"""赛题合成核心逻辑 — 节点采样、prompt 构造、去重。

纯函数为主，异步编排仅 generate_one。
通过 DI 接收 VLMProvider / EmbeddingProvider，不 import adapters/。
"""

from __future__ import annotations

from dataclasses import dataclass


@dataclass(frozen=True)
class AnchorContext:
    """锚节点上下文——生成单道题所需的全部素材。

    属性:
        node_id: 锚节点 ID。
        card_text: 锚节点 card 序列化文本。
        frame_paths: 帧图片路径列表。
        subtitle: 对应字幕（可空）。
        distractor_texts: 同视频其他节点摘要（供 VLM 生成干扰项）。
    """

    node_id: str
    card_text: str
    frame_paths: list[str]
    subtitle: str
    distractor_texts: list[str]


@dataclass(frozen=True)
class TaskTypeSpec:
    """题型的生成规格。

    属性:
        level: 锚定层级（"L3" / "L2" / "L1" / "L1-L2"）。
        needs_frames: 是否必须提供帧图。
        frame_count: 帧数范围描述（如 "1", "2-3", "0-1"）。
        context_fields: 需要提取的 card 字段元组。
    """

    level: str
    needs_frames: bool
    frame_count: str
    context_fields: tuple[str, ...]


# ---------------------------------------------------------------------------
# 12 种 Video-MME 题型 → 树层级 + 生成规格映射
# ---------------------------------------------------------------------------

TASK_TYPE_LEVEL_MAP: dict[str, TaskTypeSpec] = {
    # --- L3 单帧题型 ---
    "Object Recognition": TaskTypeSpec("L3", True, "1", ("frame_summary",)),
    "Attribute Perception": TaskTypeSpec("L3", True, "1", ("frame_summary",)),
    "OCR Problems": TaskTypeSpec("L3", True, "1", ("frame_summary",)),
    "Spatial Reasoning": TaskTypeSpec("L3", True, "1", ("frame_summary", "spatial_layout")),
    "Spatial Perception": TaskTypeSpec("L3", True, "1", ("frame_summary",)),
    # --- L2 多帧 / 事件级题型 ---
    "Action Recognition": TaskTypeSpec("L2", True, "2-3", ("event_description",)),
    "Action Reasoning": TaskTypeSpec("L2", True, "2-3", ("event_description",)),
    "Counting Problem": TaskTypeSpec("L2", True, "2-3", ("event_description",)),
    "Temporal Perception": TaskTypeSpec("L2", False, "0-1", ("event_description", "time_range")),
    # --- L1 / 跨层级题型 ---
    "Temporal Reasoning": TaskTypeSpec("L1", True, "per-L2", ("scene_summary",)),
    "Information Synopsis": TaskTypeSpec("L1", True, "per-L2", ("scene_summary",)),
    "Object Reasoning": TaskTypeSpec("L1-L2", True, "per-L2", ("event_description",)),
}