feat(api): 访谈路径轻量门控、Memoir Phase1 批处理与叙事/记忆管线加固

- 新增 utterance_substance：短时/应答/元话语可跳过记忆检索、阶段 LLM 与资料抽取 LLM；可配置
- 输入归一化：LLM 模式默认仅语音/ASR；配置项写入 .env.example
- Memoir Phase1：可选 batch LLM 一次性抽取+分类（失败回退逐段）；Extraction 空槽位时阶段与 current_stage 对齐，prompt 约束收紧
- 叙事与忠实度：narrative_safety、证据重叠/场合锚点、标题 slots 与履历短语 grounded；fidelity 解析失败 fail-open 可配置
- 章节管线：锁 TTL 上调、锁竞争 Celery 重试、Phase2 immediate singleflight 等；story_pipeline_sync / chapter_compose / memoir_tasks 联动
- Memory：compaction / repo / summarizer / evidence 小修；事实 FTS 未命中是否回退最近事实可配置
- 新增 memoir_pipeline_trace；补充 memoir_reliability 文档与多项回归/门控测试

api/app/agents/chat/orchestrator.py

@@ -19,9 +19,13 @@ from app.agents.chat.stage_detection import (
     detect_primary_life_stage,
     life_stage_display_name,
 )
+from app.agents.chat.utterance_substance import should_run_chat_stage_memory_heavy_work
 from app.core.config import settings
 from app.core.dependencies import get_llm_provider
-from app.features.conversation.input_normalize import normalize_chat_input_for_agent
+from app.features.conversation.input_normalize import (
+    apply_conversation_input_rules,
+    normalize_chat_input_for_agent,
+)
 from app.features.memoir.state_service import get_or_create_state, switch_stage
 
 
@@ -58,6 +62,11 @@ async def _fetch_interview_memory_evidence(
     msg = (user_message or "").strip()
     if not msg:
         return ""
+    if (
+        settings.chat_memory_retrieval_require_substantive
+        and not should_run_chat_stage_memory_heavy_work(msg)
+    ):
+        return ""
     try:
         ms = MemoryService(db, embedding_provider=get_embedding_provider())
         bundle = await ms.retrieve(user_id, msg, top_k=settings.chat_memory_top_k)
@@ -122,9 +131,19 @@ class ChatOrchestrator:
                         missing,
                         len(user_message or ""),
                     )
-                    extracted = await self.profile_agent.extract_profile_from_message(
-                        user_message, missing, conversation_id=conversation_id
-                    )
+                    run_extract = True
+                    if settings.chat_profile_extract_require_substantive:
+                        rules_only = apply_conversation_input_rules(user_message or "")
+                        run_extract = should_run_chat_stage_memory_heavy_work(
+                            rules_only
+                        )
+                    extracted = None
+                    if run_extract:
+                        extracted = (
+                            await self.profile_agent.extract_profile_from_message(
+                                user_message, missing, conversation_id=conversation_id
+                            )
+                        )
                     if extracted:
                         await apply_extracted_profile_fn(user, extracted, db)
 
@@ -184,12 +203,17 @@ class ChatOrchestrator:
         normalized_user_message = normalize_chat_input_for_agent(
             user_message or "",
             llm=llm_n,
+            is_from_voice=is_from_voice,
         )
         state = await get_or_create_state(user_id, db)
+        substantive_turn = should_run_chat_stage_memory_heavy_work(
+            normalized_user_message
+        )
         detected = await detect_primary_life_stage(
             normalized_user_message,
             state.current_stage,
             self.interview_agent.llm,
+            skip_llm=not substantive_turn,
         )
         if detected != state.current_stage:
             state = await switch_stage(user_id, detected, db)