Showing 15071 open source projects for "linux-lite"

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  • 1
    HumbleUI

    HumbleUI

    Clojure Desktop UI framework

    HumbleUI is a lightweight, declarative, and composable UI framework, likely intended for building graphical user interfaces in a minimal, modular way. It emphasizes ease of use, customization, and modular components. (Note: while there is a repository, I did not find a detailed README in my search to fully confirm all capabilities.) Electron is a great landmark. Normal shortcuts, icon, its own window, file system access, notifications, OS integrations. Write once, run everywhere is no longer...
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  • 2
    TreeQuest

    TreeQuest

    A Tree Search Library with Flexible API for LLM Inference-Time Scaling

    TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question...
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  • 3
    Airweave

    Airweave

    Airweave lets agents search any app

    Airweave is an open-source platform that enables agents to semantically search across various applications, databases, and APIs. By transforming disparate data sources into a unified, searchable knowledge base, Airweave facilitates intelligent information retrieval through REST APIs or the MCP protocol. It's particularly useful for building AI agents that require access to structured and unstructured data across multiple platforms.
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  • 4
    Magentic UI

    Magentic UI

    A research prototype of a human-centered web agent

    Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight.
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  • 5
    LitGPT

    LitGPT

    20+ high-performance LLMs with recipes to pretrain, finetune at scale

    LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments.
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  • 6
    ManiSkill

    ManiSkill

    SAPIEN Manipulation Skill Framework

    ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios.
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  • 7
    FastAgency

    FastAgency

    The fastest way to bring multi-agent workflows to production

    FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks.
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  • 8
    CRAB

    CRAB

    CRAB: Cross-environment Agent Benchmark for Multimodal Language Model

    CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together.
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  • 9
    TaskWeaver

    TaskWeaver

    A code-first agent framework for seamlessly planning analytics tasks

    TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks.
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    Go From Idea to Deployed AI App Fast

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  • 10
    DataProfiler

    DataProfiler

    Extract schema, statistics and entities from datasets

    DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and...
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  • 11
    Alerta

    Alerta

    Alerta monitoring system

    Email was not designed to be used as an alert console. It is not a scalable solution when it comes to monitoring and alert visualization. A minimal installation of Alerta can be deployed quickly and easily as monitoring requirements and confidence grow. There are integrations available with Prometheus, Riemann, Nagios, Zabbix, netdata, Sensu, Pingdom and Cloudwatch. Integrating bespoke systems is easy using the API or command-line tool. Alerts are submitted in JSON format to an HTTP API....
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  • 12
    Ragas

    Ragas

    Supercharge Your LLM Application Evaluations

    Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation.
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  • 13
    julep

    julep

    A new DSL and server for AI agents and multi-step tasks

    Julep is a platform for creating AI agents that remember past interactions and can perform complex tasks. It offers long-term memory and manages multi-step processes. Julep enables the creation of multi-step tasks incorporating decision-making, loops, parallel processing, and integration with numerous external tools and APIs. While many AI applications are limited to simple, linear chains of prompts and API calls with minimal branching, Julep is built to handle more complex scenarios.
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  • 14
    OpenQASM

    OpenQASM

    Quantum assembly language for extended quantum circuits

    OpenQASM is an imperative programming language designed for near-term quantum computing algorithms and applications. Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes. OpenQASM presents a parameterized set of physical logic gates and concurrent real-time classical computations. Its main goal is to serve as an intermediate representation for higher-level compilers to communicate...
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  • 15
    Bot Framework SDK for Python

    Bot Framework SDK for Python

    Build and connect intelligent bots that interact naturally

    This repository contains code for the Python version of the Microsoft Bot Framework SDK, which is part of the Microsoft Bot Framework - a comprehensive framework for building enterprise-grade conversational AI experiences. This SDK enables developers to model conversation and build sophisticated bot applications using Python. SDKs for JavaScript and .NET are also available. The Microsoft Bot Framework provides what you need to build and connect intelligent bots that interact naturally...
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  • 16
    Prompt flow

    Prompt flow

    Build high-quality LLM apps

    Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
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  • 17
    magentic

    magentic

    Seamlessly integrate LLMs as Python functions

    Easily integrate Large Language Models into your Python code. Simply use the @prompt and @chatprompt decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic.
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  • 18
    BindsNET

    BindsNET

    Simulation of spiking neural networks (SNNs) using PyTorch

    A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab.
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  • 19
    TorchAudio

    TorchAudio

    Data manipulation and transformation for audio signal processing

    The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch...
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  • 20
    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox (ART) - Python Library for ML security

    Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,...
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  • 21
    dateutil

    dateutil

    Useful extensions to the standard Python datetime features

    The dateutil module provides powerful extensions to the standard date time module, available in Python. dateutil can be installed from PyPI using pip (note that the package name is different from the importable name).
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  • 22
    arxiv_latex_cleaner

    arxiv_latex_cleaner

    arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper

    This tool allows you to easily clean the LaTeX code of your paper to submit to arXiv. From a folder containing all your code, e.g. /path/to/latex/, it creates a new folder /path/to/latex_arXiv/, that is ready to ZIP and upload to arXiv.
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  • 23
    Robusta

    Robusta

    Kubernetes observability and automation

    Keep your Kubernetes microservices up and running. Connect your existing Prometheus, gain 360° observability. Robusta is both an automation engine for Kubernetes and a multi-cluster observability platform. Robusta is commonly used alongside Prometheus, but other tools are supported too. By listening to all the events in your cluster, Robusta can tell you why alerts fired, what happened at the same time, and what you can do about it. Robusta can either improve your existing alerts or be used...
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  • 24
    nbcelltests

    nbcelltests

    Cell-by-cell testing for production Jupyter notebooks in JupyterLab

    nbcelltests is designed for writing tests for linearly executed notebooks. Its primary use is for unit testing reports. Cell-by-cell testing for production Jupyter notebooks in JupyterLab. To use in JupyterLab, you will also need the lab and server extensions. Typically, these are automatically installed alongside nbcelltests, so you should not need to do anything special to use them. The lab extension will require a rebuild of JupyterLab, which you'll be prompted to do on starting...
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  • 25
    miepython

    miepython

    Mie scattering of light by perfect spheres

    miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles.
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