An LLM function is a prompt template with some defined input variables, and a specific output type like a class, enum, union, optional string, etc.

BAML is a configuration file format to write better and cleaner LLM functions.

With BAML you can write and test a complex LLM function in 1/10 of the time it takes to setup a python LLM testing environment.

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Try it out in the playground — PromptFiddle.com

Share your creations and ask questions in our Discord.

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Features

  • Python and Typescript support: Plug-and-play BAML with other languages
  • Type validation: more resilient to common LLM mistakes than Pydantic or Zod
  • Wide model support: Ollama, Openai, Anthropic. Tested on small models like Llama2
  • Streaming: Stream structured partial outputs.
  • Realtime Prompt Previews: See the full prompt always, even if it has loops and conditionals
  • Testing support: Test functions in the playground with 1 click.
  • Resilience and fallback features: Add retries, redundancy, to your LLM calls
  • Observability Platform: Use Boundary Studio to visualize your functions and replay production requests with 1 click.

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Companies using BAML

  • Zenfetch - ChatGPT for your bookmarks
  • Vetrec - AI-powered Clinical Notes for Veterinarians
  • MagnaPlay - Production-quality machine translation for games
  • Aer Compliance - AI-powered compliance tasks
  • Haven - Automate Tenant communications with AI
  • Muckrock - FOIA request tracking and filing
  • and more! Let us know if you want to be showcased or want to work with us 1-1 to solve your usecase.

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Starter projects

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First steps

We recommend checking the examples in PromptFiddle.com. Once you’re ready to start, install the toolchain and read the guides.

FAQs