modify: add docker

Dockerfile

@@ -0,0 +1,36 @@
+# Use an official Python runtime as a parent image
+FROM python:3.12-slim
+
+# Prevents writing .pyc files and buffering stdout/stderr
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
+
+# Install system dependencies (if needed) and Python deps
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN pip install --upgrade pip
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy app code
+COPY . .
+
+# Expose Streamlit default port
+EXPOSE 8501
+
+# Streamlit config: run headless and bind to 0.0.0.0
+ENV STREAMLIT_SERVER_HEADLESS=true
+ENV STREAMLIT_SERVER_ENABLE_CORS=false
+ENV STREAMLIT_SERVER_ENABLE_XSRF_PROTECTION=false
+ENV STREAMLIT_SERVER_PORT=8501
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
+
+# Run Streamlit
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

docs/install.md

@@ -68,6 +68,25 @@ pip install streamlit-autorefresh openpyxl xlrd cryptography openai
 
 3. Open `http://localhost:8501` in your browser. The home page should load without import errors.
 
+## 5. Run with Docker (optional)
+
+If you prefer an isolated container build, use the included `Dockerfile`:
+
+```bash
+docker build -t trafficsafeanalyzer .
+docker run --rm -p 8501:8501 trafficsafeanalyzer
+```
+
+To work with local data, mount the host folder containing Excel files:
+
+```bash
+docker run --rm -p 8501:8501 \
+  -v "$(pwd)/sample:/app/sample" \
+  trafficsafeanalyzer
+```
+
+The container exposes Streamlit on port 8501 by default. Override configuration via environment variables when needed, for example `-e STREAMLIT_SERVER_PORT=8502`.
+
 ## Troubleshooting tips
 
 - **Missing package**: Re-run `pip install -r requirements.txt`.

docs/usage.md

@@ -4,7 +4,7 @@ TrafficSafeAnalyzer delivers accident analytics and decision support through a S
 
 ## Start the app
 
-1. Activate your virtual or conda environment.
+1. Activate your virtual or conda environment（或在容器中运行，见下）.
 2. From the project root, run:
 
    ```bash
@@ -13,6 +13,8 @@ TrafficSafeAnalyzer delivers accident analytics and decision support through a S
 
 3. Open `http://localhost:8501`. Keep the terminal running while you work in the browser.
 
+> 使用 Docker？运行 `docker build -t trafficsafeanalyzer .` 与 `docker run --rm -p 8501:8501 trafficsafeanalyzer` 后，同样访问 `http://localhost:8501`。
+
 ## Load input data
 
 Use the sidebar form labelled “数据与筛选”.

readme.md

@@ -19,7 +19,7 @@
 - Git
 - 可选：Docker（用于容器化部署）
 
-### 安装
+### 安装（本地环境）
 
 1. 克隆仓库：
 
@@ -63,6 +63,28 @@ streamlit run app.py
       streamlit run app.py
       ```
 
+### 使用 Docker 运行
+
+项目根目录已经包含 `Dockerfile`，无需额外配置即可容器化运行：
+
+```bash
+# 构建镜像
+docker build -t trafficsafeanalyzer .
+
+# 以临时容器方式启动
+docker run --rm -p 8501:8501 trafficsafeanalyzer
+```
+
+运行后访问 `http://localhost:8501` 即可。若需加载主机上的数据文件，可通过挂载方式注入：
+
+```bash
+docker run --rm -p 8501:8501 \
+  -v "$(pwd)/sample:/app/sample" \
+  trafficsafeanalyzer
+```
+
+容器内默认启用了示例 AI 凭据与 Streamlit Headless 模式，如需调整可在 `docker run` 时追加环境变量（例如 `-e STREAMLIT_SERVER_PORT=8502`）。
+
 ## 依赖项
 
 列于 `requirements.txt`：