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Web application for managing AI models. Experimenting with Ant Design for a modern and user-friendly interface

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antd-ai-models-manager

UI for AI Models Management

Local start

npm i
npm run dev

Note: When running locally or in production, you need to set the following environment variables:

VITE_PORT=3333
VITE_FLAI_URL=http://localhost:4010 # url to flai core

Build

npm run build

This project provides a user interface for managing AI models, built with Ant Design for styling and a streamlined development workflow using Vite.


Project Description

antd-ai-models-manager is a web-based tool for managing AI models. It allows users to add, update, and monitor AI models seamlessly. The application leverages the Ant Design UI library for a clean and responsive interface, and Vite for fast builds and HMR during development.

Dependencies Overview

  • React 18 – Core UI library
  • Ant Design 5 – UI components
  • React Router DOM 7 – Client-side routing
  • TanStack React Query 5 – Data fetching and caching
  • Zod 3 – Data validation
  • Tailwind CSS 3 – Utility-first CSS framework

Development Tools

  • Vite 6 – Build tool and dev server
  • TypeScript 5.6 – Static typing
  • ESLint 9 – Code linting with React and TypeScript support
  • PostCSS & Autoprefixer – CSS processing and compatibility

Scripts

  • npm run dev – Starts local dev server with HMR
  • npm run build – Builds the project using TypeScript and Vite
  • npm run preview – Runs a local preview server for the build
  • npm run lint – Runs ESLint for code quality checks
  • npm run lint:fix – Runs ESLint with auto-fixing enabled

Setup Instructions

Clone the repository, install dependencies, and set up the .env file with the required environment variables for local or production use. The app supports multiple environments, just comment/uncomment the relevant VITE_FLAI_URL.


Potential Improvements

  • Add Docker support for containerized deployment
  • Implement Role-Based Access Control (RBAC)
  • Integrate AI model versioning and rollback features
  • Improve test coverage with unit and integration tests
  • Add WebSocket support for real-time status updates

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Web application for managing AI models. Experimenting with Ant Design for a modern and user-friendly interface

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