OpenWebAgent is an open toolkit that enables model-based web agents to streamline human-computer interactions by automating tasks on webpages. We provide the plugin and server source code so that users can easily add their own models to the backend to get a usable web browsing agent.
The main features of thudm/openwebagent are: Agent Orchestration.
Open-source alternatives to thudm/openwebagent include: agentops-ai/agentstack — AgentStack scaffolds your agent stack - The tech stack that collectively is your agent. agno-agi/agno — Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous… brainblend-ai/atomic-agents. browser-use/browser-use — Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web… camel-ai/camel — This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified… agentops-ai/agentops — AgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability…
AgentStack scaffolds your agent stack - The tech stack that collectively is your agent
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
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