Search Results for "set"

...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.

...It is positioned as a collaborative chat platform rather than a single-user demo, which is reflected in its administrative structure, multi-user handling, and deployment-oriented documentation. The project supports OpenAI, Azure OpenAI, Claude, Gemini, and Ollama-hosted models, giving teams flexibility in how they connect model backends. Its feature set includes shareable static pages generated from conversations, searchable conversation snapshots, text file uploads, multimedia file support when the model allows it, and prompt management with shortcut-based access. The repository structure also points to both web and Flutter-based mobile components, suggesting a broader product surface than a simple browser-only interface.

...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.

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. ...

...If you would like to help the DiscordGo package please use this link to add the official DiscordGo test bot dgo to your server. This provides indispensable help to this project. Construct a new Discord client which can be used to access the variety of Discord API functions and to set callback functions for Discord events. The DiscordGo code is fairly well documented at this point and is currently the only documentation available. Go reference (below) presents that information in a nice format. This library and the Discord API are unfinished. Because of that there may be major changes to library in the future.