Search Results for "parallel port control"
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Showing 30 open source projects for "parallel port control"
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Orca
Orca is the ADE for working with a fleet of parallel agents
Orca is an agentic development environment for working with multiple coding agents in parallel. It is designed for developers who want to orchestrate agent-based coding workflows instead of running one isolated assistant at a time. The project lets users run coding agents with their own subscriptions, which keeps control over provider access in the user’s hands. Orca is available on desktop and also includes a mobile companion for monitoring and steering agents from a phone. ... -
2
LobeHub
Workspace to find, build, and collaborate with AI agents
...Users can build personalized agent teams that understand their workflows, preferences, and goals over time. LobeHub brings multiple models, tools, and modalities into a single unified environment under the user’s control. With built-in collaboration features, agents can work in parallel, share context, and support complex projects seamlessly. The platform is built around the idea of co-evolution, where both humans and agents continuously learn and improve together. -
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Maestro AI Orchestration
Agent Orchestration Command Center
...Maestro includes advanced features like Git worktrees to isolate sub-agent tasks, command-line interfaces for integration into CI/CD pipelines, remote control via phone, and comprehensive session analytics. -
4
EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
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CGraph
A general, three-party dependency-free, cross-platform
CGraph is a high-performance, cross-platform Directed Acyclic Graph (DAG) framework implemented in pure C++ with no third-party dependencies, designed for building complex task pipelines and parallel execution workflows. It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution, conditional branching, aggregation, and loop control, making it highly flexible for advanced workflows. ... -
6
Claude Ads
Comprehensive paid advertising audit & optimization skill
...The system generates structured reports, identifies inefficiencies, and suggests optimization strategies based on industry benchmarks. It supports platforms like Google Ads, Meta Ads, TikTok, LinkedIn, and more, offering a unified analysis workflow. The architecture uses parallel subagents to speed up audits and includes financial modeling and A/B testing guidance. It runs locally, ensuring privacy and control over sensitive advertising data. The project is aimed at replacing manual audit workflows with fast, automated, and repeatable analysis. -
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Prime Agent
A self-improving RLM agent for coding workflows
Prime Agent is an open-source coding and research agent designed for complex workflows and long-running autonomous tasks. Its Recursive Language Model architecture treats context as programmable variables and subagents as callable functions inside a persistent Python environment. Files, shell commands, tools, context operations, and agent coordination are handled programmatically through the same runtime. Built-in subagents can work in parallel or continue tasks independently while returning... -
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Chat On Steroids
Cross-platform local MCP capabilities for ChatGPT with Chrome
Chat On Steroids is a cross-platform desktop workspace that connects a normal ChatGPT conversation with local development and computer tools. It lets ChatGPT inspect approved files, apply patches, run terminal commands, maintain task plans, and coordinate multiple workers. Long-running tasks can continue while the user sends corrections or changes direction. Worker sessions preserve their own context so delegated jobs can be resumed or reused later. On supported desktop platforms, an... -
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Andromity
A terminal AI coding agent. Autonomous by choice, gated by trust
Andromity is an open-source AI coding agent that runs inside VS Code or as a standalone terminal workspace. It can analyze a codebase, propose a step-by-step implementation plan, and wait for approval before editing files. Multiple trust levels control whether plans, file changes, and terminal commands require confirmation. Parallel subagents can research, implement, and test different workstreams while maintaining separate session histories. Developers can connect cloud models through their own API keys or run supported local models through Ollama. Built-in diffs, one-click rollback, persistent sessions, cron jobs, MCP tools, and a live execution profiler provide visibility and control over autonomous work. ... -
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Roo Code
Roo Code gives you a whole dev team of AI agents in your code editor
...It combines a powerful VS Code extension with cloud-based agents that can take on real development tasks across GitHub, Slack, and the web. Designed to work on your terms, Roo Code gives you full control locally while enabling delegation and parallel execution at scale. Its model-agnostic architecture ensures flexibility as AI models and providers evolve, letting you choose or bring your own keys. Role-specific agent modes keep AI focused, reliable, and aligned with real engineering workflows. Open source, secure, and highly configurable, Roo Code fits seamlessly into both individual and team-based development environments. -
