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README

Overview

This repository contains a Docker Compose configuration for a client application that interacts with a machine learning inference service. It includes services for the main application, inference, and postprocessing.

Services

  • Playnode:

    • PlayaAI node for pulling task and registering node
    • Port: 3000
    • To run service on multinode Node change HOST_NAME=localhost without any quotes in docker-compose.yml file
  • Torchserve:

    • Inference service for running machine learning models
    • Ports: 8083, 8084 & 8085
  • Postprocessing:

    • Other ML tasks
    • port: 8080
  • More details is there about variable and service in the docker-compose.yml file

Setup

Step 1: Install or Clone the Repository

You can either use the installer by running the command below:

curl -sL https://playinstaller.playai.network -o playinstaller.sh && chmod +x playinstaller.sh && ./playinstaller.sh

Or clone the repository using the following command:

git clone https://github.com/PlayAINetwork/PlayAI-Node-Client.git

Step 2: Create Environment Variables

This project requires specific environment variables to be set up. Follow these steps:

  1. Create a file named .env.schema in the root directory of your project.

  2. Add the following content to the .env.schema file:

    NODE_WALLET_ADDRESS: string
    NODE_SIGNER_KEY: string
    NODE_TOKEN_IDS: string(list of int)
    
  3. Replace the placeholders with your actual values. Node Token Ids can take multiple value for example '[1,2,3]'. For example:

    NODE_WALLET_ADDRESS='0x0000000000000000000000000000000000000000'
    NODE_SIGNER_KEY='0x00000000000000000000000000000000000000000000000000000000000'
    NODE_TOKEN_IDS='[0]'
    

Step 2: Docker Compose

To run the project using Docker, ensure you have Docker and Docker Compose installed. Then, use the following command to start the services:

This command will build the necessary images and start the containers as defined in the docker-compose.yml file. Make sure to check the docker-compose.yml for any additional configuration or services.

Usage

  1. Ensure you have Docker and Docker Compose installed.
  2. Run the following command to start the services:
    docker-compose pull
    docker-compose up
  3. Access the services:

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