ludwig-ai/ludwig — Low-code framework for building custom LLMs, neural networks, and other AI models

Description and use

Ludwig is an open‑source, low‑code framework that lets developers and data scientists build, train, and deploy custom large language models, neural networks, and a wide variety of AI models without writing extensive code. By defining model architectures, data pipelines, and training parameters in simple YAML or JSON configurations, Ludwig streamlines experimentation and production‑ready deployment across AI/ML, frontend, and data‑centric workflows. It supports numerous model types, automatic preprocessing, hyperparameter tuning, and integration with popular ML libraries, making advanced AI accessible to both technical and non‑technical users.

Problem

ludwig-ai/ludwig helps add AI capability without starting from a blank model stack.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Low-code framework for building custom LLMs, neural networks, and other AI models

Source