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.
- Testers looking 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
Build a Docker image
- Build a Docker image without embedding models
- Build a Docker image including embedding models
This image is approximately 2 GB in size and relies on external LLM and embedding services.
While we also test RAGFlow on ARM64 platforms, we do not plan to 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 .
This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.
While we also test RAGFlow on ARM64 platforms, we do not plan to 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/
pip3 install huggingface_hub nltk
python3 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 .