Kairo-Jinkendo/backend/services/operating_context.py

"""Operating Context read model — AP2.3a / AP2.4."""

from __future__ import annotations

from typing import Any, Optional

from psycopg2.extras import RealDictCursor

from db import get_connection
from entity_archetypes.registry import (
    get_ui_profile_json,
    resolve_default_method_key,
    resolve_ui_profile,
)
from services.initiatives import get_initiative
from services.steering_context import ensure_steering_context, get_steering_context
from steering.graph.profiles import LIGHT, graph_profile_as_dict
from steering.methods.registry import (
    get_method,
    list_compatible_methods,
    list_composable_modifiers,
    method_to_dict,
    ui_features_as_dict,
)


def _load_ui_profile_from_db(archetype_key: str) -> Optional[dict[str, Any]]:
    conn = get_connection()
    try:
        with conn.cursor(cursor_factory=RealDictCursor) as cur:
            cur.execute(
                """
                SELECT ui_profile_json
                FROM entity_archetypes
                WHERE archetype_key = %s
                """,
                (archetype_key,),
            )
            row = cur.fetchone()
            if not row:
                return None
            profile = row.get("ui_profile_json")
            if isinstance(profile, dict) and profile:
                return dict(profile)
            return None
    finally:
        conn.close()


def _seed_ui_profile(archetype_key: str) -> dict[str, Any]:
    seed_profile = get_ui_profile_json(archetype_key)
    if seed_profile:
        return seed_profile
    return resolve_ui_profile(archetype_key)


def _normalize_ui_profile_capabilities(profile: dict[str, Any]) -> dict[str, Any]:
    """Spiegelt resolve_ui_profile: omCapabilities aus dataSlices falls fehlend."""
    result = dict(profile)
    slices = list(result.get("dataSlices") or [])
    caps = list(result.get("omCapabilities") or slices)
    result["dataSlices"] = slices
    result["omCapabilities"] = caps
    return result


def _resolve_ui_profile(archetype_key: str) -> dict[str, Any]:
    seed_profile = _seed_ui_profile(archetype_key)
    db_profile = _load_ui_profile_from_db(archetype_key)
    if not db_profile:
        return _normalize_ui_profile_capabilities(seed_profile)

    merged = {**seed_profile, **db_profile}
    if not (merged.get("omCapabilities") or merged.get("dataSlices")):
        seed_slices = seed_profile.get("dataSlices") or []
        merged["dataSlices"] = list(seed_slices)
    return _normalize_ui_profile_capabilities(merged)


def _resolve_om_capabilities(ui_profile: dict[str, Any]) -> frozenset[str]:
    caps = ui_profile.get("omCapabilities") or ui_profile.get("dataSlices") or []
    return frozenset(caps)


def _resolve_data_slices(
    *,
    om_capabilities: frozenset[str],
    method_key: str,
) -> list[str]:
    """Schnittmenge Archetyp-OM ∩ Method-Slices."""
    method = get_method(method_key)
    if method and method.data_slices:
        method_slices = set(method.data_slices)
        return [s for s in om_capabilities if s in method_slices]
    return list(om_capabilities)


def _method_capabilities(method_key: str) -> dict[str, Any]:
    method = get_method(method_key)
    if not method:
        return {
            "lifecycle_steps": [],
            "next_action_strategy_key": "default",
        }
    return {
        "lifecycle_steps": list(method.default_lifecycle_steps),
        "next_action_strategy_key": method.next_action_strategy_key,
    }


def _resolve_method_contract(method_key: str) -> dict[str, Any]:
    method = get_method(method_key)
    if not method:
        return {
            "steering_elements": [],
            "ui_features": {},
            "graph_profile": graph_profile_as_dict(LIGHT),
        }
    return {
        "steering_elements": sorted(method.steering_elements),
        "ui_features": ui_features_as_dict(method.ui_features),
        "graph_profile": graph_profile_as_dict(method.graph_profile),
    }


def _compatible_methods_payload(
    archetype_key: str,
    *,
    om_capabilities: frozenset[str],
    active_method_key: str,
) -> list[dict[str, Any]]:
    default_key = resolve_default_method_key(archetype_key)
    methods = list_compatible_methods(
        archetype_key, om_capabilities=om_capabilities
    )
    return [
        {
            **method_to_dict(m, include_compatibility=False),
            "is_default": m.key == default_key,
            "is_active": m.key == active_method_key,
        }
        for m in methods
    ]


def get_operating_context(
    *, tenant_id: str, initiative_id: str
) -> Optional[dict[str, Any]]:
    initiative = get_initiative(tenant_id=tenant_id, initiative_id=initiative_id)
    if not initiative:
        return None

    steering = get_steering_context(tenant_id=tenant_id, initiative_id=initiative_id)
    if not steering:
        steering = ensure_steering_context(
            tenant_id=tenant_id, initiative_id=initiative_id
        )

    archetype_key = initiative["archetype_key"]
    ui_profile = _resolve_ui_profile(archetype_key)
    om_capabilities = _resolve_om_capabilities(ui_profile)
    method_key = steering["method_key"]
    metadata = steering.get("lifecycle_metadata") or {}
    if isinstance(metadata, str):
        metadata = {}
    method_profile_key = metadata.get("method_profile_key")
    data_slices = _resolve_data_slices(
        om_capabilities=om_capabilities,
        method_key=method_key,
    )
    method_contract = _resolve_method_contract(method_key)

    return {
        "initiative_id": initiative_id,
        "archetype_key": archetype_key,
        "method_key": method_key,
        "method_profile_key": method_profile_key,
        "ui_profile": ui_profile,
        "om_capabilities": sorted(om_capabilities),
        "data_slices": data_slices,
        "method_capabilities": _method_capabilities(method_key),
        "steering_elements": method_contract["steering_elements"],
        "ui_features": method_contract["ui_features"],
        "graph_profile": method_contract["graph_profile"],
        "compatible_methods": _compatible_methods_payload(
            archetype_key,
            om_capabilities=om_capabilities,
            active_method_key=method_key,
        ),
        "composable_modifiers": [
            method_to_dict(m, include_compatibility=False)
            for m in list_composable_modifiers(method_key)
        ],
        "active_composition_modifier": (
            "agile_iteration"
            if _resolve_active_agile_composition(
                tenant_id=tenant_id,
                initiative_id=initiative_id,
                primary_method_key=method_key,
            )
            else None
        ),
    }


def _resolve_active_agile_composition(
    *,
    tenant_id: str,
    initiative_id: str,
    primary_method_key: str,
) -> bool:
    from services.work_cycle import get_active_work_cycle
    from steering.methods.registry import get_method

    agile = get_method("agile_iteration")
    if not agile or primary_method_key not in agile.composes_with:
        return False
    return get_active_work_cycle(tenant_id=tenant_id, initiative_id=initiative_id) is not None