Showing 15965 open source projects for "linux-debian"

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  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

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  • 1
    Perf Book

    Perf Book

    The book "Performance Analysis and Tuning on Modern CPU"

    This project is a practical guide to performance analysis and tuning on modern CPUs, bridging microarchitecture details with hands-on profiling. It explains how caches, TLBs, prefetchers, branch predictors, and out-of-order execution influence real program speed, then connects those concepts to concrete optimization strategies. Readers learn how to design trustworthy benchmarks, avoid measurement traps (warmup, turbo, frequency scaling), and interpret hardware performance counters. The book...
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  • 2
    Sippts

    Sippts

    Set of tools to audit SIP based VoIP Systems

    Sippts is a set of tools to audit VoIP servers and devices using SIP protocol. Sippts is programmed in Python and it allows us to check the security of a VoIP server using SIP protocol. You can freely use, modify and distribute. If modified, please put a reference to this site. Most security tools can be used for illegal purposes, but the purpose of this tool is to check the security of your own servers and not to use to do bad things. I am not responsible for the misuse of this tool. Sippts...
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  • 3
    Dulwich

    Dulwich

    Pure-Python Git implementation

    ...Git once attended a cocktail party. Supported Python versions are Python 3.5 and later. Versions of Dulwich prior to 0.20 also supported Python 2.7. Supported platforms include Linux, Mac OS X and Windows. Dulwich comes with both a lower-level API and higher-level plumbing ("porcelain"). By default, Dulwich' setup.py will attempt to build and install the optional C extensions. The reason for this is that they significantly improve the performance since some low-level operations that are executed often are much slower in CPython.
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  • 4
    Mopidy

    Mopidy

    Mopidy is an extensible music server written in Python

    ...Through extensions, Mopidy can play music from cloud services like Spotify, SoundCloud, and TuneIn. With Mopidy's extension support, you can easily add backends for new music sources. Mopidy is a Python application that runs in a terminal or in the background on Linux computers or Macs that have network connectivity and audio output. Out of the box, Mopidy is an HTTP server. If you install the Mopidy-MPD extension, it becomes an MPD server too. Many additional frontends for controlling Mopidy are available as extensions. You and the people around you can all connect their favorite MPD or web client to the Mopidy server to search for music and manage the playlist together.
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  • 5
    n8n Workflows

    n8n Workflows

    All of the workflows of n8n i could find (also from the site itself)

    This repository aggregates a well-organized collection of community-submitted automation workflows built for n8n, a fair-code, self-hostable automation tool. It serves as an index for discovering ready-made flows to automate tasks across multiple services and platforms. 2,057 workflows with meaningful, searchable names. 365 unique integrations across popular platforms. 29,445 total nodes with professional categorization. Quality assurance - All workflows analyzed and categorized.
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  • 6
    latexcv

    latexcv

    A collection of cv and resume templates written in LaTeX

    A collection of user-friendly LaTeX CV and résumé templates (packaged within the R Markdown vitae ecosystem), offering simple themes and templates for creating professional CVs without heavy TeX coding. Supports multiple display themes such as classic, modern, sidebar layouts.
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  • 7
    Crawl4AI

    Crawl4AI

    Open-source LLM Friendly Web Crawler & Scraper

    Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations.
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  • 8
    NErlNet

    NErlNet

    Nerlnet is a framework for research and development

    NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices.
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  • 9
    Frappe

    Frappe

    Low code web framework for real world applications

    Frappe is a full-stack, low-code web framework written in Python and JavaScript, used to build scalable and modular enterprise applications. It powers ERPNext and includes tools for REST APIs, user management, document modeling, workflows, and real-time updates. Frappe uses a "model-view-controller" approach with its own ORM and frontend system, enabling rapid development without sacrificing control or performance.
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  • 10
    Dask

    Dask

    Parallel computing with task scheduling

    Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines.
    Downloads: 0 This Week
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  • 11
    Borgmatic

    Borgmatic

    Simple, configuration-driven backup software for servers

    borgmatic is a simple, configuration-driven backup automation tool built to work with BorgBackup. It simplifies the creation, pruning, and verification of encrypted, deduplicated backups through a single YAML configuration file. Designed for both servers and desktops, borgmatic is ideal for users who want reliable, scriptable backup workflows with minimal setup and strong security.
    Downloads: 0 This Week
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  • 12
    Pony ORM

