GPT-Vis provides open-source, visual components for generative AI and LLM projects, extending beyond UI elements to include data visualization protocols and knowledge bases. It targets developers building AI applications, offering a structured way to integrate LLM-driven insights and visualizations into user interfaces.

How It Works

GPT-Vis leverages a markdown-like syntax to embed interactive visualizations and LLM agent protocols directly within content. It parses specific blocks (e.g., vis-chart, my-ui) to render charts or custom UI elements, facilitating seamless integration of data-driven narratives and LLM agent interactions into applications. The library includes pre-built chart components and a mechanism for custom renderers, enabling flexible visualization solutions.

Quick Start & Requirements

• Install via npm: $ npm i @antv/gpt-vis --save
• Usage examples provided for React and Streamlit.
• Requires Node.js environment for frontend integration.
• See Document for more details.

Highlighted Details

• LLM Protocol: Visual protocol for LLM Agent cards for conversational interaction and serialized output.
• LLM Component: 20+ built-in VIS components with expansion mechanisms for custom UI.
• LLM Access: Chart knowledge base and recommendation models for direct visual card output from LLMs.
• Streamlit Integration: Provided via the streamlit-gpt-vis package.

Maintenance & Community

• Developed by AntV, a data visualization team.
• Active development indicated by ongoing updates to datasets and features.
• Contribution welcome for chart data.

Licensing & Compatibility

• MIT License.
• Permissive license suitable for commercial use and integration into closed-source projects.

Limitations & Caveats

The project is primarily focused on web-based visualizations and LLM integration; broader platform support beyond web and Streamlit is not explicitly detailed. The effectiveness of chart recommendation and knowledge base features depends on the underlying LLM and the quality of the provided datasets.