"""Helpers for runtime model preset selection.""" from __future__ import annotations from collections.abc import Callable from typing import Any from nanobot.config.schema import ModelPresetConfig from nanobot.providers.base import LLMProvider from nanobot.providers.factory import ProviderSnapshot, build_provider_snapshot PresetSnapshotLoader = Callable[[str], ProviderSnapshot] def default_selection_signature(signature: tuple[object, ...] | None) -> tuple[object, ...] | None: return signature[:2] if signature else None def configured_model_presets(config: Any) -> dict[str, ModelPresetConfig]: return {**config.model_presets, "default": config.resolve_default_preset()} def make_preset_snapshot_loader( config: Any, provider_snapshot_loader: Callable[..., ProviderSnapshot] | None, ) -> PresetSnapshotLoader: if provider_snapshot_loader is not None: return lambda name: provider_snapshot_loader(preset_name=name) return lambda name: build_provider_snapshot(config, preset_name=name) def build_static_preset_snapshot( provider: LLMProvider, name: str, preset: ModelPresetConfig, ) -> ProviderSnapshot: provider.generation = preset.to_generation_settings() return ProviderSnapshot( provider=provider, model=preset.model, context_window_tokens=preset.context_window_tokens, signature=("model_preset", name, preset.model_dump_json()), ) def build_runtime_preset_snapshot( *, name: str, presets: dict[str, ModelPresetConfig], provider: LLMProvider, loader: PresetSnapshotLoader | None, ) -> ProviderSnapshot: if loader is not None: return loader(name) return build_static_preset_snapshot(provider, name, presets[name]) def normalize_preset_name(name: str | None, presets: dict[str, ModelPresetConfig]) -> str: if not isinstance(name, str) or not name.strip(): raise ValueError("model_preset must be a non-empty string") name = name.strip() if name not in presets: raise KeyError(f"model_preset {name!r} not found. Available: {', '.join(presets) or '(none)'}") return name