class ReportAgent:
    """报告 Agent：整理评分结果为接口和 PDF 可复用的报告结构。"""

    def build_report(self, scoring_result: dict) -> dict:
        """报告整理：校验评分结果字段并补齐展示默认值，不重新评分。"""
        dimension_scores = self._normalize_dimension_scores(scoring_result.get("dimension_scores", []))
        total_score = self._safe_float(scoring_result.get("total_score"), 0)
        return {
            "score_type": scoring_result.get("score_type", "percentage"),
            "total_score": total_score,
            "dimension_scores": dimension_scores,
            "score_details": self._normalize_score_details(scoring_result.get("score_details", []), dimension_scores),
            "errors": self._ensure_list(scoring_result.get("errors")),
            "improvement_plan": self._ensure_list(scoring_result.get("improvement_plan")),
            "evidence_summary": self._ensure_list(scoring_result.get("evidence_summary")),
            "guideline_refs": self._ensure_list(scoring_result.get("guideline_refs")),
            "overall_comment": scoring_result.get("overall_comment", ""),
            "_llm_model": scoring_result.get("_llm_model"),
            "_latency_metrics": scoring_result.get("_latency_metrics", {}),
        }

    def _normalize_dimension_scores(self, raw_scores: object) -> list[dict]:
        """维度校验：把模型输出归一为前端和数据库可保存的评分列表。"""
        if not isinstance(raw_scores, list):
            return []
        normalized: list[dict] = []
        for item in raw_scores:
            if not isinstance(item, dict):
                continue
            normalized.append(
                {
                    "dimension": str(item.get("dimension", "未命名维度")),
                    "score": self._safe_float(item.get("score"), 0),
                    "max_score": self._safe_float(item.get("max_score"), 0),
                    "comment": str(item.get("comment", "")),
                    "evidence": self._ensure_list(item.get("evidence")),
                    "deductions": self._ensure_list(item.get("deductions")),
                    "improvement": str(item.get("improvement", "")),
                }
            )
        return normalized

    def _normalize_score_details(self, raw_details: object, dimension_scores: list[dict]) -> list[dict]:
        """评分明细校验：保留可写入 training_score_detail 的细粒度字段。"""
        source = raw_details if isinstance(raw_details, list) and raw_details else dimension_scores
        normalized: list[dict] = []
        for item in source:
            if not isinstance(item, dict):
                continue
            deductions = self._ensure_list(item.get("deductions"))
            normalized.append(
                {
                    "rule_id": item.get("rule_id"),
                    "dimension": str(item.get("dimension", "综合表现")),
                    "score": self._safe_float(item.get("score"), 0),
                    "deducted_reason": str(item.get("deducted_reason") or "；".join(str(value) for value in deductions)),
                    "evidence_message_ids": self._ensure_list(item.get("evidence_message_ids") or item.get("evidence")),
                    "ai_confidence": self._safe_float(item.get("ai_confidence"), 0.85),
                    "comment": str(item.get("comment") or item.get("improvement") or ""),
                }
            )
        return normalized

    def _ensure_list(self, value: object) -> list:
        """列表校验：保证报告中的数组字段稳定返回 list。"""
        return value if isinstance(value, list) else []

    def _safe_float(self, value: object, default: float) -> float:
        """数值校验：把模型输出中的分数安全转换为 float。"""
        try:
            return float(value)
        except (TypeError, ValueError):
            return default