fetch', fetchMock);

    const result = await generateMedia({
      projectRoot,
      projectsRoot,
      projectId: 'project-1',
      surface: 'video',
      model: 'xAI/grok-imagine-video',
      prompt: 'A short cinematic camera push through a neon market',
      aspect: '16:9',
      length: 8,
      output: 'imagerouter.mp4',
    });

    expect(result.providerId).toBe('imagerouter');
    expect(result.name).toBe('imagerouter.mp4');
    expect(result.providerNote).toContain('imagerouter/xAI/grok-imagine-video');
    const bytes = await readFile(path.join(projectsRoot, 'project-1', 'imagerouter.mp4'));
    expect(bytes.length).toBeGreaterThan(0);
  });
});