https://www.tensorzero.com/docs has similar abstractions but doesn't require Python and doesn't require committing to the framework or a language. It's also pretty hard to onboard, but solves the same problems better and makes evaluating changes to models / prompts much easier to reason about.

▲ TheTaytay an hour ago | parent | next [-]

Yes, I was more impressed with their decoupling of prompts from parameters!

▲ sbpayne 5 hours ago | parent | prev [-]

I saw this some time ago! I personally have a distaste for external DSLs as I think it generally introduces complexity that I don't think is actually worthwhile, so I skipped over it. Also why I'm very "meh" on BAML.

	▲	GabrielBianconi 4 hours ago \| parent [-]
		TensorZero works with the OpenAI SDK out of the box: ``` from openai import OpenAI # Point the client to the TensorZero Gateway client = OpenAI(base_url="http://localhost:3000/openai/v1", api_key="not-used") response = client.chat.completions.create( `# Call any model provider (or TensorZero function) model="tensorzero::model_name::anthropic::claude-sonnet-4-6", messages=[ { "role": "user", "content": "Share a fun fact about TensorZero.", } ],` ) ``` You can layer additional features only as needed (fallbacks, templates, A/B testing, etc).