Search Results for "input-output model"

...It supports scenarios such as nested objects, graphs of entities, and action types with input/output constraints, which makes it suitable for rich metadata authoring and linked-data workflows. While it is maintained by Google, it is not an officially supported Google product.

starter-applets is a collection of minimal, sandboxed example “applets” that demonstrate how to compose Gemini-powered microapps (chat widgets, image generation, workflows) that can be embedded in other applications or used standalone. The applets are structured with a focus on simplicity: each presents a prompt input, minimal UI logic, and inline display of the resulting output or widget (e.g. generated text, images). They are built to illustrate best practices (e.g. safety guards, prompt templates, streaming UI updates) rather than production feature sets. The repo supplies a CLI or script to scaffold new applet templates, letting developers spin up small Gemini-powered components quickly. ...

mcp-cli is a lightweight, Bun-based command-line interface (CLI) tool that simplifies how developers discover, inspect, and interact with Model Context Protocol (MCP) servers from the terminal. The Model Context Protocol is an emerging open standard for connecting language models and external tools, and mcp-cli helps mitigate common pain points like context window bloat by dynamically discovering MCP servers and reducing token load during interactions. It’s designed to be fast and shell-friendly, compiling to a single standalone binary and producing machine-readable output (e.g., JSON) that plays well with other CLI tooling like jq and standard piping. mcp-cli supports both stdio and HTTP-based MCP servers, connection pooling with a lazy-spawn daemon to keep connections warm, and flexible tool filtering via easy configuration options.

Tambo is a React-oriented AI orchestration framework that enables integration of “generative UI” components—that is, components that can be dynamically rendered or updated in response to AI decisions or prompts. It acts as the bridge between an AI assistant and the React front end, letting your AI agent not only send text responses, but also generate interactive UI elements (forms, charts, dashboards, etc.). The library includes tools to scaffold a Tambo app, manage state, and integrate with...

...Watch for changes in your GraphQL schema and operations, and automatically generate code as you go. Codegen easily integrates into your development workflow. One of the goals of GraphQL Codegen is to allow you to easily customize the output, and add custom behaviour according to your needs. You can generate your resolvers' signatures, dump schemas, model types, query builders, React Hooks, Angular Services, and much more! By analyzing the schema and documents and parsing it, GraphQL Code Generator can output code at a wide variety of formats, based on pre-defined templates or based on custom user-defined ones. ...

A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite...

Peinture is a sleek, dark-themed web application that brings AI-powered image generation to artists, designers, and casual creators through a modern interface built with React, TypeScript, and Tailwind CSS. Instead of tying users to a single service, Peinture integrates multiple backend providers, including Hugging Face, Gitee AI, Model Scope, and others, so you can switch between models or extend support to custom endpoints — giving you flexibility over where and how your images are...

...It supports configuration via environment variables or config files so you can set your API key, preferred model, message style, and more. There are also options to preview, edit, or regenerate the AI-proposed message before actually committing, giving developers control instead of blindly trusting the output. Because it’s published as an npm package and even as a Homebrew formula, installation is straightforward across platforms.