11
security-audit
A coding-agent skill for multi-phase security audits
...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 positives. The skill produces human-readable reports, detailed finding traces, structured JSON output, and independent verification against the actual source code. ... -
12
Koog
Koog is the official Kotlin framework for building AI agents
...A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring. -
13
Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight. -
14
Humanoid-Gym
Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real
Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training. ... -
15
abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
abtop is a terminal monitoring tool for AI coding agents, inspired by system monitors like htop and btop. It gives users a real-time view of active Claude Code, Codex CLI, and OpenCode sessions from local process and file state. The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop... -
16
wllama
WebAssembly binding for llama.cpp - Enabling on-browser LLM inference
wllama is a WebAssembly-based library that enables large language model inference directly inside a web browser. Built as a binding for the llama.cpp inference engine, the project allows developers to run LLM models locally without requiring a server backend or dedicated GPU hardware. The library leverages WebAssembly SIMD capabilities to achieve efficient execution within modern browsers while maintaining compatibility across platforms. By running models locally on the user’s device, wllama... -
17
Meta-World
Collections of robotics environments
...The environments adhere to the Gymnasium API, which makes them easy to plug into existing RL pipelines, and they support both synchronous and asynchronous vectorized execution for running many environments in parallel. Installation is done via pip, with official support for Python versions 3.8 through 3.11 on Linux and macOS, and the project is licensed under MIT to encourage broad academic and industry use. -
18
HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. 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... -
19
Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with... -
20
Mastra
The TypeScript AI agent framework
...Model routing lets you connect to dozens of providers (OpenAI, Anthropic, Gemini, and others) through a single standardized interface, while agents orchestrate LLM calls and tools to solve open-ended tasks with internal reasoning loops. When explicit control is needed, Mastra’s workflow engine uses a graph-style API (.then(), .branch(), .parallel()) to orchestrate multi-step processes. -
21
ClawBridge
The OpenClaw Mobile Dashboard.
The OpenClaw Mobile Dashboard. Monitor agent's real-time thoughts, actions, track token costs, and manage tasks from anywhere using your pocket-sized Mission Control. -
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FreedomGPT
React and Electron-based app that executes the FreedomGPT LLM locally
FreedomGPT is a locally executed large language model (LLM) application built using React and Electron, allowing users to interact with AI models privately on their Mac or Windows devices. The app enables offline operation, ensuring privacy and security while providing a chat-based interface for seamless communication with the AI. It supports integration with models like Liberty Edge and offers an open-source solution for those seeking more control over their AI interactions. The app's setup... -
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Make-A-Video - Pytorch (wip)
Implementation of Make-A-Video, new SOTA text to video generator
Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch. They combine pseudo-3d convolutions (axial convolutions) and temporal attention and show much better temporal fusion. The pseudo-3d convolutions isn't a new concept. It has been explored before in other contexts, say for protein contact prediction as "dimensional hybrid residual networks". The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning... -
24
ADAMS
ADAMS is a workflow engine for building complex knowledge workflows.
ADAMS is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is processed (sequentially/parallel). This allows rapid development and easy maintenance of large workflows, with hundreds or thousands of operators. Operators include machine learning (WEKA, MOA, MEKA) and image processing (ImageJ, JAI, BoofCV, LIRE and Gnuplot). R available using Rserve. WEKA webservice allows other frameworks to use WEKA models. ... -
25
ControlNet
Let us control diffusion models
ControlNet is a neural network architecture designed to add conditional control to text-to-image diffusion models. Rather than training from scratch, ControlNet “locks” the weights of a pre-trained diffusion model and introduces a parallel trainable branch that learns additional conditions—like edges, depth maps, segmentation, human pose, scribbles, or other guidance signals. This allows the system to control where and how the model should focus during generation, enabling users to steer layout, structure, and content more precisely than prompt text alone. ...
