Added two developer guide and removed from README ' builder docker image' and 'launch service from source' (#2590)

docs/references/CONTRIBUTING.md → CONTRIBUTING.md

@@ -1,16 +1,10 @@
----
-sidebar_position: 0
-slug: /contribution_guidelines
----
-
 # Contribution guidelines
 
-Thanks for wanting to contribute to RAGFlow. This document offers guidlines and major considerations for submitting your contributions. 
+This document offers guidlines and major considerations for submitting your contributions to RAGFlow.
 
 - To report a bug, file a [GitHub issue](https://github.com/infiniflow/ragflow/issues/new/choose) with us.
 - For further questions, you can explore existing discussions or initiate a new one in [Discussions](https://github.com/orgs/infiniflow/discussions).
 
-
 ## What you can contribute
 
 The list below mentions some contributions you can make, but it is not a complete list.
@@ -27,7 +21,7 @@ The list below mentions some contributions you can make, but it is not a complet
 ### General workflow
 
 1. Fork our GitHub repository.
-2. Clone your fork to your local machine: 
+2. Clone your fork to your local machine:
 `git clone git@github.com:<yourname>/ragflow.git`
 3. Create a local branch: 
 `git checkout -b my-branch`
@@ -39,14 +33,16 @@ The list below mentions some contributions you can make, but it is not a complet
 
 ### Before filing a PR
 
-- Consider splitting a large PR into multiple smaller, standalone PRs to keep a traceable development history. 
+- Consider splitting a large PR into multiple smaller, standalone PRs to keep a traceable development history.
 - Ensure that your PR addresses just one issue, or keep any unrelated changes small.
 - Add test cases when contributing new features. They demonstrate that your code functions correctly and protect against potential issues from future changes.
-### Describing your PR 
+
+### Describing your PR
 
 - Ensure that your PR title is concise and clear, providing all the required information.
-- Refer to a corresponding GitHub issue in your PR description if applicable. 
+- Refer to a corresponding GitHub issue in your PR description if applicable.
 - Include sufficient design details for *breaking changes* or *API changes* in your description.
 
 ### Reviewing & merging a PR
-- Ensure that your PR passes all Continuous Integration (CI) tests before merging it.
+
+Ensure that your PR passes all Continuous Integration (CI) tests before merging it.

README.md

@@ -42,8 +42,6 @@
 - 🔎 [System Architecture](#-system-architecture)
 - 🎬 [Get Started](#-get-started)
 - 🔧 [Configurations](#-configurations)
-- 🛠️ [Build RAGFlow image](#-build-ragflow-image)
-- 🛠️ [Launch service from source for development](#-launch-service-from-source-for-development)
 - 📚 [Documentation](#-documentation)
 - 📜 [Roadmap](#-roadmap)
 - 🏄 [Community](#-community)
@@ -188,7 +186,7 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 
    > See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.
 
-   _The show is now on!_
+   _The show is on!_
 
 ## 🔧 Configurations
 
@@ -210,79 +208,6 @@ Updates to the above configurations require a reboot of all containers to take e
 > $ docker-compose -f docker/docker-compose.yml up -d
 > ```
 
-## 🛠️ Build RAGFlow image
-
-To build the Docker images from source:
-
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-$ docker build -f Dockerfile.scratch -t infiniflow/ragflow:dev .
-```
-
-## 🛠️ Launch service from source for development
-
-To launch the service from source:
-
-1. Clone the repository: 
-
-   ```bash
-   $ git clone https://github.com/infiniflow/ragflow.git
-   $ cd ragflow/
-   ```
-
-2. Install all python dependencies in a newly created virtual environment named `.venv`:
-
-   ```bash
-   $ curl -sSL https://install.python-poetry.org | python3 -
-   $ $HOME/.local/bin/poetry install --sync --no-root
-   ```
-
-3. Copy the entry script and configure environment variables:
-   
-   ```bash
-   # Adjust configurations according to your actual situation (the following two export commands are newly added):
-   # - Comment out `LD_LIBRARY_PATH`, if it is configured.
-   # - Optional: Add Hugging Face mirror.
-   source ~/.venv/bin/activate
-   export PYTHONPATH=$(pwd)
-   export HF_ENDPOINT=https://hf-mirror.com
-   ```
-
-4. Launch the third-party services (MinIO, Elasticsearch, Redis, and MySQL):
-
-   ```bash
-   $ docker compose -f docker/docker-compose-base.yml up -d
-   ```
-
-5. Adjust configurations
-   Add the following line to `/etc/hosts` to resolve all hosts in `docker/service_conf.yaml` to `127.0.0.1`:
-
-   ```
-   127.0.0.1       es01 mysql minio redis
-   ```
-
-   Edit `docker/service_conf.yaml` to change mysql port to `5455` and es port to `1200`, as specified in `docker/.env`.
-
-6. Launch the RAGFlow backend service:
-   Comment out the `nginx` line in `docker/entrypoint.sh` and run the script:
-
-   ```bash
-   $ bash docker/entrypoint.sh
-   ```
-
-7. Launch the frontend service:
-
-   ```bash
-   $ cd web
-   $ npm install --force
-   $ vim .umirc.ts
-   # Update proxy.target to http://127.0.0.1:9380
-   $ npm run dev 
-   ```
-
-8. In your web browser, enter `http://127.0.0.1/`.
-
 ## 📚 Documentation
 
