Version: dev

DB-GPT Docker Build Guide

This guide provides comprehensive instructions for building DB-GPT Docker images with various configurations using the docker/base/build_image.sh script.

Overview

The DB-GPT build script allows you to create Docker images tailored to your specific requirements. You can choose from predefined installation modes or customize the build with specific extras, environment variables, and other settings.

Available Installation Modes

Default
OpenAI
VLLM
Llama-cpp
Full

CUDA-based image with standard features.

bash docker/base/build_image.sh

Includes: CUDA support, proxy integrations (OpenAI, Ollama, Zhipuai, Anthropic, Qianfan, Tongyi), RAG capabilities, graph RAG, Hugging Face integration, and quantization support.

CPU-based image optimized for OpenAI API usage.

bash docker/base/build_image.sh --install-mode openai

Includes: Basic functionality, all proxy integrations, and RAG capabilities without GPU acceleration.

CUDA-based image with VLLM for optimized inference.

bash docker/base/build_image.sh --install-mode vllm

Includes: All default features plus VLLM support for high-performance inference.

CUDA-based image with Llama-cpp support.

bash docker/base/build_image.sh --install-mode llama-cpp

Includes: All default features plus Llama-cpp and Llama-cpp server with CUDA acceleration enabled via CMAKE_ARGS="-DGGML_CUDA=ON".

CUDA-based image with all available features.

bash docker/base/build_image.sh --install-mode full

Includes: All features from other modes plus embedding capabilities.

Basic Usage

View Available Modes

To see all available installation modes and their configurations:

bash docker/base/build_image.sh --list-modes

Get Help

Display all available options:

bash docker/base/build_image.sh --help

Customization Options

Python Version

DB-GPT requires Python 3.10 or higher. The default is Python 3.11, but you can specify a different version:

bash docker/base/build_image.sh --python-version 3.10

Custom Image Name

Set a custom name for the built image:

bash docker/base/build_image.sh --image-name mycompany/dbgpt

Image Name Suffix

Add a suffix to the image name for versioning or environment identification:

bash docker/base/build_image.sh --image-name-suffix v1.0

This will generate eosphorosai/dbgpt-v1.0 for the default mode or eosphorosai/dbgpt-MODE-v1.0 for specific modes.

PIP Mirror

Choose a different PIP index URL:

bash docker/base/build_image.sh --pip-index-url https://pypi.org/simple

Ubuntu Mirror

Control whether to use Tsinghua Ubuntu mirror:

bash docker/base/build_image.sh --use-tsinghua-ubuntu false

Language Preference

Set your preferred language (default is English):

bash docker/base/build_image.sh --language zh

Advanced Customization

Custom Extras

You can customize the Python package extras installed in the image:

Override Extras
Add Extras
Mode-Specific

Completely replace the default extras with your own selection:

bash docker/base/build_image.sh --extras "base,proxy_openai,rag,storage_chromadb"

Keep the default extras and add more:

bash docker/base/build_image.sh --add-extras "storage_milvus,storage_elasticsearch,datasource_postgres"

Add specific extras to a particular installation mode:

bash docker/base/build_image.sh --install-mode vllm --add-extras "storage_milvus,datasource_postgres"

Available Extra Options

Here are some useful extras you can add:

Extra Package	Description
`storage_milvus`	Vector store integration with Milvus
`storage_elasticsearch`	Vector store integration with Elasticsearch
`datasource_postgres`	Database connector for PostgreSQL
`vllm`	VLLM integration for optimized inference
`llama_cpp`	Llama-cpp Python bindings
`llama_cpp_server`	Llama-cpp HTTP server

You can run uv run install_help.py list in your local DB-GPT repository to see all available extras.

Environment Variables

DB-GPT build supports environment variables for specialized builds. The main environment variable used is CMAKE_ARGS which is particularly important for Llama-cpp compilation.

