feat: supports docker compose deployment

2025-07-24 04:36:23 +00:00 · 2023-07-26 20:07:25 +08:00 · 2023-07-26 20:07:25 +08:00 · 671cddf4e7
commit 671cddf4e7
parent 700d9bf3e9
16 changed files with 531 additions and 45 deletions
--- a/docker-compose.yml
+++ b/docker-compose.yml
@ -2,57 +2,45 @@ version: '3.10'

 services:
  db:
-    image: mysql:8.0.33
+    image: mysql/mysql-server
    environment:
-      MYSQL_DATABASE: 'db'
      MYSQL_USER: 'user'
      MYSQL_PASSWORD: 'password'
      MYSQL_ROOT_PASSWORD: 'aa123456'
    ports:
      - 3306:3306
    volumes:
-      - my-db:/var/lib/mysql
+      - dbgpt-myql-db:/var/lib/mysql
+      - ./docker/examples/my.cnf:/etc/my.cnf
+      - ./docker/examples/sqls:/docker-entrypoint-initdb.d
+      - ./assets/schema/knowledge_management.sql:/docker-entrypoint-initdb.d/knowledge_management.sql
    restart: unless-stopped
+    networks:
+      - dbgptnet
  webserver:
-    build:
-      context: .
-      dockerfile: Dockerfile
-    command: python3 pilot/server/webserver.py
+    image: db-gpt:latest
+    command: python3 pilot/server/dbgpt_server.py
    environment:
-      - MODEL_SERVER=http://llmserver:8000
      - LOCAL_DB_HOST=db
-      - WEB_SERVER_PORT=7860
+      - LOCAL_DB_PASSWORD=aa123456
      - ALLOWLISTED_PLUGINS=db_dashboard
-    depends_on:
-      - db
-      - llmserver
-    volumes:
-      - ./models:/app/models
-      - ./plugins:/app/plugins
-      - data:/app/pilot/data
-    env_file:
-      - .env.template
-    ports:
-      - 7860:7860/tcp
-    expose:
-      - 7860/tcp
-    restart: unless-stopped
-  llmserver:
-    build:
-      context: .
-      dockerfile: Dockerfile
-    command: python3 pilot/server/llmserver.py
-    environment:
-      - LOCAL_DB_HOST=db
+      - LLM_MODEL=vicuna-13b
    depends_on:
      - db
    volumes:
-      - ./models:/app/models
+      - /data:/data
+      # Please modify it to your own model directory
+      - /data/models:/app/models
+      - dbgpt-data:/app/pilot/data
+      - dbgpt-message:/app/pilot/message
    env_file:
      - .env.template
    ports:
-      - 8000:8000
+      - 5000:5000/tcp
+    # webserver may be failed, it must wait all sqls in /docker-entrypoint-initdb.d execute finish.
    restart: unless-stopped
+    networks:
+      - dbgptnet
    deploy:
      resources:
        reservations:
@ -60,17 +48,11 @@ services:
            - driver: nvidia
              device_ids: ['0']
              capabilities: [gpu]
-  tunnel:
-    image: cloudflare/cloudflared:latest
-    container_name: cloudflared-tunnel
-    restart: unless-stopped
-    environment:
-      - TUNNEL_URL=http://webserver:7860
-    command: tunnel --no-autoupdate
-    depends_on:
-      - webserver
-
-
 volumes:
-  my-db:
-  data:
+  dbgpt-myql-db:
+  dbgpt-data:
+  dbgpt-message:
+networks:
