Showing 1624 open source projects for "code source ping"

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  • 1
    agentmemory

    agentmemory

    #1 Persistent memory for AI coding agents

    agentmemory is a persistent memory server for AI coding agents that captures project context, past decisions, bugs, preferences, and implementation details so users do not have to re-explain the same information in every session. It works across tools such as Claude Code, Cursor, Gemini CLI, Codex CLI, OpenCode, Cline, and any client that supports MCP or REST APIs. The system automatically records what agents do, compresses that activity into searchable memory, and injects relevant context...
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  • 2
    Skills For Real Engineers

    Skills For Real Engineers

    Skills for Real Engineers. Straight from my .claude directory

    Skills For Real Engineers is a curated collection of modular AI “skills” designed to improve how developers interact with coding agents by enforcing structured engineering workflows. Each skill is a small, focused instruction set that guides an AI through tasks such as planning, refactoring, testing, or architectural analysis. Instead of relying on vague prompts, the system encodes repeatable processes that ensure consistent and higher-quality outputs. The repository includes tools for...
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  • 3
    yek

    yek

    Serialize repositories into LLM-ready context w/ smart prioritization

    Yek is a Rust-based CLI tool designed to serialize text-based files from a repository or directory into a single structured output for large language model use. It scans projects using .gitignore rules to exclude irrelevant files and automatically filters out binary or oversized content. Yek prioritizes files based on Git history, placing more important content later in the output to align with how language models process context. Yek supports multiple directories, individual files, and glob...
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  • 4
    deepjazz

    deepjazz

    Deep learning driven jazz generation using Keras & Theano

    deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music. The system analyzes musical sequences from an input MIDI file and then generates new musical notes that follow similar stylistic...
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  • 5
    TimesFM

    TimesFM

    Pretrained time-series foundation model developed by Google Research

    TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to...
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  • 6
    Softaworks Agent Skills

    Softaworks Agent Skills

    A curated collection of skills for AI coding agents

    The Softaworks Agent Toolkit is a comprehensive collection of agent skills, commands, and sub-agents designed to augment AI coding assistants like Claude Code, Codex, and Cursor with practical workflow capabilities. It packages broad categories of modular skills that help with development automation, documentation creation, planning, architecture, testing, and soft professional workflows. Beyond simple skills, it also includes agents and CLI slash commands that help developers automate...
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  • 7
    Sygil WebUI

    Sygil WebUI

    Stable Diffusion web UI

    Sygil WebUI is a browser-based interface for running Stable Diffusion image generation locally or on a server, wrapping common text-to-image and image-to-image workflows into a practical UI. It provides multiple UI modes (including a legacy Gradio interface) and focuses on making iterative prompting, parameter tuning, and post-processing accessible without writing code. The UI exposes core generation controls like resolution, CFG guidance, sampling steps, samplers, seeds, and batch...
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  • 8
    ticket

    ticket

    Fast, powerful, git-native ticket tracking in a single bash script

    ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage...
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  • 9
    Oasis

    Oasis

    Inference script for Oasis 500M

    Open-Oasis provides inference code and released weights for Oasis 500M, an interactive world model that generates gameplay frames conditioned on user keyboard input. Instead of rendering a pre-built game world, the system produces the next visual state via a diffusion-transformer approach, effectively “imagining” the world response to your actions in real time. The project focuses on enabling action-conditional frame generation so developers can experiment with interactive, model-generated...
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  • 10
    ByteHook

    ByteHook

    ByteHook is an Android PLT hook library

    ByteHook is a ByteDance-hosted project whose name suggests a hooking or instrumentation library, likely used for hooking system calls or API calls for monitoring, sandboxing or instrumentation. The repository appears to aim at low-level hooking/injection capabilities, perhaps to support runtime introspection, behavioral monitoring, or hooking-based instrumentation (e.g. for security, tracing, sandboxing, or debugging). Because hooking is a common technique for intercepting library or system...
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  • 11
    Lingvo

    Lingvo

    Framework for building neural networks

    Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state...
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  • 12
    StatsForecast

    StatsForecast

    Fast forecasting with statistical and econometric models

    StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery...
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  • 13
    Vision Transformer Pytorch

    Vision Transformer Pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA

    This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and...
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  • 14
    nanochat

    nanochat

    The best ChatGPT that $100 can buy

    nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and...
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  • 15
    Granite 3.0 Language Models

    Granite 3.0 Language Models

    New set of lightweight state-of-the-art, open foundation models

    This repository introduces Granite 3.0 language models as lightweight, state-of-the-art open foundation models built to natively support multilinguality, coding, reasoning, and tool usage. A central goal is efficient deployment, including the potential to run on constrained compute resources while remaining useful for a broad span of enterprise tasks. The repo positions the models for both research and commercial use under an Apache-2.0 license, signaling permissive adoption paths....
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  • 16
    Purple Llama

    Purple Llama

    Set of tools to assess and improve LLM security

    Purple Llama is an umbrella safety initiative that aggregates tools, benchmarks, and mitigations to help developers build responsibly with open generative AI. Its scope spans input and output safeguards, cybersecurity-focused evaluations, and reference shields that can be inserted at inference time. The project evolves as a hub for safety research artifacts like Llama Guard and Code Shield, along with dataset specs and how-to guides for integrating checks into applications. CyberSecEval, one...
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  • 17
    DreamCraft3D

    DreamCraft3D

    Official implementation of DreamCraft3D

    DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or...
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  • 18
    Instructor

    Instructor

    Structured outputs for llms

    Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of...
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  • 19
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++...
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  • 20
    Kubeflow pipelines

    Kubeflow pipelines

    Machine Learning Pipelines for Kubeflow

    Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as...
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  • 21
    GoCV

    GoCV

    Go package for computer vision using OpenCV 4 and beyond

    GoCV gives programmers who use the Go programming language access to the OpenCV 4 computer vision library. The GoCV package supports the latest releases of Go and OpenCV v4.5.4 on Linux, macOS, and Windows. Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software...
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  • 22
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models...
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  • 23
    Telegram Bot SDK

    Telegram Bot SDK

    Telegram Bot API PHP SDK to build Telegram Bots

    Telegram Bot SDK lets you develop Telegram Bots in PHP easily! Supports Laravel out of the box. Telegram Bot API is an HTTP-based interface created for developers keen on building bots for Telegram. Complete API Methods Support. Laravel Support out of the box! Clean, Highly Documented & Industry Standard Code. PSR Standards, popular & widely used. Powered by Laravel Collection API for Response Objects. Events/Plugin Support to Extend Features Conversational Support. Well-designed, tested &...
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  • 24
    Data Version Control

    Data Version Control

    Git-based data version control for machine learning workflows

    ...DVC also provides a pipeline system that defines the stages of machine learning workflows, making experiments reproducible and easier to manage. By tracking dependencies between code, data, and parameters, the system ensures that only the necessary stages are re-run when changes occur. DVC also includes experiment tracking capabilities that allow users to compare different training runs.
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  • 25
    Slack MCP Server

    Slack MCP Server

    The most powerful MCP Slack Server with no permission requirements

    ...Through this architecture, AI assistants can read message histories, interact with channels, and retrieve contextual information from Slack conversations in order to perform tasks such as automated analysis, collaboration assistance, or contextual code review. The server supports multiple communication transports, including standard input/output streams, HTTP, and Server-Sent Events, allowing flexible integration with different AI client environments.
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