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Posted to issues@hugegraph.apache.org by "weijinglin (via GitHub)" <gi...@apache.org> on 2025/05/28 07:02:59 UTC

[PR] docs: add Docker deployment instructions for HugeGraph-AI [incubator-hugegraph-doc]

weijinglin opened a new pull request, #403:
URL: https://github.com/apache/incubator-hugegraph-doc/pull/403

   ## Changes
   - Added Docker deployment instructions to `hugegraph-ai.md` documentation
   - Added detailed information about two Docker images:
     - hugegraph/rag: For building and running RAG functionality
     - hugegraph/rag-bin: Binary version for more stable performance
   - Added complete Docker deployment steps including:
     - Image pulling
     - Container startup
     - Interactive demo running
     - Access methods
   
   ## Related Issues
   <!-- If there are related issues, please link them here -->
   
   ## Testing
   - [x] Verified document formatting
   - [x] Verified consistency between Chinese and English documentation
   - [x] Verified all links are accessible
   
   ## Notes
   - This is a documentation update only, no code changes
   - Maintains consistency with existing documentation style
   - Added Docker deployment as a new section in the preparation steps
   - Updated step numbering to accommodate the new section
   
   ## Additional Context
   The Docker deployment instructions provide users with an alternative way to quickly deploy and use HugeGraph-AI, especially for those who prefer containerized environments.
   
   ## Difference
   ![image](https://github.com/user-attachments/assets/76db53c6-3c2d-4fc6-a778-b79e75356bbf)
   


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Re: [PR] docs: add Docker deployment instructions for HugeGraph-AI [incubator-hugegraph-doc]

Posted by "imbajin (via GitHub)" <gi...@apache.org>.
imbajin commented on code in PR #403:
URL: https://github.com/apache/incubator-hugegraph-doc/pull/403#discussion_r2111180847


##########
content/cn/docs/quickstart/hugegraph-ai.md:
##########
@@ -16,40 +16,75 @@ hugegraph-ai 旨在探索 HugeGraph 与人工智能（AI）的融合，包括与
 
 1. 启动HugeGraph数据库，可以通过 [Docker](https://hub.docker.com/r/hugegraph/hugegraph)/[Binary Package](https://hugegraph.apache.org/docs/download/download/) 运行它。  
     请参阅详细[文档](https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#31-use-docker-container-convenient-for-testdev)以获取更多指导
-2. 克隆项目
+
+2. **Docker部署**  
+   如果您希望使用Docker来部署HugeGraph-AI，请按照以下步骤操作：
+   - 确保您已安装Docker。
+   - 在项目根目录下，使用以下命令拉取远端Docker容器镜像，我们提供了两种容器镜像：
+     - **镜像1**：[hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags)  
+       该镜像用于构建和运行HugeGraph-AI的RAG（检索增强生成）功能，适合需要快速部署和使用的用户。
+     - **镜像2**：[hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags)  
+       该镜像提供了二进制版本的HugeGraph-AI，适合需要更稳定和高效性能的用户。
+   - 使用以下命令拉取远端Docker容器镜像：
+     ```bash
+     docker pull hugegraph/rag:latest # 拉取镜像1
+     docker pull hugegraph/rag-bin:latest # 拉取镜像2
+     ```
+   - 使用以下指令启动Docker容器：
+     ```bash
+     docker run -it --name rag -p 8001:8001 hugegraph/rag bash
+     docker run -it --name rag -p 8001:8001 hugegraph/rag-bin bash
+     ```
+   - 启动 **Graph RAG** 的 gradio 交互 demo，可以使用以下命令运行：
+     ```bash
+     python ./src/hugegraph_llm/demo/rag_demo/app.py # 在镜像一创建的容器中启动demo
+     ```
+     ```bash
+     ./app.dist/app.bin # 在镜像二创建的容器中启动demo
+     ```
+   - 启动后，您可以通过访问 http://localhost:8001 来使用HugeGraph-AI的交互式界面。
+
+3. 克隆项目
     ```bash
     git clone https://github.com/apache/incubator-hugegraph-ai.git
     ```
-3. 安装 [hugegraph-python-client](../hugegraph-python-client) 和 [hugegraph_llm](src/hugegraph_llm)
+
+4. 安装 [hugegraph-python-client](../hugegraph-python-client) 和 [hugegraph_llm](src/hugegraph_llm)
     ```bash
     cd ./incubator-hugegraph-ai # better to use virtualenv (source venv/bin/activate) 
     pip install ./hugegraph-python-client
     pip install -r ./hugegraph-llm/requirements.txt
     ```
-4. 进入项目目录
+
+5. 进入项目目录
     ```bash
     cd ./hugegraph-llm/src
     ```
-5. 启动 **Graph RAG** 的 gradio 交互 demo，可以使用以下命令运行，启动后打开 http://127.0.0.1:8001
+
+6. 启动 **Graph RAG** 的 gradio 交互 demo，可以使用以下命令运行，启动后打开 http://127.0.0.1:8001
     ```bash
     python3 -m hugegraph_llm.demo.rag_demo.app
     ```
     默认主机为 `0.0.0.0` ，端口为 `8001` 。您可以通过传递命令行参数 `--host` 和 `--port` 来更改它们。
     ```bash
     python3 -m hugegraph_llm.demo.rag_demo.app --host 127.0.0.1 --port 18001
     ```
-6. 启动 **Text2Gremlin** 的 gradio 交互演示，可以使用以下命令运行，启动后打开 http://127.0.0.1:8002 ，您还可以按上述方式更改默认主机 `0.0.0.0` 和端口 `8002` 。(🚧ing)
+
+7. 启动 **Text2Gremlin** 的 gradio 交互演示，可以使用以下命令运行，启动后打开 http://127.0.0.1:8002 ，您还可以按上述方式更改默认主机 `0.0.0.0` 和端口 `8002` 。(🚧ing)
     ```bash
     python3 -m hugegraph_llm.demo.gremlin_generate_web_demo
    ```
-7. 在运行演示程序后，配置文件文件将被删除。`.env ` 将自动生成在 `hugegraph-llm/.env` 路径下。此外，还有一个与 prompt 相关的配置文件 `config_prompt.yaml` 。也会在`hugegraph-llm/src/hugegraph_llm/resources/demo/config_prompt.yaml`路径下生成。
+
+8. 在运行演示程序后，配置文件文件将被删除。`.env ` 将自动生成在 `hugegraph-llm/.env` 路径下。此外，还有一个与 prompt 相关的配置文件 `config_prompt.yaml` 。也会在`hugegraph-llm/src/hugegraph_llm/resources/demo/config_prompt.yaml`路径下生成。

