finalize medical consultation agent backend

backend/app/agents/report_agent.py

@@ -9,6 +9,7 @@ class ReportAgent:
             "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")),
@@ -32,6 +33,30 @@ class ReportAgent:
                     "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