feat:

1. 建立问题库大纲，对应每个人生阶段槽位
2. 鼓励使用更生活化的交流语言共情与总结
3. 降低评审模型可能发生截断的概率
4. 成稿质量维度强化情感表达和上下文连贯性

api/app/features/evaluation/eval_trace_service.py

@@ -121,7 +121,9 @@ class EvalTraceService:
             return "partial"
         return "fallback"
 
-    async def build_chapter_bundle(self, user_id: str, chapter: Chapter) -> ChapterEvidenceBundle:
+    async def build_chapter_bundle(
+        self, user_id: str, chapter: Chapter
+    ) -> ChapterEvidenceBundle:
         notes: list[str] = []
         live_segment_ids = normalize_source_segment_ids(
             getattr(chapter, "source_segments", None)
@@ -130,7 +132,15 @@ class EvalTraceService:
         row = getattr(chapter, "current_evidence_snapshot", None)
         row_has_closure = bool(
             (row and (row.segment_ids or []))
-            or (row and (row.memory_chunk_ids or row.memory_fact_ids or row.timeline_event_ids or row.summary_ids))
+            or (
+                row
+                and (
+                    row.memory_chunk_ids
+                    or row.memory_fact_ids
+                    or row.timeline_event_ids
+                    or row.summary_ids
+                )
+            )
         )
         if (
             row is not None
@@ -139,19 +149,13 @@ class EvalTraceService:
             and int(row.schema_version or 0) == EVIDENCE_SNAPSHOT_SCHEMA_VERSION
             and row_has_closure
         ):
-            segment_ids = [
-                str(x) for x in (row.segment_ids or []) if str(x).strip()
-            ]
+            segment_ids = [str(x) for x in (row.segment_ids or []) if str(x).strip()]
             conv_ids = sorted(
                 {str(x) for x in (row.conversation_ids or []) if str(x).strip()}
             )
-            chunk_ids = [
-                str(x) for x in (row.memory_chunk_ids or []) if str(x).strip()
-            ]
+            chunk_ids = [str(x) for x in (row.memory_chunk_ids or []) if str(x).strip()]
             fact_ids = [str(x) for x in (row.memory_fact_ids or []) if str(x).strip()]
-            tl_ids = [
-                str(x) for x in (row.timeline_event_ids or []) if str(x).strip()
-            ]
+            tl_ids = [str(x) for x in (row.timeline_event_ids or []) if str(x).strip()]
             sum_ids = [str(x) for x in (row.summary_ids or []) if str(x).strip()]
             notes.extend([str(x) for x in (row.notes or []) if x])
             notes.append("evidence_from_chapter_evidence_snapshot_table")
@@ -163,7 +167,9 @@ class EvalTraceService:
                 sum_ids=sum_ids,
             )
             if live_segment_ids and set(live_segment_ids) != set(segment_ids):
-                notes.append("live_source_segments_differ_from_snapshot_reconcile_in_pipeline")
+                notes.append(
+                    "live_source_segments_differ_from_snapshot_reconcile_in_pipeline"
+                )
             dlg = getattr(row, "message_lineage_json", None)
             return ChapterEvidenceBundle(
                 user_id=user_id,
@@ -202,14 +208,24 @@ class EvalTraceService:
         )
 
