RNet AI
  • INTRODUCTION
    • About Rnet
    • Quickstart
    • Core Concepts
      • List of Model Providers
  • GETTING STARTED
    • Model
      • Add New Provider
      • Predefined Model Integration
      • Custom Model Integration
      • Interfaces
      • Schema
    • Application Orchestration
      • Overview
      • Interactive Chat Application
      • Agent
      • App Kits
    • Workflow
      • Core Concepts
      • Node Overview
        • Start
        • Question Classifier
        • Knowledge Retrieval
        • Variable Aggregator
        • LLM
        • Direct Reply
        • IF/ELSE
        • HTTP Request
        • End
    • Knowledge Base
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  1. GETTING STARTED

Application Orchestration

An "Application" is a practical solution designed around large language models like GPT, tailored to address specific needs. Building an application on Rnet offers several key advantages that empower developers to create powerful AI-driven solutions efficiently and effectively:

  • Seamless API Integration: Rnet provides a user-friendly API that can be easily integrated with backend or frontend applications, simplifying the development process. Authentication via Token ensures secure access to your AI-powered features.

  • Ready-to-Use WebApp: Rnet offers a fully functional, aesthetically pleasing hosted WebApp that’s ready for immediate deployment. This saves time and resources, allowing developers to focus on customization and refinement using the WebApp template.

  • Intuitive Interface: With tools for prompt engineering, context management, log analysis, and annotation, Rnet’s interface streamlines the development and fine-tuning of AI applications, making it easier to manage complex workflows.

  • Enhanced Productivity: By providing integrated tools and a comprehensive platform, Rnet reduces the complexity of AI application development, enabling developers to focus on innovation and delivering value faster.

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Last updated 9 months ago