 - [Quickstart](https://ragflow.io/docs/dev/)
@@ -302,4 +227,4 @@ See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162)
 
 ## 🙌 Contributing
 
-RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](./docs/references/CONTRIBUTING.md) first.
+RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](./CONTRIBUTING.md) first.

README_ja.md

@@ -194,79 +194,6 @@
 > $ docker-compose up -d
 > ```
 
-## 🛠️ ソースからビルドする
-
-ソースからDockerイメージをビルドするには:
-
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-$ docker build -t infiniflow/ragflow:v0.11.0 .
-$ cd ragflow/docker
-$ chmod +x ./entrypoint.sh
-$ docker compose up -d
-```
-
-## 🛠️ ソースコードからサービスを起動する方法
-
-ソースコードからサービスを起動する場合は、以下の手順に従ってください:
-
-1. リポジトリをクローンします
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-```
-
-2. 仮想環境を作成します（AnacondaまたはMinicondaがインストールされていることを確認してください）
-```bash
-$ conda create -n ragflow python=3.11.0
-$ conda activate ragflow
-$ pip install -r requirements.txt
-```
-CUDAのバージョンが12.0以上の場合、以下の追加コマンドを実行してください：
-```bash
-$ pip uninstall -y onnxruntime-gpu
-$ pip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
-```
-
-3. エントリースクリプトをコピーし、環境変数を設定します
-```bash
-$ cp docker/entrypoint.sh .
-$ vi entrypoint.sh
-```
-以下のコマンドで Python のパスとragflowプロジェクトのパスを取得します：
-```bash
-$ which python
-$ pwd
-```
-
-`which python` の出力を `PY` の値として、`pwd` の出力を `PYTHONPATH` の値として設定します。
-
-`LD_LIBRARY_PATH` が既に設定されている場合は、コメントアウトできます。
-
-```bash
-# 実際の状況に応じて設定を調整してください。以下の二つの export は新たに追加された設定です
-PY=${PY}
-export PYTHONPATH=${PYTHONPATH}
-# オプション：Hugging Face ミラーを追加
-export HF_ENDPOINT=https://hf-mirror.com
-```
-
-4. 基本サービスを起動します
-```bash
-$ cd docker
-$ docker compose -f docker-compose-base.yml up -d 
-```
-
-5. 設定ファイルを確認します
-**docker/.env** 内の設定が**conf/service_conf.yaml**内の設定と一致していることを確認してください。**service_conf.yaml**内の関連サービスのIPアドレスとポートは、ローカルマシンのIPアドレスとコンテナが公開するポートに変更する必要があります。
-
-6. サービスを起動します
-```bash
-$ chmod +x ./entrypoint.sh
-$ bash ./entrypoint.sh
-```
-
 ## 📚 ドキュメンテーション
 
 - [Quickstart](https://ragflow.io/docs/dev/)
@@ -286,4 +213,4 @@ $ bash ./entrypoint.sh
 
 ## 🙌 コントリビュート
 
-RAGFlow はオープンソースのコラボレーションによって発展してきました。この精神に基づき、私たちはコミュニティからの多様なコントリビュートを受け入れています。 参加を希望される方は、まず [コントリビューションガイド](./docs/references/CONTRIBUTING.md)をご覧ください。
+RAGFlow はオープンソースのコラボレーションによって発展してきました。この精神に基づき、私たちはコミュニティからの多様なコントリビュートを受け入れています。 参加を希望される方は、まず [コントリビューションガイド](./CONTRIBUTING.md)をご覧ください。

