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mxdeploy

License Python PyPI Platform

国产 GPU(MetaX 曦云 C500 / MXMACA 生态)一键部署 + 评测 + AI 排障 CLI。 一条命令把模型跑起来,出 benchmark 报告,报错自动诊断。

📖 新手教程docs/TUTORIAL.md — 从安装到实战,10 分钟上手。

Features

  • 一键部署:精度检查 → vLLM 配置生成 → 服务拉起 → 健康检查,全程自动化,FP8 等不支持的模型自动拦截
  • 环境体检:自动检测 mx-smi / torch(+metax) / vLLM(+maca) 适配状态,部署前先排雷
  • 性能评测:流式压测吞吐 / 首token延迟 / P95 / TPOT / 显存,输出 table / JSON / Markdown 报告
  • AI 排障:内置真实踩坑知识库(8+ 条规则),喂日志即出根因和修复方案,critical 级别自动失败退出

安装

pip install mxdeploy

要求 Python 3.10+,目标平台为 Linux(模力方舟曦云 C500 实测环境)。

快速开始

# 1. 环境体检 —— 检测 mx-smi / torch(+metax) / vLLM(+maca)
mxdeploy init

# 2. 一键部署模型
mxdeploy deploy Qwen/Qwen2.5-3B-Instruct

# 3. 性能测试,出报告
mxdeploy bench Qwen/Qwen2.5-3B-Instruct

# 4. AI 排障 —— 把报错日志喂给它
mxdeploy doctor deploy.log

命令一览

命令 功能
mxdeploy init 环境体检:mx-smi / torch / vLLM / 系统信息
mxdeploy deploy <model> 一键部署:精度检查、配置生成、服务拉起、健康检查
mxdeploy bench <model> 性能测试:吞吐 / TTFT / P95 / TPOT / 显存
mxdeploy doctor <log> AI 排障:规则引擎 + LLM 分析
mxdeploy version 版本信息

实测数据(模力方舟曦云 C500 16G vGPU,统一配置:并发8/请求50/max_tokens 256/util 0.8)

模型 精度 吞吐 (t/s) TTFT (ms) TPOT (ms) 显存 (MB) 成功率
Qwen2.5-1.5B FP16 204.75 38.15 4.77 13573 100%
DeepSeek-R1-Distill-1.5B FP16 200.55 34.54 4.93 13561 100%
Qwen2.5-3B FP16 153.65 48.21 6.40 13599 100%
Qwen2.5-7B-GPTQ-Int8 INT8 159.21 41.67 6.15 13827 100%

完整矩阵报告见 docs/BENCHMARK_MATRIX_C500_16G.md

排障知识库

全部规则来自真实部署实测,命中即给出修复方案:

规则 场景
NET-001 huggingface.co 超时 → 自动提示 HF_ENDPOINT 镜像
ENV-001 非交互 SSH 缺 MACA_PATH → vLLM import 崩溃
PIP-001 pip 覆盖官方 torch(+metax) 适配版
FP8-001 曦云 C500 不支持 FP8 → 提示换 FP16/INT8
OOM-001 显存不足 → 给出量化/换卡建议
MEM-002 util 0.9 + torch.compile autotune OOM → 降 0.8
... 更多规则见 mxdeploy doctor --list

兼容性

  • 平台:Linux(模力方舟曦云 C500 实例实测)
  • Python:3.10+
  • 依赖:沐曦适配版 torch(+metax)、vllm(+maca)——切勿用 pip 覆盖官方适配版
  • 注意:非交互 SSH 环境需显式 export MACA_PATH=/opt/maca

开发

git clone https://github.com/leo1852098393-blip/mxdeploy
cd mxdeploy
pip install -e ".[dev]"
pytest        # 40 tests

License

Apache-2.0

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