AI-Powered generation of music visualizers.
vismind is not a hosted web application, nor a traditional source code repository.
It is a public documentation and creative exploration of how AI tools, especially Google AI Studio (Gemini), can be used collaboratively to design, generate, and iterate over a music visualizer concept — all through prompt-based development.
This project demonstrates the potential of using LLMs (Large Language Models) not just to assist, but to actually build the structure, layout, and core generative logic of an entire interactive application.
vismind boasts a range of features, primarily driven by AI-generation capabilities:
- AI-Powered Visualizer Generation: Create unique, audio-reactive canvas visualizers from text-based descriptions or by providing an inspirational image.
- Iterative Enhancement Mode: Refine existing AI-generated visualizers with new prompts or images, allowing for an evolutionary design process.
- Dynamic Audio Analysis: Visuals respond in real-time to frequency data, beat intensity, bass, mids, and treble from uploaded audio files.
- Save & Load States: Preserve your visualizer creations (including AI-generated code and prompts) as
.aivisfiles. These files can optionally embed the audio track for a complete, shareable experience. - Undo/Redo for Enhancements: Easily navigate through the history of changes made during the visualizer enhancement process.
- Responsive User Interface: Designed to be usable across different screen sizes, with a modern, glassmorphic aesthetic.
Here are a few conceptual examples of prompts and the kinds of visualizers they could generate.
Prompt: "A 3D rotating cube with RGB glowing edges, music visualizer edges with glow, background synchronized with the color of the cube."
Prompt: "A deep blue and purple ocean waves, with particles shimmering like stars in the water, reacting to the bass and mids of the music."
Prompt: "A dark blue background, with rain and affected by wind, with a weak light at the bottom that is affected by the rhythm, thunder appears with very strong rhythms of the music."
Prompt: "A clean, dark background where a small number of white particles elegantly dance and swirl, their speed and brightness tied to the overall music intensity."
The core of this project was developed through prompt-driven interactions with Google AI Studio (Gemini model).
The process included:
- Generating initial app structure (HTML, TypeScript, React components) and layout using descriptive prompts.
- Iteratively refining the user interface and user experience (UX) over several cycles based on feedback and new requirements, all guided by prompts.
- Implementing core functionalities like audio processing, playback controls, and state management by requesting specific code structures and logic from the AI.
- Developing the AI-to-canvas pipeline, where Gemini generates JavaScript code that is then dynamically executed to render visuals.
- Making manual adjustments directly in the code, primarily for fine-tuning UI aesthetics, complex state interactions, and ensuring overall coherence when AI-generated parts needed bridging.
- Using ChatGPT (as an auxiliary AI) for drafting and refining documentation, including this README, and for high-level technical discussions.
No external UI component libraries were manually installed or integrated; most UI elements and their styling originated from prompts and Gemini’s generation capabilities, with subsequent edits and architectural guidance provided by MTDev.
- There is no live demo — Google AI Studio (the environment where this was prototyped) does not provide free public hosting for complex applications like this.
- No traditional complete, standalone codebase is provided in a ready-to-deploy format; the focus here is on the methodology, the interaction with AI, and the documented outcome.
- The application was created and iterated upon within a specialized AI-assisted development environment, and its "source code" is effectively the sum of the prompts, the AI's outputs, and the manual edits documented here.
This repository showcases what’s possible when we combine human creativity, AI-driven code generation, and iterative, prompt-based development workflows.
It serves as inspiration for developers, designers, and AI enthusiasts who are curious about the evolving landscape of software creation, where LLMs act as collaborative partners.
It also reflects the significant human effort, experimentation, prompt engineering, and critical evaluation required — AI may generate, but humans still curate, architect, and direct the final outcome.
All documentation, prompts, and descriptive content in this repository are released under the CC0 1.0 Universal License.
You may reuse, adapt, or share it freely, with no restrictions. The AI-generated code snippets are illustrative of the process; their direct usability may vary.
Created and refined by MTDev using Google AI Studio (Gemini model), with support from ChatGPT.
This is a documentation-first project dedicated to the public domain under CC0 1.0.