README_ko.md

@@ -198,111 +198,6 @@
 > $ docker-compose up -d
 > ```
 
-## 🛠️ 소스에서 빌드하기
-
-Docker 이미지를 소스에서 빌드하려면:
-
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-$ docker build -t infiniflow/ragflow:dev .
-$ cd ragflow/docker
-$ chmod +x ./entrypoint.sh
-$ docker compose up -d
-```
-
-
-## 🛠️ 소스에서 서비스 시작하기
-
-서비스를 소스에서 시작하려면:
-
-1. 레포지토리를 클론하세요: 
-
-   ```bash
-   $ git clone https://github.com/infiniflow/ragflow.git
-   $ cd ragflow/
-   ```
-
-2. 가상 환경을 생성하고, Anaconda 또는 Miniconda가 설치되어 있는지 확인하세요:
-   ```bash
-   $ conda create -n ragflow python=3.11.0
-   $ conda activate ragflow
-   $ pip install -r requirements.txt
-   ```
-   
-   ```bash
-   # CUDA 버전이 12.0보다 높은 경우, 다음 명령어를 추가로 실행하세요:
-   $ pip uninstall -y onnxruntime-gpu
-   $ pip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
-   ```
-
-3. 진입 스크립트를 복사하고 환경 변수를 설정하세요:
-   ```bash
-   # 파이썬 경로를 받아옵니다:
-   $ which python
-   # RAGFlow 프로젝트 경로를 받아옵니다:
-   $ pwd
-   ```
-   
-   ```bash
-   $ cp docker/entrypoint.sh .
-   $ vi entrypoint.sh
-   ```
-
-   ```bash
-   # 실제 상황에 맞게 설정 조정하기 (다음 두 개의 export 명령어는 새로 추가되었습니다):
-   # - `which python`의 결과를 `PY`에 할당합니다.
-   # - `pwd`의 결과를 `PYTHONPATH`에 할당합니다.
-   # - `LD_LIBRARY_PATH`가 설정되어 있는 경우 주석 처리합니다.
-   # - 선택 사항: Hugging Face 미러 추가.
-   PY=${PY}
-   export PYTHONPATH=${PYTHONPATH}
-   export HF_ENDPOINT=https://hf-mirror.com
-   ```
-
-4. 다른 서비스(MinIO, Elasticsearch, Redis, MySQL)를 시작하세요:
-   ```bash
-   $ cd docker
-   $ docker compose -f docker-compose-base.yml up -d 
-   ```
-
-5. 설정 파일을 확인하여 다음 사항을 확인하세요:
-  - **docker/.env**의 설정이 **conf/service_conf.yaml**의 설정과 일치하는지 확인합니다.
-  - **service_conf.yaml**의 관련 서비스에 대한 IP 주소와 포트가 로컬 머신의 IP 주소와 컨테이너에서 노출된 포트와 일치하는지 확인합니다.
-
-
-6. RAGFlow 백엔드 서비스를 시작합니다:
-
-   ```bash
-   $ chmod +x ./entrypoint.sh
-   $ bash ./entrypoint.sh
-   ```
-
-7. 프론트엔드 서비스를 시작합니다:
-
-   ```bash
-   $ cd web
-   $ npm install --registry=https://registry.npmmirror.com --force
-   $ vim .umirc.ts
-   # proxy.target을 http://127.0.0.1:9380로 업데이트합니다.
-   $ npm run dev 
-   ```
-
-8. 프론트엔드 서비스를 배포합니다:
-
-   ```bash
-   $ cd web
-   $ npm install --registry=https://registry.npmmirror.com --force
-   $ umi build
-   $ mkdir -p /ragflow/web
-   $ cp -r dist /ragflow/web
-   $ apt install nginx -y
-   $ cp ../docker/nginx/proxy.conf /etc/nginx
-   $ cp ../docker/nginx/nginx.conf /etc/nginx
-   $ cp ../docker/nginx/ragflow.conf /etc/nginx/conf.d
-   $ systemctl start nginx
-   ```
-
 ## 📚 문서
 
 - [Quickstart](https://ragflow.io/docs/dev/)
@@ -322,4 +217,4 @@ $ docker compose up -d
 
 ## 🙌 컨트리뷰션
 
-RAGFlow는 오픈소스 협업을 통해 발전합니다. 이러한 정신을 바탕으로, 우리는 커뮤니티의 다양한 기여를 환영합니다. 참여하고 싶으시다면, 먼저 [가이드라인](./docs/references/CONTRIBUTING.md)을 검토해 주세요.
+RAGFlow는 오픈소스 협업을 통해 발전합니다. 이러한 정신을 바탕으로, 우리는 커뮤니티의 다양한 기여를 환영합니다. 참여하고 싶으시다면, 먼저 [가이드라인](./CONTRIBUTING.md)을 검토해 주세요.

