Hackerman
A hackable, AI-first text editor.
Description
Hackerman is an innovative, AI-first text editor developed for users who prioritize local processing and speed. It operates as a native application, ensuring instant responses without relying on cloud services, forks, or unnecessary bloat, making it an ideal tool for focused and efficient text manipulation. The editor is designed with a 'hackable' philosophy, catering to users who seek deep customization and control over their environment.
This tool provides built-in AI support, allowing users to integrate and switch between their preferred AI models directly within the editor. Configuration is simplified through editable plain text files with hot-reloading capabilities. Users can also create custom functions with keybindings, load their own lexers or use built-in options like Lexilla, and benefit from features like an Emacs-like scratch buffer for temporary notes. This comprehensive customizability aims to offer an experience akin to 'the Emacs of the AI age.'
Key Features
- AI-First Design: Natively integrates AI capabilities for enhanced text editing.
- Local Inference: Processes data locally for speed, privacy, and offline use.
- Highly Hackable: Offers deep customization through plain text configuration and hot-reloading.
- Native Application: Runs as a standalone app with no cloud, no forks, and no bloat.
- Custom Function & Keybindings: Allows users to create and call their own functions with personalized shortcuts.
- Lexer Support: Supports custom lexers and built-in options like Lexilla for syntax highlighting.
- Emacs-like Scratch Buffer: Provides a temporary space for unsaved notes and quick edits.
- Mix-and-Match AI Models: Built-in support to use various AI models.
Use Cases
- Developing software with AI-assisted coding.
- Drafting and editing technical documentation with AI enhancements.
- Rapidly prototyping scripts and configurations in a local environment.
- Customizing a text editing environment for specific development workflows.
- Secure, local-first text editing for sensitive information or code.
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