Llmdog – lightweight TUI for prepping files for LLMs

Git for LLMs - a Context Management Tool

I created a tool that consolidates information from the following inputs: GitHub repository URL (e.g., https://github.com/jimmc414/onefilellm) arXiv abstract URL (e.g., https://arxiv.org/abs/2401.14295) Local folder path (e.g., C:\python\PipMyRide) Youtube video URL (e.g., https://www.youtube.com/watch?v=KZ_NlnmPQYk) Webpage URL (e.g., https://llm.datasette.io/en/stable/) It outputs the repo, web documentation, arXiv paper or YT transcript to a text file and the clipboard, displaying a token count. It also…

LLM Globber is a command-line utility written in Rust for collecting files from various locations, filtering them, and outputting their contents to a single text file. This tool is designed to prepare local files for analysis by Language Learning Models (LLMs). Criticism welcome.

I've created uithub, a tool that allows developers to easily get LLM context for their coding questions and perform AI repo analysis at scale. Here's what it does: - Get Context: Simply change the 'g' in github.com to 'u' to access AI-powered insights on any GitHub repo. - Flexible Querying: Fetch entire repos, specific branches/subfolders, or filter by file type and size. - API for Developers: Power the next generation of development tools with our API. Key features: - Customizable token limits - File type filtering - Multiple response formats - Size-based file exclusion I built this…

Slupe lets you use web-based LLMs to modify local files without leaving the browser. npx slupe --clipboard It's a CLI tool that watches for LLM commands and executes them on your computer. Key features: - Custom syntax (NESL) designed for LLM reliability - fewer search/replace failures than existing approaches - Clipboard mode: copy from browser → Slupe executes → paste results back to clipboard - Generates instructions for LLMs based on your allowed actions - Sandboxed filesystem operations with configurable permissions + automatic git backups Motivation: I wanted to use web based Opus…

Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…