feat(eval): populate EvalReport.per_chapter + failed_chapters in score()

src/genesis/eval/scorer.py

@@ -36,12 +36,19 @@ class ChapterArtifact:
     template_sections_expected: list[str]
 
 
+# 逐章评估通过阈值（基于逐章总分）
+PASS_THRESHOLD: float = 0.6
+# 内容充分性维度：文本长度达到该值即视为充分
+ADEQUACY_MIN_LEN: int = 15
+
+
 @dataclass
 class EvalReport:
     dimensions: list[DimensionScore]
     total_score: float
     passed: bool
     failed_chapters: list[str] = field(default_factory=list)
+    per_chapter: list["EvalReport"] = field(default_factory=list)
 
 
 # 维度默认通过阈值
@@ -75,7 +82,20 @@ class ChapterScorer:
 
         total = sum(d.score for d in dimensions) / len(dimensions) if dimensions else 0.0
         passed = all(d.passed for d in dimensions)
-        return EvalReport(dimensions=dimensions, total_score=round(total, 4), passed=passed)
+
+        # 逐章评估：对每一章节独立评分，收集 per_chapter，并标记未达标章节
+        per_chapter = [self._score_chapter(ch, source) for ch in chapters]
+        failed_chapters = [
+            ch.chapter_id for ch, r in zip(chapters, per_chapter) if r.failed_chapters
+        ]
+
+        return EvalReport(
+            dimensions=dimensions,
+            total_score=round(total, 4),
+            passed=passed,
+            failed_chapters=failed_chapters,
+            per_chapter=per_chapter,
+        )
 
     # ---------- 确定性维度 ----------
 
@@ -123,3 +143,35 @@ class ChapterScorer:
         avg = sum(s.score for s in scores) / len(scores) if scores else 0.5
         detail = " | ".join(s.detail for s in scores) if scores else "no chapters"
         return DimensionScore(name, round(avg, 4), all(s.passed for s in scores), detail)
+
+    # ---------- 逐章评估 ----------
+
+    def _score_chapter(self, chapter: ChapterArtifact, source: StructuredSource) -> EvalReport:
+        """对单个章节独立评分，返回该章节的 EvalReport。
+
+        复用确定性维度逻辑（可追溯性/占位符残留）并计算内容充分性，
+        总分低于 PASS_THRESHOLD 即判该章节失败。
+        """
+        dims = [
+            self._traceability([chapter], source),
+            self._placeholder_residue([chapter]),
+            self._adequacy(chapter),
+        ]
+        total = sum(d.score for d in dims) / len(dims) if dims else 0.0
+        failed = (not all(d.passed for d in dims)) or total < PASS_THRESHOLD
+        return EvalReport(
+            dimensions=dims,
+            total_score=round(total, 4),
+            passed=not failed,
+            failed_chapters=[chapter.chapter_id] if failed else [],
+            per_chapter=[],
+        )
+
+    def _adequacy(self, chapter: ChapterArtifact) -> DimensionScore:
+        """内容充分性：基于正文字本长度启发式判定章节是否充分。"""
+        text = chapter.text or ""
+        score = 1.0 if len(text) >= ADEQUACY_MIN_LEN else 0.3
+        passed = score >= PASS_THRESHOLD
+        return DimensionScore(
+            "adequacy", score, passed, f"内容长度 {len(text)}（充分阈值 {ADEQUACY_MIN_LEN}）"
+        )