+  dbgptnet:
+    driver: bridge
+    name: dbgptnet
--- a/docker/allinone/Dockerfile
+++ b/docker/allinone/Dockerfile
@ -0,0 +1,30 @@
+ARG BASE_IMAGE="db-gpt:latest"
+
+FROM ${BASE_IMAGE}
+
+RUN apt-get update && apt-get install -y wget gnupg lsb-release net-tools
+
+RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 467B942D3A79BD29
+
+RUN wget https://dev.mysql.com/get/mysql-apt-config_0.8.17-1_all.deb
+RUN dpkg -i mysql-apt-config_0.8.17-1_all.deb
+
+RUN apt-get update && apt-get install -y mysql-server && apt-get clean
+
+# Remote access
+RUN sed -i 's/bind-address\s*=\s*127.0.0.1/bind-address = 0.0.0.0/g' /etc/mysql/mysql.conf.d/mysqld.cnf \
+    && echo "[mysqld]\ncharacter_set_server=utf8mb4\ncollation-server=utf8mb4_unicode_ci\ninit_connect='SET NAMES utf8mb4'\n[mysql]\ndefault-character-set=utf8mb4\n[client]\ndefault-character-set=utf8mb4\n" >> /etc/mysql/my.cnf
+
+# Init sql
+RUN mkdir /docker-entrypoint-initdb.d \
+    && echo "USE mysql;\nUPDATE user SET Host='%' WHERE User='root';\nFLUSH PRIVILEGES;" > /docker-entrypoint-initdb.d/init.sql
+
+ENV MYSQL_ROOT_PASSWORD=aa123456
+ENV LOCAL_DB_PASSWORD="$MYSQL_ROOT_PASSWORD"
+
+RUN cp /app/assets/schema/knowledge_management.sql /docker-entrypoint-initdb.d/
+
+COPY docker/allinone/allinone-entrypoint.sh /usr/local/bin/allinone-entrypoint.sh
+COPY docker/examples/sqls/ /docker-entrypoint-initdb.d/
+
+ENTRYPOINT ["/usr/local/bin/allinone-entrypoint.sh"]
--- a/docker/allinone/allinone-entrypoint.sh
+++ b/docker/allinone/allinone-entrypoint.sh
@ -0,0 +1,17 @@
+#!/bin/bash
+
+service mysql start
+
+# execute all mysql init script
+for file in /docker-entrypoint-initdb.d/*.sql
+do
+    echo "execute sql file: $file"
+    mysql -u root -p${MYSQL_ROOT_PASSWORD} < "$file"
+done
+
+mysql -u root -p${MYSQL_ROOT_PASSWORD} -e "
+ALTER USER 'root'@'%' IDENTIFIED WITH mysql_native_password BY '$MYSQL_ROOT_PASSWORD';
+FLUSH PRIVILEGES;
+"
+
+python3 pilot/server/dbgpt_server.py
--- a/docker/allinone/build_image.sh
+++ b/docker/allinone/build_image.sh
@ -0,0 +1,9 @@
+#!/bin/bash
+
+SCRIPT_LOCATION=$0
+cd "$(dirname "$SCRIPT_LOCATION")"
+WORK_DIR=$(pwd)
+
+IMAGE_NAME="db-gpt-allinone"
+
+docker build -f Dockerfile -t $IMAGE_NAME $WORK_DIR/../../
--- a/docker/allinone/run.sh
+++ b/docker/allinone/run.sh
@ -0,0 +1,13 @@
+#!/bin/bash
+
+docker run --gpus "device=0" -d -p 3306:3306 \
+    -p 5000:5000 \
+    -e LOCAL_DB_HOST=127.0.0.1 \
+    -e LOCAL_DB_PASSWORD=aa123456 \
+    -e MYSQL_ROOT_PASSWORD=aa123456 \
+    -e LLM_MODEL=vicuna-13b \
+    -e LANGUAGE=zh \
+    -v /data:/data \
+    -v /data/models:/app/models \
+    --name db-gpt-allinone \
+    db-gpt-allinone
--- a/docker/allinone/run_proxyllm.sh
+++ b/docker/allinone/run_proxyllm.sh
@ -0,0 +1,19 @@
+#!/bin/bash
+
+# Your api key
+PROXY_API_KEY="$PROXY_API_KEY"
