Search Results for "model-builder"

...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. ...

PicoClaw is an ultra-lightweight, open-source personal AI assistant written in Go, architected from the ground up to operate with extremely low memory usage (under 10 MB) and fast boot times, making it suitable for inexpensive hardware platforms and embedded devices. Inspired by earlier AI assistant projects like “nanobot,” it was refactored to emphasize resource efficiency while still supporting meaningful AI-driven interactions such as conversational workflows, planning tasks, and...

GoClaw is an enterprise AI agent platform that rebuilds OpenClaw in Go for stronger concurrency, simpler deployment, and production-oriented multi-agent orchestration. It acts as a gateway that connects language models to tools, channels, memory, and organizational data through a single binary. The platform is built for teams that need multiple agents to collaborate, delegate tasks, and operate across different providers without losing tenant isolation. It supports more than 20 LLM providers...

Vibium is an open-source browser automation infrastructure built to serve both AI agents and human developers by simplifying control and interaction with real browsers. It integrates a single lightweight binary that manages browser lifecycle, implements a WebDriver BiDi proxy, and exposes a Model Context Protocol (MCP) server so language models or automation clients can control browser behavior without complex setup. This design makes it ideal for AI agents that need to interact with the web, perform tasks, or simulate human interactions in a browser environment, and it also works well for traditional testing and automation workflows. ...

Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. ...

This is an open‑source, powerful novel‑writing and AI programming assistant with the following core strengths: Model Aggregation: Natively supports the latest DeepSeek and seamlessly integrates with top‑tier models such as Gemini, Claude, GPT, Tongyi Qianwen, Kimi, and others—both domestic and international—delivering a one‑stop intelligent experience. Multimodal Capability: Accurately interprets images and PDF content, and supports invoking advanced models for high‑quality text‑to‑image generation. ...