imbajin commented on code in PR #280: URL: https://github.com/apache/incubator-hugegraph-ai/pull/280#discussion_r2165470045
########## hugegraph-llm/README.md: ########## @@ -30,27 +30,66 @@ You can choose one of the following two deployment methods: ### 3.1 Docker Deployment -**Docker Deployment** - Deploy HugeGraph-AI using Docker for quick setup: - - Ensure Docker is installed - - We provide two container images to choose from: +**Option 1: Network-based Deployment (Recommended)** Review Comment: ```suggestion **Option 1: Network-composed Deployment (Recommended)** ``` ########## docker/env.template: ########## Review Comment: How do users know the key of configuration items 🤔 ########## docker/docker-compose-network.yml: ########## @@ -0,0 +1,51 @@ +networks: + hugegraph-network: + driver: bridge + +services: + # HugeGraph Server + hugegraph-server: + image: hugegraph/hugegraph + container_name: server + restart: unless-stopped + ports: + - "8080:8080" + networks: + - hugegraph-network + environment: + - HUGEGRAPH_HOST=0.0.0.0 + - HUGEGRAPH_PORT=8080 + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8080/versions";] + interval: 30s + timeout: 10s + retries: 3 + start_period: 40s + + # HugeGraph LLM RAG Service + hugegraph-rag: + image: hugegraph/rag + container_name: rag + restart: unless-stopped + ports: + - "8001:8001" + volumes: + # Mount .env file, please modify according to actual path + - ${PROJECT_PATH}/hugegraph-llm/.env:/home/work/hugegraph-llm/.env + # Optional: mount resources file + # - ${PROJECT_PATH}/hugegraph-llm/src/hugegraph_llm/resources:/home/work/hugegraph-llm/src/hugegraph_llm/resources + networks: + - hugegraph-network + environment: + # Set HugeGraph server address, use container name as hostname + - HUGEGRAPH_HOST=server + - HUGEGRAPH_PORT=8080 + depends_on: + hugegraph-server: + condition: service_healthy + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8001/";] + interval: 30s + timeout: 10s + retries: 3 + start_period: 60s Review Comment: ```suggestion start_period: 60s ``` ########## hugegraph-llm/README.md: ########## @@ -30,27 +30,66 @@ You can choose one of the following two deployment methods: ### 3.1 Docker Deployment -**Docker Deployment** - Deploy HugeGraph-AI using Docker for quick setup: - - Ensure Docker is installed - - We provide two container images to choose from: +**Option 1: Network-based Deployment (Recommended)** + +For production environments, we recommend using Docker Compose to deploy both HugeGraph Server and HugeGraph LLM RAG Service in the same network: + +1. **Set up environment variables:** + ```bash + # Copy the template and modify the project path + cp docker/env.template docker/.env + # Edit docker/.env and set PROJECT_PATH to your actual project path + ``` + +2. **Start the containers:** + ```bash + cd docker + docker-compose -f docker-compose-network.yml up -d + ``` + +3. **Check container status:** + ```bash + docker-compose -f docker-compose-network.yml ps + ``` + +4. **Access the services:** + - HugeGraph Server: http://localhost:8080 + - RAG Service: http://localhost:8001 + +**Option 2: Individual Container Deployment** + +Alternatively, you can deploy HugeGraph-AI using individual Docker containers: + - Ensure you have Docker installed + - We provide two container images: - **Image 1**: [hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags) For building and running RAG functionality for rapid deployment and direct source code modification - **Image 2**: [hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags) - A binary translation of C compiled with Nuitka, for better performance and efficiency. - - Pull one of the Docker images: - ```bash - docker pull hugegraph/rag:latest # Pull Image 1 - docker pull hugegraph/rag-bin:latest # Pull Image 2 - ``` - - Start one of the Docker containers: - ```bash - # Replace '/path/to/.env' with your actual .env file path - docker run -itd --name rag -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag - # or - docker run -itd --name rag-bin -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag-bin - ``` - - Access the interface at http://localhost:8001 + Binary version compiled with Nuitka for more stable and efficient performance in production + +1. **Create Hugegraph Network:** + ```bash + docker network create -d bridge hugegraph-net + ``` + +2. **Start HugeGraph Server:** + ```bash + docker run -itd --name=server -p 8080:8080 --network hugegraph-net hugegraph/hugegraph + ``` + +3. **Start RAG Service:** + ```bash + # Pull the Docker image + docker pull hugegraph/rag:latest + # or + docker pull hugegraph/rag-bin:latest + + # Start the RAG container (replace /path/to/your/project with actual path) + docker run -it --name rag -v path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag Review Comment: ```suggestion # Run it (replace /path2project with actual path) & modify .env file for your needs docker run -it --name rag -v /path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag ``` ########## hugegraph-llm/README.md: ########## @@ -30,27 +30,66 @@ You can choose one of the following two deployment methods: ### 3.1 Docker Deployment -**Docker Deployment** - Deploy HugeGraph-AI using Docker for quick setup: - - Ensure Docker is installed - - We provide two container images to choose from: +**Option 1: Network-based Deployment (Recommended)** + +For production environments, we recommend using Docker Compose to deploy both HugeGraph Server and HugeGraph LLM RAG Service in the same network: + +1. **Set up environment variables:** + ```bash + # Copy the template and modify the project path + cp docker/env.template docker/.env + # Edit docker/.env and set PROJECT_PATH to your actual project path + ``` + +2. **Start the containers:** + ```bash + cd docker + docker-compose -f docker-compose-network.yml up -d + ``` + +3. **Check container status:** + ```bash + docker-compose -f docker-compose-network.yml ps + ``` + +4. **Access the services:** + - HugeGraph Server: http://localhost:8080 + - RAG Service: http://localhost:8001 + +**Option 2: Individual Container Deployment** + +Alternatively, you can deploy HugeGraph-AI using individual Docker containers: + - Ensure you have Docker installed + - We provide two container images: - **Image 1**: [hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags) For building and running RAG functionality for rapid deployment and direct source code modification - **Image 2**: [hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags) - A binary translation of C compiled with Nuitka, for better performance and efficiency. - - Pull one of the Docker images: - ```bash - docker pull hugegraph/rag:latest # Pull Image 1 - docker pull hugegraph/rag-bin:latest # Pull Image 2 - ``` - - Start one of the Docker containers: - ```bash - # Replace '/path/to/.env' with your actual .env file path - docker run -itd --name rag -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag - # or - docker run -itd --name rag-bin -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag-bin - ``` - - Access the interface at http://localhost:8001 + Binary version compiled with Nuitka for more stable and efficient performance in production + +1. **Create Hugegraph Network:** + ```bash + docker network create -d bridge hugegraph-net + ``` + +2. **Start HugeGraph Server:** + ```bash + docker run -itd --name=server -p 8080:8080 --network hugegraph-net hugegraph/hugegraph + ``` + +3. **Start RAG Service:** + ```bash + # Pull the Docker image + docker pull hugegraph/rag:latest + # or + docker pull hugegraph/rag-bin:latest + + # Start the RAG container (replace /path/to/your/project with actual path) + docker run -it --name rag -v path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag + # or + docker run -it --name rag-bin -v path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag-bin Review Comment: ```suggestion # same as the "rag-bin" image... ``` ########## hugegraph-llm/README.md: ########## @@ -30,27 +30,66 @@ You can choose one of the following two deployment methods: ### 3.1 Docker Deployment -**Docker Deployment** - Deploy HugeGraph-AI using Docker for quick setup: - - Ensure Docker is installed - - We provide two container images to choose from: +**Option 1: Network-based Deployment (Recommended)** + +For production environments, we recommend using Docker Compose to deploy both HugeGraph Server and HugeGraph LLM RAG Service in the same network: + +1. **Set up environment variables:** + ```bash + # Copy the template and modify the project path + cp docker/env.template docker/.env + # Edit docker/.env and set PROJECT_PATH to your actual project path + ``` + +2. **Start the containers:** + ```bash + cd docker + docker-compose -f docker-compose-network.yml up -d + ``` + +3. **Check container status:** + ```bash + docker-compose -f docker-compose-network.yml ps + ``` + +4. **Access the services:** + - HugeGraph Server: http://localhost:8080 + - RAG Service: http://localhost:8001 + +**Option 2: Individual Container Deployment** + +Alternatively, you can deploy HugeGraph-AI using individual Docker containers: + - Ensure you have Docker installed + - We provide two container images: - **Image 1**: [hugegraph/rag](https://hub.docker.com/r/hugegraph/rag/tags) For building and running RAG functionality for rapid deployment and direct source code modification - **Image 2**: [hugegraph/rag-bin](https://hub.docker.com/r/hugegraph/rag-bin/tags) - A binary translation of C compiled with Nuitka, for better performance and efficiency. - - Pull one of the Docker images: - ```bash - docker pull hugegraph/rag:latest # Pull Image 1 - docker pull hugegraph/rag-bin:latest # Pull Image 2 - ``` - - Start one of the Docker containers: - ```bash - # Replace '/path/to/.env' with your actual .env file path - docker run -itd --name rag -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag - # or - docker run -itd --name rag-bin -v /path/to/.env:/home/work/hugegraph-llm/.env -p 8001:8001 hugegraph/rag-bin - ``` - - Access the interface at http://localhost:8001 + Binary version compiled with Nuitka for more stable and efficient performance in production + +1. **Create Hugegraph Network:** + ```bash + docker network create -d bridge hugegraph-net + ``` + +2. **Start HugeGraph Server:** + ```bash + docker run -itd --name=server -p 8080:8080 --network hugegraph-net hugegraph/hugegraph + ``` + +3. **Start RAG Service:** + ```bash + # Pull the Docker image + docker pull hugegraph/rag:latest + # or + docker pull hugegraph/rag-bin:latest + + # Start the RAG container (replace /path/to/your/project with actual path) + docker run -it --name rag -v path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag + # or + docker run -it --name rag-bin -v path2project/hugegraph-llm/.env:/home/work/hugegraph-llm/.env -p 8001:8001 --network hugegraph-net hugegraph/rag-bin + ``` + +4. **Access the interface at http://localhost:8001** Review Comment: ```suggestion 4. **Access the UI at http://localhost:8001** ``` -- This is an automated message from the Apache Git Service. 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