Search Results for "g-code" - Page 17
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Showing 1797 open source projects for "g-code"
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LLM Scraper
Extract structured data from webpages using LLM-powered scraping
...Multiple content processing modes are supported, including raw HTML, cleaned HTML, Markdown, extracted text, screenshots, and custom inputs, making it adaptable to a wide range of scraping scenarios. LLM Scraper also provides streaming output and code generation capabilities that help developers build reusable scraping workflows. -
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Flexpilot IDE
Open-Source AI Native IDE
Flexpilot IDE is an open-source integrated development environment designed specifically for AI-assisted software development. Built as a fork of Visual Studio Code, the project provides a familiar development interface while integrating advanced AI capabilities directly into the coding workflow. The platform is designed to be privacy-focused and flexible, allowing developers to use their own API keys for different large language models rather than relying on a single proprietary AI provider. ... -
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Swift Concurrency Agent Skill
Add expert Swift Concurrency guidance to your AI coding tool
Swift Concurrency Agent Skill is an open-source “agent skill” designed to give AI coding assistants deep expertise in Apple’s Swift Concurrency model, including async/await, structured concurrency, task groups, actors, and thread safety. It is formatted according to the Agent Skills specification so that tools like Claude Code, Cursor, Copilot, and other LLM-powered systems can load it and apply guidance when relevant. The skill codifies practical best practices for writing efficient, safe, and modern concurrent Swift code and outlines how to modernize existing legacy code toward Swift 6 conventions. Rather than teaching basic Swift, it targets the nuanced behaviors of concurrency primitives, actor isolation, and safety annotations like @MainActor and Sendable. ... -
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9arm-skills
Agent skills loaded by Claude Code
...Its engineering skills focus on practical development behaviors such as debugging, scrutiny, review, and postmortem writing. The productivity side provides reusable patterns for non-code tasks and daily workflows. 9arm-skills is most useful for users who want their AI agents to behave with more discipline, consistency, and context-specific structure. -
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Raven
Self-evolving multi-agent ecosystem for all-domain collaboration
...It ships with built-in agents for research, coding, visual design, and supervision of long-running jobs. Raven can also orchestrate third-party agents such as Claude Code, Codex, OpenCode, GitHub Copilot, Pi, and others. Its runtime is powered by EverOS, allowing user context, agent experience, and reusable knowledge to persist across sessions. The system can generate task graphs, delegate work, combine results, and evolve tools, skills, and workflows over time. Raven supports a terminal interface, web UI, plugins, provider routing, and self-hosted deployment. ... -
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FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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A2UI
A Protocol for Agent-Driven Interfaces
...This approach separates UI intent from UI implementation, making it possible for the same agent-generated interface to be rendered across different platforms such as web, mobile, and desktop applications. A key design principle of A2UI is security, as it avoids executing arbitrary code generated by models and instead restricts output to structured data that maps to a predefined catalog of trusted UI components. The system also supports incremental updates, allowing agents to progressively modify the interface as a conversation evolves. -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
...DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. DeepAnalyze provides multiple interaction interfaces, including a web-based UI, a command-line interface, and a Jupyter-style notebook environment for interactive workflows. -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
...It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and coding assistants to automate tasks such as code research, planning, and implementation while maintaining a structured development process. HumanLayer introduces advanced context management techniques that help AI agents understand large repositories and operate effectively across multiple tasks. ... -
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LEANN
Local RAG engine for private multimodal knowledge search on devices
...By recomputing embeddings during queries and using compact graph-based indexing structures, LEANN can maintain high search accuracy while minimizing disk usage. It aims to act as a unified personal knowledge layer that connects different types of data such as documents, code, images, and other local files into a searchable context for language models. -
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SAM 3
Code for running inference and finetuning with SAM 3 model
SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an... -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance. -
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OpenRig
Multi-agent harness that runs Claude Code and Codex together
OpenRig is an open-source multi-agent harness that runs Claude Code and Codex together as one coordinated development system. Each agent occupies a persistent seat with its own identity, work queue, lessons, and terminal session. Work can be assigned between agents instead of forcing every task through one model. The system runs on the user’s own infrastructure and keeps its orchestration visible through tmux. -
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OpenResearch
Turn your coding agents into research agents
