Build a RAGFlow Docker Image

A guide explaining how to build a RAGFlow Docker image from its source code. By following this guide, you'll be able to create a local Docker image that can be used for development, debugging, or testing purposes.

Target Audience

• Developers who have added new features or modified the existing code and require a Docker image to view and debug their changes.
• Developers seeking to build a RAGFlow Docker image for an ARM64 platform.
• Testers aiming to explore the latest features of RAGFlow in a Docker image.

Prerequisites

• CPU ≥ 4 cores
• RAM ≥ 16 GB
• Disk ≥ 50 GB
• Docker ≥ 24.0.0 & Docker Compose ≥ v2.26.1
• For ARM64 platforms, please upgrade the xgboost version in pyproject.toml to 1.6.0 and ensure unixODBC is properly installed.

Build a Docker image

Build a Docker image without embedding models

This image is approximately 2 GB in size and relies on external LLM and embedding services.

NOTE

While we also test RAGFlow on ARM64 platforms, we do not maintain RAGFlow Docker images for ARM. However, you can build an image yourself on a linux/arm64 or darwin/arm64 host machine as well.

git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .

Build a Docker image including embedding models

This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.

NOTE

While we also test RAGFlow on ARM64 platforms, we do not maintain RAGFlow Docker images for ARM. However, you can build an image yourself on a linux/arm64 or darwin/arm64 host machine.

git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
uv run download_deps.py
docker build -f Dockerfile.deps -t infiniflow/ragflow_deps .
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .