Showing 4 open source projects for "performance monitor"

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    NVIDIA NeMo Agent Toolkit

    NVIDIA NeMo Agent Toolkit

    Library for efficiently connecting and optimizing teams of AI agents

    NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze token-level performance to identify bottlenecks and improve efficiency. ...
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  • 2
    Tiledesk Dashboard

    Tiledesk Dashboard

    Tiledesk is the open source AI agent builder

    Tiledesk Dashboard is the frontend management interface for the Tiledesk platform, allowing administrators to configure settings, monitor live chats, and manage chatbot workflows.
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  • 3
    ClawPort

    ClawPort

    Open-source AI agent command center for Claude Code agent teams

    ClawPort is an open-source web-based dashboard designed to act as a centralized command center for managing and interacting with OpenClaw AI agent systems. It provides a visual interface that replaces fragmented terminal-based workflows, allowing users to monitor, control, and communicate with multiple agents from a single location. The platform is built to improve visibility into multi-agent environments, offering insights into agent activity, task execution, and system performance in real time. It supports direct interaction with agents through chat interfaces, enabling users to guide or override automated workflows when necessary. ...
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  • 4
    OpenClaw Office

    OpenClaw Office

    OpenClaw Office is the visual monitoring and management frontend

    ...The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to understand and debug. Users can observe communication flows between agents through visual connections, track token usage and operational costs, and analyze performance through integrated dashboards and charts. The system also includes live chat capabilities, allowing users to monitor conversations and tool calls as they occur.
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