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Updated Build Docker Image (#2706)
### What problem does this PR solve? ### Type of change - [x] Documentation Update
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@ -42,8 +42,8 @@
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- 🔎 [System Architecture](#-system-architecture)
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- 🎬 [Get Started](#-get-started)
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- 🔧 [Configurations](#-configurations)
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- 🪛 [Build the docker image without embedding models](#-build-the-docker-image-without-embedding-models)
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- 🪚 [Build the docker image including embedding models](#-build-the-docker-image-including-embedding-models)
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- 🔧 [Build a docker image without embedding models](#-build-the-docker-image-without-embedding-models)
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- 🔧 [Build a docker image including embedding models](#-build-the-docker-image-including-embedding-models)
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- 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)
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- 📚 [Documentation](#-documentation)
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- 📜 [Roadmap](#-roadmap)
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@ -213,7 +213,7 @@ Updates to the above configurations require a reboot of all containers to take e
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> $ docker-compose -f docker/docker-compose.yml up -d
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> ```
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## 🪛 Build the Docker image without embedding models
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## 🔧 Build a Docker image without embedding models
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This image is approximately 1 GB in size and relies on external LLM and embedding services.
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@ -225,7 +225,7 @@ 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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## 🪚 Build the Docker image including embedding models
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## 🔧 Build a Docker image including embedding models
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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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@ -195,7 +195,7 @@
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> $ docker-compose up -d
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> ```
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## 🪛 ソースコードでDockerイメージを作成（埋め込みモデルなし）
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## 🔧 ソースコードでDockerイメージを作成（埋め込みモデルなし）
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この Docker イメージのサイズは約 1GB で、外部の大モデルと埋め込みサービスに依存しています。
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@ -207,7 +207,7 @@ 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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## 🪚 ソースコードをコンパイルしたDockerイメージ（埋め込みモデルを含む）
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## 🔧 ソースコードをコンパイルしたDockerイメージ（埋め込みモデルを含む）
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この Docker のサイズは約 9GB で、埋め込みモデルを含むため、外部の大モデルサービスのみが必要です。
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@ -197,7 +197,7 @@
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> $ docker-compose up -d
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> ```
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## 🪛 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함하지 않음)
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## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함하지 않음)
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이 Docker 이미지의 크기는 약 1GB이며, 외부 대형 모델과 임베딩 서비스에 의존합니다.
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@ -209,7 +209,7 @@ 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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## 🪚 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
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## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
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이 Docker의 크기는 약 9GB이며, 이미 임베딩 모델을 포함하고 있으므로 외부 대형 모델 서비스에만 의존하면 됩니다.
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@ -197,7 +197,7 @@
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> $ docker compose -f docker-compose.yml up -d
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> ```
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## 🪛 源码编译 Docker 镜像（不含 embedding 模型）
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## 🔧 源码编译 Docker 镜像（不含 embedding 模型）
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本 Docker 镜像大小约 1 GB 左右并且依赖外部的大模型和 embedding 服务。
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@ -209,7 +209,7 @@ 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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## 🪚 源码编译 Docker 镜像（包含 embedding 模型）
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## 🔧 源码编译 Docker 镜像（包含 embedding 模型）
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本 Docker 大小约 9 GB 左右。由于已包含 embedding 模型，所以只需依赖外部的大模型服务即可。
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@ -1,87 +0,0 @@
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---
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sidebar_position: 1
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slug: /build_docker_image
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---
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# Build a RAGFlow Docker Image
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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.
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## Target Audience
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- Developers who have added new features or modified the existing code and require a Docker image to view and debug their changes.
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- Testers looking to explore the latest features of RAGFlow in a Docker image.
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## Prerequisites
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- CPU ≥ 4 cores
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- RAM ≥ 16 GB
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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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## Build a RAGFlow Docker Image
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To build a RAGFlow Docker image from source code:
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### Git Clone the Repository
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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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```
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### Build the Docker Image
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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.
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#### Build and push multi-arch image `infiniflow/ragflow:dev-slim`
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On a `linux/amd64` host:
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```bash
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docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim-amd64 .
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docker push infiniflow/ragflow:dev-slim-amd64
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```
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On a `linux/arm64` host:
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```bash
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docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim-arm64 .
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docker push infiniflow/ragflow:dev-slim-arm64
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```
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On a Linux host:
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```bash
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docker manifest create infiniflow/ragflow:dev-slim --amend infiniflow/ragflow:dev-slim-amd64 --amend infiniflow/ragflow:dev-slim-arm64
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docker manifest push infiniflow/ragflow:dev-slim
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```
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This image is approximately 1 GB in size and relies on external LLM services, as it does not include deepdoc, embedding, or chat models.
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#### Build and push multi-arch image `infiniflow/ragflow:dev`
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On a `linux/amd64` host:
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```bash
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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-amd64 .
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docker push infiniflow/ragflow:dev-amd64
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```
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On a `linux/arm64` host:
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```bash
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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-arm64 .
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docker push infiniflow/ragflow:dev-arm64
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```
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On any linux host:
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```bash
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docker manifest create infiniflow/ragflow:dev --amend infiniflow/ragflow:dev-amd64 --amend infiniflow/ragflow:dev-arm64
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docker manifest push infiniflow/ragflow:dev
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```
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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.
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64
docs/guides/develop/build_docker_image.mdx
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64
docs/guides/develop/build_docker_image.mdx
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@ -0,0 +1,64 @@
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---
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sidebar_position: 1
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slug: /build_docker_image
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---
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# Build a RAGFlow Docker Image
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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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.
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## Target Audience
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- Developers who have added new features or modified the existing code and require a Docker image to view and debug their changes.
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- Testers looking to explore the latest features of RAGFlow in a Docker image.
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## Prerequisites
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- CPU ≥ 4 cores
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- RAM ≥ 16 GB
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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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## Build a Docker image
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<Tabs
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defaultValue="without"
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values={[
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{label: 'Build a Docker image without embedding models', value: 'without'},
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{label: 'Build a Docker image including embedding models', value: 'including'}
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]}>
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<TabItem value="without">
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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/
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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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```
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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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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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</TabItem>
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</Tabs>
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