Showing 3021 open source projects for "python windows"

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  • 1
    Fragments by E2B

    Fragments by E2B

    Open source template for AI-powered code generation apps w/ sandboxes

    Fragments is an open source template designed for building applications where artificial intelligence generates and executes code directly from natural language prompts. It provides a ready-to-use web interface where users can chat with AI models to create code snippets, applications, or scripts in various programming environments. Generated code can be executed safely in isolated sandbox environments using the E2B SDK, which helps protect the host system while running AI-produced programs....
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  • 2
    LLaMA-Mesh

    LLaMA-Mesh

    Unifying 3D Mesh Generation with Language Models

    LLaMA-Mesh is a research framework that extends large language models so they can understand and generate 3D mesh data alongside text. The system introduces a method for representing 3D meshes in a textual format by encoding vertex coordinates and face definitions as sequences that can be processed by a language model. By serializing 3D geometry into text tokens, the approach allows existing transformer architectures to generate and interpret 3D models without requiring specialized visual...
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  • 3
    second-brain-ai-assistant-course

    second-brain-ai-assistant-course

    Learn to build your Second Brain AI assistant with LLMs

    The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. The concept of a “second brain” refers to a personal knowledge repository containing notes, research, and documents that can be queried...
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  • 4
    mergekit

    mergekit

    Tools for merging pretrained large language models

    mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of...
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    Demo Series - Small Business Backup By Veeam

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  • 5
    AutoAgent

    AutoAgent

    AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework

    AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. The framework emphasizes self-managing workflow generation, where it can...
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  • 6
    Paper2Slides

    Paper2Slides

    From Paper to Presentation in One Click

    Paper2Slides is an automation tool that converts research papers, reports, and other documents into polished slide decks and posters with minimal manual effort. It is designed to replace the repetitive work of turning dense technical documents into presentation-friendly structure by extracting key points, figures, and data into a coherent visual narrative. The system supports multiple input formats, so you can process PDFs and common office documents rather than being locked to a single file...
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  • 7
    CosyVoice

    CosyVoice

    Multi-lingual large voice generation model, providing inference

    CosyVoice is a multilingual large voice generation model that offers a full-stack solution for training, inference, and deployment of high-quality TTS systems. The model supports multiple languages, including Chinese, English, Japanese, Korean, and a range of Chinese dialects such as Cantonese, Sichuanese, Shanghainese, Tianjinese, and Wuhanese. It is designed for zero-shot voice cloning and cross-lingual or mix-lingual scenarios, so a single reference voice can be used to synthesize speech...
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  • 8
    SAM 2

    SAM 2

    The repository provides code for running inference with SAM 2

    SAM2 is a next-generation version of the Segment Anything Model (SAM), designed to improve performance, generalization, and efficiency in promptable image segmentation tasks. It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time...
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  • 9
    GLM-4-Voice

    GLM-4-Voice

    GLM-4-Voice | End-to-End Chinese-English Conversational Model

    GLM-4-Voice is an open-source speech-enabled model from ZhipuAI, extending the GLM-4 family into the audio domain. It integrates advanced voice recognition and generation with the multimodal reasoning capabilities of GLM-4, enabling smooth natural interaction via spoken input and output. The model supports real-time speech-to-text transcription, spoken dialogue understanding, and text-to-speech synthesis, making it suitable for conversational AI, virtual assistants, and accessibility...
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  • 10
    CogAgent

    CogAgent

    An open sourced end-to-end VLM-based GUI Agent

    CogAgent is a 9B-parameter bilingual vision-language GUI agent model based on GLM-4V-9B, trained with staged data curation, optimization, and strategy upgrades to improve perception, action prediction, and generalization across tasks. It focuses on operating real user interfaces from screenshots plus text, and follows a strict input–output format that returns structured actions, grounded operations, and optional sensitivity annotations. The model is designed for agent-style execution rather...
    Downloads: 1 This Week
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  • 11
    Qwen2.5-Math

    Qwen2.5-Math

    A series of math-specific large language models of our Qwen2 series

    Qwen2.5-Math is a series of mathematics-specialized large language models in the Qwen2 family, released by Alibaba’s QwenLM. It includes base models (1.5B / 7B / 72B parameters), instruction-tuned versions, and a reward model (RM) to improve alignment. Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical...
    Downloads: 1 This Week
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  • 12
    Diffusers

