export function queueSteps(chunkMs, computeMs, count = 8) {
  if (
    !Number.isFinite(chunkMs) ||
    !Number.isFinite(computeMs) ||
    chunkMs <= 0 ||
    computeMs <= 0
  ) {
    throw new RangeError("Time values must be finite and positive.");
  }
  let previousEnd = 0;
  return Array.from({ length: count }, (_, index) => {
    const arrival = (index + 1) * chunkMs;
    const start = Math.max(arrival, previousEnd);
    const end = start + computeMs;
    previousEnd = end;
    return { index: index + 1, arrival, start, end, wait: start - arrival };
  });
}

export const architectures = {
  cascade: {
    nodes: [
      ["用户语音", "声音输入", "input"],
      ["ASR", "识别成文本"],
      ["文本 LLM", "生成回答"],
      ["TTS", "合成声音"],
      ["系统语音", "播放输出", "output"],
    ],
    detail:
      "<p><strong>两个独立的文本接口。</strong>ASR 把用户语音交给文本模型，TTS 再把回答读出。模块可以独立替换。仅传文字时，输入声学信息会在接口处被压缩。</p><p>持续双工需要在这些模块之间保持新输入、话轮状态、取消与播放进度的一致。</p>",
  },
  two: {
    nodes: [
      ["用户语音", "声音输入", "input"],
      ["语音理解 LLM", "直接读取音频特征"],
      ["回答文本", "内容接口"],
      ["TTS", "合成声音"],
      ["系统语音", "播放输出", "output"],
    ],
    detail:
      "<p><strong>输入端直接理解声音。</strong>模型接收音频特征并生成回答文字，之后由独立 TTS 合成。输入端可以保留语气等线索，输出端仍通过文本接口组织。</p><p>本页以 Ultravox 核心加外接 TTS 作为这一工作定义的例子。</p>",
  },
  native: {
    nodes: [
      ["用户语音", "声音输入", "input"],
      ["语音表示", "编码或特征"],
      ["联合交互模型", "声音与内容建模"],
      ["语音解码", "还原波形"],
      ["系统语音", "播放输出", "output"],
    ],
    detail:
      "<p><strong>语音直接参与内容与声学生成。</strong>编码器、音频 token、文字辅助流和波形解码器可以共同存在，具体组织依模型而异。</p><p>持续听说依赖输入更新方式、因果训练与实时服务。原生语音接口与全双工行为分别核验。</p>",
  },
};

export const benchmarks = [
  { name: "级联管线", first: 8.78, answer: 10.12 },
  { name: "Ultravox 0.7", first: 3.88, answer: 8.4 },
  { name: "GPT-Realtime 1.5", first: 6.36, answer: 6.89 },
  { name: "Gemini Live 3.1", first: 3.95, answer: 4.25 },
];