Showing 3691 open source projects for "project"

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    Ship Agents Faster

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    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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  • 1
    Train LLM From Scratch

    Train LLM From Scratch

    A straightforward method for training your LLM

    Train LLM From Scratch is an educational PyTorch project that shows how to build and train a transformer-based language model from the ground up. It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model.
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  • 2
    SmartNode

    SmartNode

    Visual simulation platform for space-based data backhaul scenarios

    smartNode is a visual simulation platform for space-based intelligent relay and satellite data-return scenarios. It models the relationship between satellites, ground stations, relay links, and content-driven task scheduling. The project includes a Python backend and a browser-based frontend, making it suitable for local simulation, teaching, and secondary development. Users can view a three-dimensional space situation, submit data return tasks, and monitor resource states in real time. The system exposes APIs for health checks, simulation data, resource status, utilization metrics, and configuration updates. smartNode is best suited for aerospace students, communications learners, instructors, and developers exploring space-based network simulation.
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  • 3
    MathCode

    MathCode

    A Frontier Mathematical Coding Agent

    MathCode is a terminal-based AI coding assistant focused on mathematical formalization and theorem proving. It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. ...
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  • 4
    Python Slack SDK

    Python Slack SDK

    Slack Developer Kit for Python

    ...It is useful for bots, workflow tools, internal automations, admin dashboards, notifications, onboarding assistants, and Slack-native business applications. Developers can use it to send messages, respond to events, verify requests, manage app authorization, and integrate Slack into Python services. The project is especially helpful for teams that want a maintained, first-party Python interface instead of manually building every Slack API request.
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  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

    Learn how to protect your Microsoft 365 data, with simple, actionable tips today.

    Watch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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  • 5
    paqctl

    paqctl

    Unified proxy manager for bypassing firewalls

    ...The tool supports two different approaches: Paqet, which uses KCP over raw sockets for simpler cases, and GFW-Knocker, which combines TCP and QUIC tunneling for heavier censorship scenarios. It provides guided installation, configuration, service management, status checks, and backup-oriented dual-backend operation. The project focuses on making complex proxy infrastructure easier to install and operate from a single shell-based interface. It is best understood as an automation layer for users who already need managed proxy connectivity between a local machine and a remote server.
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  • 6
    NVIDIA AI Blueprint

    NVIDIA AI Blueprint

    Suite of reference architectures for building GPU-accelerated vision

    ...It combines accelerated vision microservices, vision language models, large language models, embeddings, and NVIDIA NIM microservices to process both stored and streaming video. The project is organized around real-time video intelligence, downstream analytics, and agentic offline processing. It supports workflows such as natural-language video search, visual question answering, long-video summarization, clip retrieval, verified alerts, and incident analysis. It is designed for technical users who need deployable reference architectures for smart spaces, warehouse automation, SOP validation, monitoring, and operational video analytics. ...
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  • 7
    OpenSwarm

    OpenSwarm

    Claude code for everything except coding

    ...The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch campaigns, visual assets, and multimedia projects. The project can connect to external services through integrations and can be customized into purpose-specific swarms for areas such as SEO, sales, marketing, finance, customer support, or research. Its main appeal is giving technical users a forkable, terminal-based framework for building agent teams that produce polished business and creative deliverables.
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  • 8
    Viral-Clips-Crew

    Viral-Clips-Crew

    Your CrewAI Powered Video Editing Assistant

    ...The system integrates tools like FFmpeg and AI models to handle segmentation, cropping, and formatting for vertical video platforms. It supports automation workflows that allow creators to produce multiple clips efficiently at scale. The project focuses on content repurposing, helping users adapt long videos into formats suitable for platforms like TikTok and YouTube Shorts. Its modular design allows customization of each processing stage, including selection logic and visual formatting. Overall, it serves as a tool for automating short-form content creation.
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  • 9
    Flow-Next

    Flow-Next

    Plan-first AI workflow plugin for Claude Code, OpenAI Codex

    ...The system emphasizes modularity, enabling tasks to be broken down into smaller components that can be reused across different workflows. It supports integration with various tools and services, making it adaptable to different environments. The project is designed to handle both simple and complex workflows, providing flexibility for a wide range of use cases. It also includes features for monitoring and managing execution, ensuring that workflows run reliably. Overall, Flow Next provides a structured approach to organizing and automating tasks in modern development environments.
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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

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  • 10
    LLM Telegram Bot

    LLM Telegram Bot

    A Telegram bot for Large Language Models

    LLM Telegram Bot is a self-hosted Telegram chatbot that connects messaging interactions with large language models, typically powered by Ollama or similar backends. The project is designed to provide a customizable AI assistant that can operate within Telegram conversations, supporting dynamic responses based on user input and configurable parameters. It includes features such as conversation memory, allowing the bot to maintain context across multiple messages and provide more coherent responses. The system supports multiple modes or personas, enabling users to switch between different conversational styles or use cases. ...
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  • 11
    Nothing Ever Happens

    Nothing Ever Happens

    Focused async Python bot for Polymarket

    Nothing Ever Happens is an experimental open-source trading bot designed for the Polymarket platform that implements a deliberately simple and unconventional strategy: automatically buying “No” positions across non-sports binary prediction markets. The project is built in Python using asynchronous architecture, allowing it to monitor markets, evaluate opportunities, and execute trades continuously with minimal latency. Its core concept is based on statistical observations that a majority of prediction market outcomes resolve negatively, and it attempts to exploit this base-rate bias through systematic participation rather than predictive modeling. ...
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  • 12
    colleague-skill

    colleague-skill

    Transform a cold separation into a warm Skill

    colleague-skill is a specialized agent skill designed to simulate a collaborative teammate within AI-driven workflows, enabling agents to behave more like human colleagues in problem-solving scenarios. The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. ...
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  • 13
    Clawith