README_zh.md

@@ -192,108 +192,6 @@
 > $ docker compose -f docker-compose-CN.yml up -d
 > ```
 
-## 🛠️ 源码编译、安装 Docker 镜像
-
-如需从源码安装 Docker 镜像：
-
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-$ docker build -t infiniflow/ragflow:v0.11.0 .
-$ cd ragflow/docker
-$ chmod +x ./entrypoint.sh
-$ docker compose up -d
-```
-
-## 🛠️ 源码启动服务
-
-如需从源码启动服务，请参考以下步骤：
-
-1. 克隆仓库
-
-```bash
-$ git clone https://github.com/infiniflow/ragflow.git
-$ cd ragflow/
-```
-
-2. 创建虚拟环境（确保已安装 Anaconda 或 Miniconda）
-
-```bash
-$ conda create -n ragflow python=3.11.0
-$ conda activate ragflow
-$ pip install -r requirements.txt
-```
-如果 cuda > 12.0，需额外执行以下命令：
-```bash
-$ pip uninstall -y onnxruntime-gpu
-$ pip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
-```
-
-3. 拷贝入口脚本并配置环境变量
-
-```bash
-$ cp docker/entrypoint.sh .
-$ vi entrypoint.sh
-```
-使用以下命令获取python路径及ragflow项目路径：
-```bash
-$ which python
-$ pwd
-```
-
-将上述 `which python` 的输出作为 `PY` 的值，将 `pwd` 的输出作为 `PYTHONPATH` 的值。
-
-`LD_LIBRARY_PATH` 如果环境已经配置好，可以注释掉。
-
-```bash
-# 此处配置需要按照实际情况调整，两个 export 为新增配置
-PY=${PY}
-export PYTHONPATH=${PYTHONPATH}
-# 可选：添加 Hugging Face 镜像
-export HF_ENDPOINT=https://hf-mirror.com
-```
-
-4. 启动基础服务
-
-```bash
-$ cd docker
-$ docker compose -f docker-compose-base.yml up -d 
-```
-
-5. 检查配置文件
-确保**docker/.env**中的配置与**conf/service_conf.yaml**中配置一致， **service_conf.yaml**中相关服务的IP地址与端口应该改成本机IP地址及容器映射出来的端口。
-
-6. 启动服务
-
-```bash
-$ chmod +x ./entrypoint.sh
-$ bash ./entrypoint.sh
-```
-
-7. 启动WebUI服务
-
-```bash
-$ cd web
-$ npm install --registry=https://registry.npmmirror.com --force
-$ vim .umirc.ts
-# 修改proxy.target为http://127.0.0.1:9380
-$ npm run dev 
-```
-
-8. 部署WebUI服务
-
-```bash
-$ cd web
-$ npm install --registry=https://registry.npmmirror.com --force
-$ umi build
-$ mkdir -p /ragflow/web
-$ cp -r dist /ragflow/web
-$ apt install nginx -y
-$ cp ../docker/nginx/proxy.conf /etc/nginx
-$ cp ../docker/nginx/nginx.conf /etc/nginx
-$ cp ../docker/nginx/ragflow.conf /etc/nginx/conf.d
-$ systemctl start nginx
-```
 ## 📚 技术文档
 
 - [Quickstart](https://ragflow.io/docs/dev/)
@@ -313,7 +211,7 @@ $ systemctl start nginx
 
 ## 🙌 贡献指南
 
-RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们欢迎来自社区的各种贡献。如果您有意参与其中,请查阅我们的 [贡献者指南](./docs/references/CONTRIBUTING.md) 。
+RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们欢迎来自社区的各种贡献。如果您有意参与其中,请查阅我们的 [贡献者指南](./CONTRIBUTING.md) 。
 
