import assert from "node:assert/strict";
import fs from "node:fs/promises";
import os from "node:os";
import path from "node:path";
import test from "node:test";

import {
  createTaskArgs,
  detectProvider,
  getConfiguredMaxWorkers,
  getConfiguredProviderRateLimits,
  getWorkerCount,
  isRetryableGenerationError,
  loadBatchTasks,
  mergeConfig,
  normalizeOutputImagePath,
  parseArgs,
  parseSimpleYaml,
} from "../../../skills/baoyu-image-gen/scripts/main.ts";

function makeArgs(overrides = {}) {
  return {
    prompt: null,
    promptFiles: [],
    imagePath: null,
    provider: null,
    model: null,
    aspectRatio: null,
    size: null,
    quality: null,
    imageSize: null,
    referenceImages: [],
    n: 1,
    batchFile: null,
    jobs: null,
    json: false,
    help: false,
    ...overrides,
  };
}

function useEnv(t, values) {
  const previous = new Map();
  for (const [key, value] of Object.entries(values)) {
    previous.set(key, process.env[key]);
    if (value == null) {
      delete process.env[key];
    } else {
      process.env[key] = value;
    }
  }

  t.after(() => {
    for (const [key, value] of previous.entries()) {
      if (value == null) {
        delete process.env[key];
      } else {
        process.env[key] = value;
      }
    }
  });
}

async function makeTempDir(prefix) {
  return fs.mkdtemp(path.join(os.tmpdir(), prefix));
}

test("parseArgs parses the main image-gen CLI flags", () => {
  const args = parseArgs([
    "--promptfiles",
    "prompts/system.md",
    "prompts/content.md",
    "--image",
    "out/hero",
    "--provider",
    "openai",
    "--quality",
    "2k",
    "--imageSize",
    "4k",
    "--ref",
    "ref/one.png",
    "ref/two.jpg",
    "--n",
    "3",
    "--jobs",
    "5",
    "--json",
  ]);

  assert.deepEqual(args.promptFiles, ["prompts/system.md", "prompts/content.md"]);
  assert.equal(args.imagePath, "out/hero");
  assert.equal(args.provider, "openai");
  assert.equal(args.quality, "2k");
  assert.equal(args.imageSize, "4K");
  assert.deepEqual(args.referenceImages, ["ref/one.png", "ref/two.jpg"]);
  assert.equal(args.n, 3);
  assert.equal(args.jobs, 5);
  assert.equal(args.json, true);
});

test("parseArgs falls back to positional prompt and rejects invalid provider", () => {
  const positional = parseArgs(["draw", "a", "cat"]);
  assert.equal(positional.prompt, "draw a cat");

  assert.throws(
    () => parseArgs(["--provider", "stability"]),
    /Invalid provider/,
  );
});

test("parseSimpleYaml parses nested defaults and provider limits", () => {
  const yaml = `
version: 2
default_provider: openrouter
default_quality: normal
default_aspect_ratio: '16:9'
default_image_size: 2K
default_model:
  google: gemini-3-pro-image-preview
  openai: gpt-image-1.5
batch:
  max_workers: 8
  provider_limits:
    google:
      concurrency: 2
      start_interval_ms: 900
    openai:
      concurrency: 4
`;

  const config = parseSimpleYaml(yaml);

  assert.equal(config.version, 2);
  assert.equal(config.default_provider, "openrouter");
  assert.equal(config.default_quality, "normal");
  assert.equal(config.default_aspect_ratio, "16:9");
  assert.equal(config.default_image_size, "2K");
  assert.equal(config.default_model?.google, "gemini-3-pro-image-preview");
  assert.equal(config.default_model?.openai, "gpt-image-1.5");
  assert.equal(config.batch?.max_workers, 8);
  assert.deepEqual(config.batch?.provider_limits?.google, {
    concurrency: 2,
    start_interval_ms: 900,
  });
  assert.deepEqual(config.batch?.provider_limits?.openai, {
    concurrency: 4,
  });
});

test("mergeConfig only fills values missing from CLI args", () => {
  const merged = mergeConfig(
    makeArgs({
      provider: "openai",
      quality: null,
      aspectRatio: null,
      imageSize: "4K",
    }),
    {
      default_provider: "google",
      default_quality: "2k",
      default_aspect_ratio: "3:2",
      default_image_size: "2K",
    },
  );

  assert.equal(merged.provider, "openai");
  assert.equal(merged.quality, "2k");
  assert.equal(merged.aspectRatio, "3:2");
  assert.equal(merged.imageSize, "4K");
});

