Search Results for "path"

OpenClaw Installer is an open-source one-click deployment and configuration tool for installing OpenClaw — a personal AI assistant — onto systems with minimal manual setup, giving users a streamlined path to get their own AI assistant running quickly. The project provides shell scripts and configuration menus that detect the host environment, install dependencies, download OpenClaw, configure core settings like AI models and identity channels, and start the server automatically. It supports multiple platforms, including macOS, Linux distributions (Ubuntu, Debian, CentOS), and Windows environments via compatible shells, and simplifies otherwise complex installation steps into a guided, terminal-based experience. ...

nono is an open-source, kernel-enforced capability shell designed to safely run AI agents and other untrusted processes under strict operating system controls. The project addresses a growing security concern: modern coding agents typically execute with full user permissions, which means they can potentially read sensitive files, modify system configurations, or exfiltrate credentials if compromised. nono solves this by applying default-deny sandboxing at the kernel level using technologies...

robotic-warehouse is a simulation environment and framework for robotic warehouse automation, enabling research and development of AI and robotic agents to manage warehouse logistics, such as item picking and transport.

eve is Vercel’s open-source framework for building, running, and scaling durable backend AI agents. It uses a filesystem-first model where an agent is defined as a directory of files, making the project structure itself the agent contract. The framework is designed to include production concerns from the start instead of leaving developers to assemble durability, sandboxing, approvals, and deployment separately. Eve supports durable execution, sandboxed compute, human-in-the-loop approvals,...

...For personalization, it organizes memory from raw conversations into atoms, scenarios, and persona-level knowledge. The design keeps high-level memory inspectable while preserving a drill-down path back to raw evidence. It is built for OpenClaw and Hermes-style agent workflows that need lower token usage, better continuity, and no external API dependency.

...Version 2.0 focuses on native function calling instead of rigid structured JSON responses. The assistant can read files, read multiple files, create files, create multiple files, and edit specific snippets when needed. It includes safeguards such as path validation, directory traversal protection, file size limits, and binary file exclusion. Overall, it is designed for developers who want a conversational coding tool that can inspect, modify, and reason about project files from the command line.

...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems.

multi_agent_path_planning is a Python-based implementation of multi-agent pathfinding algorithms for coordinating multiple agents in shared environments without collisions. It is useful in robotics, warehouse automation, and gaming AI.