    Pony ORM

    Pony Object Relational Mapper

    Pony ORM is a Python ORM that enables developers to write database queries using generator expressions and Pythonic syntax, making code more readable and intuitive. It automatically translates Python expressions into SQL and supports multiple databases including SQLite, MySQL, PostgreSQL, and Oracle. With an emphasis on simplicity and maintainability, Pony ORM is suitable for both small projects and complex applications.
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  • 13
    Tortoise ORM

    Tortoise ORM

    Familiar asyncio ORM for python, built with relations in mind

    Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) for Python, inspired by Django's ORM. It is designed to work with asynchronous frameworks, providing a simple and familiar API for interacting with databases. Tortoise ORM supports various relational databases and is suitable for building high-performance web applications.
    Downloads: 0 This Week
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  • 14
    cmake-conan

    cmake-conan

    CMake wrapper for conan C and C++ package manager

    cmake-conan is a CMake wrapper for the Conan C and C++ package manager, designed to streamline the integration of Conan into CMake-based projects. It automates the process of installing and managing dependencies, allowing developers to define their requirements in Conan and have them seamlessly integrated into their CMake build process. This tool simplifies dependency management and enhances reproducibility in C++ projects.
    Downloads: 0 This Week
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  • 15
    PDM

    PDM

    A modern Python package and dependency manager

    PDM (Python Development Master) is a modern Python package and dependency manager that adheres to the latest PEP standards. It emphasizes a declarative approach to project configuration using pyproject.toml, facilitating reproducible builds and streamlined workflows. PDM's focus on simplicity and compliance with Python's evolving ecosystem makes it a valuable tool for developers seeking modern project management solutions.​
    Downloads: 0 This Week
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  • 16
    MCP Server Qdrant

    MCP Server Qdrant

    An official Qdrant Model Context Protocol (MCP) server implementation

    The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. ​
    Downloads: 0 This Week
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  • 17
    Clay Foundation Model

    Clay Foundation Model

    The Clay Foundation Model - An open source AI model and interface

    The Clay Foundation Model is an open-source AI model and interface designed to provide comprehensive data and insights about Earth. It aims to serve as a foundational tool for environmental monitoring, research, and decision-making by integrating various data sources and offering an accessible platform for analysis.
    Downloads: 0 This Week
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  • 18
    LazyLLM

    LazyLLM

    Easiest and laziest way for building multi-agent LLMs applications

    LazyLLM is an optimized, lightweight LLM server designed for easy and fast deployment of large language models. It is fully compatible with the OpenAI API specification, enabling developers to integrate their own models into applications that normally rely on OpenAI’s endpoints. LazyLLM emphasizes low resource usage and fast inference while supporting multiple models.
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  • 19
    Liger Kernel

    Liger Kernel

    Efficient Triton Kernels for LLM Training

    Liger Kernel is a unified kernel developed by LinkedIn to streamline data science and machine learning workflows across different languages and tools. It provides a consistent interface for running code in various languages (such as Python, R, SQL) within a single Jupyter-like environment, enhancing productivity and collaboration for data scientists working in mixed-language projects.
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  • 20
    RL Baselines3 Zoo

    RL Baselines3 Zoo

    Training framework for Stable Baselines3 reinforcement learning agents

    rl-baselines3-zoo is a collection of pre-trained models, benchmarks, and hyperparameter tuning tools built on top of Stable Baselines3, a reinforcement learning library. It provides an easy way to test, evaluate, and train RL agents across a wide variety of environments.
    Downloads: 0 This Week
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  • 21
    LiteMultiAgent

    LiteMultiAgent

    The Library for LLM-based multi-agent applications

    LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments.
    Downloads: 0 This Week
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  • 22
    RWARE

    RWARE

    MuA multi-agent reinforcement learning environment

    robotic-warehouse is a simulation environment and framework for robotic warehouse automation, enabling research and development of AI and robotic agents to manage warehouse logistics, such as item picking and transport.
    Downloads: 0 This Week
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  • 23
    Vanna

    Vanna

    Chat with your SQL database

    Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users.
    Downloads: 0 This Week
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  • 24
    Tensorforce

    Tensorforce

    A TensorFlow library for applied reinforcement learning

    Tensorforce is an open-source deep reinforcement learning framework built on TensorFlow, emphasizing modularized design and straightforward usability for applied research and practice.
    Downloads: 0 This Week
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  • 25
    Keras Hub

    Keras Hub

    Pretrained model hub for Keras 3

    Keras Hub is a repository of pre-trained models for Keras 3, offering a collection of ready-to-use models for various machine-learning tasks. KerasHub is an extension of the core Keras API; KerasHub components are provided as Layer and Model implementations. If you are familiar with Keras, congratulations. You already understand most of KerasHub.
    Downloads: 0 This Week
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