"""Prompt evaluation rubrics for platform Prompt Operations."""

from __future__ import annotations

from copy import deepcopy
from typing import Any


DEFAULT_PROMPT_EVAL_RUBRIC: dict[str, Any] = {
    "rubric_key": "default_prompt_eval_v1",
    "label": "通用 Prompt 发布评估",
    "dimensions": {
        "contract_adherence": "是否遵守输入/输出契约、变量约束和格式要求。",
        "business_correctness": "是否围绕业务场景给出准确、可执行且不过度扩展的结果。",
        "evidence_grounding": "是否明确证据、上下文与不确定性，不把无依据内容包装成事实。",
        "safety_boundary": "是否遵守 PMFlow 主链边界、权限边界和 fail-closed 规则。",
        "operator_readability": "是否便于运营、审查和后续沉淀样本。",
    },
    "release_policy": {
        "recommend_release": "平均表现优于或不低于 baseline，且无关键风险。",
        "needs_revision": "存在可修订问题，但不构成强阻塞。",
        "block_release": "违反核心契约、边界或高风险样本失败。",
        "manual_review": "证据不足或模型评估不稳定，需要人工复核。",
    },
}


FAMILY_PROMPT_EVAL_RUBRICS: dict[str, dict[str, Any]] = {
    "classification": {
        "rubric_key": "classification_prompt_eval_v1",
        "label": "分类/路由 Prompt 评估",
        "focus": [
            "分类字段是否稳定、可解释。",
            "不确定时是否澄清或返回 uncertain，而不是强行裁决。",
            "是否避免在执行层恢复关键词/对象词表二次拍板。",
        ],
    },
    "extraction": {
        "rubric_key": "extraction_prompt_eval_v1",
        "label": "结构化抽取 Prompt 评估",
        "focus": [
            "字段完整度、JSON 可解析性和 pending 标注是否可靠。",
            "证据不足时是否显式失败或待确认。",
            "是否避免模板句、默认句冒充抽取成功。",
        ],
    },
    "planning": {
        "rubric_key": "planning_prompt_eval_v1",
        "label": "规划/拆解 Prompt 评估",
        "focus": [
            "任务拆解是否可执行、顺序清晰且边界明确。",
            "是否保留人工确认和高风险审批边界。",
            "是否避免自动写入项目真相层或越过主链。",
        ],
    },
    "response": {
        "rubric_key": "response_prompt_eval_v1",
        "label": "回答呈现 Prompt 评估",
        "focus": [
            "来源合同是否清楚，内部/外部/不确定是否分明。",
            "是否使用客户可理解中文，不泄露 raw source/internal label。",
            "是否避免过度自信、泛化结论和内部术语外露。",
        ],
    },
    "governance": {
        "rubric_key": "governance_prompt_eval_v1",
        "label": "治理/安全 Prompt 评估",
        "focus": [
            "是否严格遵守权限、审计和 fail-closed 边界。",
            "风险、阻塞和人工确认原因是否清楚。",
            "是否避免为了完整回答而绕过运行时护栏。",
        ],
    },
}


PROMPT_KEY_EVAL_RUBRICS: dict[str, dict[str, Any]] = {
    "PROMPT_RAG_QUERY_SEMANTICS": {
        "rubric_key": "rag_query_semantics_eval_v1",
        "label": "Query Route Gateway 语义路由评估",
        "focus": [
            "route_mode / decision_origin / reply_contract 是否由结构化语义证据支撑。",
            "internal/external/uncertain 分流是否遵守 Query Route Gateway，而不是靠对象词表补判。",
            "证据不足时是否澄清或 external-first，禁止默认混合答案。",
        ],
    },
    "PROMPT_EXTERNAL_DIRECT_FACT_QA": {
        "rubric_key": "external_direct_fact_eval_v1",
        "label": "外部实时问答评估",
        "focus": [
            "是否仅使用外部 verified evidence，不混入 Feishu/PMFlow 内部来源。",
            "外部证据不足时是否显式说明限制。",
            "来源摘要是否客户可读且不暴露 raw provider/source label。",
        ],
    },
}


def get_prompt_eval_rubric(*, prompt_key: str, prompt_family: str) -> dict[str, Any]:
    """Return a merged rubric payload for a prompt key/family."""

    rubric = deepcopy(DEFAULT_PROMPT_EVAL_RUBRIC)
    family = FAMILY_PROMPT_EVAL_RUBRICS.get(str(prompt_family or "").strip())
    if family:
        rubric.update(deepcopy(family))
        rubric["base_rubric_key"] = DEFAULT_PROMPT_EVAL_RUBRIC["rubric_key"]
    prompt_specific = PROMPT_KEY_EVAL_RUBRICS.get(str(prompt_key or "").strip())
    if prompt_specific:
        rubric.update(deepcopy(prompt_specific))
        rubric["family_rubric_key"] = family.get("rubric_key") if family else None
    return rubric