test("detectProvider rejects non-ref-capable providers and prefers Google first when multiple keys exist", (t) => {
  assert.throws(
    () =>
      detectProvider(
        makeArgs({
          provider: "dashscope",
          referenceImages: ["ref.png"],
        }),
      ),
    /Reference images require a ref-capable provider/,
  );

  useEnv(t, {
    GOOGLE_API_KEY: "google-key",
    OPENAI_API_KEY: "openai-key",
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
    ARK_API_KEY: null,
  });
  assert.equal(detectProvider(makeArgs()), "google");
});

test("detectProvider selects an available ref-capable provider for reference-image tasks", (t) => {
  useEnv(t, {
    GOOGLE_API_KEY: null,
    OPENAI_API_KEY: "openai-key",
    OPENROUTER_API_KEY: null,
    DASHSCOPE_API_KEY: null,
    REPLICATE_API_TOKEN: null,
    JIMENG_ACCESS_KEY_ID: null,
    JIMENG_SECRET_ACCESS_KEY: null,
    ARK_API_KEY: null,
  });
  assert.equal(
    detectProvider(makeArgs({ referenceImages: ["ref.png"] })),
    "openai",
  );
});

test("batch worker and provider-rate-limit configuration prefer env over EXTEND config", (t) => {
  useEnv(t, {
    BAOYU_IMAGE_GEN_MAX_WORKERS: "12",
    BAOYU_IMAGE_GEN_GOOGLE_CONCURRENCY: "5",
    BAOYU_IMAGE_GEN_GOOGLE_START_INTERVAL_MS: "450",
  });

  const extendConfig = {
    batch: {
      max_workers: 7,
      provider_limits: {
        google: {
          concurrency: 2,
          start_interval_ms: 900,
        },
      },
    },
  };

  assert.equal(getConfiguredMaxWorkers(extendConfig), 12);
  assert.deepEqual(getConfiguredProviderRateLimits(extendConfig).google, {
    concurrency: 5,
    startIntervalMs: 450,
  });
});

test("loadBatchTasks and createTaskArgs resolve batch-relative paths", async (t) => {
  const root = await makeTempDir("baoyu-image-gen-batch-");
  t.after(() => fs.rm(root, { recursive: true, force: true }));

  const batchFile = path.join(root, "jobs", "batch.json");
  await fs.mkdir(path.dirname(batchFile), { recursive: true });
  await fs.writeFile(
    batchFile,
    JSON.stringify({
      jobs: 2,
      tasks: [
        {
          id: "hero",
          promptFiles: ["prompts/hero.md"],
          image: "out/hero",
          ref: ["refs/hero.png"],
          ar: "16:9",
        },
      ],
    }),
  );

  const loaded = await loadBatchTasks(batchFile);
  assert.equal(loaded.jobs, 2);
  assert.equal(loaded.batchDir, path.dirname(batchFile));
  assert.equal(loaded.tasks[0].id, "hero");

  const taskArgs = createTaskArgs(
    makeArgs({
      provider: "replicate",
      quality: "2k",
      json: true,
    }),
    loaded.tasks[0],
    loaded.batchDir,
  );

  assert.deepEqual(taskArgs.promptFiles, [
    path.join(loaded.batchDir, "prompts/hero.md"),
  ]);
  assert.equal(taskArgs.imagePath, path.join(loaded.batchDir, "out/hero"));
  assert.deepEqual(taskArgs.referenceImages, [
    path.join(loaded.batchDir, "refs/hero.png"),
  ]);
  assert.equal(taskArgs.provider, "replicate");
  assert.equal(taskArgs.aspectRatio, "16:9");
  assert.equal(taskArgs.quality, "2k");
  assert.equal(taskArgs.json, true);
});

test("path normalization, worker count, and retry classification follow expected rules", () => {
  assert.match(normalizeOutputImagePath("out/sample"), /out[\\/]+sample\.png$/);
  assert.match(normalizeOutputImagePath("out/sample.webp"), /out[\\/]+sample\.webp$/);

  assert.equal(getWorkerCount(8, null, 3), 3);
  assert.equal(getWorkerCount(2, 6, 5), 2);
  assert.equal(getWorkerCount(5, 0, 4), 1);

  assert.equal(isRetryableGenerationError(new Error("API error (401): denied")), false);
  assert.equal(isRetryableGenerationError(new Error("socket hang up")), true);
});