Datawhale 用Markdown语法轻松开发AI应用202512 第1次作业

感谢我们组的小组长尚同学！

一开始先用vscode配置环境：

配置环境：

(base) PS E:\Datawhale\Markdown202512> node --version

v25.0.0

(base) PS E:\Datawhale\Markdown202512> npm --version

11.6.2

(base) PS E:\Datawhale\Markdown202512> git --version

bash 复制代码

python -m venv venv

bash 复制代码

(base) PS E:\Datawhale\Markdown202512\vibe-coding-app\demo> # 列出当前目录文件/文件夹
>> ls

输出：

目录: E:\Datawhale\Markdown202512\vibe-coding-app\demo

Mode LastWriteTime Length Name

d----- 2025/12/15 22:12 app

d----- 2025/12/15 22:12 frontend

d----- 2025/12/15 22:13 venv

-a---- 2025/12/15 22:12 288 .env.example

-a---- 2025/12/15 22:12 38185 AGENTS.md

-a---- 2025/12/15 22:12 198 dev.sh

-a---- 2025/12/15 22:12 786 main.py

-a---- 2025/12/15 22:12 1439 requirements.txt

bash 复制代码

# 安装依赖
pip install -r requirements.txt

输出：

Looking in indexes: https://mirrors.cernet.edu.cn/pypi/web/simple, https://pypi.org/simple/

Collecting annotated-types==0.7.0 (from -r requirements.txt (line 1))

Downloading annotated_types-0.7.0-py3-none-any.whl.metadata (15 kB)

Collecting anyio==4.9.0 (from -r requirements.txt (line 2))

Downloading anyio-4.9.0-py3-none-any.whl.metadata (4.7 kB)

Collecting black==24.1.1 (from -r requirements.txt (line 3))

Downloading black-24.1.1-cp312-cp312-win_amd64.whl.metadata (73 kB)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 73.3/73.3 kB 7.3 kB/s eta 0:00:00

Collecting certifi==2025.7.9 (from -r requirements.txt (line 4))

Downloading certifi-2025.7.9-py3-none-any.whl.metadata (2.4 kB)

Collecting cfgv==3.4.0 (from -r requirements.txt (line 5))

Downloading cfgv-3.4.0-py2.py3-none-any.whl.metadata (8.5 kB)
ERROR: Could not find a version that satisfies the requirement charset-normalizer==3.4.3 (from versions: none)
ERROR: No matching distribution found for charset-normalizer==3.4.3

单独安装charset-normalizer（自动适配Python 3.12的版本）

bash 复制代码

pip install charset-normalizer -i https://pypi.tuna.tsinghua.edu.cn/simple

1. 克隆项目

git clone https://www.gitlink.org.cn/ai-shifu/vibe-coding-app.git

cd demo

2. 修改配置文件

将.env.example 文件复制为 .env

修改 .env 文件中的内容

LLM_BASE_URL="https://xxx"

LLM_API_KEY="xxx"

LLM_MODEL="xxx"

3. 启动后端

pip install -r requirements.txt

python main.py

4. 启动前端（新终端）

cd frontend

npm install

npm run dev

输出：