APIs Developer

APIs Developer

Welcome to the Greennode AI Platform API documentation! This guide will walk you through accessing our Swagger-based API documentation and provide examples for interacting with the core modules: Notebook Instances, Training Models, Model Registry, and Model Endpoints.

Step 1: Accessing the API Documentation

  1. Login to the Greennode AI Platform: Use your credentials to log into the Greennode AI Platform.
  2. Navigate to API Docs:
    1. Locate the "API Documentation" section within the portal by clicking on the "?" icon next to your account at header bar. 

    2. Or you can access directly to Swagger UI through https://aiplatform.console.greennode.ai/api-docs
  3. Swagger UI: You'll be presented with the Swagger UI, an interactive tool that displays all available API endpoints, their parameters, and expected responses.

Step 2: Obtaining Your Access Token

  1. Token Generation: The Swagger UI will generate an access token for you. This token is usually short-lived (e.g., valid for one hour). Click on "Your access token" button at the top right corner to copy the access token. 
  2. Authentication: Most Greennode APIs require an access token for authentication. You'll typically find an "Authorize" button within the Swagger UI. Click it to open the authorization popup and pass your copied access into the value field, then click on "Authorize" button to complete the process. 

Step 3: Using cURL with Swagger UI

  1. Find the Endpoint: Locate the API endpoint you want to interact with in the Swagger UI.
  2. Expand the Endpoint: Click on the endpoint to expand its details.
  3. "Try it out" Button: Click the "Try it out" button to open an interactive form.
  4. Fill in Parameters: Provide the required parameters for the API call.
  5. Execute: Click the "Execute" button to send the API request.
  6. ​cURL Command: The Swagger UI will automatically generate a cURL command that you can copy and paste into your terminal or script.

    • Related Articles

    • Overview

      GreenNode offers Model as a Service (MaaS) to help developers and businesses integrate powerful AI capabilities into their applications with ease. Whether you're working with language models, vision models, or multi-modal AI systems, GreenNode ...

    • Training Mode

      Training Moe Definition Characteristics Use Cases Single training Single training refers to training a machine learning model using a single instance or node. Utilizes a single compute instance for model training. Suitable for small to medium-sized ...

    • Supported code editor & framework

      What Can I Do With Code Editor? Jupyter Lab A code editor on AI Platforms, like Jupyter Lab, offers a robust environment for data exploration, analysis, and model development in various programming languages like Python, R, and Julia. Here's what you ...

    • Create an endpoint

      After training and registering the model, the online prediction component enables the deployment and serving of models to make real-time predictions or inferences on new data. This component provides endpoints or APIs that can be integrated into ...

    • How it works?

      Overall, the GreenNode AI Platform forms an end-to-end pipeline for building, training, managing, and deploying machine learning models in an AI platform, which includes four main components Notebook Instance, Model Training, Model Registry and ...