Showing 4 open source projects for "libamd.so.1"

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  • 1
    Harness-1

    Harness-1

    Ultra Recipe for Training Long-Horizon Search Agents

    Harness-1 is a 20B search agent trained with reinforcement learning inside a stateful retrieval harness. It is designed for long-horizon search tasks where the model must search, inspect documents, curate evidence, verify claims, and decide when enough evidence has been gathered. The harness externalizes search state, including candidate documents, evidence links, verification records, and budget-aware context.
    Downloads: 0 This Week
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  • 2
    LobeHub

    LobeHub

    Workspace to find, build, and collaborate with AI agents

    LobeHub is an all-in-one workspace designed to help humans and AI agents collaborate, grow, and evolve together. It treats AI agents as true teammates rather than one-off tools, enabling deeper context, continuity, and productivity. Users can build personalized agent teams that understand their workflows, preferences, and goals over time. LobeHub brings multiple models, tools, and modalities into a single unified environment under the user’s control.
    Downloads: 34 This Week
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  • 3
    LazyCodex

    LazyCodex

    The one and only agent harness for complex codebases

    ...It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced. LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. ...
    Downloads: 8 This Week
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  • 4
    GELab-Zero

    GELab-Zero

    GUI Exploration Lab. One of the best GUI agent solutions

    GELab-Zero is an open-source “GUI Agent” framework aiming to automate interactions with graphical user interfaces (GUIs), combining both the agent model and all supporting infrastructure — including inference, input orchestration, and GUI automation logic — in a plug-and-play package that runs locally, without cloud dependencies. The idea is to let developers or users harness an AI agent that can simulate clicking, typing, reading UI elements, and interacting with apps in a human-like way...
    Downloads: 0 This Week
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