Review Comment:
   ```suggestion
   8. 在运行演示程序后，配置文件将被删除。`.env ` 将自动生成在 `hugegraph-llm/.env` 路径。此外，还有一个与 prompt 相关的配置文件 `config_prompt.yaml` 。也会在`hugegraph-llm/src/hugegraph_llm/resources/demo/config_prompt.yaml`路径下生成。
   ```



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Re: [PR] docs: add Docker deployment instructions for HugeGraph-AI [incubator-hugegraph-doc]

Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #403:
URL: https://github.com/apache/incubator-hugegraph-doc/pull/403#discussion_r2111124690


##########
content/en/docs/quickstart/hugegraph-ai.md:
##########
@@ -9,92 +9,110 @@ hugegraph-ai aims to explore the integration of HugeGraph and artificial intelli
 with large models, integration with graph machine learning components, etc., to provide comprehensive support for developers to use HugeGraph's AI capabilities in projects.
 
 ## 2 Environment Requirements
-- python 3.9+ 
-- hugegraph-server 1.2+
+- Python 3.9+ (better to use `3.10`)  
+- HugeGraph Server 1.3+
 
 ## 3 Preparation
 
 1. Start the HugeGraph database, you can run it via [Docker](https://hub.docker.com/r/hugegraph/hugegraph)/[Binary Package](https://hugegraph.apache.org/docs/download/download/).  
     Refer to detailed [doc](https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#31-use-docker-container-convenient-for-testdev) for more guidance
 
-2. Clone this project
+2. **Docker Deployment**  
+   If you wish to deploy HugeGraph-AI using Docker, follow these steps:
+   - Ensure you have Docker installed.
+   - In the project root directory, use the following command to pull the remote Docker container images. We provide two container images:
+     - **Image 1**: [hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags)  
+       This image is used to build and run the RAG (Retrieval-Augmented Generation) functionality of HugeGraph-AI, suitable for users who need quick deployment and usage.
+     - **Image 2**: [hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags)  
+       This image provides a binary version of HugeGraph-AI, suitable for users who require more stable and efficient performance.
+   - Use the following command to pull the remote Docker container images:
+     ```bash
+     docker pull hugegraph/rag:latest # Pull Image 1
+     docker pull hugegraph/rag-bin:latest # Pull Image 2
+     ```
+   - Use the following command to start the Docker container:
+     ```bash
+     docker run -it --name rag -p 8001:8001 hugegraph/rag bash

Review Comment:
   Using the same container name 'rag' for both Docker images may lead to conflicts if the containers are run concurrently. Consider using unique container names for each Docker image to avoid potential runtime issues.



##########
content/cn/docs/quickstart/hugegraph-ai.md:
##########
@@ -16,40 +16,75 @@ hugegraph-ai 旨在探索 HugeGraph 与人工智能（AI）的融合，包括与
 
 1. 启动HugeGraph数据库，可以通过 [Docker](https://hub.docker.com/r/hugegraph/hugegraph)/[Binary Package](https://hugegraph.apache.org/docs/download/download/) 运行它。  
     请参阅详细[文档](https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#31-use-docker-container-convenient-for-testdev)以获取更多指导
-2. 克隆项目
+
+2. **Docker部署**  
+   如果您希望使用Docker来部署HugeGraph-AI，请按照以下步骤操作：
+   - 确保您已安装Docker。
+   - 在项目根目录下，使用以下命令拉取远端Docker容器镜像，我们提供了两种容器镜像：
+     - **镜像1**：[hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags)  
+       该镜像用于构建和运行HugeGraph-AI的RAG（检索增强生成）功能，适合需要快速部署和使用的用户。
+     - **镜像2**：[hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags)  
+       该镜像提供了二进制版本的HugeGraph-AI，适合需要更稳定和高效性能的用户。
+   - 使用以下命令拉取远端Docker容器镜像：
+     ```bash
+     docker pull hugegraph/rag:latest # 拉取镜像1
+     docker pull hugegraph/rag-bin:latest # 拉取镜像2
+     ```
+   - 使用以下指令启动Docker容器：
+     ```bash
+     docker run -it --name rag -p 8001:8001 hugegraph/rag bash

Review Comment:
   使用相同的容器名称 'rag' 来启动两个 Docker 镜像可能会导致同时运行时发生冲突。建议为每个镜像使用唯一的容器名称以避免潜在的运行时问题。



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Re: [PR] docs: add Docker deployment instructions for HugeGraph-AI [incubator-hugegraph-doc]

Posted by "weijinglin (via GitHub)" <gi...@apache.org>.
weijinglin closed pull request #403: docs: add Docker deployment instructions for HugeGraph-AI
URL: https://github.com/apache/incubator-hugegraph-doc/pull/403


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