         if use_snap and isinstance(snap, dict):
-            segment_ids = [str(x) for x in (snap.get("segment_ids") or []) if str(x).strip()]
+            segment_ids = [
+                str(x) for x in (snap.get("segment_ids") or []) if str(x).strip()
+            ]
             conv_ids = sorted(
                 {str(x) for x in (snap.get("conversation_ids") or []) if str(x).strip()}
             )
-            chunk_ids = [str(x) for x in (snap.get("memory_chunk_ids") or []) if str(x).strip()]
-            fact_ids = [str(x) for x in (snap.get("memory_fact_ids") or []) if str(x).strip()]
-            tl_ids = [str(x) for x in (snap.get("timeline_event_ids") or []) if str(x).strip()]
-            sum_ids = [str(x) for x in (snap.get("summary_ids") or []) if str(x).strip()]
+            chunk_ids = [
+                str(x) for x in (snap.get("memory_chunk_ids") or []) if str(x).strip()
+            ]
+            fact_ids = [
+                str(x) for x in (snap.get("memory_fact_ids") or []) if str(x).strip()
+            ]
+            tl_ids = [
+                str(x) for x in (snap.get("timeline_event_ids") or []) if str(x).strip()
+            ]
+            sum_ids = [
+                str(x) for x in (snap.get("summary_ids") or []) if str(x).strip()
+            ]
             notes.extend([str(x) for x in (snap.get("notes") or []) if x])
             notes.append("evidence_from_chapter_evidence_bundle_json_column")
             tier = self._chapter_closure_tier(
@@ -220,8 +236,12 @@ class EvalTraceService:
                 sum_ids=sum_ids,
             )
             if live_segment_ids and set(live_segment_ids) != set(segment_ids):
-                notes.append("live_source_segments_differ_from_snapshot_reconcile_in_pipeline")
-            snap_dlg = snap.get("message_lineage_json") if isinstance(snap, dict) else None
+                notes.append(
+                    "live_source_segments_differ_from_snapshot_reconcile_in_pipeline"
+                )
+            snap_dlg = (
+                snap.get("message_lineage_json") if isinstance(snap, dict) else None
+            )
             return ChapterEvidenceBundle(
                 user_id=user_id,
                 chapter_id=str(chapter.id),
@@ -256,8 +276,15 @@ class EvalTraceService:
         resolved_seg_ids = [s.id for s in segments] or segment_ids
         if len(segments) < len(segment_ids):
             notes.append("some_segments_missing_or_foreign_user")
-        conv_ids = sorted({str(s.conversation_id) for s in segments if s.conversation_id})
-        chunk_ids, fact_ids, tl_ids, sum_ids = await fetch_memory_closure_for_conversations(
+        conv_ids = sorted(
+            {str(s.conversation_id) for s in segments if s.conversation_id}
+        )
+        (
+            chunk_ids,
+            fact_ids,
+            tl_ids,
+            sum_ids,
+        ) = await fetch_memory_closure_for_conversations(
             self._db, user_id=user_id, conversation_ids=conv_ids
         )
         tier = self._chapter_closure_tier(
@@ -339,8 +366,12 @@ class EvalTraceService:
         )
         return formatted, bundle
 
-    async def build_story_bundle(self, user_id: str, story_id: str) -> StoryEvidenceBundle:
-        st = await get_story_for_eval_trace(self._db, user_id=user_id, story_id=story_id)
+    async def build_story_bundle(
+        self, user_id: str, story_id: str
+    ) -> StoryEvidenceBundle:
+        st = await get_story_for_eval_trace(
+            self._db, user_id=user_id, story_id=story_id
+        )
         if not st:
             return StoryEvidenceBundle(
                 user_id=user_id,
@@ -378,7 +409,9 @@ class EvalTraceService:
             segments = await fetch_segments_for_user(
                 self._db, user_id=user_id, segment_ids=dedup_seg
             )
-            conv_ids = sorted({str(s.conversation_id) for s in segments if s.conversation_id})
+            conv_ids = sorted(
+                {str(s.conversation_id) for s in segments if s.conversation_id}
+            )
             if dedup_seg and not segments:
                 notes.append("chapter_segment_ids_unresolved")
             if conv_ids:
@@ -428,11 +461,16 @@ class EvalTraceService:
             segments = await fetch_segments_for_user(
                 self._db, user_id=user_id, segment_ids=dedup_seg
             )
-            conv_ids = sorted({str(s.conversation_id) for s in segments if s.conversation_id})
-            chunk_ids, fact_ids, tl_ids, sum_ids = (
-                await fetch_memory_closure_for_conversations(
-                    self._db, user_id=user_id, conversation_ids=conv_ids
-                )
+            conv_ids = sorted(
+                {str(s.conversation_id) for s in segments if s.conversation_id}
+            )
+            (
+                chunk_ids,
+                fact_ids,
+                tl_ids,
+                sum_ids,
+            ) = await fetch_memory_closure_for_conversations(
+                self._db, user_id=user_id, conversation_ids=conv_ids
             )
             notes.append("fallback_lineage_no_story_evidence_links")
             notes.append("augmented_with_chapter_context")