Search Results for "linux software development" - Page 45

Showing 5808 open source projects for "linux software development"

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  • 1
    Python Code Tutorials

    Python Code Tutorials

    The Python Code Tutorials

    Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and...
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  • 2
    Amazing-Python-Scripts

    Amazing-Python-Scripts

    Curated collection of Amazing Python scripts

    Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning...
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  • 3
    AI Engineer Headquarters

    AI Engineer Headquarters

    A collection of scientific methods, processes, algorithms

    AI-Engineer-Headquarters is a comprehensive educational repository designed to help developers become advanced AI engineers through a structured learning path and practical system-building exercises. The project serves as a curated collection of resources, methodologies, and tools covering topics across the entire artificial intelligence development lifecycle. Rather than focusing only on theoretical knowledge, the repository emphasizes applied learning and encourages engineers to build real...
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  • 4
    WFGY 3.0

    WFGY 3.0

    A tension reasoning engine over 131 S-class problems

    WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply...
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  • 5
    HuixiangDou

    HuixiangDou

    Overcoming Group Chat Scenarios with LLM-based Technical Assistance

    HuixiangDou is an open-source large language model assistant designed specifically for technical question answering in group chat environments. The project addresses a common problem in developer communities where discussion channels become overwhelmed by repeated or irrelevant questions. To solve this issue, HuixiangDou implements a multi-stage pipeline that analyzes incoming messages, filters irrelevant conversations, and selectively generates responses when the assistant determines it can...
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  • 6
    DocETL

    DocETL

    A system for agentic LLM-powered data processing and ETL

    DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL...
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  • 7
    bitsandbytes

    bitsandbytes

    Accessible large language models via k-bit quantization for PyTorch

    bitsandbytes is an open-source library designed to make training and inference of large neural networks more efficient by dramatically reducing memory usage. Built primarily for the PyTorch ecosystem, the library introduces advanced quantization techniques that allow models to operate using reduced numerical precision while maintaining high accuracy. These optimizations enable large language models and other deep learning architectures to run on hardware with limited memory resources,...
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  • 8
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,...
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  • 9
    NVIDIA Earth2Studio

    NVIDIA Earth2Studio

    Open-source deep-learning framework

    NVIDIA Earth2Studio is an open-source Python package and framework designed to accelerate the development and deployment of AI-driven weather and climate science workflows. It provides a unified API that lets researchers, data scientists, and engineers build complex forecasting and analysis pipelines by combining modular prognostic and diagnostic AI models with a diverse range of real-world data sources such as global forecast systems, reanalysis datasets, and satellite feeds. The toolkit...
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  • 10
    LitterBox

    LitterBox

    A secure sandbox environment for malware developers and red teamers

    LitterBox is a controlled malware-analysis and payload-testing sandbox aimed at red teams who need to validate evasions and behaviors before deployment. It provides an isolated environment to exercise payloads against modern detection stacks, verify signatures and heuristics, and observe runtime characteristics without leaking binaries to third-party vendors. The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling...
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  • 11
    Phidata

    Phidata

    Build multi-modal Agents with memory, knowledge, tools and reasoning

    Phidata is an open source platform for building, deploying, and monitoring AI agents. It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to...
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  • 12
    Modin

    Modin

    Scale your Pandas workflows by changing a single line of code

    Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. Additionally, it is not necessary to...
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  • 13
    Videomass

    Videomass

    Videomass is a free, open source and cross-platform GUI for FFmpeg

    Videomass is a free, open-source graphical interface for FFmpeg designed to make advanced video and audio processing accessible to both beginners and experienced users. Built in Python using wxPython, it provides a cross-platform environment for managing encoding, conversion, and editing tasks through a visual interface. The software supports multitasking operations, allowing users to process multiple media files simultaneously. It offers extensive configuration options while also providing...
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  • 14
    fireworks-tech-graph

    fireworks-tech-graph

    Claude Code skill for generating production-quality SVG+PNG technical

    fireworks-tech-graph is an AI-driven project focused on building structured knowledge graphs that map relationships between technologies, concepts, and entities within technical domains. It aims to transform unstructured information into interconnected graphs that can be queried and analyzed for insights, making it easier to understand complex ecosystems such as software stacks or research fields. The system likely leverages AI techniques for entity extraction, relationship mapping, and...
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  • 15
    Toonily Downloader

    Toonily Downloader

    A python tool for downloading manga from Toonily

    Toonily Downloader is a Python-based scraping and downloading tool designed specifically for manga and manhwa hosted on Toonily, enabling users to fetch entire series efficiently while preserving original image quality and structure. It provides both a command-line interface and a graphical user interface, making it accessible for both technical and non-technical users. The software supports downloading full series or selected chapters by parsing Toonily URLs and organizing content into...
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  • 16
    Quantitative Trading System

    Quantitative Trading System

    A comprehensive quantitative trading system with AI-powered analysis

    Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and...
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  • 17
    OneFileLLM

    OneFileLLM

    Specify a github or local repo, github pull request

    OneFileLLM is an open-source project designed to simplify the distribution and execution of large language model applications by packaging them into a single portable file. The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable...
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  • 18
    Integuru v0

    Integuru v0

    The first AI agent that builds permissionless integrations

    Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this...
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  • 19
    Open Wearables

    Open Wearables

    Self-hosted platform to unify wearable health data

    Open Wearables is an open-source initiative that aims to provide a community-driven ecosystem for wearable device software and interoperability by connecting sensor data, activity tracking, and health insights across multiple platforms and devices. Instead of relying on closed vendor ecosystems, the project provides standardized data models and APIs that let developers and hobbyists collect, sync, and analyze biometric and environmental data from wearables, DIY sensors, and open hardware...
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  • 20
    OpenAdapt

    OpenAdapt

    Open Source Generative Process Automation

    OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and...
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  • 21
    Spring AI Alibaba Examples

    Spring AI Alibaba Examples

    Spring AI Alibaba examples for building and testing AI apps

    Spring AI Alibaba Examples provides a collection of example projects that demonstrate how to use Spring AI and Spring AI Alibaba across different scenarios, from basic setups to more advanced AI applications. It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph...
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  • 22
    Claude Code Tools

    Claude Code Tools

    Practical productivity tools for Claude Code, Codex-CLI

    Claude Code Tools is an open-source collection of command-line utilities and productivity plugins designed to enhance developer workflows when using AI coding agents such as Claude Code and Codex-CLI. The project focuses on solving common problems encountered in AI-assisted development environments, including managing session history, automating terminal interactions, and maintaining context across multiple coding sessions. It includes tools that allow developers to search conversation logs...
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  • 23
    ERNIE

    ERNIE

    The official repository for ERNIE 4.5 and ERNIEKit

    ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment. It supports both full-parameter training and parameter-efficient approaches so teams can choose...
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  • 24
    Learn Claude Code

    Learn Claude Code

    Bash is all you need, write a claude code with only 16 line code

    Learn Claude Code is an educational repository that teaches how modern AI coding agents work by walking learners through a sequence of progressively more complex agent implementations, starting with a minimal Bash-based agent and culminating in agents with explicit planning, subagents, and skills. It emphasizes a hands-on learning path where each version (from v0 to v4) adds conceptual building blocks like the core agent loop, todo planning, task decomposition, and domain knowledge skills,...
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  • 25
    Acontext

    Acontext

    Context data platform for building observable, self-learning AI agents

    Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also...
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