30 open-source projects similar to agi-templar/stable-alignment, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Stable Alignment alternative.
Recent advancements in Large Language Models (LLMs) have shown significant progress in understanding complex natural language. However, LLMs still face challenges in generating and executing programming codes accurately. While some efforts have been made to leverage LLMs for code generation,…
This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It functions as a computational graph orchestrator that organizes agent interactions and tool sequences as a trainable graph of nodes. The framework focuses on data-centric agent optimization, allowing agent pipelines and prompts to be upgraded through data-driven training rather than manual engineering. It utilizes a symbolic learning process that applies language-based loss and textual reflections to refine the operational logic and symbolic components of an agent. The system
Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"
🎉 Updates (2025-05-03) MaAS is accepted as ICML'25 Oral (Top ~1% among 12,107 submissions)! - 🚩 Updates (2025-02-06) Initial upload to arXiv (see PDF).
(Aug 29, 2025) It is based on the TRL (Transformer Reinforcement Learning) package. We are also planning to use Verl to make this easy to use, especially for the inference time scaling, so stay tuned!
[Website](http://craftjarvis-jarvis1.github.io/) [Paper](https://arxiv.org/abs/2311.05997) [Twitter](https://twitter.com/jeasinema/status/1723900032653643796)
This repo contains the source code for making plans based on problems decribed by natural language.
This repository contains code released by Curai Health. For a list of all publications at Curai Health, see our blog.
MetaGPT is an agentic workflow orchestrator and multi-agent framework designed to transform natural language requirements into complete software deliverables. It functions as an AI software engineering suite that automates the creation of technical documentation, data structures, and source code by treating natural language as a programming environment. The system distinguishes itself by assigning professional roles to large language models, creating specialized agent teams that collaborate through a shared communication structure. It utilizes standard operating procedures to convert organiza
Official implementation of our ScoreFlow. Affiliation: University of Chicago, Princeton University, University of Oxford.
Original Flan (2021) | The Flan Collection (2022) | Flan 2021 Citation | License
Teaching Language Models to Critique via Reinforcement Learning
CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch. Works with Claude Code, Codex, Cursor, OpenCode, Kiro, and more.
This project introduces a novel agent architecture that simulates the attitudes and behaviors of real individuals by applying large language models (LLMs) to qualitative interviews about their lives. These agents replicate participants' responses on various social science measures, providing a…
🐝 The First Self-Improving agents with RL / Prompting Optimization
This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into structured dialogue sequences between specialized agents. The system distinguishes itself through its message-passing orchestration, which manages state transitions and task delegation between independent participants. It supports dynamic conversation state management to provid
RD-Agent is an autonomous framework designed to orchestrate multi-step software engineering and data science workflows. By leveraging large language models, the system decomposes complex technical requirements into actionable research, planning, and execution phases, ultimately generating and running code to solve specific development tasks. The platform distinguishes itself through a containerized execution sandbox that ensures secure dependency management and system stability for all autonomously generated code. It employs multi-agent orchestration to manage iterative feedback loops, allowi
TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
TinyTroupe is a multi-agent simulation framework designed to create populations of persona-based agents that interact to generate synthetic behavioral data and business insights. It serves as a persona-based agent orchestrator and synthetic data generator, allowing for the definition of agents with specific personality traits and goals to coordinate their interactions through structured workflows. The project features an extensible plugin system for connecting simulated agents to external tools and servers to execute code and access remote data. It includes an agentic simulation dashboard tha
Voyager is an autonomous embodied agent and lifelong learning framework that uses a large language model to explore virtual environments. It functions as a code-based action controller, translating natural language instructions into executable scripts to interact with its surroundings. The system features an automatic curriculum generator that creates sequences of exploration goals to discover new items and behaviors without human intervention. It maintains a skill library manager that stores learned behaviors as reusable code fragments, which can be composed to execute complex tasks. The fr
Swarm is a framework for building conversational systems that coordinate multi-agent workflows. It functions as an orchestration engine that manages persistent, multi-turn dialogues by routing tasks between specialized agents and executing local functions. The system is designed to handle complex, multi-step processes by maintaining shared state and context across agent interactions. The framework distinguishes itself through its approach to dynamic task delegation and execution control. It enables agents to hand off tasks to one another by returning agent objects, allowing for modular, domai
Agentverse is a multi-agent framework and orchestrator designed for deploying and managing multiple large language model agents. It provides a simulation environment where agents interact based on custom personas and defined interaction rules to solve tasks or simulate social dynamics. The system features a tool integration layer that connects agents to external functional plugins and specialized tools, extending their capabilities beyond text generation. It uses a combination of persona-based prompt injection and state-managed memory to maintain agent consistency and specialized skill sets d