Search Results for "obd source code" - Page 97

Showing 20861 open source projects for "obd source code"

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    ChatJS

    ChatJS

    Production-ready AI chat. Start here and make it your own

    ChatJS is a production-ready AI chat foundation for developers who want to launch customizable chat applications without rebuilding common infrastructure from scratch. The project presents itself as a starting point that already includes authentication, model access, streaming, and tool support so teams can focus on their own product-specific features. Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and...
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  • 2
    AI Agents From Scratch

    AI Agents From Scratch

    Demystify AI agents by building them yourself. Local LLMs

    AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external...
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  • 3
    mgrep

    mgrep

    A calm, CLI-native way to semantically grep everything, like code

    This project is a modern, semantic search tool that brings the simplicity of traditional command-line grep to the world of natural language and multimodal content, enabling users to search across codebases, documents, PDFs, and even images using meaning-aware queries. Built with a focus on calm CLI experiences, it lets you index and query your local files with semantic understanding, delivering results that are relevant to your intent rather than simple pattern matches, which is especially...
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  • 4
    n-skills

    n-skills

    Curated plugin marketplace for AI agents

    n-skills is a curated plugin marketplace and universal skills collection for AI coding agents that standardizes how skills are defined, discovered, and installed across multiple frameworks and agent platforms. It organizes skills into categories such as workflow orchestration, tools, automation, and documentation support, making it easy for developers to add capabilities like browser automation, multi-agent workflow coordination, or repo maintenance assistance. The repository includes a...
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    Context Engineering Template

    Context Engineering Template

    Context engineering is the new vibe coding

    Context Engineering Template is a comprehensive template and workflow repository designed to teach and implement context engineering, a structured approach to preparing and organizing the information necessary for AI coding assistants to complete complex tasks reliably. Instead of relying solely on short prompts, this project encourages developers to create rich, structured context files that include project rules, examples, and validation criteria so that AI systems can act more like...
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  • 6
    CSS Reference

    CSS Reference

    Fee visual guide to the most popular CSS properties

    CSS Reference is a human-friendly, example-driven reference for CSS that focuses on how properties behave in practice rather than only listing their syntax. Each entry explains what a property does, shows concise examples, and illustrates the visual result so you can internalize concepts quickly. The reference highlights common pitfalls and “gotchas,” helping you avoid surprises when mixing layout modes like Flexbox and Grid or when dealing with overflow and positioning. It favors clarity...
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  • 7
    handson-ml2

    handson-ml2

    Jupyter notebooks that walk you through the fundamentals of ML

    This repository contains the Jupyter notebooks and code for the second edition of a popular hands-on machine learning book that teaches both classical ML and deep learning using modern tooling. The notebooks emphasize end-to-end workflows: data preparation, model selection, tuning, and reliable evaluation. Deep learning sections use the contemporary Keras/TensorFlow 2 ecosystem, highlighting clean APIs and eager execution to make experiments easier to reason about. Traditional ML topics...
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  • 8
    Front-End Performance Checklist

    Front-End Performance Checklist

    The only Front-End Performance Checklist that runs faster

    Front-End-Performance-Checklist is a comprehensive, developer-friendly guide that consolidates the most impactful client-side performance practices into a single, scannable resource. It frames performance as a front-end responsibility and turns broad principles into concrete, verifiable checks you can apply before shipping. The checklist is organized by areas such as HTML, CSS, JavaScript, fonts, images, and network delivery, so teams can tackle bottlenecks systematically. Each section...
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  • 9
    phpunit/php-timer

    phpunit/php-timer

    Utility class for timing

    php-timer is a tiny utility library that provides high-resolution timing for PHP scripts, originating from the PHPUnit ecosystem. It wraps PHP’s underlying timing functions to give consistent start/stop measurements even across different PHP versions and environments. The library’s API is intentionally small so you can drop it into tests, benchmarks, and command-line tools without overhead. Beyond raw seconds, it can format durations into human-readable strings, which is especially handy for...
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  • 10
    Tunix

    Tunix

    A JAX-native LLM Post-Training Library

    Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation,...
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  • 11
    Wuffs

    Wuffs

    Wrangling Untrusted File Formats Safely

    Wuffs is a memory-safe, zero-dependency library and domain-specific language for writing high-performance image codecs and related parsers. Instead of trusting ad-hoc C, Wuffs code is compiled to C with strong bounds, integer, and state checks inserted by construction, aiming to eliminate whole classes of security bugs without a heavy runtime. The design prioritizes predictable performance: decoders avoid dynamic allocation by default, return explicit “short read” signals, and run well in...
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  • 12
    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. Training/inference configs and issues discuss things...
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  • 13
    JEPA

    JEPA

    PyTorch code and models for V-JEPA self-supervised learning from video

    JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well...
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  • 14
    PowerHub

