Eli Felse: a framework for safer autonomous AI assistants
Eli Felse is a framework designed to explore safer ways to create autonomous AI assistants. It uses LLMs to power an AI agent that can play games, chat, browse the web, and perform creative tasks, all while demonstrating safety measures. The framework is aimed at researchers and developers interested in building safer autonomous agents.
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AgentMaker: a new Python framework for building LLM agents and multi-agent systems
AgentMaker is a general-purpose Python framework for building LLM agents and multi-agent systems, featuring tools, memory, RAG, context engineering, guardrails, human-in-the-loop, and observability. It is released under MIT license on GitHub and PyPI.
Runeward: Sandbox AI agents with policy gates
Runeward is a sandboxing tool for AI agents that enforces policy gates to restrict agent actions. It uses LLMs to interpret and enforce user-defined policies, solving the problem of unsafe or unintended agent behavior for developers building autonomous AI systems.
Enola: engineering intelligence layer for AI coding agents
Enola is an open-source engineering intelligence layer that helps AI coding agents understand existing codebases. It answers questions about change impact, dependency reachability, safe module deletion, refactoring priorities, and architecture drift. The tool uses LLMs to analyze code context and provide insights that reduce mistakes from both humans and AI agents.
Hermes Agent: personal AI with memory, tools, and daily workflow integration
Hermes Agent is a personal AI agent that goes beyond chatbots by incorporating memory, tools, and daily workflow integration. It uses LLMs to remember user context, execute actions via tools, and become a persistent part of the user's routine, solving the problem of AI tools being ephemeral and disconnected from daily tasks.
LLM-based intelligent chatbot with session history
A full-stack chatbot project that uses an LLM (Anthropic Claude by default) to answer user messages while maintaining per-session conversation history. It provides a simple, self-contained setup with a Node.js backend and a plain HTML/CSS/JS frontend, suitable for developers who want to quickly deploy an LLM-powered chat interface.
