Search Results for "machine"
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Showing 20 open source projects for "machine"
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1
Wingman
An open source AI coding assistant VSCode extension
The Wingman-AI extension brings high-quality AI-assisted coding right to your computer, it's 100% free and private which means data never leaves your machine. The AI will look for natural pauses in typing to decide when to offer code suggestions (keep in mind the speed is limited by your machine). The code completion feature will also analyze comments you type and generate suggestions based on that context. -
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Tabby
Self-hosted AI coding assistant
Tabby is an open-source, self-hosted AI coding assistant that provides code completion and suggestions within your preferred development environment. It enhances developer productivity by leveraging machine learning models to predict and generate code snippets. -
3
Codex Mobile
Run Codex Mobile Anywhere: Linux, Windows, or Termux on Android
...It is designed to let users run a Codex-style UI on Linux, Windows, or Termux-powered Android setups. The project starts a local web server with one command, then lets the user open the interface from the same machine, a LAN device, or another reachable connection. It can also create a Cloudflare tunnel by default, making remote access easier when the local setup allows it. Codex Mobile is useful for developers who want to control coding-agent sessions from a phone, tablet, remote browser, or nonstandard environment. Its main value is making Codex app workflows more portable, accessible, and usable beyond a traditional desktop terminal. -
4
AsmJit
Low-latency machine code generation
AsmJit is a low-level code generation library designed for dynamically creating machine code at runtime, enabling just-in-time (JIT) compilation for performance-critical applications. It provides a high-level API that abstracts away the complexity of writing raw assembly while still allowing fine-grained control over instruction generation. The library supports multiple architectures, including x86 and x64, making it versatile for cross-platform development. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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5
Alook
The collaboration layer for your AI workforce
...It lets users give agents defined roles, email addresses, task boards, calendars, and shared workflows so they can collaborate more like a real team. The platform connects local agents to external communication channels while keeping the actual agents and codebase running on the user’s own machine. It is designed for developers, solo founders, and teams that want multiple AI agents to handle development, operations, research, and routine work with clearer structure. Alook also emphasizes memory and traceability, so agents can remember past decisions, learn preferences, and keep a record of instructions and replies. Its main value is turning separate AI coding tools into an organized, always-on operating system for agent-based work. -
6
Dyad
Free, local, open-source AI app builder
Dyad is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 2.5 Pro, GPT-4.1, Claude Sonnet 4) or local via Ollama, so you’re never locked in. ... -
7
CodexPro
Use ChatGPT Developer Mode as a local coding agent for your repo
...Public access can be routed through options such as Cloudflare tunnels, ngrok, Tailscale Funnel, or local-only mode. CodexPro is useful for developers who want ChatGPT to act like a repo-aware coding assistant while keeping the actual workspace on their own machine. -
8
RA.Aid
Develop software autonomously
...It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality. -
9
49 Agents IDE
Open-source 2D IDE for managing AI agents in native CLIs
49Agents is an open-source “agentic IDE” that reimagines how developers interact with multiple AI agents, terminals, and development environments by placing everything onto a single infinite, zoomable canvas. Instead of relying on traditional tab-based workflows, it provides a spatial interface where terminals, editors, Git views, and monitoring tools coexist as movable panes, enabling users to manage complex multi-agent systems visually and intuitively. The platform is designed to work... -
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10
Superset LLM
Run an army of Claude Code, Codex, etc. on your machine
Superset is a development environment and terminal-based platform designed to orchestrate multiple AI coding agents simultaneously within a single workspace. The tool enables developers to run many autonomous coding agents in parallel without the typical overhead of manually managing multiple terminals, repositories, or branches. Each agent task is isolated in its own Git worktree, ensuring that code changes from different agents do not interfere with each other while allowing developers to... -
11
skills-manage
Desktop app to manage AI coding agent skills across Claude Code
...It also scans local projects for skill libraries, including project-level folders and Obsidian-style vaults. Its local-first design keeps metadata, collections, settings, scan results, and cached explanations on the user’s machine unless a feature explicitly requires network access. -
12
security-audit
A coding-agent skill for multi-phase security audits
security-audit is a coding-agent skill for running structured security audits on software repositories. It organizes the audit into multiple phases so the agent does not simply search randomly for vulnerabilities. The workflow begins with reconnaissance, then moves into parallel hunting across attack classes such as injection, access control, business logic, cryptography, feature abuse, and chained attacks. Findings are then challenged through separate validation agents to reduce false... -
13
DESIGN.md
A format specification for describing a visual identity
design.md is an open specification created by Google Labs that defines a standardized way to describe design systems for AI coding agents. It allows developers to encode visual identity elements such as colors, typography, spacing, and components in a structured format. The file combines machine-readable design tokens with human-readable explanations, enabling agents to generate consistent user interfaces aligned with a brand. By providing persistent design context, it eliminates the need to repeatedly describe styling requirements to AI tools. The format supports interoperability across platforms and tools, making it a potential standard for agent-driven UI generation. ... -
14
darwin-skill
Autoresearch-inspired autonomous skill optimization for Claude Code
darwin-skill is an experimental framework designed to automatically improve AI agent “skills” through iterative evaluation and optimization loops inspired by machine learning training processes. Instead of treating prompts or skill definitions as static assets, the system applies a continuous improvement cycle that evaluates performance, proposes changes, tests outcomes, and either retains or reverts modifications. The framework introduces a scoring system across multiple dimensions, enabling quantitative assessment of skill quality and ensuring that only improvements are preserved over time. ... -
15
Codex Autoresearch
A codex plugin for running optimization loops inside a codebase
...The system operates in a loop where the agent modifies code, evaluates results against measurable metrics, and either keeps or discards changes based on performance. It generalizes the concept of autoresearch beyond machine learning, allowing optimization of test coverage, latency, lint errors, and overall code quality. Developers define a goal and verification command, and the agent continuously runs experiments to reach the desired outcome. The framework supports multiple operational modes, including debugging, planning, security auditing, and release validation. ... -
16
Adaptive Intelligence
Adaptive Intelligence also known as "Artificial General Intelligence"
Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills. -
17
CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. ... -
18
DevProjex
Turn any codebase into clean AI-ready context: GUI, TUI, CLI, MCP
DevProjex turns any folder or Git repository into clean, token-efficient context for AI assistants and coding agents, and shows exactly what leaves your machine before you send it. Use it as a desktop app (GUI), a keyboard-first terminal workspace (TUI), a scriptable CLI for CI, or a read-only MCP server for Claude Code, Cursor, and other agents. An open-source alternative to Repomix, gitingest, and code2prompt, with a visual file tree and live preview. Smart Ignore drops build output, dependencies, and caches based on real project evidence; Git modes pack only tracked, staged, changed, or diff files. ... -
19
Kite
Primary Kite repo, private bits replaced with XXXXXXX
...We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs available for running larger jobs and for testing our cloud services. We bundle a lot of pre-computed datasets & machine learning models into the Kite app through the use of a custom filemap & encoding on top of go-bindata. The data, located in kite-go/client/datadeps, is kept in Git-LFS. -
20
Tabnine
Vim client for TabNine
...Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or content assist, you probably already know that it can save you tons of time, easily cutting your keystrokes in half. Powered by sophisticated machine learning models trained on billions of lines of trusted open source code from GitHub, Tabnine is the most advanced AI-powered code completion copilot available today. And like GitHub, it is an essential tool for professional developers.
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