Showing 1749 open source projects for "framework"

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  • 1
    FlaskBB

    FlaskBB

    A classic Forum Software in Python using Flask

    ...Our goal is to develop a forum system with modern technologies and sticking to already well-tested and approved layouts. FlaskBB is a simple and extensible forum software that should be seen as the foundation for building communities. It is written in Python using the web framework Flask. FlaskBB is being distributed under the BSD 3-Clause License.
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  • 2
    RecBole

    RecBole

    A unified, comprehensive and efficient recommendation library

    ...We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. It can be installed from pip, conda and source, and is easy to use. We have implemented more than 100 recommender system models, covering four common recommender system categories in RecBole and eight toolkits of RecBole2.0, including General Recommendation, Sequential Recommendation, Context-aware Recommendation, and Knowledge-based Recommendation and sub-packages.
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  • 3
    PyQt-SiliconUI

    PyQt-SiliconUI

    A powerful and artistic UI library based on PyQt5

    PyQt-SiliconUI is an open source UI framework built on top of PyQt5 that focuses on delivering visually elegant and highly customizable desktop application interfaces. It is designed as a comprehensive collection of UI components, layouts, and utilities that allow developers to build rich graphical user interfaces in Python with a modern and artistic aesthetic. The library includes a wide range of refactored widgets such as buttons, containers, editors, menus, sliders, and progress bars, all structured to work seamlessly with Qt’s layout system. ...
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  • 4
    Pika Skills

    Pika Skills

    A collection of open-source skills for AI coding agents

    Pika Skills is an open-source framework designed to extend the capabilities of AI coding agents by introducing modular, reusable “skills” that can be dynamically invoked during development workflows. Each skill acts as a self-contained unit composed of structured instructions, executable scripts, and dependency definitions, enabling agents to autonomously perform complex tasks without requiring manual configuration or orchestration.
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    Preswald

    Preswald

    Python tool for browser-based interactive data apps in one file

    Preswald is an open source Python-based framework and static-site generator designed for building interactive data applications that run entirely in the browser. It packages application logic, data processing, and user interface components into a single self-contained output, enabling easy sharing and deployment without requiring local dependencies. Preswald leverages a WebAssembly runtime along with technologies like Pyodide and DuckDB to execute Python code directly in the browser environment. ...
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  • 6
    MineContext

    MineContext

    MineContext is your proactive context-aware AI partner

    ...Unlike traditional chat-based assistants, MineContext operates in the background and delivers proactive outputs such as daily summaries, task suggestions, and contextual reminders without requiring explicit prompts. It is built around a context engineering framework that manages the full lifecycle of data, including capture, processing, storage, retrieval, and consumption. The platform emphasizes privacy through a local-first architecture, allowing users to keep their data stored and processed on their own device rather than relying on external cloud services.
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  • 7
    DreamerV3

    DreamerV3

    Mastering Diverse Domains through World Models

    ...This approach enables the algorithm to efficiently learn policies for decision-making tasks that would otherwise require enormous amounts of data or computational resources. DreamerV3 was designed as a general reinforcement learning framework that can solve diverse tasks using the same configuration of hyperparameters across many environments. In research demonstrations, the algorithm has been shown to perform strongly across more than one hundred control tasks and complex simulated environments.
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  • 8
    TimeMixer

    TimeMixer

    Decomposable Multiscale Mixing for Time Series Forecasting

    TimeMixer is a deep learning framework designed for advanced time series forecasting and analysis using a multiscale neural architecture. The model focuses on decomposing time series data into multiple temporal scales in order to capture both short-term seasonal patterns and long-term trends. Instead of relying on traditional recurrent or transformer-based architectures, TimeMixer is implemented as a fully multilayer perceptron–based model that performs temporal mixing across different resolutions of the data. ...
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  • 9
    face.evoLVe

    face.evoLVe

    High-Performance Face Recognition Library on PaddlePaddle & PyTorch

    face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. The repository supports multiple neural network backbones such as ResNet, DenseNet, MobileNet, and ShuffleNet, enabling experimentation with different architectures depending on performance requirements. ...
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  • 10
    AutoTrain Advanced

    AutoTrain Advanced

    Faster and easier training and deployments

    AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence embedding training, and large language model fine-tuning. ...
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  • 11
    Claude Code Skills & Plugins Hub

