Clipboard Conqueror is a universal AI copilot that integrates Large Language Models (LLMs) into any text field, enhancing productivity for writers, developers, and students. It allows users to leverage local or online LLMs without sign-ins or API keys for basic use, offering configurable prompt control and multi-hop inference capabilities.

How It Works

The tool operates by intercepting text copied with a specific delimiter (" ||| ") followed by a prompt. It then sends this prompt to a configured LLM inference server (local or online) and places the generated response back onto the clipboard. This approach bypasses the need for dedicated applications or browser extensions, enabling seamless integration into existing workflows across multiple desktop platforms.

Quick Start & Requirements

• Install: No explicit installation command is provided in the README. The project appears to be a JavaScript-based tool, likely requiring manual setup or execution.
• Prerequisites:
  • Local LLM inference servers (KoboldCPP, Text Generation WebUI, Ollama, LMStudio) or online API endpoints (Novita AI, OpenAI, Groq, etc.).
  • setup.js file for configuration (API keys, endpoint selection).
• Resources: Requires a compatible LLM inference backend.
• Links:
  • Quick demo video: https://www.youtube.com/watch?v=j_y_13_2Q94
  • Installation video: https://www.youtube.com/watch?v=j_y_13_2Q94

Highlighted Details

• Supports both local LLM inference (enhancing privacy) and numerous online API endpoints.
• Features a no-code multi-hop inference framework for complex prompt chaining.
• Offers extensive prompt customization and on-the-fly system prompt saving.
• Includes bookmarklets for web page interaction ("Toggle Design Mode").

Maintenance & Community

The project is maintained by aseichter2007. Contact is available via email (clipboard.aseichter2007@gmail.com) or GitHub issues. The developer is open to GUI contributions and prompt engineering consultations.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive for commercial use and closed-source linking. The project aims for offline functionality with local LLMs.

Limitations & Caveats

The README mentions a past bug related to "context leaking" with "Context Shift," which has since been fixed. The project is primarily JavaScript-based, and a GUI is not included, suggesting a command-line or manual execution approach.