OpenResearch is a local-first workspace that turns coding agents into research agents capable of running structured scientific workflows. It works with Claude Code, Codex, OpenCode, and Cursor while letting each research direction use an independent session and Git worktree. Agents can review literature, propose hypotheses, modify code, launch experiments, inspect results, and generate research artifacts. Experiments are tracked through a Git-native tree that preserves lineage and immutable snapshots. ... -
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WooYun Legacy
wooyun-legacy skill for claude code
...A lightweight installation provides condensed indexes, while the full repository exposes the complete case collection for deeper research. It is intended for authorized testing, risk analysis, code review, and defensive security work. The maintainers have stated that the project is no longer actively maintained. -
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mpai
Make Codex and Claude Code sessions multiplayer from the terminal
mpai is an open-source coordination layer that makes AI coding sessions collaborative directly from the terminal. It lets a named teammate enter an existing Codex or Claude Code conversation without switching tools or recreating its context. The host explicitly chooses which native sessions to share, while Tailscale provides the private device network. Teammates can follow live transcripts, switch sessions, show presence, and submit prompts with their identity attached. Viewer and participant roles, revocation, shared access rules, and an append-only audit trail help preserve owner control. ... -
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
Three.js Object Sculptor is a Codex plugin that converts a reference image into a procedural Three.js object written entirely in code. It first evaluates whether the image is suitable and produces an ObjectSculptSpec describing geometry, materials, lighting, hierarchy, pivots, and quality targets. Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for animation, transformation, physics, and destruction. ... -
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OpenACP
Self-hosted bridge that lets you interact with AI coding agents
OpenACP is a self-hosted bridge for controlling AI coding agents from messaging platforms. It connects agents such as Claude Code, Codex, Gemini, and Cursor to Telegram, Discord, and Slack through the Agent Client Protocol. The project lets users send a chat message, launch or continue an agent session, stream tool calls and results, and review code work in real time. It is useful for developers who want to manage coding agents from a phone, team chat, or remote environment without staying inside a terminal. ... -
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Book6_First-Course-in-Data-Science
From Addition, Subtraction, Multiplication, and Division to ML
Book6_First-Course-in-Data-Science is an open-source educational project that serves as part of the “Iris Book” series focused on teaching data science and machine learning concepts through a combination of mathematics, programming, and visualization. The repository contains draft chapters, supporting Python code, and visual materials designed to guide readers from basic mathematical operations toward practical machine learning understanding. The goal of the project is to make complex topics such as statistics, algorithms, and data analysis more accessible to learners by breaking concepts into clear explanations supported by code examples and diagrams. ... -
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ML-NLP
This project is a common knowledge point and code implementation
ML-NLP is a large open-source repository that collects theoretical knowledge, practical explanations, and code examples related to machine learning, deep learning, and natural language processing. The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training methods, and common algorithmic techniques. ... -
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AgentHub
GitHub is for humans. AgentHub is for agents
...The project functions as a lightweight infrastructure layer that combines a Git repository with a message-board-style communication system, allowing multiple agents to coordinate development tasks within the same workspace. Rather than focusing solely on human collaboration, the system is designed around an “agent-first” paradigm where AI agents can contribute code, discuss changes, and coordinate problem solving. The platform treats code repositories not just as storage for files but as active environments where agents can propose modifications, review changes, and exchange structured messages. This approach reflects emerging research in multi-agent software development where groups of AI systems collaborate on complex engineering problems. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
...That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. It supports both open-source LLMs and proprietary models (via integration with model backends), and works with containerized or sandboxed environments for safe tool execution or external code runs. -
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Laravel Boost
Laravel-focused MCP server for augmenting AI powered local development
Boost is a Laravel-first toolkit that supercharges AI-assisted development by giving assistants structured, Laravel-aware context. At its core it runs as an MCP server that exposes a battery of Laravel-specific tools, so an AI agent can explore your app, inspect code and config, and take targeted actions instead of guessing. It ships opinionated, composable guidelines tuned for popular Laravel packages, which helps keep generated code idiomatic and consistent with framework norms. The package also curates a large body of vectorized Laravel ecosystem knowledge that’s scoped to what you’ve actually installed, improving retrieval precision and response quality. ... -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ... -
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agents.md
A simple, open format for guiding coding agents
...The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of putting everything in README or doc files (which are more human-oriented and might mix high-level narrative), AGENTS.md is intended to surface agent-relevant details that help them “do the right thing” (tests, style, project structure, tooling).