+PROXY_SERVER_URL="${PROXY_SERVER_URL-'https://api.openai.com/v1/chat/completions'}"
+
+docker run --gpus "device=0" -d -p 3306:3306 \
+    -p 5000:5000 \
+    -e LOCAL_DB_HOST=127.0.0.1 \
+    -e LOCAL_DB_PASSWORD=aa123456 \
+    -e MYSQL_ROOT_PASSWORD=aa123456 \
+    -e LLM_MODEL=proxyllm \
+    -e PROXY_API_KEY=$PROXY_API_KEY \
+    -e PROXY_SERVER_URL=$PROXY_SERVER_URL \
+    -e LANGUAGE=zh \
+    -v /data:/data \
+    -v /data/models:/app/models \
+    --name db-gpt-allinone \
+    db-gpt-allinone
--- a/docker/base/Dockerfile
+++ b/docker/base/Dockerfile
@ -0,0 +1,25 @@
+FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
+
+RUN apt-get update && apt-get install -y git python3 pip wget \
+    && apt-get clean
+
+# download code from githu: https://github.com/csunny/DB-GPT
+# ENV DBGPT_VERSION="v0.3.3"
+# RUN wget https://github.com/csunny/DB-GPT/archive/refs/tags/$DBGPT_VERSION.zip
+
+# clone latest code, and rename to /app
+RUN git clone https://github.com/csunny/DB-GPT.git /app
+
+WORKDIR /app
+
+RUN pip3 install --upgrade pip \
+    && pip3 install --no-cache-dir -r requirements.txt \
+    && pip3 install seaborn mpld3 \
+    && wget https://github.com/explosion/spacy-models/releases/download/zh_core_web_sm-3.5.0/zh_core_web_sm-3.5.0-py3-none-any.whl -O /tmp/zh_core_web_sm-3.5.0-py3-none-any.whl \
+    && pip3 install /tmp/zh_core_web_sm-3.5.0-py3-none-any.whl \
+    && rm /tmp/zh_core_web_sm-3.5.0-py3-none-any.whl \
+    && rm -rf `pip3 cache dir` 
+
+# RUN python3 -m spacy download zh_core_web_sm
+
+EXPOSE 5000
--- a/docker/base/build_image.sh
+++ b/docker/base/build_image.sh
@ -0,0 +1,8 @@
+#!/bin/bash
+
+SCRIPT_LOCATION=$0
+cd "$(dirname "$SCRIPT_LOCATION")"
+WORK_DIR=$(pwd)
+
+IMAGE_NAME="db-gpt"
+docker build -f Dockerfile -t $IMAGE_NAME $WORK_DIR/../../
--- a/docker/build_all_images.sh
+++ b/docker/build_all_images.sh
@ -0,0 +1,9 @@
+#!/bin/bash
+
+SCRIPT_LOCATION=$0
+cd "$(dirname "$SCRIPT_LOCATION")"
+WORK_DIR=$(pwd)
+
+bash $WORK_DIR/base/build_image.sh
+
+bash $WORK_DIR/allinone/build_image.sh
--- a/docker/examples/my.cnf
+++ b/docker/examples/my.cnf
@ -0,0 +1,44 @@
+# For advice on how to change settings please see
+# http://dev.mysql.com/doc/refman/8.0/en/server-configuration-defaults.html
+
+[mysqld]
+#
+# Remove leading # and set to the amount of RAM for the most important data
+# cache in MySQL. Start at 70% of total RAM for dedicated server, else 10%.
+# innodb_buffer_pool_size = 128M
+#
+# Remove leading # to turn on a very important data integrity option: logging
+# changes to the binary log between backups.
+# log_bin
+#
+# Remove leading # to set options mainly useful for reporting servers.
+# The server defaults are faster for transactions and fast SELECTs.
+# Adjust sizes as needed, experiment to find the optimal values.
