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Free, open-source, and customizable UI components based on shadcn/ui, designed for easy integration into your LLM applications.

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Enhance Your LLM Applications with Accessible UI Components

Discover marcusschiesser/ui, a collection of free, open-source UI components designed for seamless integration into your Large Language Model applications. These elements are accessible, customizable, and built upon the well-regarded shadcn/ui framework. Developers can easily copy and paste these beautifully designed components to accelerate the creation of interactive and user-friendly interfaces for AI-powered projects. The library aims to simplify front-end development for LLM apps, providing robust building blocks for common UI patterns.

Features:

  • Accessible Components: Designed with accessibility standards for broader usability.
  • Customizable Components: Easily adapt the look and feel to match your application's branding.
  • Copy-and-Paste Integration: Quickly integrate components into your LLM applications by copying code.
  • LLM Application Focus: Tailored UI elements specifically designed for LLM-driven interfaces.
  • Free and Open Source: Available under the MIT license for unrestricted use and community contributions.
  • Built on shadcn/ui: Leverages the popular and robust shadcn/ui library as its foundation.
  • Chat Interface Components: Provides elements for building interactive chat playgrounds and interfaces, as demonstrated in examples.
  • Code Display with Actions: Offers components for presenting code snippets, including features like 'Copy code' and 'Download'.
  • Comprehensive Documentation: Includes detailed guides and examples to facilitate easy adoption and usage.

Summary:

marcusschiesser/ui delivers a practical toolkit of UI components for developers building LLM applications. It emphasizes accessibility, customization, and ease of use through copy-paste integration. With elements like chat interface components and code display utilities, all open-source and based on shadcn/ui, this library helps you quickly construct polished and engaging user experiences for your AI projects. Consult the documentation for detailed implementation guidance and examples.

Distribution:
opensource
GitHub:
98 Stars
6 Forks
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