docs: Add instructions for launching service from source (#619)

This commit includes detailed steps for setting up and launching the
service directly from the source code. It covers cloning the repository,
setting up a virtual environment, configuring environment variables, and
starting the service using Docker. This update ensures that developers
have clear guidance on how to get the service running in a development
environment.

### What problem does this PR solve?

_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._

### Type of change
- [x] Documentation Update

README.md

@@ -186,6 +186,66 @@ $ chmod +x ./entrypoint.sh
 $ docker compose up -d
 ```
 
+## 🛠️ Launch Service from Source
+
+To launch the service from source, please follow these steps:
+
+1. Clone the repository
+```bash
+$ git clone https://github.com/infiniflow/ragflow.git
+$ cd ragflow/
+```
+
+2. Create a virtual environment (ensure Anaconda or Miniconda is installed)
+```bash
+$ conda create -n ragflow python=3.11.0
+$ conda activate ragflow
+$ pip install -r requirements.txt
+```
+If CUDA version is greater than 12.0, execute the following additional commands:
+```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. Copy the entry script and configure environment variables
+```bash
+$ cp docker/entrypoint.sh .
+$ vi entrypoint.sh
+```
+Use the following commands to obtain the Python path and the ragflow project path:
+```bash
+$ which python
+$ pwd
+```
+
+Set the output of `which python` as the value for `PY` and the output of `pwd` as the value for `PYTHONPATH`.
+
+If `LD_LIBRARY_PATH` is already configured, it can be commented out.
+
+```bash
+# Adjust configurations according to your actual situation; the two export commands are newly added.
+PY=${PY}
+export PYTHONPATH=${PYTHONPATH}
+# Optional: Add Hugging Face mirror
+export HF_ENDPOINT=https://hf-mirror.com
+```
+
+4. Start the base services
+```bash
+$ cd docker
+$ docker compose -f docker-compose-base.yml up -d 
+```
+
+5. Check the configuration files
+Ensure that the settings in **docker/.env** match those in **conf/service_conf.yaml**. The IP addresses and ports for related services in **service_conf.yaml** should be changed to the local machine IP and ports exposed by the container.
+
+6. Launch the service
+```bash
+$ chmod +x ./entrypoint.sh
+$ bash ./entrypoint.sh
+```
+
 ## 📚 Documentation
 
 - [FAQ](./docs/faq.md)

README_ja.md

@@ -186,6 +186,66 @@ $ 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
 
 - [FAQ](./docs/faq.md)

README_zh.md

@@ -186,6 +186,66 @@ $ 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
+```
+
 ## 📚 技术文档
 
 - [FAQ](./docs/faq.md)