+# join_buffer_size = 128M
+# sort_buffer_size = 2M
+# read_rnd_buffer_size = 2M
+
+# Remove leading # to revert to previous value for default_authentication_plugin,
+# this will increase compatibility with older clients. For background, see:
+# https://dev.mysql.com/doc/refman/8.0/en/server-system-variables.html#sysvar_default_authentication_plugin
+# default-authentication-plugin=mysql_native_password
+skip-host-cache
+skip-name-resolve
+datadir=/var/lib/mysql
+socket=/var/lib/mysql/mysql.sock
+secure-file-priv=/var/lib/mysql-files
+user=mysql
+
+pid-file=/var/run/mysqld/mysqld.pid
+
+# add example config
+
+default-authentication-plugin=mysql_native_password
+character_set_server=utf8mb4
+collation-server=utf8mb4_unicode_ci
+init_connect='SET NAMES utf8mb4'
+
+[mysql]
+default-character-set=utf8mb4
+[client]
+default-character-set=utf8mb4
--- a/docker/examples/sqls/case_1_student_manager.sql
+++ b/docker/examples/sqls/case_1_student_manager.sql
@ -0,0 +1,63 @@
+create database case_1_student_manager character set utf8;
+use case_1_student_manager;
+
+CREATE TABLE students (
+    student_id INT PRIMARY KEY,
+    student_name VARCHAR(100) COMMENT '学生姓名',
+    major VARCHAR(100) COMMENT '专业',
+    year_of_enrollment INT COMMENT '入学年份',
+    student_age INT COMMENT '学生年龄'
+) COMMENT '学生信息表';
+
+CREATE TABLE courses (
+    course_id INT PRIMARY KEY,
+    course_name VARCHAR(100) COMMENT '课程名称',
+    credit FLOAT COMMENT '学分'
+) COMMENT '课程信息表';
+
+CREATE TABLE scores (
+    student_id INT,
+    course_id INT,
+    score INT COMMENT '得分',
+    semester VARCHAR(50) COMMENT '学期',
+    PRIMARY KEY (student_id, course_id),
+    FOREIGN KEY (student_id) REFERENCES students(student_id),
+    FOREIGN KEY (course_id) REFERENCES courses(course_id)
+) COMMENT '学生成绩表';
+
+
+INSERT INTO students (student_id, student_name, major, year_of_enrollment, student_age) VALUES
+(1, '张三', '计算机科学', 2020, 20),
+(2, '李四', '计算机科学', 2021, 19),
+(3, '王五', '物理学', 2020, 21),
+(4, '赵六', '数学', 2021, 19),
+(5, '周七', '计算机科学', 2022, 18),
+(6, '吴八', '物理学', 2020, 21),
+(7, '郑九', '数学', 2021, 19),
+(8, '孙十', '计算机科学', 2022, 18),
+(9, '刘十一', '物理学', 2020, 21),
+(10, '陈十二', '数学', 2021, 19);
+
+INSERT INTO courses (course_id, course_name, credit) VALUES
+(1, '计算机基础', 3),
+(2, '数据结构', 4),
+(3, '高等物理', 3),
+(4, '线性代数', 4),
+(5, '微积分', 5),
+(6, '编程语言', 4),
+(7, '量子力学', 3),
+(8, '概率论', 4),
+(9, '数据库系统', 4),
+(10, '计算机网络', 4);
+
+INSERT INTO scores (student_id, course_id, score, semester) VALUES
+(1, 1, 90, '2020年秋季'),
+(1, 2, 85, '2021年春季'),
+(2, 1, 88, '2021年秋季'),
+(2, 2, 90, '2022年春季'),
+(3, 3, 92, '2020年秋季'),
+(3, 4, 85, '2021年春季'),
+(4, 3, 88, '2021年秋季'),
+(4, 4, 86, '2022年春季'),
+(5, 1, 90, '2022年秋季'),
+(5, 2, 87, '2023年春季');
--- a/docker/examples/sqls/case_2_ecom.sql
+++ b/docker/examples/sqls/case_2_ecom.sql
@ -0,0 +1,63 @@
+create database case_2_ecom character set utf8;
+use case_2_ecom;
+
+CREATE TABLE users (
+    user_id INT PRIMARY KEY,
+    user_name VARCHAR(100) COMMENT '用户名',
+    user_email VARCHAR(100) COMMENT '用户邮箱',
