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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
:::tip NOTE If you have not installed Docker on your local machine (Windows, Mac, or Linux), see the Install Docker Engine guide. :::
Build a RAGFlow Docker Image
To build a RAGFlow Docker image from source code:
Git Clone the Repository
git clone https://github.com/infiniflow/ragflow.git
cd ragflow
Build the Docker Image
Navigate to the ragflow directory where the Dockerfile and other necessary files are located. Now you can build the Docker image using the provided Dockerfile. The command below specifies which Dockerfile to use and tags the image with a name for reference purpose.
Build and push multi-arch image infiniflow/ragflow:dev-slim
On a linux/amd64 host:
docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim-amd64 .
docker push infiniflow/ragflow:dev-slim-amd64
On a linux/arm64 host:
docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim-arm64 .
docker push infiniflow/ragflow:dev-slim-arm64
On a Linux host:
docker manifest create infiniflow/ragflow:dev-slim --amend infiniflow/ragflow:dev-slim-amd64 --amend infiniflow/ragflow:dev-slim-arm64
docker manifest push infiniflow/ragflow:dev-slim
This image is approximately 1 GB in size and relies on external LLM services, as it does not include deepdoc, embedding, or chat models.
Build and push multi-arch image infiniflow/ragflow:dev
On a linux/amd64 host:
pip3 install huggingface-hub
python3 download_deps.py
docker build -f Dockerfile -t infiniflow/ragflow:dev-amd64 .
docker push infiniflow/ragflow:dev-amd64
On a linux/arm64 host:
pip3 install huggingface-hub
python3 download_deps.py
docker build -f Dockerfile -t infiniflow/ragflow:dev-arm64 .
docker push infiniflow/ragflow:dev-arm64
On any linux host:
docker manifest create infiniflow/ragflow:dev --amend infiniflow/ragflow:dev-amd64 --amend infiniflow/ragflow:dev-arm64
docker manifest push infiniflow/ragflow:dev
This image's size is approximately 9 GB in size and can reference via either local CPU/GPU or an external LLM, as it includes deepdoc, embedding, and chat models.