    PowerHub

    A post exploitation tool based on a web application

    PowerHub is a PowerShell-based automation framework designed to centralize and orchestrate common administrative tasks across Windows environments. It exposes a modular command set for inventorying systems, managing services, deploying packages, and executing remote commands with consistent logging and error handling. The project places emphasis on discoverability and reuse: scripts are organized into reusable modules and functions with clear parameter contracts so teams can compose...
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  • 15
    Remarkable for Linux

    Remarkable for Linux

    The Markdown Editor for Linux

    With Live Preview you can see your changes as you make them. There is no need to export first to check your syntax. This is accompanied by synchronized scrolling. Remarkable has Github Flavoured Markdown. This has a simple, easy-to-learn syntax with features like checklists, highlighting, links, images and more. Remarkable allows you to export your files to PDF and HTML from within the app. The HTML code is even prettified and PDFs have a TOC. You can style your markdown documents however...
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  • 16
    ParallelStencil.jl

    ParallelStencil.jl

    Package for writing high-level code for parallel stencil computations

    ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array...
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  • 17
    CxxWrap

    CxxWrap

    Package to make C++ libraries available in Julia

    This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. This dynamic library is then loaded into Julia, where the Julia part of this package uses the data provided through a...
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  • 18
    Hutool

    Hutool

    A set of tools that keep Java sweet

    Hutool is a small but comprehensive Java tool class library. Through static method encapsulation, it reduces the learning cost of related APIs, improves work efficiency, makes Java as elegant as a functional language, and makes the Java language "sweet". The tools and methods in Hutool come from each user's meticulous attention to detail. It covers all aspects of the underlying code of Java development. It is not only a sharp tool to solve small problems in large-scale project development,...
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  • 19
    Tacit

    Tacit

    CSS framework for dummies, without a single CSS class

    Tacit is a CSS framework for dummies, who want their web services to look attractive but have almost zero skills in graphic design, just like myself. Tacit is a primitive CSS framework for dummies, like myself, who don't know anything about graphic design but want their web services to look eatable. No classes, no layouts. Just design plain and simple web pages compliant with HTML5 and they will look OK. Tacit's goal is to be super simple and always with the same look-and-feel. If you want...
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  • 20
    ROAPI

    ROAPI

    Create full-fledged APIs for slowly moving datasets without writing

    Create full-fledged APIs for slowly moving datasets without writing a single line of code. ROAPI automatically spins up read-only APIs and query frontends for slowly moving datasets without requiring you to write a single line of code. It builds on top of Apache Arrow and Datafusion. Query frontends to translate SQL, GraphQL and REST API queries into Datafusion plans. Datafusion for query plan execution. Data layer to load datasets from a variety of sources and formats with automatic schema...
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  • 21
    Laravel Analytics

    Laravel Analytics

    A Laravel package to retrieve pageviews and other data

    One of our more popular packages is laravel-analytics. The package makes it easy to fetch information such as pageviews, top referrers, etc... from the Google Analytics API. In our Blender-based projects we use the fetched data to display a nice chart in the admin section. Laravel-analytics is one of the first packages we ever created. Since the first release the preferred way of authenticating with Google has changed. We also learned a lot on how to create readable code. That's why we did a...
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  • 22
    Miniredis

    Miniredis

    Pure Go Redis server for Go unittests

    Sometimes you want to test code which uses Redis, without making it a full-blown integration test. Miniredis implements (parts of) the Redis server, to be used in unittests. It enables a simple, cheap, in-memory, Redis replacement, with a real TCP interface. It saves you from using mock code, and since the redis server lives in the test process you can query for values directly, without going through the server stack. There are no dependencies on external binaries, so you can easily...
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  • 23
    Foal

    Foal

    Full-featured Node.js framework, with no complexity

    It provides a set of ready-to-use components so you don't have to reinvent the wheel every time. In one single place, you have a complete environment to build web applications. This includes a CLI, testing tools, frontend utilities, scripts, advanced authentication, ORM, deployment environments, GraphQL and Swagger API, AWS utilities, and more. You no longer need to get lost on npm searching for packages and making them work together. All is provided. But while offering all these features,...
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  • 24
    NSubstitute

    NSubstitute

    A friendly substitute for .NET mocking libraries

    NSubstitute is designed for Arrange-Act-Assert (AAA) testing, so you just need to arrange how it should work, then assert it received the calls you expected once you're done. Because you've got more important code to write than whether you need a mock or a stub. It is an attempt to satisfy our craving for a mocking library with a succinct syntax that helps us keep the focus on the intention of our tests, rather than on the configuration of our test doubles. We've tried to make the most...
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  • 25
    IVY

    IVY

    The Unified Machine Learning Framework

    Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an...
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