+    registration_date DATE COMMENT '注册日期',
+    user_country VARCHAR(100) COMMENT '用户国家'
+) COMMENT '用户信息表';
+
+CREATE TABLE products (
+    product_id INT PRIMARY KEY,
+    product_name VARCHAR(100) COMMENT '商品名称',
+    product_price FLOAT COMMENT '商品价格'
+) COMMENT '商品信息表';
+
+CREATE TABLE orders (
+    order_id INT PRIMARY KEY,
+    user_id INT,
+    product_id INT,
+    quantity INT COMMENT '数量',
+    order_date DATE COMMENT '订单日期',
+    FOREIGN KEY (user_id) REFERENCES users(user_id),
+    FOREIGN KEY (product_id) REFERENCES products(product_id)
+) COMMENT '订单信息表';
+
+
+INSERT INTO users (user_id, user_name, user_email, registration_date, user_country) VALUES
+(1, 'John', 'john@gmail.com', '2020-01-01', 'USA'),
+(2, 'Mary', 'mary@gmail.com', '2021-01-01', 'UK'),
+(3, 'Bob', 'bob@gmail.com', '2020-01-01', 'USA'),
+(4, 'Alice', 'alice@gmail.com', '2021-01-01', 'UK'),
+(5, 'Charlie', 'charlie@gmail.com', '2020-01-01', 'USA'),
+(6, 'David', 'david@gmail.com', '2021-01-01', 'UK'),
+(7, 'Eve', 'eve@gmail.com', '2020-01-01', 'USA'),
+(8, 'Frank', 'frank@gmail.com', '2021-01-01', 'UK'),
+(9, 'Grace', 'grace@gmail.com', '2020-01-01', 'USA'),
+(10, 'Helen', 'helen@gmail.com', '2021-01-01', 'UK');
+
+INSERT INTO products (product_id, product_name, product_price) VALUES
+(1, 'iPhone', 699),
+(2, 'Samsung Galaxy', 599),
+(3, 'iPad', 329),
+(4, 'Macbook', 1299),
+(5, 'Apple Watch', 399),
+(6, 'AirPods', 159),
+(7, 'Echo', 99),
+(8, 'Kindle', 89),
+(9, 'Fire TV Stick', 39),
+(10, 'Echo Dot', 49);
+
+INSERT INTO orders (order_id, user_id, product_id, quantity, order_date) VALUES
+(1, 1, 1, 1, '2022-01-01'),
+(2, 1, 2, 1, '2022-02-01'),
+(3, 2, 3, 2, '2022-03-01'),
+(4, 2, 4, 1, '2022-04-01'),
+(5, 3, 5, 2, '2022-05-01'),
+(6, 3, 6, 3, '2022-06-01'),
+(7, 4, 7, 2, '2022-07-01'),
+(8, 4, 8, 1, '2022-08-01'),
+(9, 5, 9, 2, '2022-09-01'),
+(10, 5, 10, 3, '2022-10-01');
--- a/docker/examples/sqls/test_case.md
+++ b/docker/examples/sqls/test_case.md
@ -0,0 +1,87 @@
+# 测试问题
+
+## 场景一 
+
+学校管理系统，主要测试SQL助手的联合查询，条件查询和排序功能。
+
+我们的数据库有三个表：学生表、课程表和成绩表。我们要测试SQL助手能否处理复杂的SQL查询，包括连接多个表，按照一定的条件筛选数据，以及对结果进行排序。
+
+### Q1
+
+查询所有学生的姓名，专业和成绩，按成绩降序排序
+
+SQL：
+```sql
+SELECT students.student_name, students.major, scores.score
+FROM students
+JOIN scores ON students.student_id = scores.student_id
+ORDER BY scores.score DESC;
+```
+
+### Q2
+
+查询 "计算机科学" 专业的学生的平均成绩
+
+SQL：
+```sql
+SELECT AVG(scores.score) as avg_score
+FROM students
+JOIN scores ON students.student_id = scores.student_id
+WHERE students.major = '计算机科学';
+```
+
+### Q3
+
+查询哪些学生在 "2023年春季" 学期的课程学分总和超过2学分
+
+```sql
+SELECT students.student_name
+FROM students
+JOIN scores ON students.student_id = scores.student_id
+JOIN courses ON scores.course_id = courses.course_id
+WHERE scores.semester = '2023年春季'
+GROUP BY students.student_id
+HAVING SUM(courses.credit) > 2;
+```
+
+## 场景二：电商系统，主要测试SQL助手的数据聚合和分组功能。
+
+我们的数据库有三个表：用户表、商品表和订单表。我们要测试SQL助手能否处理复杂的SQL查询，包括对数据进行聚合和分组。
+
+### Q1
+
+查询每个用户的总订单数量
+
+SQL:
+
+```sql
