Showing 16938 open source projects for "engineering"

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  • 1
    TurboDiffusion

    TurboDiffusion

    100–200× Acceleration for Video Diffusion Models

    TurboDiffusion is an advanced open-source framework designed to dramatically accelerate video diffusion model generation, aiming for performance improvements on the order of 100–200× compared with traditional implementations while retaining high output quality. It achieves this by combining a suite of algorithmic and engineering optimizations, including attention acceleration techniques, efficient step distillation methods, and quantization strategies that reduce computational overhead. The project targets large video models and enables developers to run accelerated generation even on single high-end GPUs, making fast video synthesis more practical for research and creative workflows. ...
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  • 2
    AI-Job-Notes

    AI-Job-Notes

    AI algorithm position job search strategy

    AI-Job-Notes is a pragmatic notebook for landing roles in machine learning, computer vision, and related engineering tracks. It assembles study paths, checklists, and interview prep materials, but also covers job-search mechanics—portfolio building, resume patterns, and communication tips. The emphasis is on doing: practicing with project ideas, setting up reproducible experiments, and showcasing results that convey impact. It ties technical study (ML/DL fundamentals) to real hiring signals like problem-solving, code quality, and experiment logging. ...
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  • 3
    The Swift Programming Language Chinese

    The Swift Programming Language Chinese

    The Swift Programming Language in Chinese

    The Chinese version of Apple's official Swift tutorial "The Swift Programming Language" Swift is a fantastic way to write software, whether it’s for phones, desktops, servers, or anything else that runs code. It’s a safe, fast, and interactive programming language that combines the best in modern language thinking with wisdom from the wider Apple engineering culture and the diverse contributions from its open-source community. The compiler is optimized for performance and the language is optimized for development, without compromising on either. Swift is friendly to new programmers. It’s an industrial-quality programming language that’s as expressive and enjoyable as a scripting language. ...
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  • 4
    EQUINOX PROJECT

    EQUINOX PROJECT

    Full ASP.NET Core 5 application with DDD, CQRS and event sourcing

    ...Full architecture with responsibility separation concerns, solid and clean code. Booking application with domain model pattern, CQRS and ES concepts. Maybe you don't need a lot of implementations that is included, try avoid the over-engineering.
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  • 5
    AnalysisAVP

    AnalysisAVP

    Encode decode, rgb yuv h264 aac flv mp4 rtmp

    ...The repository also references various multimedia frameworks and libraries like FFmpeg, SDL2, and x264, helping users understand their integration. It is designed as both a study guide and a reference for developers learning multimedia engineering. Overall, it serves as a structured learning path for audio and video system development.
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  • 6
    Keychron Hardware Design

    Keychron Hardware Design

    Industrial design files for Keychron keyboards and mice

    The Keychron-Keyboards-Hardware-Design project is a source-available repository that provides production-grade industrial design files for a wide range of Keychron keyboards and mice. It includes over one hundred device models with detailed CAD assets, allowing users to explore real-world hardware engineering practices and understand how commercial peripherals are constructed. The repository contains multiple file formats such as STEP, DXF, DWG, and PDF, enabling compatibility with professional CAD software and fabrication workflows. It is designed both as an educational resource and as a foundation for creating compatible accessories, giving users the ability to measure, remix, and prototype hardware components. ...
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  • 7
    AI Agent Deep Dive

    AI Agent Deep Dive

    AI Agent Source Code Deep Research Report

    ...The project is organized as a learning resource rather than a standalone framework, making it particularly useful for developers who want to move beyond surface-level prompt engineering into full agent system design. It explores how agents interact with environments, execute tasks, and maintain context over time, highlighting both strengths and limitations of current approaches. The repository likely includes diagrams, annotated code samples, and conceptual walkthroughs that mirror real production systems.
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  • 8
    G0DM0D3

    G0DM0D3

    LIBERATED AI CHAT

    G0DM0D3 is an experimental AI interaction framework designed to enable unrestricted or “liberated” conversational behavior in language models by altering how prompts and system instructions are structured. It is part of a broader ecosystem of projects that explore the boundaries of AI alignment, control, and prompt engineering. The tool provides a collection of prompt templates and interaction patterns that attempt to override or bypass built-in behavioral constraints in language models. It is primarily used for experimentation, red-teaming, and studying how AI systems respond to unconventional or adversarial inputs. The framework reflects a growing interest in understanding how system prompts influence model outputs and how those constraints can be manipulated. ...
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  • 9
    XenosRecomp

    XenosRecomp

    A tool for converting Xbox 360 shaders to HLSL

    ...This allows recompiled games to maintain visual fidelity while benefiting from modern hardware acceleration. The project addresses one of the most complex aspects of console reverse engineering, which is accurately reproducing proprietary GPU behavior in a portable and efficient way. By reconstructing the graphics pipeline, XenosRecomp enables developers to render scenes correctly without relying on emulation layers that can introduce performance overhead or inaccuracies.
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  • 10
    Devon

    Devon

    Open source AI pair programmer for coding, debugging, automation

    Devon is an open source AI-powered pair programming tool designed to assist developers with software engineering tasks through natural language interaction. It operates as an agent-based system that can explore codebases, edit files, and execute development workflows with minimal manual intervention. Devon uses a client-server architecture with a Python backend and multiple user interfaces, including a terminal interface and an Electron-based desktop application.
    Downloads: 0 This Week
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  • 11
    GCP Config Connector

