3 Repos
Using natural language prompts to generate full functional applications or software components.
Distinct from Prompt-Based Text Generation: Distinct from general text generation: focuses on producing deployable application code and structures rather than just text sequences.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Application Generation. Refine with filters or upvote what's useful.
Baserow is a no-code relational database and application builder that allows users to create structured data tables and business tools through a visual interface. It functions as a headless REST API data backend and a self-hosted data workspace, providing a platform for managing collaborative databases while maintaining full control over data residency. The platform integrates large language models to serve as an LLM-powered data platform, capable of generating database structures, record content, and technical workflows from natural language. It also acts as a Model Context Protocol server,
Provides the ability to generate full functional database structures and application layouts using natural language prompts.
vibesdk is an agentic software development platform and framework designed to coordinate autonomous agents that write, debug, and refine full-stack applications from natural language. It serves as a cloud-native application orchestrator and an LLM-powered code generation framework that converts prompts into functional code through iterative conversations and multi-phase agent behaviors. The project distinguishes itself by providing a complete toolchain for building AI development platforms. This includes the ability to integrate various model providers, construct custom LLM toolkits, and mana
Creates new applications or components using natural language prompts and configurable generation behaviors.
gptme is a multi-agent orchestration platform designed for autonomous software engineering, terminal-based AI integration, and RAG-enhanced code navigation. It enables the deployment of persistent agents and specialized subagents to decompose complex tasks and execute parallel technical workflows. The system distinguishes itself through a combination of vision-based GUI automation for controlling desktop applications and surgical patching mechanisms for targeted source code modifications. It utilizes git-based memory management to maintain a versioned history of agent identities, lessons, and
Generates complete source code for applications, games, or simulations using natural language descriptions.