+SELECT users.user_name, COUNT(orders.order_id) as order_count
+FROM users
+JOIN orders ON users.user_id = orders.user_id
+GROUP BY users.user_id;
+```
+
+### Q2
+
+查询每种商品的总销售额
+
+```sql
+SELECT products.product_name, SUM(products.product_price * orders.quantity) as total_sales
+FROM products
+JOIN orders ON products.product_id = orders.product_id
+GROUP BY products.product_id;
+```
+
+### Q3
+
+查询2023年最受欢迎的商品（订单数量最多的商品）
+
+```sql
+SELECT products.product_name
+FROM products
+JOIN orders ON products.product_id = orders.product_id
+WHERE YEAR(orders.order_date) = 2023
+GROUP BY products.product_id
+ORDER BY COUNT(orders.order_id) DESC
+LIMIT 1;
+```
--- a/docker/examples/sqls/test_case_info.sql
+++ b/docker/examples/sqls/test_case_info.sql
@ -0,0 +1,19 @@
+create database test_case_info character set utf8;
+use test_case_info;
+
+CREATE TABLE test_cases (
+    case_id INT AUTO_INCREMENT PRIMARY KEY,
+    scenario_name VARCHAR(100) COMMENT '场景名称',
+    scenario_description TEXT COMMENT '场景描述',
+    test_question VARCHAR(500) COMMENT '测试问题',
+    expected_sql TEXT COMMENT '预期SQL',
+    correct_output TEXT COMMENT '正确输出'
+) COMMENT '测试用例表';
+
+INSERT INTO test_cases (scenario_name, scenario_description, test_question, expected_sql, correct_output) VALUES
+('学校管理系统', '测试SQL助手的联合查询，条件查询和排序功能', '查询所有学生的姓名，专业和成绩，按成绩降序排序', 'SELECT students.student_name, students.major, scores.score FROM students JOIN scores ON students.student_id = scores.student_id ORDER BY scores.score DESC;', '返回所有学生的姓名，专业和成绩，按成绩降序排序的结果'),
+('学校管理系统', '测试SQL助手的联合查询，条件查询和排序功能', '查询计算机科学专业的学生的平均成绩', 'SELECT AVG(scores.score) as avg_score FROM students JOIN scores ON students.student_id = scores.student_id WHERE students.major = ''计算机科学'';', '返回计算机科学专业学生的平均成绩'),
+('学校管理系统', '测试SQL助手的联合查询，条件查询和排序功能', '查询哪些学生在2023年秋季学期的课程学分总和超过15', 'SELECT students.student_name FROM students JOIN scores ON students.student_id = scores.student_id JOIN courses ON scores.course_id = courses.course_id WHERE scores.semester = ''2023年秋季'' GROUP BY students.student_id HAVING SUM(courses.credit) > 15;', '返回在2023年秋季学期的课程学分总和超过15的学生的姓名'),
+('电商系统', '测试SQL助手的数据聚合和分组功能', '查询每个用户的总订单数量', 'SELECT users.user_name, COUNT(orders.order_id) as order_count FROM users JOIN orders ON users.user_id = orders.user_id GROUP BY users.user_id;', '返回每个用户的总订单数量'),
+('电商系统', '测试SQL助手的数据聚合和分组功能', '查询每种商品的总销售额', 'SELECT products.product_name, SUM(products.product_price * orders.quantity) as total_sales FROM products JOIN orders ON products.product_id = orders.product_id GROUP BY products.product_id;', '返回每种商品的总销售额'),
+('电商系统', '测试SQL助手的数据聚合和分组功能', '查询2023年最受欢迎的商品（订单数量最多的商品）', 'SELECT products.product_name FROM products JOIN orders ON products.product_id = orders.product_id WHERE YEAR(orders.order_date) = 2023 GROUP BY products.product_id ORDER BY COUNT(orders.order_id) DESC LIMIT 1;', '返回2023年最受欢迎的商品（订单数量最多的商品）的名称');
--- a/docker/examples/sqls/user_config.sql
+++ b/docker/examples/sqls/user_config.sql
@ -0,0 +1,3 @@
+USE mysql;
+UPDATE user SET Host='%' WHERE User='root';
+FLUSH PRIVILEGES;
