API Reference

MAC constructor

Param	Default	Description
`model`	`"gpt-4o"`	Tier 1: Worker model (annotator)
`provider`	`"openai"`	Provider (`openai`, `openrouter`, `local`, `cerebras`)
`base_url`	`None`	Custom endpoint for worker (vLLM, etc.)
`temperature`	`1`	LLM temperature for worker
`mac_model`	`None`	Tier 2: MAC agents. Falls back to `model`.
`mac_provider`	`None`	Provider for MAC agents. Falls back to `provider`.
`mac_base_url`	`None`	Endpoint for MAC agents. Does NOT fall back to `base_url`.
`mac_temperature`	`None`	Temperature for MAC agents. Falls back to `temperature`.
`adapt_model`	`None`	Tier 3: Prompt adaptation. Falls back to `mac_model` → `model`.
`adapt_provider`	`None`	Provider for adaptation. Falls back to `mac_provider` → `provider`.
`adapt_base_url`	`None`	Endpoint for adaptation. Falls back to `mac_base_url`.
`adapt_temperature`	`None`	Temperature for adaptation. Falls back to `mac_temperature`.
`api_key`	env `OPENAI_API_KEY`	API key
`num_epochs`	`1`	Training epochs
`batch_size`	`4`	Examples per batch
`task_prompt`	`""`	Mode 1: your prompt (must contain `{{CONSTITUTION_BLOCK}}`)
`task_description`	`""`	Mode 2: enables meta-model prompt adaptation
`rule_type`	`""`	e.g. "math rules", "NER rules"
`output_key`	`"answer"`	JSON key in annotator output

compile()

compiler.compile(
    trainset: List[Example],   # Training examples
    holdout: List[Example],    # Held-out validation examples
    metric: Callable,          # (prediction, gold) -> float
) -> CompiledMAC

CompiledMAC

optimized = compiler.compile(trainset, holdout, metric)

optimized("input text")            # Single inference → str
optimized.predict_batch(texts)     # Batch inference → List[str]
optimized.overview()               # Rich panel: baseline → final, rules tree
optimized.rules                    # List[str] - the learned rules
optimized.constitution             # str - formatted constitution
optimized.baseline_score           # float - score before training

optimized.save("rules.json")
loaded = CompiledMAC.load("rules.json")