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[DOC] We have no plan to maintain Docker images for ARM. Please build your … (#3808)

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…Docker image

### What problem does this PR solve?


### Type of change


- [x] Documentation Update

docs/guides/develop/build_docker_image.mdx CHANGED
@@ -21,10 +21,6 @@ A guide explaining how to build a RAGFlow Docker image from its source code. By
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  - Disk ≥ 50 GB
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  - Docker ≥ 24.0.0 & Docker Compose ≥ v2.26.1
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- :::tip NOTE
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- If you have not installed Docker on your local machine (Windows, Mac, or Linux), see the [Install Docker Engine](https://docs.docker.com/engine/install/) guide.
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- :::
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-
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  ## Build a Docker image
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  <Tabs
@@ -37,6 +33,10 @@ If you have not installed Docker on your local machine (Windows, Mac, or Linux),
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  This image is approximately 1 GB in size and relies on external LLM and embedding services.
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  ```bash
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  git clone https://github.com/infiniflow/ragflow.git
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  cd ragflow/
@@ -45,37 +45,23 @@ python3 download_deps.py
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  docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
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  ```
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  </TabItem>
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  <TabItem value="including">
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- ## Build a Docker image including embedding models
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-
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  This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.
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- ```bash
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- git clone https://github.com/infiniflow/ragflow.git
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- cd ragflow/
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- pip3 install huggingface-hub nltk
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- python3 download_deps.py
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- docker build -f Dockerfile -t infiniflow/ragflow:dev .
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- ```
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-
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- </TabItem>
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- <TabItem value="linux/arm64">
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-
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- ## 🔧 Build a Docker image for linux arm64
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-
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- We are currently unable to regularly build multi-arch images with CI and have no plans to publish arm64 images in the near future.
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- However, you can build an image yourself on a linux/arm64 host machine:
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  ```bash
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  git clone https://github.com/infiniflow/ragflow.git
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  cd ragflow/
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  pip3 install huggingface-hub nltk
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  python3 download_deps.py
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- docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
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  docker build -f Dockerfile -t infiniflow/ragflow:dev .
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  ```
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- </TabItem>
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  </Tabs>
 
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  - Disk &ge; 50 GB
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  - Docker &ge; 24.0.0 & Docker Compose &ge; v2.26.1
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  ## Build a Docker image
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  <Tabs
 
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  This image is approximately 1 GB in size and relies on external LLM and embedding services.
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+ :::tip NOTE
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+ 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.
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+ :::
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+
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  ```bash
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  git clone https://github.com/infiniflow/ragflow.git
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  cd ragflow/
 
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  docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
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  ```
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+
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  </TabItem>
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  <TabItem value="including">
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  This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.
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+ :::tip NOTE
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+ 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.
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+ :::
 
 
 
 
 
 
 
 
 
 
 
 
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  ```bash
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  git clone https://github.com/infiniflow/ragflow.git
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  cd ragflow/
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  pip3 install huggingface-hub nltk
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  python3 download_deps.py
 
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  docker build -f Dockerfile -t infiniflow/ragflow:dev .
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  ```
 
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+ </TabItem>
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  </Tabs>
docs/quickstart.mdx CHANGED
@@ -14,17 +14,21 @@ This quick start guide describes a general process from:
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  - Starting up a local RAGFlow server,
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  - Creating a knowledge base,
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  - Intervening with file parsing, to
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- - Establishing an AI chat based on your datasets.
 
 
 
 
 
 
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  ## Prerequisites
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- - CPU &ge; 4 cores;
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  - RAM &ge; 16 GB;
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  - Disk &ge; 50 GB;
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  - Docker &ge; 24.0.0 & Docker Compose &ge; v2.26.1.
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- > If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
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-
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  ## Start up the server
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  This section provides instructions on setting up the RAGFlow server on Linux. If you are on a different operating system, no worries. Most steps are alike.
 
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  - Starting up a local RAGFlow server,
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  - Creating a knowledge base,
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  - Intervening with file parsing, to
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+ - Establishing an AI chat based on your datasets.
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+
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+ :::danger IMPORTANT
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+ We officially support x86 CPU and Nvidia GPU, and this document offers instructions on deploying RAGFlow using Docker on x86 platforms. While we also test RAGFlow on ARM64 platforms, we do not plan to maintain RAGFlow Docker images for ARM.
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+
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+ If you are on an ARM platform, following [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a RAGFlow Docker image.
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+ :::
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  ## Prerequisites
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+ - CPU &ge; 4 cores (x86);
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  - RAM &ge; 16 GB;
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  - Disk &ge; 50 GB;
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  - Docker &ge; 24.0.0 & Docker Compose &ge; v2.26.1.
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  ## Start up the server
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  This section provides instructions on setting up the RAGFlow server on Linux. If you are on a different operating system, no worries. Most steps are alike.