Showing 4 open source projects for "microsoft office mac"

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    Magentic UI

    Magentic UI

    A research prototype of a human-centered web agent

    Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight.
    Downloads: 3 This Week
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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...
    Downloads: 3 This Week
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  • 3
    OpenAdapt

    OpenAdapt

    Open Source Generative Process Automation

    OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and...
    Downloads: 0 This Week
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  • 4
    Agent Lightning

    Agent Lightning

    The absolute trainer to light up AI agents

    Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling...
    Downloads: 0 This Week
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