ragflow / docs /guides /develop /build_docker_image.mdx
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[DOC] We have no plan to maintain Docker images for ARM. Please build your … (#3808)
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---
sidebar_position: 1
slug: /build_docker_image
---
# Build a RAGFlow Docker Image
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
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
<Tabs
defaultValue="without"
values={[
{label: 'Build a Docker image without embedding models', value: 'without'},
{label: 'Build a Docker image including embedding models', value: 'including'}
]}>
<TabItem value="without">
This image is approximately 1 GB in size and relies on external LLM and embedding services.
:::tip NOTE
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.
:::
```bash
git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
pip3 install huggingface-hub nltk
python3 download_deps.py
docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
```
</TabItem>
<TabItem value="including">
This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.
:::tip NOTE
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.
:::
```bash
git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
pip3 install huggingface-hub nltk
python3 download_deps.py
docker build -f Dockerfile -t infiniflow/ragflow:dev .
```
</TabItem>
</Tabs>