BAML

BAML treats prompts as typed functions with structured inputs and outputs, reducing errors in LLM responses, as demonstrated in the ChatAgent example with clear type definitions.

You can call BAML functions from Python, TypeScript, Ruby, and other languages without rewriting your app, shown in the Python code snippet for agent workflows.

Includes IDE extensions (VS Code, JetBrains) and a playground for fast prompt testing and visualization, enabling parallel testing to speed up development cycles.

Schema-aligned parsing allows reliable tool-calling with any LLM, even without native APIs, as highlighted with support for models like Deepseek-R1 and OpenAI O1.

Provides fully type-safe streaming interfaces for real-time UIs in frameworks like Next.js, with examples and hooks for building responsive applications.