A discovery and compression tool for your Python codebase. Creates a knowledge graph for a LLM context window, efficiently outlining your project | Code structure visualization | LLM Context Window Efficiency | Static analysis for AI | Large Language Model tooling #LLM #AI #Python #CodeAnalysis #ContextWindow #DeveloperTools

A lightweight tool to optimize your Javascript / Typescript project for LLM context windows by using a knowledge graph | AI code understanding | LLM context enhancement | Code structure visualization | Static analysis for AI | Large Language Model tooling #LLM #AI #JavaScript #TypeScript #CodeAnalysis #ContextWindow #DeveloperTools

A lightweight tool to optimize your C# project for LLM context windows by using a knowledge graph | Code structure visualization | Static analysis for AI | Large Language Model tooling | .NET ecosystem support #LLM #AI #CSharp #DotNet #CodeAnalysis #ContextWindow #DeveloperTools

A discovery and compression tool for your Java codebase. Creates a knowledge graph for a LLM context window, efficiently outlining your project #LLM #AI #Java #CodeAnalysis #ContextWindow #DeveloperTools #StaticAnalysis #CodeVisualization

repo-map generates LLM-enhanced summaries and analysis of software repositories, providing developers with valuable insights into project structures, file purposes, and potential considerations across various programming languages.

Interactive documentation generator that creates comprehensive markdown docs with project trees, TOC, and code navigation.

A powerful CLI tool that uses vector embeddings and LLMs (via Together AI) to help developers understand and explore codebases through natural language. Ask questions about your code in plain English, get context-aware responses with relevance scoring, manage multiple projects, and integrate directly with GitHub repositories.

🌱💧A Django-based application to manage hydroponic systems with full CRUD capabilities, sensor data management, and user authentication.

A 4-week Python Developer internship program

Designed for human-in-the-loop code documentation, source code dataset creation, and efficient source code archiving, all tailored for RAG (Retrieval-Augmented Generation) applications

An AI tool for automatic documentation generation of Jupyter Notebooks. It extracts and processes code cells to generate detailed documentation, reducing the manual effort needed for writing code descriptions. It helps improve workflow efficiency for data scientists and developers by automating the documentation process.