Quick Start Install Ax and run a typed LLM program. python quick-start quick-start website/content-src/templates/quick-start.md quick-start Quick Start

Quick Start

Ax gives Python one typed contract for LLM programs: signatures for data shape, ai() for model access, ax() for structured generation, agent() for tool-using runtime loops, and AxGEPA for improving programs with examples.

Install

Shell
pip install "axllm @ git+https://github.com/ax-llm/ax#subdirectory=packages/python"

First Program

Start with a small typed task. The signature declares the fields the model receives and the fields Ax must parse back out.

Python
from axllm import ai, ax

llm = ai('openai', api_key=os.environ['OPENAI_API_KEY'])
classify = ax('review:string -> sentiment:class "positive, negative, neutral"')

That is the core loop:

  • create a provider client
  • declare the input and output contract
  • run the program with typed inputs
  • read typed outputs instead of scraping prose
flowchart LR
  A["ai() client"] --> C["forward() with typed inputs"]
  B["Signature"] --> C
  C --> D["Validate + retry"]
  D --> E["Typed output"]

The rest of the site keeps the same concepts but swaps install commands, imports, examples, and API names for Python.

Where To Go Next

Use Examples when you want runnable files. Use Concepts when you want the mental model. Use Subsystems when you know which surface you are trying to use and want the practical call shape.

Docs