LazyLLM is a multi-agent framework and orchestration engine designed for building complex AI applications. It provides a system for chaining large language models into sequential or parallel pipelines, utilizing a tool registry to convert standard functions into discoverable tools that models can invoke via reasoning. The project features an application deployment kit that enables hosting model workflows as web services with integrated chat interfaces and API gateways. It includes an infrastructure abstraction layer that allows users to switch between bare-metal servers, clusters, and public
Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web interfaces using natural language instructions. By acting as an orchestration layer between large language models and browser automation protocols, it enables the execution of complex, multi-step workflows without relying on brittle selectors. The system functions as a headless browser controller, providing a programmatic interface to manage browser instances and execute granular interactions. The project distinguishes itself through its ability to translate high-level intent into
AgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability of autonomous agents powered by large language models. It serves as a system for tracking AI agent behavior, debugging complex workflows, and benchmarking model performance. The platform is distinguished by its ability to visualize multi-agent workflows through execution path graphing and session replays. It provides specific tools for calculating financial spend across various language model providers and supports a self-hosted observability stack for users who require full
Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat
A lightweight framework for building LLM-based agents
internlm/lagent 的主要功能包括：Agent Frameworks, Agent Orchestration。
internlm/lagent 的开源替代品包括： lazyagi/lazyllm — LazyLLM is a multi-agent framework and orchestration engine designed for building complex AI applications. It provides… composiohq/composio — Composio is an integration platform designed to connect autonomous agents with external software services and APIs. It… agentops-ai/agentops — AgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability… agno-agi/agno — Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous… camel-ai/camel — This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified… browser-use/browser-use — Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web…