    GCP Config Connector

    GCP Config Connector, a Kubernetes add-on for managing GCP resources

    ...Its central idea is that infrastructure objects such as Cloud Storage or Cloud Spanner resources can be described declaratively in manifests, after which Config Connector creates or updates the corresponding Google Cloud resources and continuously reconciles them to match the declared state. This makes the project highly valuable for teams practicing GitOps, platform engineering, or Kubernetes-centered operations, because it brings cloud resource management into the same control model used for application deployment. The repository also reflects an active emphasis on resource development and reconciliation reliability, including a newer direct development approach intended to provide a more Kubernetes-native authoring experience.
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  • 12
    MEDIUM_NoteBook

    MEDIUM_NoteBook

    Repository containing notebooks of my posts on Medium

    ...Each notebook typically focuses on explaining a specific concept through step-by-step examples that combine explanatory text, code, and visual outputs. The repository covers a wide variety of data science topics such as predictive modeling, data preprocessing, statistical analysis, and feature engineering. Because the notebooks are designed as educational materials, they often emphasize readability and reproducibility so that readers can easily run and modify the examples. The project is useful for learners who want to explore machine learning concepts interactively using Python and common data science libraries.
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  • 13
    Reco-papers

    Reco-papers

    Classic papers and resources on recommendation

    ...The repository includes papers from academic institutions and industry organizations and groups them according to topics such as retrieval and reranking, reinforcement learning in recommendation, and feature engineering infrastructure. By structuring these materials into categories, the project helps practitioners quickly discover relevant research for designing recommendation engines in production environments.
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  • 14
    Hephaestus

    Hephaestus

    Semi-Structured Agentic Framework. Workflows build themselves

    Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,...
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  • 15
    SkillForge

    SkillForge

    Ultimate meta-skill for generating best-in-class Claude Code skills

    SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before consideration complete. The system includes tooling that routes natural language inputs to existing skills, augments them, or generates new ones using autonomous phases, enforcing quality, extensibility, security, and timelessness. ...
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  • 16
    huihut interview

    huihut interview

    A summary of C/C++ technical interview basics

    interview is a curated repository of technical interview questions, solutions, and explanations covering a wide range of topics in computer science and software engineering. It aims to help developers prepare for job interviews by providing sample problems in algorithms, data structures, system design, databases, and programming language intricacies, often with code snippets and discussion. The repo is designed so learners can practice real interview scenarios, compare approaches, and internalize foundational concepts that are frequently tested by tech companies. ...
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  • 17
    DevOps Exercises

    DevOps Exercises

    Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git

    DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. Because it’s structured as Q&A and exercises, you can go through it progressively or dip into specific domains where you need strengthening. ...
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  • 18
    repren

    repren

    Rename anything

    ...It handles recursive directory walks, lets you filter which files to touch, and supports multiple patterns in a single run to keep transformations consistent. Because it’s script-friendly, it slots well into project maintenance, codebase migrations, or release engineering tasks. The goal is to give you a reliable, repeatable alternative to ad-hoc shell loops when large-scale text and filename changes are needed.
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  • 19
    MiniMax-M1

    MiniMax-M1

    Open-weight, large-scale hybrid-attention reasoning model

    MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to...
    Downloads: 1 This Week
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  • 20
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. The framework is...
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  • 21
    Text-to-image Playground

    Text-to-image Playground

    A playground to generate images from any text prompt using SD

    ...Originally built around DALL-E Mini, the project later transitioned to using Stable Diffusion, enabling more detailed and higher-quality image synthesis. The system combines a backend machine learning service with a browser-based frontend interface that lets users experiment interactively with prompt engineering and generative AI. Developers can run the application locally or deploy it using cloud infrastructure, making it accessible both for experimentation and educational use. The platform demonstrates how large generative models can be integrated into user-friendly tools for creative exploration and rapid prototyping. It also serves as a reference architecture for building full-stack generative AI applications that connect model inference pipelines with web interfaces.
    Downloads: 0 This Week
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  • 22
    AutoTrain Advanced

    AutoTrain Advanced

    Faster and easier training and deployments

    ...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. The system integrates closely with the Hugging Face ecosystem and allows developers to train models using datasets hosted on the Hugging Face Hub. ...
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  • 23
    Prompt Poet

    Prompt Poet

    Streamlines and simplifies prompt design for both developers

    Prompt Poet is an open-source framework designed to simplify the creation, organization, and maintenance of prompts for large language model applications. The project focuses on transforming prompt engineering into a structured design process rather than ad-hoc string manipulation within application code. It allows developers and non-technical users to build prompts using templated configurations based on YAML and Jinja2, which makes prompts easier to compose, reuse, and modify across different environments. By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. ...
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  • 24
    AI CODE GUIDE

    AI CODE GUIDE

    AI Code Guide is a roadmap to start coding with AI

    ...Instead of focusing on a single framework or technology, the guide aggregates information about a wide ecosystem of tools including AI code editors, development platforms, and programming assistants. It also highlights best practices and common pitfalls developers may encounter when relying on AI tools in software engineering workflows.
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  • 25
    LearnLLM.AI

    LearnLLM.AI

    Sharing knowledge about big models that everyone can understand

    LLMForEverybody is an open-source educational repository designed to make large language model concepts accessible to a broad audience, including beginners, developers, and job candidates preparing for AI-related interviews. The project organizes knowledge about LLMs into a structured learning path that begins with foundational research papers and progresses through the evolution of modern model architectures. It covers a wide range of topics including attention mechanisms, tokenization...
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