add docker support for whole project
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23
.dockerignore
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23
.dockerignore
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# 忽略 Git 相关的文件夹
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.git
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.gitignore
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# 忽略 Python 的缓存文件
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__pycache__/
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*.pyc
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*.pyo
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# 忽略虚拟环境目录
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venv/
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env/
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# 忽略 node_modules 文件夹(前端项目)
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web/node_modules/
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# 忽略日志和临时文件
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*.log
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*.tmp
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# 忽略 Docker 本身的文件
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Dockerfile
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docker-compose.yml
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17
Dockerfile
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Dockerfile
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# 使用基础镜像
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FROM pytorch/pytorch:2.4.1-cuda11.8-cudnn9-runtime
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# 设置工作目录
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WORKDIR /app
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# 复制 requirements.txt 文件(这一步如果文件没变,Docker 会使用缓存)
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COPY requirements.txt /app/requirements.txt
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# 安装依赖(Docker 会缓存这一步,除非 requirements.txt 发生变化)
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RUN pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
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# 复制代码到容器中
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COPY ./src /app/src
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# 运行应用
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CMD ["python", "-m", "src.api"]
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35
README.md
35
README.md
@ -19,9 +19,9 @@ PyYAML==6.0.1
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zhipuai
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```
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### 【可选】配置图数据库 neo4j
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### 配置图数据库 neo4j (可选)
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使用 docker 部署 neo4j 服务,配置文件见 [local_neo4j/docker-compose.yml](local_neo4j/docker-compose.yml).
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使用 docker 部署 neo4j 服务,配置文件见 [local_neo4j/docker-compose.yml](local_neo4j/docker-compose.yml).
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默认账号密码见最后一行,可以使用 `http://localhost:7474/` 在浏览器可视化访问。
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```bash
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@ -36,17 +36,44 @@ docker compose up -d
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## 启动
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### 1. 手动启动
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```bash
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python -m src.api
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python -m src.api
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cd web
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npm install
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npm run server
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```
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或者
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### 2. 脚本启动
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```bash
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bash run.sh
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```
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### 3. Docker 启动
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**提醒**:此部分暂时依赖于前端打包之后的内容(后面考虑更新),同时会自动启动 neo4j 图数据库。
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```bash
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docker compose up --build
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```
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如果需要使用到本地模型,比如向量模型或者重排序模型,则需要将环境变量中设置的 `MODEL_ROOT_DIR` 做映射,比如本地模型都是存放在 `/hdd/models` 里面,则需要在 `docker-compose.yml` 中添加:
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```yml
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services:
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# 后端服务
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backend:
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image: pytorch/pytorch:2.4.1-cuda11.8-cudnn9-runtime # 或者您可以自定义 Python 基础镜像
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container_name: backend
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working_dir: /app
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volumes:
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- ./src:/app/src # 映射源代码
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- ./requirements.txt:/app/requirements.txt
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- ./saves:/app/saves
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- /hdd/models:/hdd/models # <=== 修改这里
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...
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```
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63
docker-compose.yml
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63
docker-compose.yml
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version: '3.9'
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services:
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# 后端服务
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backend:
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build: .
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container_name: backend
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working_dir: /app
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volumes:
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- ./src:/app/src # 映射源代码
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- ./saves:/app/saves
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- /hdd/zwj/models:/hdd/zwj/models
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- backend-pip-cache:/root/.cache/pip # 缓存 pip 依赖
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ports:
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- "5000:5000" # 曝露后端端口
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depends_on:
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- neo4j # 确保 Neo4j 启动
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networks:
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- app-network
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environment:
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- NEO4J_URI=bolt://neo4j:7687 # 使用 neo4j 容器名称而非 localhost
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- NEO4J_USERNAME=neo4j
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- NEO4J_PASSWORD=0123456789
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# 前端服务
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frontend:
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build:
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context: ./web # 设置构建上下文为 web 文件夹
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dockerfile: Dockerfile # 使用 web 文件夹内的 Dockerfile
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container_name: frontend
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ports:
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- "80:80"
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depends_on:
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- backend
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networks:
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- app-network
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# Neo4j 图数据库服务
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neo4j:
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image: neo4j:latest
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container_name: neo4j
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volumes:
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- ./local_neo4j/conf:/var/lib/neo4j/conf
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- ./local_neo4j/import:/var/lib/neo4j/import
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- ./local_neo4j/plugins:/plugins
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- ./local_neo4j/data:/data
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- ./local_neo4j/logs:/var/lib/neo4j/logs
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restart: always
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ports:
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- "7474:7474"
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- "7687:7687"
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environment:
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- NEO4J_AUTH=neo4j/0123456789
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networks:
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- app-network
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# 定义网络
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networks:
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app-network:
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driver: bridge
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volumes:
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backend-pip-cache:
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@ -1,18 +1,21 @@
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dashscope==1.20.5
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FlagEmbedding==1.2.11
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Flask==3.0.3
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Flask_Cors==4.0.1
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llama_index==0.11.1
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neo4j==5.23.1
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openai==1.42.0
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paddleocr==2.8.1
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pymilvus==2.4.5
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python-dotenv==1.0.1
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PyYAML==6.0.2
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qianfan==0.4.6
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torch==2.4.0
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tqdm==4.66.5
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zhipuai==2.1.4.20230814
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PyMuPDF
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llama-index-readers-file
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peft
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dashscope>=1.20.3
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PyMuPDF==1.23.26
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peft>=0.11.1
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FlagEmbedding>=1.2.11
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Flask>=3.0.3
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Flask_Cors>=4.0.1
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llama_index>=0.11.8
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openai>=1.44.1
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paddleocr>=2.8.1
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pandas>=2.2.2
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Pillow>=10.4.0
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pymilvus>=2.4.4
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python-dotenv>=1.0.1
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PyYAML>=6.0.2
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qianfan>=0.4.7
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torch>=2.4.0
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tqdm>=4.66.1
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zhipuai>=2.1.2
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neo4j>=5.22.0
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sentencepiece==0.1.99
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llama-index-readers-file
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23
web/Dockerfile
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23
web/Dockerfile
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# 使用 Node.js 作为基础镜像,用于构建前端
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FROM node:16-alpine AS build-stage
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WORKDIR /app
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# 将 package.json 和 package-lock.json 复制到工作目录
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COPY ./package*.json ./
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# 安装依赖
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RUN npm install
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# 复制前端源代码并运行构建
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COPY . .
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RUN npm run build
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# 使用 Nginx 作为生产镜像
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FROM nginx:alpine AS production-stage
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COPY --from=build-stage /app/dist /usr/share/nginx/html
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# 复制 Nginx 配置文件
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COPY ../nginx.conf /etc/nginx/nginx.conf
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EXPOSE 80
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CMD ["nginx", "-g", "daemon off;"]
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34
web/nginx.conf
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34
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worker_processes 1;
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events {
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worker_connections 1024;
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}
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http {
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include /etc/nginx/mime.types;
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default_type application/octet-stream;
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sendfile on;
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keepalive_timeout 65;
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# This is where the server block should be placed
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server {
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listen 80;
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server_name localhost;
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location / {
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root /usr/share/nginx/html;
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try_files $uri /index.html;
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}
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# Proxy to backend API service
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location /api/ {
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proxy_pass http://backend:5000/;
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proxy_set_header Host $host;
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proxy_set_header X-Real-IP $remote_addr;
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proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
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proxy_set_header X-Forwarded-Proto $scheme;
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}
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}
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}
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