Showing 7371 open source projects for "linux-debian"

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  • 1
    Zep

    Zep

    Zep: A long-term memory store for LLM / Chatbot applications

    Easily add relevant documents, chat history memory & rich user data to your LLM app's prompts. Understands chat messages, roles, and user metadata, not just texts and embeddings. Zep Memory and VectorStore implementations are shipped with your favorite frameworks: LangChain, LangChain.js, LlamaIndex, and more. Automatically embed texts and messages using state-of-the-art opeb source models, OpenAI, or bring your own vectors. Zep’s local embedding models and async enrichment ensure a snappy...
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  • 2
    TwitchIO

    TwitchIO

    An Async Bot/API wrapper for Twitch made in Python

    A fully asynchronous Python IRC, API, EventSub and PubSub library for Twitch. Full asynchronous design. Covers 100% of the Twitch API. IRC Commands extension for creating powerful chatbots. EventSub and PubSub support. Helper extensions for Music/Sounds and Background Tasks. Object-orientated design with stateful objects. TwitchIO is an asynchronous Python wrapper around the Twitch API and IRC, with a powerful command extension for creating Twitch Chat Bots. TwitchIO covers almost all of the...
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  • 3
    terminalGPT

    terminalGPT

    Get GPT like ChatGPT on your terminal

    Get GPT like ChatGPT on your terminal Note: This doesn't use OpenAI ChatGPT, it uses text-davinci-003 model (by default) You'll need to have your own OpenAi apikey to operate this package. 1. Go to https://beta.openai.com 2. Select you profile menu and go to View API Keys 3. Select + Create new secret key 4. Copy generated key Get started: Using tgpt: npm -g install terminalgpt or yarn global add terminalgpt Run tgpt chat ps.: If it is your first time...
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  • 4
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared...
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  • 5
    Lightly

    Lightly

    A python library for self-supervised learning on images

    ...We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions.
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  • 6
    dm_control

    dm_control

    DeepMind's software stack for physics-based simulation

    ...At least one of these three backends must be available in order render through dm_control. Hardware rendering with a windowing system is supported via GLFW and GLEW. On Linux these can be installed using your distribution's package manager. "Headless" hardware rendering (i.e. without a windowing system such as X11) requires EXT_platform_device support in the EGL driver. While dm_control has been largely updated to use the pybind11-based bindings provided via the mujoco package, at this time it still relies on some legacy components that are automatically generated.
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  • 7
    agentic-stack

    agentic-stack

    One brain, many harnesses. Portable .agent/ folder

    agentic-stack is a framework or toolkit designed to build, orchestrate, and deploy AI agents in a structured and scalable way. It likely provides components for managing agent workflows, communication, and task execution across different systems. The project emphasizes modularity, enabling developers to assemble custom pipelines using various AI models, tools, and APIs. It may include abstractions for memory, planning, and tool usage, reflecting modern agentic AI design patterns. The stack...
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  • 8
    GoDex

    GoDex

    AI coding agent

    GoDex is a developer-focused tool designed to enhance code exploration and understanding through AI-assisted workflows. It provides an interface that allows users to analyze codebases, generate insights, and interact with code using natural language queries. The system is built to improve productivity by reducing the time required to understand complex projects or unfamiliar code structures. It integrates with language models to provide contextual explanations, summaries, and suggestions....
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  • 9
    Excalibur

    Excalibur

    Excalibur is a highly opinionated agent harness

    Excalibur is an experimental or utility-oriented project that appears to focus on enabling structured execution, control, or enhancement of workflows within AI or development environments. The system likely provides tools for managing tasks, orchestrating processes, or enhancing decision-making capabilities in automated systems. Its design suggests an emphasis on control and precision, allowing users to define how tasks are executed and monitored. It may include abstractions for handling...
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  • 10
    Claude Code Best V3

    Claude Code Best V3

    The original Claude Code is runnable and buildable

    Claude Code Best V3 is an agentic coding system that enables developers to interact with their codebases through natural language while automating repetitive and complex development tasks. It operates primarily in terminal or IDE environments, where it can analyze code, explain logic, and perform actions such as refactoring, debugging, and managing version control. The system is designed to understand the structure and intent of a codebase, allowing it to provide context-aware assistance...
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  • 11
    Crucix

    Crucix

    Your personal intelligence agent

    Crucix is a project focused on creating a structured system for understanding and organizing complex concepts, often leveraging AI to assist in breaking down information into more digestible forms. It aims to help users navigate and synthesize knowledge by transforming raw information into structured insights. The system is designed to support iterative exploration, where users can refine their understanding through repeated interaction and analysis. Crucix emphasizes clarity and...
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  • 12
    TorchCode

    TorchCode

    Practice implementing softmax, attention, GPT-2 and more

    TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,...
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  • 13
    FIT Framework

    FIT Framework

    An enterprise-level AI development framework

    FIT Framework is an open-source infrastructure designed to support the development, training, and evaluation of machine learning and AI models through a modular and scalable architecture. It aims to streamline the lifecycle of AI systems by providing standardized components for data processing, model training, evaluation, and deployment. The framework is particularly useful for research and production environments where reproducibility and consistency are critical, as it enforces structured...
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  • 14
    Writing AI Conference Papers

