Showing 656 open source projects for "command-line kill linux"

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  • 1
    Mentat

    Mentat

    Mentat - The AI Coding Assistant

    Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them...
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  • 2
    Claude Code Hooks Mastery

    Claude Code Hooks Mastery

    Master Claude Code Hooks

    Claude Code Hooks Mastery is a trending community-centric GitHub repository aimed at helping developers master Claude Code hooks — customizable integration points that let users extend, automate, and augment workflows when using Claude Code, an agentic terminal coding assistant. Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to...
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  • 3
    Sec-Context

    Sec-Context

    AI Code Security Anti-Patterns distilled from 150+ sources

    Sec-Context is a curated security research project that distills common code anti-patterns and vulnerabilities that generative AI tends to produce, presenting them as a comprehensive set of examples and secure alternatives that can be used to train or guide AI assistants and reviewers toward safer code generation. It compiles insights from over 150 industry and academic sources into structured reference documents that outline real-world security problems such as hardcoded secrets, SQL...
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  • 4
    SimpleLLM

    SimpleLLM

    950 line, minimal, extensible LLM inference engine built from scratch

    SimpleLLM is a minimal, extensible large language model inference engine implemented in roughly 950 lines of code, built from scratch to serve both as a learning tool and a research platform for novel inference techniques. It provides the core components of an LLM runtime—such as tokenization, batching, and asynchronous execution—without the abstraction overhead of more complex engines, making it easier for developers and researchers to understand and modify. Designed to run efficiently on...
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  • 5
    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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  • 6
    VLMEvalKit

    VLMEvalKit

    Open-source evaluation toolkit of large multi-modality models (LMMs)

    VLMEvalKit is an open-source evaluation toolkit designed for benchmarking large vision-language models that combine visual understanding with natural language reasoning. The toolkit provides a unified framework that allows researchers and developers to evaluate multimodal models across a wide range of datasets and standardized benchmarks with minimal setup. Instead of requiring complex data preparation pipelines or multiple repositories for each benchmark, the system enables evaluation...
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  • 7
    Archon

    Archon

    The knowledge and task management backbone for AI coding assistants

    Archon is an open-source “command center” designed to enhance AI coding assistant workflows by giving developers a centralized environment for knowledge management, context engineering, and task coordination across AI agents. It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. Users can...
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  • 8
    OpenMLDB

    OpenMLDB

    OpenMLDB is an open-source machine learning database

    OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference. OpenMLDB is an open-source machine learning database that is committed to solving the data and feature challenges. OpenMLDB has been deployed in hundreds of real-world enterprise applications. It prioritizes the capability of feature engineering using SQL for open-source, which offers a feature platform enabling consistent features for training and...
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  • 9
    ChatGPT Discord Bot

    ChatGPT Discord Bot

    Integrate ChatGPT into your own discord bot

    Build your own Discord bot using ChatGPT. Using certain personas may generate vulgar or disturbing content. Use at your own risk. Public mode (default), the bot directly replies on the channel. The bot's reply can only be seen by the person who used the command. Invite your bot to your server via OAuth2 URL Generator. Email/Password authentication (Not supported for Google/Microsoft accounts). A system prompt would be invoked when the bot is first started or reset. You can set it up by...
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  • 10
    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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  • 11
    Personal AI Infrastructure

    Personal AI Infrastructure

    Agentic AI Infrastructure for magnifying HUMAN capabilities

    Personal AI Infrastructure (PAI) is an ambitious open-source project focused on building a deeply personalized agentic AI system that learns from every interaction to magnify human capabilities across tasks and workflows. Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code...
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  • 12
    AnyTool

    AnyTool

    AnyTool: Universal Tool-Use Layer for AI Agents

    AnyTool is an open-source universal tool-use layer for AI agents that addresses the critical problem of how autonomous agents reliably interact with external tools and environments. Rather than having each agent handle tool invocation logic on its own, AnyTool provides a standardized interface and orchestrator that intelligently selects and manages tools, reduces context overhead, and improves execution reliability across diverse capabilities like web APIs, local commands, and GUI...
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  • 13
    AutoMaker