--- a/docs/getting_started/getting_started.md
+++ b/docs/getting_started/getting_started.md
@ -86,3 +86,98 @@ $ python pilot/server/dbgpt_server.py --light

 If you want to learn about dbgpt-webui, read https://github.com/csunny/DB-GPT/tree/new-page-framework/datacenter

+### 4. Docker (Experimental)
+
+#### 4.1 Building Docker image
+
+```bash
+$ bash docker/build_all_images.sh
+```
+
+Review images by listing them:
+
+```bash
+$ docker images|grep db-gpt
+```
+
+Output should look something like the following:
+
+```
+db-gpt-allinone    latest     e1ffd20b85ac   45 minutes ago   14.5GB
+db-gpt             latest     e36fb0cca5d9   3 hours ago      14GB
+```
+
+#### 4.2. Run all in one docker container
+
+**Run with local model**
+
+```bash
+$ docker run --gpus "device=0" -d -p 3306:3306 \
+    -p 5000:5000 \
+    -e LOCAL_DB_HOST=127.0.0.1 \
+    -e LOCAL_DB_PASSWORD=aa123456 \
+    -e MYSQL_ROOT_PASSWORD=aa123456 \
+    -e LLM_MODEL=vicuna-13b \
+    -e LANGUAGE=zh \
+    -v /data/models:/app/models \
+    --name db-gpt-allinone \
+    db-gpt-allinone
+```
+
+Open http://localhost:5000 with your browser to see the product.
+
+
+- `-e LLM_MODEL=vicuna-13b`, means we use vicuna-13b as llm model, see /pilot/configs/model_config.LLM_MODEL_CONFIG
+- `-v /data/models:/app/models`, means we mount the local model file directory `/data/models` to the docker container directory `/app/models`, please replace it with your model file directory.
+
+You can see log with command:
+
+```bash
+$ docker logs db-gpt-allinone -f
+```
+
+**Run with openai interface**
+
+```bash
+$ PROXY_API_KEY="You api key"
+$ PROXY_SERVER_URL="https://api.openai.com/v1/chat/completions"
+$ docker run --gpus "device=0" -d -p 3306:3306 \
+    -p 5000:5000 \
+    -e LOCAL_DB_HOST=127.0.0.1 \
+    -e LOCAL_DB_PASSWORD=aa123456 \
+    -e MYSQL_ROOT_PASSWORD=aa123456 \
+    -e LLM_MODEL=proxyllm \
+    -e PROXY_API_KEY=$PROXY_API_KEY \
+    -e PROXY_SERVER_URL=$PROXY_SERVER_URL \
+    -e LANGUAGE=zh \
+    -v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese \
+    --name db-gpt-allinone \
+    db-gpt-allinone
+```
+
+- `-e LLM_MODEL=proxyllm`, means we use proxy llm(openai interface, fastchat interface...)
+- `-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese`, means we mount the local text2vec model to the docker container.
+
+#### 4.2. Run with docker compose
+
+```bash
+$ docker compose up -d
+```
+
+Output should look something like the following:
+```
+[+] Building 0.0s (0/0)
+[+] Running 2/2
+ ✔ Container db-gpt-db-1         Started                                                                                                                                                                                          0.4s
+ ✔ Container db-gpt-webserver-1  Started
+```
+
+You can see log with command:
+
+```bash
+$ docker logs db-gpt-webserver-1 -f
+```
+
+Open http://localhost:5000 with your browser to see the product.
+
+You can open docker-compose.yml in the project root directory to see more details.