Override Env Vars
Add Env Vars

Replace the default environment variables:

bash docker/base/build_image.sh --env-vars "CMAKE_ARGS=\"-DGGML_CUDA=ON -DLLAMA_CUBLAS=ON\""

Add additional environment variables:

bash docker/base/build_image.sh --install-mode llama-cpp --add-env-vars "FORCE_CMAKE=1"

note

For Llama-cpp mode, CMAKE_ARGS="-DGGML_CUDA=ON" is automatically set to enable CUDA acceleration.

Docker Network

Specify a Docker network for building:

bash docker/base/build_image.sh --network host

Custom Dockerfile

Use a custom Dockerfile:

bash docker/base/build_image.sh --dockerfile Dockerfile.custom

Example Scenarios

Enterprise DB-GPT with PostgreSQL and Elasticsearch

Build a full-featured enterprise version with PostgreSQL and Elasticsearch support:

bash docker/base/build_image.sh --install-mode full \
  --add-extras "storage_elasticsearch,datasource_postgres" \
  --image-name-suffix enterprise \
  --python-version 3.10 \
  --load-examples false

Optimized Llama-cpp for Specific Hardware

Build with custom Llama-cpp optimization flags:

bash docker/base/build_image.sh --install-mode llama-cpp \
  --env-vars "CMAKE_ARGS=\"-DGGML_CUDA=ON -DGGML_AVX2=OFF -DGGML_AVX512=ON\"" \
  --python-version 3.11

Lightweight OpenAI Proxy

Build a minimal OpenAI proxy image:

bash docker/base/build_image.sh --install-mode openai \
  --use-tsinghua-ubuntu false \
  --pip-index-url https://pypi.org/simple \
  --load-examples false

Development Build with Milvus

Build a development version with Milvus support:

bash docker/base/build_image.sh --install-mode vllm \
  --add-extras "storage_milvus" \
  --image-name-suffix dev

Troubleshooting

Common Build Issues

CUDA Not Found

If you encounter CUDA-related errors:

# Try building with a different CUDA base image
bash docker/base/build_image.sh --base-image nvidia/cuda:12.1.0-devel-ubuntu22.04

Package Installation Failures

If extras fail to install:

# Try building with fewer extras to isolate the problem
bash docker/base/build_image.sh --extras "base,proxy_openai,rag"

Network Issues

If you encounter network problems:

# Use a specific network
bash docker/base/build_image.sh --network host

API Reference

Script Options

Option	Description	Default Value
`--install-mode`	Installation mode	`default`
`--base-image`	Base Docker image	`nvidia/cuda:12.4.0-devel-ubuntu22.04`
`--image-name`	Docker image name	`eosphorosai/dbgpt`
`--image-name-suffix`	Suffix for image name
`--pip-index-url`	PIP mirror URL	`https://pypi.tuna.tsinghua.edu.cn/simple`
`--language`	Interface language	`en`
`--load-examples`	Load example data	`true`
`--python-version`	Python version	`3.11`
`--use-tsinghua-ubuntu`	Use Tsinghua Ubuntu mirror	`true`
`--extras`	Extra packages to install	Mode dependent
`--add-extras`	Additional extra packages
`--env-vars`	Build environment variables	Mode dependent
`--add-env-vars`	Additional environment variables
`--dockerfile`	Dockerfile to use	`Dockerfile`
`--network`	Docker network to use

DB-GPT Docker Build Guide

Overview​

Available Installation Modes​

Basic Usage​

View Available Modes​

Get Help​

Customization Options​

Python Version​

Custom Image Name​

Image Name Suffix​

PIP Mirror​

Ubuntu Mirror​

Language Preference​

Advanced Customization​

Custom Extras​

Available Extra Options​

Environment Variables​

Docker Network​

Custom Dockerfile​

Example Scenarios​

Enterprise DB-GPT with PostgreSQL and Elasticsearch​

Optimized Llama-cpp for Specific Hardware​

Lightweight OpenAI Proxy​

Development Build with Milvus​

Troubleshooting​

CUDA Not Found​

Package Installation Failures​

Network Issues​

API Reference​

Script Options​

Additional Resources​