    Writing AI Conference Papers

    Writing AI Conference Papers: A Handbook for Beginners

    WritingAIPaper is an open-source guide designed to help beginners understand and navigate the process of writing and publishing academic papers in the field of artificial intelligence. The project provides structured guidance on how to transform research ideas into complete manuscripts, covering topics such as defining the core contribution, organizing the paper structure, and refining technical details. It emphasizes practical advice and common pitfalls, making it especially useful for...
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  • 15
    pix2pixHD

    pix2pixHD

    Synthesizing and manipulating 2048x1024 images with conditional GANs

    pix2pixHD is a PyTorch-based implementation of a conditional generative adversarial network designed for high-resolution image-to-image translation, capable of producing photorealistic outputs at resolutions up to 2048×1024. It is widely used to convert structured inputs such as semantic label maps into realistic images, making it particularly valuable in applications like autonomous driving simulation, face synthesis, and scene generation. The model improves upon earlier GAN approaches by...
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  • 16
    Machine Learning Study

    Machine Learning Study

    This repository is for helping those interested in machine learning

    Machine Learning Study is an educational repository containing tutorials and study materials related to machine learning and data science using Python. The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through...
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  • 17
    daily.dev

    daily.dev

    Network for developers to learn, collaborate, and grow together

    daily.dev is the open-source codebase behind the daily.dev developer news platform, which aggregates and personalizes technical content for programmers. The project focuses on delivering curated feeds of articles, tutorials, and community discussions tailored to developer interests. It combines content aggregation, ranking algorithms, and user personalization to create an engaging discovery experience. The platform is built with modern web technologies and emphasizes performance and...
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  • 18
    Modular Platform

    Modular Platform

    The Modular Platform (includes MAX & Mojo)

    Modular is a high-performance AI infrastructure company repository focused on building next-generation compute and software tools for machine learning workloads. The project centers on enabling developers to run AI models faster and more efficiently by rethinking the traditional ML software stack. It is closely associated with the Mojo programming language and related tooling that aims to combine Python usability with systems-level performance. Modular’s ecosystem is designed to simplify...
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  • 19
    Taskmaster

    Taskmaster

    An AI-powered task-management system

    Taskmaster is an AI-powered task management system designed to enhance AI-driven software development workflows. The project can be integrated into environments such as Cursor, Windsurf, and other AI coding tools to help structure, track, and execute development tasks more effectively. It uses structured task formats and orchestration logic to coordinate how AI assistants plan and complete work. The system supports multiple model providers through configurable keys, allowing teams to choose...
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  • 20
    OpenSpec

    OpenSpec

    Spec-driven development (SDD) for AI coding assistants

    OpenSpec is a lightweight specification layer designed to improve reliability when working with AI coding assistants by formalizing requirements before code generation begins. The project addresses the common issue where AI tools produce inconsistent results when specifications exist only in chat history. It introduces a structured workflow that encourages teams to agree on what should be built before implementation starts. OpenSpec integrates into development pipelines and acts as a source...
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  • 21
    zclaw

    zclaw

    Your personal AI assistant at all-in 888KiB

    zclaw is a highly compact personal AI assistant framework designed to run on constrained embedded hardware such as the ESP32. The project focuses on delivering core assistant capabilities within an extremely small footprint, demonstrating how AI-driven automation can operate on microcontrollers. It includes support for GPIO control, scheduled tasks, memory handling, and other embedded automation features that enable real-world device interaction. The architecture is optimized for efficiency,...
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  • 22
    Ralph Wiggum Marketer

    Ralph Wiggum Marketer

    A Claude Code Plugin that provides an autonomous AI copywriter

    Ralph Wiggum Marketer is a Claude Code plugin that serves as an autonomous AI copywriter tailored for SaaS content marketing, enabling automated generation of marketing copy such as landing pages, taglines, feature summaries, and promotional messaging. It leverages the Ralph Wiggum loop concept — a continuous iteration pattern named after the iconic character that symbolizes persistent, repeated refinement — to let Claude Code keep iterating on content until predefined completion criteria...
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  • 23
    Monoio

    Monoio

    Rust async runtime based on io-uring

    Monoio is a Rust asynchronous runtime designed for high-performance I/O-bound servers and applications, built around native OS async I/O primitives (e.g. io_uring on Linux, epoll / kqueue on other Unix-like systems), rather than layering atop an existing runtime. Its design philosophy centers on a “thread-per-core” model where each core runs its own event loop, minimizing cross-thread synchronization needs, avoiding the overhead and complexity of task scheduling, and letting developers write efficient, low-overhead asynchronous networking or I/O code. ...
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  • 24
    LRSLibrary

    LRSLibrary

    Low-Rank and Sparse Tools for Background Modeling and Subtraction

    LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine...
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  • 25
    Coze Studio

    Coze Studio

    An AI agent development platform with all-in-one visual tools

    Coze Studio is ByteDance’s open‑source, visual AI agent development platform. It offers no-code/low-code workflows to build, debug, and deploy conversational agents, integrating prompting, RAG-based knowledge bases, plugin systems, and workflow orchestration. Developed in Go (backend) and React/TypeScript (frontend), it uses a containerized microservices architecture suitable for enterprise deployment.
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