Showing 3 open source projects for "set"

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    ZeroBot-Plugin

    ZeroBot-Plugin

    OneBot plugin based on ZeroBot

    ...The repository is aimed mainly at QQ and OneBot-style chatbot deployments, with plugins that can be enabled, modified, or extended by developers. It is designed for users who want a richer bot feature set without writing every plugin from scratch. The project supports a community-oriented workflow where plugins can evolve and new ideas can be tested in related playground repositories. It is most useful for bot operators and Go developers building modular chat automation around the ZeroBot framework.
    Downloads: 19 This Week
    Last Update:
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  • 2
    kagent

    kagent

    Kubernetes native framework for building AI agents

    ...It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. It supports multiple model providers through a dedicated configuration resource, allowing teams to switch providers or run mixed environments while keeping the agent spec stable. A major focus is tool integration via MCP: agents can connect to MCP servers for tool access, and kagent includes an MCP server with tools for common Kubernetes and platform engineering systems.
    Downloads: 11 This Week
    Last Update:
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  • 3
    Agent Executor (AX)

    Agent Executor (AX)

    Google's open source distributed agent runtime

    Agent Executor (AX) is a Google research project for learning discrete choice models through differentiable maximum likelihood estimation. It is designed for situations where a model needs to predict choices from a finite set of alternatives, such as ranking, recommendation, preference modeling, or decision behavior analysis. The project provides JAX-based tools for defining and training choice models with automatic differentiation. It focuses on flexible model construction rather than a single fixed estimator, making it useful for researchers who want to experiment with different utility functions and optimization setups. ax is especially relevant for machine learning and econometrics workflows that need scalable, differentiable approaches to choice modeling. ...
    Downloads: 5 This Week
    Last Update:
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