Showing 602 open source projects for "linux cli minimal"

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  • 1
    Chandra

    Chandra

    OCR model for complex documents with layout-aware structured outputs

    Chandra is an advanced OCR model designed to extract and structure information from complex documents such as tables, forms, handwritten notes, and mathematical content. It focuses on preserving full document layout, meaning that extracted text is accompanied by positional metadata like bounding boxes for each element. Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. It is capable of...
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  • 2
    TONL

    TONL

    TONL (Token-Optimized Notation Language)

    TONL is a cutting-edge data platform built around a production-ready serialization format designed to be both compact and powerful, combining human readability with performance features that make it suitable for large-scale applications and AI workflows. It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems. TONL isn’t just a format — it...
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  • 3
    Spark TTS

    Spark TTS

    Spark-TTS Inference Code

    Spark TTS is an open-source, PyTorch-based text-to-speech inference system that leverages large language models to produce highly natural, intelligible speech from text input. It uses an efficient single-stream architecture where speech tokens are directly reconstructed from the predictions of an LLM, removing the need for external acoustic models or complex vocoders and making the generation pipeline cleaner and faster. The project supports zero-shot voice cloning, meaning it can imitate a...
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  • 4
    Sled

    Sled

    Teleport Claude Code, Codex or Gemini CLI to your phone

    Sled under the layercodedev account appears to be a lightweight web and mobile UI aimed at interacting with local coding agents, likely including AI-assisted coding models or remote execution integrations; it’s designed in TypeScript/JavaScript and intended to let developers use or control coding agents from various devices. Although specific details in the repository are limited without direct project documentation, context and related online mentions indicate it functions as a local...
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  • 5
    Magika

    Magika

    Fast and accurate AI powered file content types detection

    Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for...
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  • 6
    DeepEval
    DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning,...
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  • 7
    Anthony Fu's Skills

    Anthony Fu's Skills

    Anthony Fu's curated collection of agent skills

    Anthony Fu's Skills is an open-source collection of agent skills — modular instruction packages that teach AI coding assistants how to perform specific tasks automatically when relevant. These skills are typically simple, human-readable files that contain structured steps, rules, examples, and workflow logic, letting tools like Claude Code or Copilot CLI load and run them only when they apply to the user’s input. By offloading detailed task patterns into discrete skill modules, developers...
    Downloads: 1 This Week
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  • 8
    files-to-prompt

    files-to-prompt

    Concatenate a directory full of files into a single prompt

    files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It...
    Downloads: 2 This Week
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  • 9
    FastKoko

    FastKoko

    Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model

    FastKoko is a self-hosted text-to-speech server built around the Kokoro-82M model and exposed through a FastAPI backend. It is designed to be easy to deploy via Docker, with separate CPU and GPU images so that users can choose between pure CPU inference and NVIDIA GPU acceleration. The project exposes an OpenAI-compatible speech endpoint, which means existing code that talks to the OpenAI audio API can often be pointed at a Kokoro-FastAPI instance with minimal changes. It supports multiple...
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  • 10
    VGGSfM

    VGGSfM

    VGGSfM: Visual Geometry Grounded Deep Structure From Motion

    VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support...
    Downloads: 1 This Week
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  • 11
    GluonTS

    GluonTS

    Probabilistic time series modeling in Python

    GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models. GluonTS requires Python 3.6 or newer, and the easiest way to install it is via pip. We train a DeepAR-model and make predictions using the simple "airpassengers" dataset. The dataset consists of a single time-series, containing monthly international passengers between the years 1949 and 1960, a total of 144 values (12 years * 12 months). We split the dataset into train and test parts,...
    Downloads: 1 This Week
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  • 12
    How to Train Your GPT

    How to Train Your GPT

    Build a modern LLM from scratch. Every line commented

    How to Train Your GPT is an interactive textbook that teaches users how to build, train, and run a modern language model from scratch. It is written for learners with minimal machine-learning background, using simple explanations, commented code, and practical examples. The project covers the same broad family of architecture behind systems such as GPT-style models, LLaMA-style models, Claude-style systems, and Mistral-style models. It includes chapters and topic explainers on tokenizers,...
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  • 13
    Rust Port

