BAML is a domain-specific language to generate structured outputs from LLMs (docs.boundaryml.com)

BAML, a newly introduced domain-specific language, is designed to enhance the developer experience when generating structured outputs from large language models (LLMs). This innovative tool enables the creation of reliable chatbots, agents, and data extraction solutions (e.g., PDFs) with remarkable efficiency. Key features of BAML include a fast development experience in the VSCode playground, fully type-safe outputs that support autocomplete, and compatibility with any LLM and programming language. Notably, BAML claims to produce structured outputs that can outperform OpenAI’s own models, including those based on open-source architectures. The significance of BAML for the AI/ML community lies in its capability to simplify the complex task of crafting LLM prompts. Traditionally, developers faced challenges like lacking type safety and needing extensive setups for minor prompt adjustments. BAML addresses these issues by allowing prompts to be operated directly within the development environment, similar to how Markdown Preview functions. This approach streamlines prompt engineering, making it as seamless as coding with TSX/JSX for web development. By optimizing the process, BAML empowers developers to craft more sophisticated AI-driven applications without the burden of cumbersome setups and organization challenges.