    Diffusers

    State-of-the-art diffusion models for image and audio generation

    Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions. State-of-the-art diffusion pipelines that can be run in inference with just a...
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  • 13
    Key-book

    Key-book

    Proofs, cases, concept supplements, and reference explanations

    The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven...
    Downloads: 1 This Week
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  • 14
    DeepXDE

    DeepXDE

    A library for scientific machine learning & physics-informed learning

    DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving...
    Downloads: 1 This Week
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  • 15
    SemIf

    SemIf

    Semantic ifs from open models, on a 3090 at home

    SemIf, formerly OpenJev, is an independent research project for making small semantic decisions with open language models. Instead of generating text and parsing it afterward, it reads probabilities directly from declared answer options. Each request supplies state, a runtime-defined question, and typed choices, allowing the model to behave like a semantic conditional. Shared-state execution can reuse a long context across many related decisions to reduce repeated computation. Backends...
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  • 16
    Kev

    Kev

    Jev-like family of decision models built on top of Qwen3.5/3.8

    Kev is a family of open decision models inspired by Jev and built on Qwen3.5 and Qwen3.8 foundations. It processes a document together with multiple typed questions and returns probabilities instead of generated prose. Supported question formats include yes-or-no, multiple choice, and ordered scoring. Checkpoints range from a compact 0.8B model for smaller hardware to a 27B version for high-end systems. The models include probability calibration and can run through CUDA, ROCm, or MLX...
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  • 17
    MSA: Memory Sparse Attention

    MSA: Memory Sparse Attention

    Trainable latent-memory framework for 100M-token contexts

    MSA, or Memory Sparse Attention, is a research framework for scaling language-model memory to extremely long contexts. It replaces full attention over all tokens with sparse selection of compressed latent memory states. Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. Its Memory Parallel engine distributes scoring and transfers...
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  • 18
    Hiring Agent

    Hiring Agent

    AI agent to evaluate and score resumes

    Hiring Agent is an AI-powered resume evaluation pipeline for screening technical candidates. It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence,...
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  • 19
    HRM-Text

    HRM-Text

    1B text generation model based on the HRM architecture

    HRM-Text is a one-billion-parameter text generation model and pretraining framework based on the Hierarchical Reasoning Model architecture. It is designed to make foundation model pretraining more accessible by reducing compute and data requirements compared with traditional scaling-heavy approaches. The system combines hierarchical recurrent design, task-completion strengthening, and latent-space reasoning. Its training stack includes PrefixLM sequence packing, FlashAttention 3 kernels,...
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  • 20
    Dia2

    Dia2

    TTS model capable of streaming conversational audio in realtime

    Dia2 is a streaming dialogue text-to-speech model created by Nari Labs for generating conversational audio in real time. It is designed to begin producing speech before receiving the entire input text, which makes it useful for interactive voice applications. The model supports audio conditioning, allowing generated speech to follow a reference voice or conversational style more naturally. Dia2 provides 1B and 2B model checkpoints along with inference code for research and experimentation....
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  • 21
    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. It supports training smaller or larger models, including million- and...
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  • 22
    Agent Control

    Agent Control

    Centralized agent control plane for governing runtime agent behavior

    Agent Control is a centralized control plane for governing AI agent behavior at runtime across different frameworks and deployment environments. It lets teams define controls once and apply them consistently to agents without rewriting the agent’s core code. The platform evaluates agent inputs and outputs against configurable policies to reduce risks such as prompt injection, unsafe responses, sensitive data exposure, and policy drift. It is designed for production environments where...
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  • 23
    Flow-Next

    Flow-Next

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

    Flow-Next is a workflow orchestration tool designed to manage complex processes by structuring tasks into organized and repeatable pipelines. It focuses on improving productivity by allowing users to define workflows that can be executed step by step or in parallel. 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...
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  • 24
    GEO Content Writer

    GEO Content Writer

    Backlog-row-first content production system for teams

    GEO Content Writer is an AI-based content generation tool designed to create optimized content tailored for geographic and semantic search contexts. It focuses on producing articles, pages, and structured content that align with both traditional SEO requirements and emerging AI search patterns. The system leverages language models to generate content that is context-aware, location-specific, and optimized for discoverability. It supports automated workflows for generating large volumes of...
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  • 25
    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...
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