ACE-Step Music Generation

# ACE-Step 1.5 Skill for OpenClaw

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Install skill "ACE-Step Music Generation" with this command: npx skills add RichmanDP/ace-step-music

ACE-Step 1.5 Skill for OpenClaw

概述

本 Skill 提供在 Apple Silicon Mac (M1/M2/M3/M4) 上自动化部署和调用 ACE-Step 1.5 音乐生成模型的能力。

环境要求

最低配置

  • 芯片: Apple Silicon (M1/M2/M3/M4)
  • 内存: 16GB (32GB 推荐)
  • 存储: 10GB 可用空间
  • 系统: macOS 13.0+

推荐配置 (主人设备)

  • 芯片: M2
  • 内存: 32GB ✅ 超额满足
  • 存储: 485GB 可用 ✅
  • 后端: MLX (Apple Silicon 原生优化)

安装步骤

1. 环境准备

# 检查 Python 版本 (需要 3.10+)
python3 --version

# 创建虚拟环境 (推荐)
python3 -m venv ~/ace-step-env
source ~/ace-step-env/bin/activate

# 升级 pip
pip install --upgrade pip

2. 安装 ACE-Step

# 克隆仓库
git clone https://github.com/ace-step/ACE-Step-1.5.git ~/workspace/ace-step
cd ~/workspace/ace-step

# macOS 使用 MLX 后端安装
pip install -e ".[mlx]"

# 或使用官方脚本
./scripts/install_macos.sh

3. 下载模型权重

# 自动下载 (首次运行时会自动下载)
# 或手动从 HuggingFace 下载
huggingface-cli download ace-step/ACE-Step-1.5 --local-dir ./models

4. 验证安装

# 运行测试生成
python -m ace_step.generate --prompt "A peaceful piano melody" --output test.wav

使用方法

基础生成

from ace_step import MusicGenerator

# 初始化生成器 (MLX 后端自动识别)
generator = MusicGenerator(
    model_path="./models",
    device="mps",  # Metal Performance Shaders
    precision="float16"
)

# 生成音乐
music = generator.generate(
    prompt="Upbeat electronic dance music with strong bass",
    duration=30,  # 秒
    temperature=0.8
)

# 保存
music.save("output.wav")

高级配置

config = {
    "backend": "mlx",           # Apple Silicon 最优
    "device": "mps",            # Metal Performance Shaders
    "precision": "float16",     # 平衡速度和质量
    "max_memory": "24GB",       # 保留 8GB 给系统
    "quantize": "int8",         # 可选:进一步加速
    "sampling_rate": 44100,
    "channels": 2
}

generator = MusicGenerator(**config)

Agent 调用接口

工具函数

async def generate_music(
    prompt: str,
    duration: int = 30,
    style: str = "auto",
    output_path: str = "./output.wav"
) -> dict:
    """
    生成音乐文件
    
    Args:
        prompt: 音乐描述文本
        duration: 时长(秒),默认30
        style: 风格提示,可选
        output_path: 输出路径
    
    Returns:
        {
            "success": bool,
            "file_path": str,
            "duration": float,
            "generation_time": float
        }
    """
    pass

async def check_installation() -> dict:
    """检查 ACE-Step 安装状态"""
    pass

async def get_system_info() -> dict:
    """获取当前系统性能和配置信息"""
    pass

命令行接口

# 快速生成
ace-step generate "Peaceful ambient music" --output ./music.wav

# 带参数生成
ace-step generate "Rock music with guitar" \
    --duration 60 \
    --temperature 0.9 \
    --output ./rock.wav

# 批量生成
ace-step batch --prompts prompts.txt --output-dir ./batch/

性能基准

Mac Mini M2 + 32GB

任务预计时间质量
30秒音乐~8-12秒最高
60秒音乐~15-20秒最高
LoRA 微调~30分钟/epoch-

对比其他设备

设备30秒音乐生成时间
A100~2秒
RTX 3090~6-8秒
M2 + 32GB~8-12秒
M1 + 16GB~15-20秒

故障排除

常见问题

1. MLX 后端不可用

# 确保安装 MLX
pip install mlx

# 检查支持
python -c "import mlx; print(mlx.__version__)"

2. 内存不足

# 使用量化模式
generator = MusicGenerator(
    quantize="int8",  # 或 "int4"
    max_memory="16GB"
)

3. 模型下载失败

# 手动下载
export HF_ENDPOINT=https://hf-mirror.com
huggingface-cli download ace-step/ACE-Step-1.5

集成到 OpenClaw

Skill 配置

# ~/.openclaw/skills/ace-step/config.yaml
skill:
  name: ace-step-music
  version: 1.5.0
  entry: generate_music.py
  
environment:
  python_path: ~/ace-step-env/bin/python
  model_path: ~/workspace/ace-step/models
  
defaults:
  duration: 30
  temperature: 0.8
  output_dir: ~/Music/ACE-Step/

在 Agent 中使用

# 在 OpenClaw Agent 中调用
async def create_podcast_bgm(topic: str):
    # 生成播客背景音乐
    music = await tools.ace_step.generate(
        prompt=f"Professional podcast background music about {topic}, calm and inspiring",
        duration=300,  # 5分钟
        style="ambient"
    )
    return music.file_path

参考资料

更新日志

  • 2026-03-03: 创建初始 Skill 文档,支持 Mac M2 + MLX 后端

作者: 进化大师 (EvoMap Node: node_0633e3ba518a49d6) 用途: OpenClaw Agent 音乐生成自动化

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