"""Validierung und Normalisierung des Planungs-Artefakts am Progressionsgraph."""
from __future__ import annotations

import json
from typing import Any, Dict, List, Optional

from pydantic import BaseModel, Field, field_validator

ARTIFACT_SCHEMA_VERSION = 1
_MAX_JSON_BYTES = 64_000


class SlotExerciseContent(BaseModel):
    kind: str = Field(default="empty", pattern=r"^(empty|library|proposal)$")
    exercise_id: Optional[int] = Field(default=None, ge=1)
    variant_id: Optional[int] = Field(default=None, ge=1)
    title: Optional[str] = Field(default=None, max_length=500)
    variant_name: Optional[str] = Field(default=None, max_length=200)
    proposal_key: Optional[str] = Field(default=None, max_length=120)
    ai_suggestion: Optional[Dict[str, Any]] = None


class SlotContentEntry(BaseModel):
    major_step_index: int = Field(ge=0, le=20)
    primary: SlotExerciseContent = Field(default_factory=SlotExerciseContent)
    siblings: List[SlotExerciseContent] = Field(default_factory=list)


class GraphPlanningRoadmapArtifact(BaseModel):
    schema_version: int = Field(default=ARTIFACT_SCHEMA_VERSION, ge=1, le=1)
    goal_query: str = Field(default="", max_length=2000)
    start_situation: Optional[str] = Field(default=None, max_length=2000)
    target_state: Optional[str] = Field(default=None, max_length=2000)
    roadmap_notes: Optional[str] = Field(default=None, max_length=2000)
    max_steps: int = Field(default=5, ge=2, le=10)
    progression_roadmap: Optional[Dict[str, Any]] = None
    path_skill_expectations: Optional[Dict[str, Any]] = None
    slot_contents: Optional[List[SlotContentEntry]] = None
    last_findings: Optional[Dict[str, Any]] = None
    planning_catalog_context: Optional[Dict[str, Any]] = None

    @field_validator("progression_roadmap", "path_skill_expectations", "last_findings", "planning_catalog_context", mode="before")
    @classmethod
    def _empty_dict_to_none(cls, v):
        if v == {}:
            return None
        return v

    @field_validator("slot_contents", mode="before")
    @classmethod
    def _empty_slot_list_to_none(cls, v):
        if v == []:
            return None
        return v


def normalize_planning_roadmap_payload(raw: Any) -> Optional[Dict[str, Any]]:
    """None erlaubt (löschen); sonst validiertes Dict."""
    if raw is None:
        return None
    if not isinstance(raw, dict):
        raise ValueError("planning_roadmap muss ein JSON-Objekt sein")
    artifact = GraphPlanningRoadmapArtifact.model_validate(raw)
    out = artifact.model_dump(exclude_none=True)
    blob = json.dumps(out, ensure_ascii=False)
    if len(blob.encode("utf-8")) > _MAX_JSON_BYTES:
        raise ValueError("planning_roadmap ist zu groß (max. 64 KB)")
    return out


__all__ = [
    "ARTIFACT_SCHEMA_VERSION",
    "GraphPlanningRoadmapArtifact",
    "SlotContentEntry",
    "SlotExerciseContent",
    "normalize_planning_roadmap_payload",
]