 ## 🤝 商务合作
 

docs/guides/_category_.json

@@ -1,8 +1,8 @@
 {
-  "label": "User Guides",
+  "label": "Guides",
   "position": 2,
   "link": {
     "type": "generated-index",
-    "description": "RAGFlow User Guides"
+    "description": "Guides for RAGFlow users and developers."
   }
 }

docs/guides/agentic_rag/_category_.json

@@ -3,6 +3,6 @@
   "position": 3,
   "link": {
     "type": "generated-index",
-    "description": "RAGFlow v0.8.0 introduces an agent mechanism, featuring a no-code workflow editor on the front end and a comprehensive graph-based task orchestration framework on the back end."
+    "description": "RAGFlow v0.8.0 introduces an agent mechanism, featuring a no-code workflow editor on the front end and a comprehensive graph-based task orchestration framework on the backend."
   }
 }

docs/guides/agentic_rag/agent_introduction.md

@@ -53,9 +53,9 @@ Please review the flowing description of the RAG-specific components before you
 | -------------- | ------------------------------------------------------------ |
 | **Retrieval**  | A component that retrieves information from specified knowledge bases and returns 'Empty response' if no information is found. Ensure the correct knowledge bases are selected. |
 | **Generate**   | A component that prompts the LLM to generate responses. You must ensure the prompt is set correctly. |
-| **Answer**     | A component that serves as the interface between human and the bot, receiving user inputs and displaying the agent's responses. |
+| **Interact**   | A component that serves as the interface between human and the bot, receiving user inputs and displaying the agent's responses. |
 | **Categorize** | A component that uses the LLM to classify user inputs into predefined categories. Ensure you specify the name, description, and examples for each category, along with the corresponding next component. |
-| **Message**    | A component that sends out a static message. If multiple messages are supplied, it randomly selects one to send. Ensure its downstream is **Answer**, the interface component. |
+| **Message**    | A component that sends out a static message. If multiple messages are supplied, it randomly selects one to send. Ensure its downstream is **Interact**, the interface component. |
 | **Relevant**   | A component that uses the LLM to assess whether the upstream output is relevant to the user's latest query. Ensure you specify the next component for each judge result. |
 | **Rewrite**    | A component that refines a user query if it fails to retrieve relevant information from the knowledge base. It repeats this process until the predefined looping upper limit is reached. Ensure its upstream is **Relevant** and downstream is **Retrieval**. |
 | **Keyword**    | A component that retrieves top N search results from wikipedia.org. Ensure the TopN value is set properly before use. |
@@ -63,8 +63,8 @@ Please review the flowing description of the RAG-specific components before you
 :::caution NOTE
 
 - Ensure **Rewrite**'s upstream component is **Relevant** and downstream component is **Retrieval**.
-- Ensure the downstream component of **Message** is **Answer**.
-- The downstream component of **Begin** is always **Answer**.
+- Ensure the downstream component of **Message** is **Interact**.
+- The downstream component of **Begin** is always **Interact**.
 
 :::
 

docs/guides/agentic_rag/general_purpose_chatbot.md

@@ -26,7 +26,7 @@ To create a general-purpose chatbot agent using our template:
 3. On the **agent template** page, hover over the card on **General-purpose chatbot** and click **Use this template**.  
    *You are now directed to the **no-code workflow editor** page.*
 
-   ![workflow_editor](https://github.com/user-attachments/assets/9fc6891c-7784-43b8-ab4a-3b08a9e551c4)
+   ![workflow_editor](https://github.com/user-attachments/assets/52e7dc62-4bf5-4fbb-ab73-4a6e252065f0)
 
 :::tip NOTE
 RAGFlow's no-code editor spares you the trouble of coding, making agent development effortless.
@@ -40,10 +40,9 @@ Here’s a breakdown of each component and its role and requirements in the chat
   - Function: Sets the opening greeting for the user.
   - Purpose: Establishes a welcoming atmosphere and prepares the user for interaction.
 
-- **Answer**
+- **Interact**
   - Function: Serves as the interface between human and the bot.
   - Role: Acts as the downstream component of **Begin**.  
-  - Note: Though named "Answer", it does not engage with the LLM.
 
