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Ultra-lightweight personal AI assistant framework (~4,000 lines of Python). Supports MCP, 9+ chat channels, and extensible skills system.
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Neofuzz is an open-source Python library that provides high-speed fuzzy text search functionality. It is hosted on GitHub under the x-tabdeveloping repository and is available for community use and contribution.
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neonrvm is an open-source machine learning library for performing regression tasks using the Relevance Vector Machine (RVM) technique. It is written in Python and available on GitHub. The library aims to provide efficient implementations for RVM-based regression.
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Netron is a viewer for neural network, deep learning and machine learning models. It supports formats including ONNX, TensorFlow Lite, PyTorch, TensorFlow, Core ML, OpenVINO, Keras, Caffe, Darknet, Safetensors and NumPy. It is available as a browser version and installers for macOS, Linux and Windows, plus a Python package. Experimental support exists for MLIR, JAX, GGUF and other formats.
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NeuPy is a Python library built on Tensorflow for prototyping and building neural networks. The repository notes that the library is no longer actively maintained. It includes examples and notebooks covering algorithms such as Boltzmann machines and self-organizing maps.
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NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
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NeuroNER is a program that performs named-entity recognition using neural networks. It relies on Python 3 and TensorFlow 1.0+, optionally uses the BRAT annotation tool, and provides installation instructions, sample datasets and pretrained models.
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A Python wrapper for the Discord API forked from discord.py
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Nilearn provides statistical and machine-learning tools for analyses of brain volumes and surfaces, with documentation and a community. It supports general linear model based analysis and uses the scikit-learn toolbox for multivariate statistics, with applications such as predictive modeling, classification, decoding and connectivity analysis. It is written in Python and installable with pip.
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A GitHub repository collecting AI learning resources, including over 100 cheat-sheets, free online books, courses, videos and lectures, papers, tutorials, researchers, websites, datasets, conferences, frameworks and tools. Topics include machine learning, deep learning, big data, data science and Python.
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NobodyWho is an inference engine that runs LLMs locally and offline on any device, powered by llama.cpp. Bindings are available for Kotlin, Swift, React Native, Flutter, Python and Godot. It supports GGUF models, tool calling, multimodal input, text-to-speech and speech-to-text.
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Oils is a project that provides an upgrade path from Bash to a better language and runtime. It is also intended for Python and JavaScript users who avoid shell scripting. The repository includes source code, contribution guidelines, and development build instructions.
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Okrolearn is a machine learning library created in Python by Okerew. It provides a Tensor type and can be installed from PyPI for CPU or GPU use. The repository was archived by its owner on Sep 14, 2025, and is now read-only.
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This Python application is an OSINT (Open Source Intelligence) tool called "Ominis OSINT - Web Hunter." It performs online information gathering by querying Google for search results related to a user-inputted query. The tool extracts relevant information such as titles, URLs, and potential mentions of the query in the results.
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OneComp is a Python package for large language model (LLM) compression, hosted as a public repository under the FujitsuResearch GitHub organization. The project is designed for LLM compression tasks and accepts community contributions to its codebase.
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Open RAG Eval is an open-source Python evaluation toolkit for Retrieval-Augmented Generation pipelines. It provides TREC-RAG evaluation metrics and a modular design for custom metrics and connectors, with core metrics that do not require golden chunks or golden answers.
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An open solution to the Data Science Bowl 2018, based on the topcoders winning solution from ods.ai. The repository was archived by the owner on Jun 22, 2022 and is now read-only. It uses PyTorch and references neptune.ml, though running it as a plain Python script is possible.
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An archived, read-only GitHub repository holding an open solution to the Google AI Open Images Object Detection Track. It offers starter code, configs and notebooks, with RetinaNet training and references to the Neptune experiment platform; Neptune use is optional and the code can run as a plain Python script. The README notes the competition used Open Images Dataset V4.
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An archived, read-only GitHub repository holding an open solution to the Home Credit Default Risk challenge. It provides code, configs and notebooks plus documented solutions using LightGBM, sklearn and XGBoost with engineered features; the README lists cross-validation and leaderboard scores for each. References to Neptune are optional and the solution can run as a plain Python script.
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Gitingest converts any Git repository into a prompt-friendly text ingest for LLMs. Users can replace hub with ingest in any GitHub URL to access the corresponding digest. It provides a text digest from a repository URL or directory, with smart formatting for LLM prompts and statistics on file and directory structure, extract size and token count. It is available as a CLI tool and Python package.
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OPFython is a GitHub repository offering a Python-inspired implementation of the Optimum-Path Forest classifier. The library enables classification tasks using the optimum-path forest algorithm. It includes installation instructions, quick start guides, and classifier documentation. The project is open source and welcomes contributions from the community.
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Python-based meta-heuristic optimization techniques.
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pagodo (Passive Google Dork) is a Python security tool that automates scraping of the Google Hacking Database and subsequent Google searches to identify potentially vulnerable web pages and applications. It replaces manual Google dork searches, consists of a dork retrieval component and a search execution component, uses the yagooglesearch library, and supports native HTTP(S) and SOCKS5 proxy support. Scraping Google Search results may violate Google's Terms of Service.
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LLM Comparator is an interactive data visualization tool for evaluating and analyzing large language model responses side-by-side, developed by the PAIR team. It includes a Python library for creating JSON files and a defined JSON data format.