INGInious is a secure and automated exercises assessment platform using your own tests, also providing a pluggable interface with your existing LMS.
- grading
- assessment
- education
- e-assessment
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INGInious is a secure and automated exercises assessment platform using your own tests, also providing a pluggable interface with your existing LMS.
Your Data Storage Troubleshooter 🛠
How many bugs can LMs find & fix in large codebases?
An esoteric programming language built to break LLMs and coding agents.
TranslatedDesign styles, motion films, visual guides & editable source code.
Feel how fast a local LLM runs before you buy the hardware
PocketStrike is a privacy-first mobile AI workstation. It combines zero-cloud native on-device GGUF inference (ARM NEON accelerated) │ with frontier cloud LLMs, multi-step ReAct agent tools, Model Context Protocol (MCP) servers, self-evolving cross-session memory, and FLUX neural image │ generation.
llama.cpp fork that abliterates at inference
🏃 The go-to single-cell Foundation Model
The open-source video studio for AI agents. Plan, generate, and edit films on a local-first canvas with your own models and short drama video.
Safe Exam Browser for macOS and iOS
Turn your Swift data model into a working CRUD app.
:ram: Lisp that compiles to JavaScript in the Ramda way
Read-only MCP server that connects Claude, ChatGPT and other AI assistants to Canvas LMS.
Integrate ChatGPT-style LLMs into Neovim: ask questions, keep multi-file context, pull diagnostics / command output, and chat without leaving your editor. Highly configurable, async, lua-only plugin.
An NLP library for Uralic languages such as Finnish, Skolt Sami, Moksha and so on. Also supporting some non-Uralic languages such as Spanish, French, Arabic, Swedish, Norwegian, Russian and English. LLMs, FSTs and More!
Write amazing, strong-typed and easy-to-read NSPredicate.
A JupyterHub authenticator for LTI
Safe and easy wrappers for RealmSwift
Automatically exported from code.google.com/p/audiotools
OpenTelemetry-native tracing, token tracking, cost attribution, and prompt analytics for Go backends integrating LLMs.
Instruct LLMs to do what you want in Ruby
Regular Language Representations in Coq [maintainers=@chdoc,@palmskog]
Coq plugin providing tactics for rewriting universally quantified equations, modulo associative (and possibly commutative) operators [maintainer=@palmskog]