    Claude Code Skills & Plugins Hub

    270+ Claude Code plugins with 739 agent skills

    Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and...
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  • 12
    LongWriter

    LongWriter

    Unleashing 10,000+ Word Generation from Long Context LLMs

    LongWriter is an open-source framework and set of large language models designed to enable ultra-long text generation that can exceed 10,000 words while maintaining coherence and structure. Traditional large language models can process large inputs but often struggle to generate long outputs due to limitations in training data and alignment strategies. LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer responses. ...
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  • 13
    Magicoder

    Magicoder

    Empowering Code Generation with OSS-Instruct

    Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real...
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  • 14
    Hallucination Leaderboard

    Hallucination Leaderboard

    Leaderboard Comparing LLM Performance at Producing Hallucinations

    Hallucination Leaderboard is an open research project that tracks and compares the tendency of large language models to produce hallucinated or inaccurate information when generating summaries. The project provides a standardized benchmark that evaluates different models using a dedicated hallucination detection system known as the Hallucination Evaluation Model. Each model is tested on document summarization tasks to measure how often generated responses introduce information that is not...
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  • 15
    In-The-Wild Jailbreak Prompts on LLMs

    In-The-Wild Jailbreak Prompts on LLMs

    A dataset consists of 15,140 ChatGPT prompts from Reddit

    In-The-Wild Jailbreak Prompts on LLMs is an open-source research repository that provides datasets and analytical tools for studying jailbreak prompts used to bypass safety restrictions in large language models. The project is part of a research effort to understand how users attempt to circumvent alignment and safety mechanisms built into modern AI systems. The repository includes a large collection of prompts gathered from real-world platforms such as Reddit, Discord, prompt-sharing...
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  • 16
    Chat with LLMs Everywhere

    Chat with LLMs Everywhere

    Run PyTorch LLMs locally on servers, desktop and mobile

    TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a...
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  • 17
    LLM Workflow Engine

    LLM Workflow Engine

    Power CLI and Workflow manager for LLMs (core package)

    LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger additional processes. ...
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  • 18
    Deep Search Agent

    Deep Search Agent

    Implement a concise and clear Deep Search Agent from 0

    Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. It typically combines reasoning, retrieval, and iterative refinement so the agent can break down questions, gather evidence, and synthesize structured...
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  • 19
    nanochat

    nanochat

    The best ChatGPT that $100 can buy

    ...The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection.
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  • 20
    Glazier

    Glazier

    A tool for automating the installation of Windows OS

    Glazier is an automation framework developed by Google for deploying and managing Windows operating systems at scale. It streamlines the entire Windows imaging process by booting systems into the Windows Preinstallation Environment (WinPE), retrieving installation instructions from a web server, and automatically applying operating systems, software, and configurations.
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  • 21
    MuJoCo Playground

    MuJoCo Playground

    An open source library for GPU-accelerated robot learning

    MuJoCo Playground, developed by Google DeepMind, is a GPU-accelerated suite of simulation environments for robot learning and sim-to-real research, built on top of MuJoCo MJX. It unifies a range of control, locomotion, and manipulation tasks into a consistent and scalable framework optimized for JAX and Warp backends. The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups. It also offers optional vision-based training capabilities through integration with Madrona-MJX, allowing researchers to train policies directly from image input on GPUs. ...
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  • 22
    4M

    4M

    4M: Massively Multimodal Masked Modeling

    4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities.
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  • 23
    DomainBed

    DomainBed

    DomainBed is a suite to test domain generalization algorithms

    DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and Invariant Risk Minimization (IRM) to more advanced techniques like Domain Adversarial Neural Networks (DANN), Adaptive Risk Minimization (ARM), and Invariance Principle Meets Information Bottleneck (IB-ERM/IB-IRM). ...
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  • 24
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. ...
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  • 25
    VGGT

    VGGT

    [CVPR 2025 Best Paper Award] VGGT

    VGGT is a transformer-based framework aimed at unifying classic visual geometry tasks—such as depth estimation, camera pose recovery, point tracking, and correspondence—under a single model. Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose or depth), making the system more robust to challenging viewpoints and textures. ...
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