    AutoMaker

    Start directing AI agents

    Automaker is an autonomous AI development studio designed to transform how software is built by allowing developers to describe features, then watching AI agents implement code, tests, commits, and more with minimal manual typing. Instead of writing every line of code by hand, users add feature cards to a Kanban board with natural language descriptions, and AI agents powered by the Claude Agent SDK handle multi-step tasks such as planning, generating code, running tests, and committing to an...
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  • 14
    Kodu

    Kodu

    Kodu is an autonomous coding agent that lives in your IDE

    Claude Coder is an open-source developer environment that integrates Anthropic’s Claude models directly into the coding workflow, functioning as a local or hosted AI pair programmer. It provides conversational and in-line code assistance, helping developers write, refactor, and debug code through context-aware interactions. The system runs through a local interface or within VS Code and other editors, maintaining privacy by keeping context on-device when possible. Claude Coder supports...
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  • 15
    Hunyuan3D-1

    Hunyuan3D-1

    A Unified Framework for Text-to-3D and Image-to-3D Generation

    Hunyuan3D-1 is an earlier version in the same 3D generation line (the unified framework for text-to-3D and image-to-3D tasks) by Tencent Hunyuan. It provides a framework combining shape generation and texture synthesis, enabling users to create 3D assets from images or text conditions. While less advanced than version 2.1, it laid the foundations for the later PBR, higher resolution, and open-source enhancements. (Note: less detailed public documentation was found for Hunyuan3D-1 compared to...
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  • 16
    Text2Code for Jupyter notebook

    Text2Code for Jupyter notebook

    A proof-of-concept jupyter extension which converts english queries

    Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be...
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  • 17
    CC Mirror

    CC Mirror

    Create multiple isolated Claude Code variants with custom providers

    CC Mirror is an opinionated distribution and environment manager for Claude Code that lets you create multiple isolated Claude Code variants with custom configurations, providers, and feature packs on demand. Rather than running a single global Claude Code installation, cc-mirror creates separate instances — each with its own config, session store, prompt packs, theme tweaks, and optional preloaded skills — so you can tailor different environments for specific tasks, teams, or...
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  • 18
    Koila

    Koila

    Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code

    Koila is a lightweight Python library designed to help developers avoid memory errors when training deep learning models with PyTorch. The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward...
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  • 19
    Claude Code Security Reviewer

    Claude Code Security Reviewer

    An AI-powered security review GitHub Action using Claude

    The claude-code-security-review repository implements a GitHub Action that uses Claude (via the Anthropic API) to perform semantic security audits of code changes in pull requests. Rather than relying purely on pattern matching or static analysis, this action feeds diffs and surrounding context to Claude to reason about potential vulnerabilities (e.g. injection, misconfigurations, secrets exposure, etc). When a PR is opened, the action analyzes only the changed files (diff-aware scanning),...
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  • 20
    UpTrain

    UpTrain

    Your open-source LLM evaluation toolkit

    Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison...
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  • 21
    web-eval-agent MCP Server

    web-eval-agent MCP Server

    An MCP server that autonomously evaluates web applications

    web-eval-agent is a Model Context Protocol (MCP) server that spins up a browser-use–capable debugging agent to autonomously run and evaluate web apps straight from your editor. It’s positioned as a “let the coding agent debug itself” companion: the agent launches the app, navigates flows, captures evidence, and iterates on failures without manual copy-pasting of logs. The repository focuses on developer ergonomics, exposing typed MCP tools so clients like Claude Desktop can start sessions,...
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  • 22
    Datasets

    Datasets

    Hub of ready-to-use datasets for ML models

    Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep...
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  • 23
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,...
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  • 24
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 25
    MedicalGPT

    MedicalGPT

    MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training

    MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.
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