    Clawith

    OpenClaw for Teams

    ...Its architecture suggests support for multi-agent collaboration, enabling distributed problem-solving and task delegation. It may also include monitoring and control features to ensure that agent behavior remains aligned with user goals. The project reflects a broader trend toward building AI systems that act as autonomous operators rather than passive assistants. Overall, Clawith serves as a foundation for building advanced, action-oriented AI workflows.
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  • 14
    MetaClaw

    MetaClaw

    Just talk to your agent

    MetaClaw is an AI or agent-oriented system that appears to focus on advanced control, coordination, or training of autonomous agents, potentially within reinforcement learning or tool-using environments. The project likely emphasizes meta-level reasoning, where agents are not only executing tasks but also adapting their strategies based on feedback and performance signals. It may incorporate mechanisms for learning from interactions, improving decision-making over time, and generalizing across different domains. The architecture suggests scalability, allowing the system to handle multiple agents or complex workflows simultaneously. ...
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  • 15
    autoresearch-win-rtx

    autoresearch-win-rtx

    AI agents running research on single-GPU nanochat training

    autoresearch-win-rtx is a Windows-based implementation of the autoresearch framework designed to run autonomous AI research loops on consumer NVIDIA RTX GPUs. It adapts the original autoresearch concept to a Windows environment, enabling users to perform iterative machine learning optimization without requiring specialized Linux or data center setups. The system revolves around a small set of core files, including a training script that is continuously modified by an AI agent, along with...
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  • 16
    LeWorldModel

    LeWorldModel

    Official code base for LeWorldModel: Stable End-to-End Joint-Embedding

    LeWorldModel is a minimalist tiling window manager designed for the X11 windowing system, focusing on simplicity, performance, and efficient use of screen space. It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. ...
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  • 17
    CommunityScrapers

    CommunityScrapers

    This is a public repository containing scrapers

    ...The repository contains hundreds of scraper definitions written primarily in YAML and Python, each tailored to extract structured metadata such as titles, performers, tags, and media details from specific websites. These scrapers integrate directly into Stash, allowing users to enrich their media libraries with accurate and detailed information without manual entry. The project supports both automatic installation through in-app feeds and manual configuration for advanced use cases. Some scrapers require additional configuration such as API keys or cookies, highlighting its flexibility and adaptability to different sources.
    Downloads: 0 This Week
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  • 18
    Newton

    Newton

    An open-source, GPU-accelerated physics simulation engine

    ...Newton supports OpenUSD for modern 3D scene representation and interoperability, making it suitable for complex simulation ecosystems. It is developed as a Linux Foundation project with contributions from major organizations like NVIDIA, Google DeepMind, and Disney Research, highlighting its relevance in cutting-edge robotics and AI development.
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  • 19
    ShoppingAgent

    ShoppingAgent

    Custom Chinese chatbot with Seq2Seq, GPT, and agent features

    ...ShoppingAgent is structured to support experimentation across different deep learning frameworks such as TensorFlow, PyTorch, and MindSpore, giving developers flexibility in how they train and deploy models. In addition to core chatbot functionality, the project introduces agent-based capabilities, enabling practical use cases like automated workflows and task-oriented assistants. It also includes support for small language models and local training scripts, making it accessible for users with limited computational resources. ShoppingAgent can be applied to scenarios such as customer service, question answering, and casual conversation.
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  • 20
    TNT

    TNT

    A lightweight library for PyTorch training tools and utilities

    TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps separate concerns such as model training, evaluation, logging, and checkpointing, making machine learning experiments easier to manage. ...
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  • 21
    crawler

    crawler

    Collection of JS reverse engineering examples for web scraping study

    ...It contains many case studies that demonstrate how to analyze and replicate request parameters, cookies, and encryption logic used by real websites. Each directory in the project focuses on a specific target service or scenario, showing how browser network requests and JavaScript code can be studied to reproduce API calls programmatically. Many examples illustrate techniques such as debugging scripts, intercepting requests, analyzing encrypted parameters, and understanding authentication flows. crawler also explores common anti-scraping defenses and demonstrates how developers can examine them through debugging tools and reverse engineering techniques.
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  • 22
    RL with PyTorch

    RL with PyTorch

    Clean, Robust, and Unified PyTorch implementation

    RL with PyTorch is a research-oriented repository that provides implementations of deep reinforcement learning algorithms using the PyTorch framework. The project focuses on helping developers and researchers understand reinforcement learning methods by providing clean and reproducible implementations of well-known algorithms. It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. ...
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  • 23
    Data Science Articles from CodeCut

    Data Science Articles from CodeCut

    Collection of useful data science topics along with articles

    ...Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. Each topic often includes references to code repositories, demonstrations, and video tutorials that show how the tools can be applied in real projects. The repository is intended to help practitioners stay updated with current best practices and technologies in the field of data science.
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  • 24
    machine_learning_examples

    machine_learning_examples

    A collection of machine learning examples and tutorials

    machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. ...
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  • 25
    Coursera-ML-AndrewNg-Notes

    Coursera-ML-AndrewNg-Notes

    Personal notes from Wu Enda's machine learning course

    Coursera-ML-AndrewNg-Notes is an open-source repository that provides detailed study notes and explanations for Andrew Ng’s well-known machine learning course. The project aims to help students understand the mathematical concepts, algorithms, and intuition behind fundamental machine learning techniques taught in the course. It organizes the material into clear written summaries that accompany each lecture topic, including supervised learning, regression methods, neural networks, and optimization algorithms. ...
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