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Basic Information

December is an open source, local-first AI development platform that lets developers generate full-stack applications from natural language prompts and run them on their own machines. It is presented as an alternative to closed, subscription-based services like Loveable, Replit, and Bolt by providing a self-hosted environment that integrates AI models through user-provided API keys. The project focuses on privacy, cost control, and developer control by running containerized Next.js applications with Docker, offering a backend and frontend that run locally, and including tooling to bootstrap, preview, edit, export, and deploy projects. The repo includes configuration and startup scripts to wire in compatible OpenAI SDK providers and recommends models suited for coding tasks. The README frames December as an experimental but practical way to build applications quickly while keeping code and data on your own machine.

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App Details

Features
December provides AI-driven project creation from text prompts, containerized Next.js applications packaged with Docker, and a start script that configures the environment and copies API key settings into the backend. The frontend includes a live preview with mobile and desktop views and a full-featured Monaco code editor with file management. A real-time chat assistant helps with development questions. Projects can be exported and deployed from the local environment. Configuration is handled via a config file where users supply compatible API keys and model endpoints. The repo documents recommended model settings and default ports for frontend and backend. The README also lists a roadmap that includes LLM streaming, document and image attachments, improved fault tolerance, and multi-framework support.
Use Cases
December helps developers prototype and ship applications faster by automating project creation and providing integrated editing, previewing, and containerization workflows on a local machine. It reduces dependency on cloud platforms and monthly subscriptions by letting users supply their own API keys and control costs and data residency. The local-first design enables offline work, full ownership of code and projects, and the ability to modify the platform itself. Built-in tooling such as the start script, Docker integration, and a chat assistant lowers setup friction and supports iterative development. The project is intended for experimentation and learning, and it makes it easier to generate many application variants quickly while keeping responsibility for API usage and costs with the user.

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