Dropnread – Prepare your codebase for LLMs with a simple drag and drop

Show HN: Dropnread – Prepare your codebase for LLMs with a simple drag and drop

Dropnread – Prepare your codebase for LLMs with a simple drag and drop operates in show hn launch.

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I built this tool because I found myself constantly needing to share codebases with LLMs for analysis, and manually copying files was tedious. The tool strips comments to save tokens, and excludes irrelevant files like node_modules, .git and so on. Just drag a project folder, and it combines all files into a single text that fits within your chosen LLM's token limit.Features:- Support for GPT-4, Claude, Gemini models with their respective token limits- Comment stripping for common programming languages- Configurable file/folder exclusions with sensible defaults- Token counting- No installation needed, works in your browser (the code never leaves the browser)- Respects your privacy- Open Sour

Dropnread – Prepare your codebase for LLMs with a simple drag and drop is positioned in show hn launch, a segment that rewards a clear, focused offering.

The company is listed at the Show HN launch stage of development.

Website: dropnread.io