"""Per-surface heads for the multi-surface encoder demo.

Each surface (dispute legitimacy, collections, fraud pattern, AML
anomaly, credit repayment) gets one probability head + one attribution
head + reuses the LM head for reasoning generation. Heads share the
backbone via per-surface LoRA adapters.

Doctrine sources:
  - `liquid-models-architecture` Section 10 (head selection table).
  - `liquid-finetuning-playbook` Section 10 (350M attractor states:
    prefer categorical over continuous numerics).
  - `liquid-models-architecture` Section 16 (mean-pool, not last-token,
    on LFM2.5 because the final layer is conv).
  - Multi-head decision layer ADR-014: per-task LoRA + per-batch
    homogeneous-head sampling. Co-training token + sequence heads
    naively collapsed PII to 9.9% F1.
"""

from __future__ import annotations

from encoder.src.model.heads.attribution_head import AttributionHead
from encoder.src.model.heads.probability_head import ProbabilityHead

__all__ = ["ProbabilityHead", "AttributionHead"]