llm-markdown

Project Introduction: LLM Markdown

LLM Markdown is a Next.js application designed to transform and render rich-text responses generated by Large Language Models (LLMs). By utilizing Markdown formatting along with Mermaid diagrams and LaTeX equations, it offers a dynamic way to present complex information visually and textually.

Read more about the project’s capabilities and background in the accompanying blog post, titled "Rendering rich responses from LLMs."

Examples of Usage

One of the highlights of LLM Markdown is its ability to translate data into visually appealing formats. Here are two examples:

• Top Grossing Movies: In this example, the application prompts LLM to list movies in a format structured as a Mermaid pie chart. This allows users to easily visualize the distribution of revenue among top films.

  

• Vegetable Planting Schedule: Another example shows how it prompts LLMs to provide a schedule for planting vegetables, presented as a Mermaid Gantt chart. This visualizes timelines efficiently and can be particularly helpful for planning and agriculture enthusiasts.

  

Technologies Behind LLM Markdown

The project is a testament to the integration of several cutting-edge technologies, delivering a smooth and enriching user experience:

• Next.js: A powerful React framework that enables the creation of fast and user-friendly web applications.
• Vercel AI SDK: Provides essential tools and infrastructure to design AI-driven applications easily.
• Remark: This tool processes and interprets Markdown, a lightweight markup language with plain-text formatting.
• Mermaid: Facilitates the generation of diagrams and flowcharts using simple text instructions.
• Latex.js: Enables the rendering of LaTeX equations, offering incredible utility for academic and scientific documentation.
• Additional tools further augment the application's functionality, supporting comprehensive data presentation.

Getting Started with LLM Markdown

To explore the project yourself, follow these easy steps for setup:

1. Clone the Project: Start by cloning the repository to your local machine.
2. Install Dependencies: Navigate to the project directory and run npm install to load all necessary dependencies.
3. Run the Application: Launch the development server using npm run dev.
4. View in Browser: Once the server is up and running, open your web browser and view the application.
5. Configure API Key: Set up your OpenAI API key to enable interaction with LLMs.

By following these instructions, users can effectively use LLM Markdown for diverse applications, ensuring they can transform textual data into insightful visual formats effortlessly.