    Rust Port

    The Rust workspace under rust/ is the current systems-language port

    Rust Port is an open-source reconstruction and experimentation framework derived from leaked or reverse-engineered versions of advanced AI coding agents, designed to replicate and extend the capabilities of agentic development systems. It functions as a programmable coding assistant that operates through autonomous workflows, enabling users to generate, modify, and analyze code with minimal manual intervention. The project emphasizes agent-based execution, where tasks are broken down into...
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  • 14
    Ultralytics

    Ultralytics

    Ultralytics YOLO

    Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. The framework...
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  • 15
    Humanoid-Gym

    Humanoid-Gym

    Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real

    Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training....
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  • 16
    MiniOneRec

    MiniOneRec

    Minimal reproduction of OneRec

    MiniOneRec is an open-source framework designed to explore generative approaches to recommendation systems using large language model architectures. Traditional recommender systems typically rely on large embedding tables and ranking models, but MiniOneRec adopts a generative paradigm in which items are represented as sequences of semantic identifiers generated by autoregressive models. The framework provides an end-to-end pipeline for building generative recommender systems, including...
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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
    Pathway AI Pipelines

    Pathway AI Pipelines

    Ready-to-run cloud templates for RAG

    Pathway AI Pipelines is a collection of ready-to-deploy AI pipeline templates designed to help developers rapidly build production-grade retrieval-augmented generation and enterprise search applications. The project provides end-to-end examples that connect live data sources to LLM workflows, enabling applications to stay synchronized with continuously changing information. It supports numerous connectors including local files, Google Drive, SharePoint, Kafka, PostgreSQL, and real-time APIs,...
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  • 19
    AI PDF Chatbot LangChain

    AI PDF Chatbot LangChain

    AI PDF chatbot agent built with LangChain & LangGraph

    AI PDF Chatbot LangChain is a full-stack template for building conversational agents that can ingest and answer questions about PDF documents. The project demonstrates how to combine LangChain and LangGraph with a vector database to enable retrieval-augmented question answering over user-provided files. It includes both frontend and backend components, making it suitable as a production starting point rather than just a minimal demo. The system parses uploaded PDFs into document chunks,...
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  • 20
    Neovim 99

    Neovim 99

    Neovim AI agent done right

    Neovim 99 is an experimental GitHub repository created by well-known developer and educator ThePrimeagen that explores what he describes as the “ideal AI workflow” for developers who want a streamlined, high-quality integration of AI tooling into real coding environments — particularly focused on tools like Neovim and agent-centric workflows. Rather than a polished end-product, this repo serves as a playground for testing, iterating, and documenting workflows that integrate AI agents...
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  • 21
    ZAPI

    ZAPI

    ZAPI by Adopt AI is an open-source Python library

    ZAPI is a developer-centric API framework that streamlines building, testing, and deploying APIs with strong type safety and minimal boilerplate, helping teams deliver backend services faster with fewer errors. It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication...
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  • 22
    Reader 3

    Reader 3

    Quick illustration of how one can easily read books together with LLMs

    This project is a minimalist, self-hosted EPUB reader designed to help users browse and read EPUB books one chapter at a time through a lightweight local server, making it especially easy to extract or work with chapters in external tools like large language models. It was created primarily as a simple demonstration of how to combine local book reading with LLM workflows without heavy dependencies or complicated setup, and it runs with just a small Python script and a basic HTTP server. The...
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  • 23
    fast-stable-diffusion

    fast-stable-diffusion

    Fast-stable-diffusion + DreamBooth

    fast-stable-diffusion is a community-curated GitHub repository that provides Colab notebooks and integration examples for running Stable Diffusion and associated UIs like AUTOMATIC1111, ComfyUI, and DreamBooth directly on Google Colab environments. Rather than being a standalone packaged application, this project offers ready-to-use interactive notebooks that install and launch full-feature Stable Diffusion web UIs inside Colab without requiring complex local setups or GPU installations....
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  • 24
    LingBot-VLA

    LingBot-VLA

    A Pragmatic VLA Foundation Model

    LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. The model aims to bridge...
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  • 25
    nanocode

    nanocode

    Minimal Claude Code alternative. Single Python file, zero dependencies

    nanocode is a minimalist coding agent implementation designed as a compact alternative to Claude Code, packaged in a single Python file with no external dependencies and totaling around 250 lines of code. It implements a full agentic loop where the model can reason, decide when to use tools, execute those tools, and iterate until producing a final answer, making it useful for simple AI-assisted coding workflows. It includes a set of integrated tools such as read, write, edit, glob, grep, and...
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