ASSUME Framework
✨An open-source agent-based simulation toolbox for European electricity markets, supporting deep reinforcement learning bidding strategies and grid congestion management modeling.
An open-source agent-based simulation toolbox for European electricity markets, supporting deep reinforcement learning bidding strategies and grid congestion management modeling.
A modular Python toolkit developed by the University of Innsbruck that integrates information retrieval, re-ranking, and RAG generation, featuring 40+ pre-processed datasets and single-line pipeline construction.
An AI-driven multi-agent research assistant based on LangGraph that automates the entire research workflow from hypothesis generation, data analysis, and visualization to comprehensive report writing.
A generative agent framework inspired by human dual-process theory, combining fast and slow thinking mechanisms with in-context reinforcement learning to efficiently solve complex interactive reasoning tasks.
A tutorial repository by Neural Maze for building WhatsApp AI Agents, guiding developers through deployment and development.
An agentic graph language assistant framework developed by HKUDS, based on Llama3-8B, unifying predictive tasks (e.g., node classification) and generative tasks (e.g., text summarization) on graph data through collaborative agents for generation, planning, and execution.
GPTSwarm is a graph-based framework for LLM-based agents that allows building LLM agents from graphs and enables customized, automatic self-organization of agent swarms with self-improvement capabilities.
An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models, capable of refining its research direction over time and diving deeper into subjects.
An intelligent agent designed specifically for mathematical modeling that automatically handles problem analysis, mathematical modeling, coding, error correction, and paper writing to generate complete contest-ready papers.
A collection of introductory examples for building LLM-based AI agents, accompanying the book "大模型应用开发 动手做AI Agent", designed to help beginners get started with AI agent development.
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