Showing 2698 open source projects for "g-code"

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  • 1
    Growth Lab

    Growth Lab

    An end-to-end growth tool that understands the product

    Growth Lab is an open-source agentic growth workspace that connects product understanding, market research, execution, measurement, and iteration. It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work. Each growth model follows an observe-act-review loop and keeps persistent memory of evidence, actions, results, and recommended next steps. ...
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  • 2
    NeMo Automodel

    NeMo Automodel

    Pytorch Distributed native training library for LLMs/VLMs

    NeMo AutoModel is NVIDIA's open-source PyTorch Distributed training library for scaling LLM, VLM, diffusion, and retrieval-model training. Its DTensor-native SPMD approach lets the same training code scale from one GPU to large multi-node clusters by changing configuration. Hugging Face integration provides broad model compatibility without requiring format conversion. YAML recipes and CLI overrides keep experiments concise while preserving reproducibility. The library supports composable parallelism, optimized kernels, MoE acceleration, mixed precision, sequence packing, and asynchronous checkpointing. ...
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  • 3
    itr-wala

    itr-wala

    File your Indian income tax return (ITR) from your terminal

    itr-wala is an agent skill for preparing Indian income tax returns from a terminal while keeping tax calculations in deterministic Python code. The AI reads documents such as Form 16, AIS, and broker statements, asks follow-up questions, and explains the resulting figures. A separate tax engine handles slabs, rebates, cess, surcharges, special-rate income, interest, late fees, and old-versus-new regime comparisons. Strict validation cross-checks entered values and rejects malformed or sensitive identifiers. ...
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  • 4
    MCP Agent Mail

    MCP Agent Mail

    Asynchronous coordination layer for AI coding agents

    ...Git stores human-auditable communication artifacts, while SQLite supports indexing, search, and operational queries. The HTTP-only FastMCP server works with clients such as Claude Code, Codex, Gemini CLI, and other MCP-compatible tools. Additional capabilities include acknowledgments, project directories, product-wide communication, build slots, deployment helpers, and integration with dependency-aware task tracking.
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  • 5
    The Fable Method

    The Fable Method

    How Claude Fable 5 worked, distilled into skills

    ...The repository preserves evaluation cases, raw judge outputs, failures, and results from hundreds of agent runs. Its rules include bounded retries, authorization gates, evidence requirements, and honest caveat reporting. It can be installed as a Claude Code plugin or as standalone skills.
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  • 6
    jlens

    jlens

    Companion code for the global workspace interpretability paper

    Jacobian Lens is Anthropic’s reference implementation for examining what a language model’s internal activations are inclined to produce as text. It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from...
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  • 7
    Boogu-Image-0.1

    Boogu-Image-0.1

    Apache-2.0 open-source image generation and editing model family

    ...It is designed to handle photography, posters, products, stylized art, dense text layouts, and precise in-image text edits. The repository provides checkpoints, inference code, installation instructions, demo links, and model download guidance. It is useful for researchers, builders, and creative tool developers who want a capable open image model with practical editing workflows.
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  • 8
    PixelRAG

    PixelRAG

    The beginning of scalable pixel-native search

    PixelRAG is a visual retrieval-augmented generation system that searches documents by how they look, not only by the text they contain. It renders web pages, PDFs, and images into screenshot tiles, then performs retrieval over those visual representations. This approach preserves layout, tables, charts, diagrams, infographics, and other visual structure that traditional HTML or text parsing can miss. The project includes tools for rendering, chunking, embedding, indexing, and serving visual...
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  • 9
    MathCode

    MathCode

    A Frontier Mathematical Coding Agent

    MathCode is a terminal-based AI coding assistant focused on mathematical formalization and theorem proving. It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. ...
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  • 10
    Agent Control

    Agent Control

    Centralized agent control plane for governing runtime agent behavior

    Agent Control is a centralized control plane for governing AI agent behavior at runtime across different frameworks and deployment environments. It lets teams define controls once and apply them consistently to agents without rewriting the agent’s core code. The platform evaluates agent inputs and outputs against configurable policies to reduce risks such as prompt injection, unsafe responses, sensitive data exposure, and policy drift. It is designed for production environments where organizations need observability, enforcement, and governance around autonomous or semi-autonomous AI systems. ...
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  • 11
    NVIDIA AI Blueprint

    NVIDIA AI Blueprint

    Suite of reference architectures for building GPU-accelerated vision

    ...It is designed for technical users who need deployable reference architectures for smart spaces, warehouse automation, SOP validation, monitoring, and operational video analytics. The repository includes Python agent code, Docker Compose deployment configurations, skills, scripts, and a Next.js-based UI.
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  • 12
    OpenSwarm

