build: docker compose

Author: MenxLi

README.md

@@ -32,11 +32,7 @@ git submodule update --init --recursive
 
 **Docker deployment**
 ```sh
-# build docker image
-docker build -t lires:latest .
-
-# create a conainer and start the servers
-docker run -d -p 8080:8080 -p 8081:8081 -v $HOME/.Lires:/root/.Lires --name lrs lires:latest
+docker compose up
 
 # register a user and download pdf.js viewer on the first run 
 # (no need to run again if the container is re-created / re-started)
@@ -45,7 +41,6 @@ docker exec lrs lrs-utils download_pdfjs
 ```
 Now open the browser and visit the WebUI on `http://localhost:8081`.
 
-Docker deployment is a quick way to deploy the server, but it has some limitations.  
 **Please refer to the documents for more details on [getting started](docs/gettingStarted.md).**
 
 # Manuals and documentations

compose.yaml

@@ -0,0 +1,51 @@
+
+services:
+
+  web:
+    container_name: lrs_web
+    build:
+      context: .
+      dockerfile: ./docker/web.Dockerfile
+    ports:
+      - "8081:80"
+    networks:
+      - lires_net
+
+  server:
+    container_name: lrs
+    build:
+      context: .
+      dockerfile: ./docker/server.Dockerfile
+    ports:
+      - "8080:8080"
+      # - "8731:8731"
+    volumes:
+      - "$HOME/.Lires:/root/.Lires"
+    networks:
+      - lires_net
+  
+  ai:
+    container_name: lrs_ai
+    build:
+      context: .
+      dockerfile: ./docker/iserver.Dockerfile
+    # ports:
+    #   - "8731:8731"
+    volumes:
+      - "$HOME/.Lires:/root/.Lires"
+    environment:
+      - OPENAI_API_KEY=sk-1234567890abcdef1234567890abcdef
+      - OPENAI_API_BASE=https://api.openai.com/v1
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: "nvidia"
+              count: "all"
+              capabilities: [gpu]
+    networks:
+      - lires_net
+
+networks:
+  lires_net:
+    driver: bridge

Dockerfile renamed to docker/cluster.Dockerfile

@@ -1,16 +1,16 @@
-FROM python:3.11-bookworm as iserver-build
+FROM nvcr.io/nvidia/driver:535.104.12-ubuntu22.04
 WORKDIR /
 COPY . /Lires
 
-RUN sed -i 's/deb.debian.org/mirrors.ustc.edu.cn/g' /etc/apt/sources.list.d/debian.sources
+RUN apt-get update && apt-get install -y python3 python3-pip
 RUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
 
 # Install rust and make sure it's up to date and using stable channel
 # RUN curl https://sh.rustup.rs -sSf | sh -s -- -y
 # RUN rustup update
 
-RUN python3 -m pip install --upgrade pip --break-system-packages
-RUN pip3 install -e /Lires[ai] --break-system-packages
+RUN python3 -m pip install --upgrade pip
+RUN pip3 install -e /Lires[ai]
 
 EXPOSE 8731
 

docker/iserver.Dockerfile

@@ -149,9 +149,17 @@ lrs-index build
 ## Docker deployment
 Instead of installing the server, you can also deploy the server using docker.  
 Which adds additional security and building efficiency.  
+
+### Method 1 - Use docker compose (recommended)
+**Nvidia container toolkit should be installed**
+```sh
+docker compose up
+```
+
+### Method 2 - Use the cluster image
 ```sh
 # creates a docker image named lires
-docker build -t lires:latest .
+docker build -f ./docker/cluster.Dockerfile -t lires:latest .
 
 # create the container named 'lrs', 
 # please change the port mapping and volume mapping as needed
@@ -171,6 +179,7 @@ Instead, we can set the server settings pointing to the shared LiresAI server ou
 > 
 > For example, if the LiresAI server is running on the host machine with IP address `192.168.3.6:8731`, then we can set the `iserver_host` to `192.168.3.6` and `iserver_port` to `8731`.
 
+### On the first run
 **On the first run** you need to generate the user key, which can be done by running the `lrs-keyman` command in the container.
 and you also need to download the pdf.js viewer to serve pdf with the viewer in LiresWeb.
 The user information and pdf.js viewer will be stored in the volume mapping directory, so that they will not be lost when the container is removed.

docs/gettingStarted.md

@@ -40,14 +40,17 @@ dependencies = [
     "pyyaml",
     "requests",
     "deprecated",
+
+    # used by both core and ai, may be removed in the future
+    "markdown",
+    "pyperclip",
 ]
 
 [project.optional-dependencies]
 core = [
     "pybtex",
     "pylatexenc",
     "tornado",
-    "pyperclip",
     "PyMuPDF",
     "markdown",
     "nest_asyncio",