 - **Retrieval**
   - Function: Retrieves information from specified knowledge base(s).
@@ -78,7 +77,7 @@ Here’s a breakdown of each component and its role and requirements in the chat
 
 4. Click **Relevant** to review or change its settings:  
    *You may retain the current settings, but feel free to experiment with changes to understand how the agent operates.*
-   ![relevant_settings](https://github.com/user-attachments/assets/f582cc1c-0dd5-499c-813a-294dbfb941dd)
+   ![relevant_settings](https://github.com/user-attachments/assets/9ff7fdd8-7a69-4ee2-bfba-c7fb8029150f)
 
 5. Click **Rewrite** to select a different model for query rewriting or update the maximum loop times for query rewriting:  
    ![choose_model](https://github.com/user-attachments/assets/2bac1d6c-c4f1-42ac-997b-102858c3f550)

docs/guides/develop/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "Develop",
+  "position": 10,
+  "link": {
+    "type": "generated-index",
+    "description": "Guides for Hardcore Developers"
+  }
+}

docs/guides/develop/build_docker_image.md

@@ -0,0 +1,43 @@
+---
+sidebar_position: 1
+slug: /build_docker_image
+---
+
+# 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](https://docs.docker.com/engine/install/) guide.
+:::
+
+## Build a RAGFlow Docker Image
+
+To build a RAGFlow Docker image from source code:
+
+### Git Clone the Repository
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+```
+
+### 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 tages the image with a name for reference purpose.
+
+```bash
+cd ragflow/
+docker build -f Dockerfile.scratch -t infiniflow/ragflow:dev .
+```

docs/guides/develop/launch_ragflow_from_source.md

@@ -0,0 +1,129 @@
+---
+sidebar_position: 2
+slug: /launch_ragflow_from_source
+---
+
+# Launch the RAGFlow Service from Source 
+
+A guide explaining how to set up a RAGFlow service from its source code. By following this guide, you'll be able to debug using the source code.
+
+## Target Audience
+
+Developers who have added new features or modified existing code and wish to debug using the source code, *provided that* their machine has the target deployment environment set up.
+
+## 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](https://docs.docker.com/engine/install/) guide.
+:::
+
+## Launch the Service from Source
+
+To launch the RAGFlow service from source code:
+
+### Clone the RAGFlow Repository
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+```
+
+### Install Python dependencies
+
+1. Install Poetry:
+   
+   ```bash
+   curl -sSL https://install.python-poetry.org | python3 -
+   ```
+
+2. Configure Poetry:
+
+   ```bash
+   export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
+   ```
+
+3. Install Python dependencies:
+
+   ```bash
+   ~/.local/bin/poetry install --sync --no-root
+   ```
+   *A virtual environment named `.venv` is created, and all Python dependencies are installed into the new environment.*
+
+### Launch Third-party Services
+
+The following command launches the 'base' services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:
+
+```bash
+docker compose -f docker/docker-compose-base.yml up -d
+```
+
+### Update `host` and `port` Settings for Third-party Services
+
+1. Add the following line to `/etc/hosts` to resolve all hosts specified in **docker/service_conf.yaml** to `127.0.0.1`:
+
+   ```
+   127.0.0.1       es01 mysql minio redis
+   ```
+
+2. In **docker/service_conf.yaml**, update mysql port to `5455` and es port to `1200`, as specified in **docker/.env**.
+
+### Launch the RAGFlow Backend Service
+
+1. Comment out the `nginx` line in **docker/entrypoint.sh**.
+
+   ```
+   # /usr/sbin/nginx
+   ```
+
+2. Activate the Python virtual environment:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   ```
+
+3. **Optional:** If you cannot access HuggingFace, set the HF_ENDPOINT environment variable to use a mirror site:
+ 
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+
+4. Run the **entrypoint.sh** script to launch the backend service:
+
+   ```
+   bash docker/entrypoint.sh
+   ```
+
+### Launch the RAGFlow frontend service
+
+1. Navigate to the `web` directory and install the frontend dependencies:
+
+   ```bash
+   cd web
+   npm install --force
+   ```
+
+2. Update `proxy.target` in **.umirc.ts** to `http://127.0.0.1:9380`:
+
+   ```bash
+   vim .umirc.ts
+   ```
+
+3. Start up the RAGFlow frontend service:
+
+   ```bash
+   npm run dev 
+   ```  
+
+   *The following message appears, showing the IP address and port number of your frontend service:*  
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+
+### Access the RAGFlow service
+
+In your web browser, enter `http://127.0.0.1:<PORT>/`, ensuring the port number matches that shown in the screenshot above.

docs/references/_category_.json

@@ -1,8 +1,8 @@
 {
   "label": "References",
-  "position": 3,
+  "position": 4,
   "link": {
     "type": "generated-index",
-    "description": "RAGFlow References"
+    "description": "Miscellaneous References"
   }
 }