    OpenSwarm

    Claude code for everything except coding

    OpenSwarm is an open-source multi-agent system that lets users create full deliverables from a single terminal prompt. Instead of relying on one general-purpose assistant, it coordinates a team of specialized agents through an orchestrator. The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch...
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  • 13
    Artificial Intelligence for Beginners

    Artificial Intelligence for Beginners

    12 Weeks, 24 Lessons, AI for All

    AI-For-Beginners is a comprehensive open-source educational curriculum designed to introduce learners to the foundations of artificial intelligence through structured lessons and hands-on practice. The repository provides a 12-week program composed of 24 lessons that combine theory, code examples, quizzes, and laboratory exercises. It covers a broad range of topics including neural networks, computer vision, natural language processing, and AI ethics. The curriculum is intentionally beginner-friendly while still exposing learners to widely used frameworks such as TensorFlow and PyTorch. It also supports many languages, making the material accessible to a global audience. ...
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  • 14
    SeedVR

    SeedVR

    Repo for SeedVR2 & SeedVR

    SeedVR (from the ByteDance-Seed organization) is an open-source research and implementation repository focused on cutting-edge video restoration using diffusion transformer architectures. The project includes both the original SeedVR and its successor SeedVR2 models, which are designed to restore degraded or low-quality video content by learning to reconstruct high-fidelity frames with temporal coherence. These models leverage advanced techniques such as adaptive attention mechanisms and...
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  • 15
    TorchDistill

    TorchDistill

    A coding-free framework built on PyTorch

    torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file.
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  • 16
    uAgents

    uAgents

    A fast and lightweight framework for creating decentralized agents

    uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events.
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  • 17
    Python Progressbar

    Python Progressbar

    Progressbar 2 - A progress bar for Python 2 and Python 3

    A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. This package is still backward compatible with the original progressbar package so you can safely use it as a drop-in replacement for existing projects. The ProgressBar class manages the current progress, and the format of the line is given by a number of widgets. ...
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  • 18
    Spirit

    Spirit

    Spirit is a modern Python based forum built on top of Django framework

    ...Spirit automatically saves your unfinished comments so you can complete them later. Highlight any comment you want with a "like." Spirit is mobile-first, it's meant to work in the same way in any given device. The code has been written on python employing django's framework and it can be easily integrated to pre-existing projects. Spirit is part of the open source initiative, and it's a project released under the terms of the MIT license.
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  • 19
    django-money

    django-money

    Money fields for Django forms and models

    A little Django app that uses py-moneyed to add support for Money fields in your models and forms. The default currency code length is 3 but you can change it with the CURRENCY_CODE_MAX_LENGTH setting. Currencies are listed on moneyed, and these modules use this to provide a choice list on the admin, also for validation. Django-money leaves you to use any custom model managers you like for your models, but it needs to wrap some of the methods to allow searching for models with money values. ...
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  • 20
    GLM-4.6V

    GLM-4.6V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and...
    Downloads: 1 This Week
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  • 21
    PaSa

    PaSa

    An advanced paper search agent powered by large language models

    PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand...
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  • 22
    Introduction-NLP

    Introduction-NLP

    Detailed notes on HanLP's new book, "Introduction to Natural Language"

    ...Algorithms discussed include hidden Markov models, perceptrons, conditional random fields, Naive Bayes, and support vector machines. Many chapters link to executable code examples and datasets for hands-on study. The repository is designed to help learners organize the book’s key ideas into a practical reference for Chinese NLP work.
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  • 23
    SimpleEnglish

    SimpleEnglish

    Agent skill: make LLMs write docs in ASD-STE100

    ...The repository includes a complete skill, reusable system prompts, examples, evaluations, and a compact version for limited context budgets. It works with Agent Skills-compatible tools such as Claude Code, Cursor, Codex, Copilot, Gemini CLI, Goose, and OpenCode. Users without native skill support can paste the provided prompt into chatbot instructions or project configuration files.
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  • 24
    AI Copywriter

    AI Copywriter

    An AI copywriter that uses real copywriting skills + real marketing

    ...It refuses to invent product facts or unsupported numbers and requests stronger evidence when a claim needs proof. Because the core artifact is a single SKILL.md file, it can run in Claude Code, ChatGPT, Manus, and other instruction-compatible agent systems.
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  • 25
    AI Agent Book

    AI Agent Book

    Deep Understanding AI Agents

    ...Later material covers evaluation, supervised fine-tuning, reinforcement learning, self-improvement, multimodal interaction, robotics, and multi-agent cooperation. The repository includes 88 companion experiments, with more than 70 designed to run independently. Readers can access the source chapters, generated figures, code, and downloadable PDF or EPUB editions. Community translations provide versions in several languages alongside the original Chinese text.
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