Swarm is an experimental framework managed by the OpenAI Solutions team, designed to build, orchestrate, and deploy multi-agent systems. It facilitates coordination and execution among agents (Agents) through the definition of abstract concepts of agents and handoffs. The Swarm framework emphasizes lightweight design, high controllability, and ease of testing, making it ideal for scenarios that require numerous independent functionalities and instructions. It allows developers complete transparency and fine-grained control over context, steps, and tool calls. The Swarm framework is currently in an experimental stage and is not recommended for production environments.

Windows Agent Arena (WAA) is an open-source framework dedicated to the Windows operating system for testing and developing AI agents capable of reasoning, planning, and acting using language models on PCs. It simulates a real Windows environment, allowing agents to operate freely and use the same applications, tools, and web browsers as human users to solve tasks. WAA leverages Azure for scalability and parallelization, completing comprehensive benchmark evaluations in as little as 20 minutes.

muAgent is an innovative agent framework powered by a knowledge graph engine, supporting multi-agent orchestration and collaboration technology. It leverages LLM + EKG (Eventic Knowledge Graph for industry knowledge) technology, integrating FunctionCall, CodeInterpreter, and more, to automate complex SOP processes through drag-and-drop canvas design and lightweight text scripting. muAgent is compatible with various existing agent frameworks and features core functionalities such as complex reasoning, online collaboration, human interaction, and knowledge accessibility. This framework has been validated in multiple complex DevOps scenarios at Ant Group.

QAbot-zh/query-key is a pure front-end API testing tool that supports various API formats such as oneapi/newapi and can also verify OpenAI formatted APIs. The main advantage of this tool lies in its front-end implementation, eliminating concerns about gateway timeouts while ensuring data security. It provides comprehensive test data displays, including response times and model consistency, allowing users to intuitively understand API performance. Additionally, it supports local one-click execution and online hosting via pages, making it convenient for users to deploy and use quickly.

Open-LLM-VTuber is an open-source project designed for interaction with large language models (LLMs) via voice, featuring real-time Live2D facial capture and cross-platform long-term memory capabilities. This project supports macOS, Windows, and Linux platforms, allowing users to select different speech recognition and speech synthesis backends, as well as customized long-term memory solutions. It is particularly suited for developers and enthusiasts looking to implement natural language conversations with AI across various platforms.

The multi-agent concierge is a system that employs multiple specialized agents to accomplish complex tasks, guided by a 'concierge' agent that directs users to the appropriate agents. This system is designed to manage multiple interdependent tasks using hundreds of tools. It demonstrates how to create implicit 'chains' between agents through natural language commands and manage these chains with 'continuation' agents, while employing a global state to track users and their current status.

gmft is a toolkit designed to convert tables in PDFs into various formats. It is lightweight, modular, and delivers exceptional performance. gmft relies on Microsoft's Table Transformers, recognized as one of the best-performing and most reliable solutions among many alternatives. It operates without the need for a GPU, offering high throughput and easy installation, requiring only a single line of code. It utilizes PyPDFium2, favored for its high throughput and permissive licensing. The training model TATR used by gmft is trained on the diverse dataset PubTables-1M, ensuring high reliability.

The agent-service-toolkit is a comprehensive toolkit for running AI agent services based on LangGraph, including LangGraph agents, FastAPI services, clients, and Streamlit applications, providing a complete setup from agent definition to user interface. It leverages the high control capabilities and rich ecosystem of the LangGraph framework, supporting advanced features such as concurrent execution, graph loops, and streaming results.

AgentK is a self-evolving modular self-agent general artificial intelligence (AGI) model composed of multiple collaborating agents that can construct new agents based on user needs to accomplish tasks. Built on the LangGraph and LangChain frameworks, it possesses self-testing and self-repair capabilities, designed to be a minimal set of agents and tools for self-guidance and evolution of intelligence.

awesome-LLM-resources is a platform that aggregates global resources for large language models (LLMs), offering a range of tools and resources from data acquisition and fine-tuning to inference, evaluation, and real-world applications. Its significance lies in providing researchers and developers with a comprehensive resource library to facilitate the efficient development and optimization of their language models. Maintained by Wang Rongsheng, the platform is continuously updated, providing robust support for the advancement of the LLM field.

Swarm is an experimental framework managed by the OpenAI Solutions team, designed to build, orchestrate, and deploy multi-agent systems. It facilitates coordination and execution among agents (Agents) through the definition of abstract concepts of agents and handoffs. The Swarm framework emphasizes lightweight design, high controllability, and ease of testing, making it ideal for scenarios that require numerous independent functionalities and instructions. It allows developers complete transparency and fine-grained control over context, steps, and tool calls. The Swarm framework is currently in an experimental stage and is not recommended for production environments.

Geekits is an open-source and free platform created by YGeeker, providing a suite of practical tools across various domains including Artificial Intelligence, Everyday Use, Image and Video Processing, and Programming Development. It offers convenient services for general users while also providing programming-related support for developers. The main advantages of Geekits lie in its diversity and practicality, allowing users to find tools ranging from simple everyday utilities to professional development aids, greatly enhancing work and life efficiency.

LiveKit Agents is an end-to-end framework that enables developers to construct intelligent multimodal voice assistants (AI agents) that interact with users via voice, video, and data channels. It provides a quick-start guide for creating voice assistants by integrating OpenAI's real-time API and LiveKit's WebRTC infrastructure, including pipelines for speech-to-text (STT), language models (LLM), and text-to-speech (TTS). Additionally, it supports building voice-to-voice agents, handling incoming calls, and making calls on behalf of users.

The Genspark Autopilot Agent is an intelligent agent capable of autonomously processing tasks by simulating user operations, allowing it to continue functioning even after the user closes the page. Its core advantage lies in its automation capabilities, which can significantly boost efficiency and minimize repetitive labor, enabling users to focus on more creative and strategic tasks. Developed to meet the demands for automation and efficiency in modern work environments, the Genspark Autopilot Agent is likely to offer different tiers of service to accommodate various user needs.

Windows Agent Arena (WAA) is an open-source framework dedicated to the Windows operating system for testing and developing AI agents capable of reasoning, planning, and acting using language models on PCs. It simulates a real Windows environment, allowing agents to operate freely and use the same applications, tools, and web browsers as human users to solve tasks. WAA leverages Azure for scalability and parallelization, completing comprehensive benchmark evaluations in as little as 20 minutes.

Hoody AI is a privacy-focused unified interface designed to provide anonymous access to a range of large language models (LLMs). Users can easily access multiple AI models and functions while maintaining anonymity. The platform employs advanced encryption methods to ensure data security and supports anonymous payments, protecting users' identities from being tracked. It features an intuitive, responsive dashboard that supports cross-platform access on both mobile and desktop devices.

muAgent is an innovative agent framework powered by a knowledge graph engine, supporting multi-agent orchestration and collaboration technology. It leverages LLM + EKG (Eventic Knowledge Graph for industry knowledge) technology, integrating FunctionCall, CodeInterpreter, and more, to automate complex SOP processes through drag-and-drop canvas design and lightweight text scripting. muAgent is compatible with various existing agent frameworks and features core functionalities such as complex reasoning, online collaboration, human interaction, and knowledge accessibility. This framework has been validated in multiple complex DevOps scenarios at Ant Group.

AIbase is a comprehensive platform with an extensive database of over 7,000 outstanding artificial intelligence websites and products across more than 40 different fields, such as AI-generated art, AI copywriting, AI video editing, and AI-driven marketing. Users can easily find the AI tools that best meet their needs and unlock the power of AI.