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Makefile
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.PHONY: help install setup download-data download-model train chat server test clean format lint
# 默认目标
help:
@echo "可用的命令:"
@echo " make install - 安装项目依赖"
@echo " make setup - 完整环境设置(虚拟环境 + 依赖)"
@echo " make download-data - 下载并处理训练数据"
@echo " make download-model - 下载 Qwen3-4B 模型"
@echo " make train - 开始训练模型"
@echo " make chat - 启动对话测试"
@echo " make server - 启动 API 服务器"
@echo " make test - 运行性能测试"
@echo " make clean - 清理临时文件"
@echo " make format - 格式化代码"
@echo " make lint - 代码质量检查"
# 安装依赖
install:
pip install -r requirements.txt
# 完整环境设置
setup:
@echo "创建虚拟环境..."
python3 -m venv .venv
@echo "请运行: source .venv/bin/activate"
@echo "然后运行: make install"
# 下载并处理数据
download-data:
@echo "下载自我认知数据集..."
modelscope download --dataset swift/self-cognition --local_dir ./self-cognition
@echo "转换数据格式..."
python trans_data.py
@echo "数据准备完成!"
# 下载模型
download-model:
@echo "下载 Qwen3-4B 模型..."
modelscope download --model Qwen/Qwen3-4B --local_dir ./Qwen3-4B
@echo "模型下载完成!"
# 训练模型
train:
@echo "开始训练模型..."
mlx_lm.lora --config ft_qwen3_lora.yaml
# 对话测试
chat:
@echo "启动对话测试..."
mlx_lm.chat --model Qwen3-4B --adapter-path my_qwen3_4b
# 启动 API 服务器
server:
@echo "启动 API 服务器..."
mlx_lm.server --model Qwen3-4B --adapter-path my_qwen3_4b
# 性能测试(需要先启动服务器)
test:
@echo "运行性能测试..."
evalscope perf \
--parallel 1 \
--number 10 \
--model Qwen3-4B \
--url http://127.0.0.1:8080/v1/chat/completions \
--api openai \
--dataset random \
--max-tokens 128 \
--min-tokens 128
# 清理临时文件
clean:
@echo "清理临时文件..."
find . -type d -name "__pycache__" -exec rm -rf {} +
find . -type f -name "*.pyc" -delete
find . -type f -name "*.pyo" -delete
find . -type f -name "*.log" -delete
find . -type d -name "*.egg-info" -exec rm -rf {} +
@echo "清理完成!"
# 格式化代码
format:
@echo "格式化 Python 代码..."
black . --line-length 88
@echo "格式化完成!"
# 代码质量检查
lint:
@echo "运行代码质量检查..."
flake8 . --max-line-length=88 --exclude=.venv,Qwen3-4B
@echo "检查完成!"
# 一键启动(数据 + 模型 + 训练)
all: download-data download-model train
@echo "所有步骤完成!"