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529–552 of 4,826 · Most stars

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

  • academia
  • arxiv
  • brave
  • deep-research

Multi-user anti-filtering panel, with an effortless installation and supporting more than 20 protocols to circumvent filtering plus the telegram proxy.

Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

  • yolov9

TranslatedThe most comprehensive and frequently updated AI Agent skill library, featuring curated skill packs across document processing, content creation, programming, machine learning, automated workflows, and many more domains. Also, all the skill packs are bundled and ready to install and use directly! It also automatically crawls tens of thousands of Skills projects on GitHub and organizes them by category, update time, and number of Stars.

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

  • nlp
  • nltk
  • pattern
  • python

An open-source post-exploitation framework for students, researchers and developers.

  • encrypted-connections
  • platform-independent
  • no-dependencies
  • reverse-shells

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

Common used path planning algorithms with animations.

  • astar
  • anytime-repairing-astar
  • learning-realtime-astar
  • realtime-adaptive-astar

"Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization.

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.