聊天和回忆录证据检索都走 pgvector，去掉 Postgres FTS/content_tsv，新迁移删掉 content_tsv 列（部署要先 alembic upgrade）。

Embedding 端口增加 is_available()，聊天和回忆录日志用统一方式表示向量是否真能调用。

记忆整理（compaction）支持 Beat 定期扫用户；

事实抽取提示与 subject 归一化，减少同一人多种称呼；

api/app/features/memoir/story_pipeline_sync.py

@@ -33,6 +33,7 @@ from app.agents.memoir.story_route_agent import (
 )
 from app.agents.state_schema import MemoirStateSchema
 from app.core.config import settings
+from app.core.dependencies import get_embedding_provider
 from app.core.logging import get_logger
 from app.features.memoir.cover_eligibility import chapter_needs_cover_enqueue
 from app.features.memoir.memoir_images.settings import MemoirImageSettings
@@ -714,8 +715,16 @@ def run_story_pipeline_for_category_batch(
     top_k = int(settings.evidence_top_k_default)
     if n_units > int(settings.evidence_large_batch_threshold):
         top_k = int(settings.evidence_top_k_large_batch)
+    emb = get_embedding_provider()
+    embedding_available = emb.is_available()
     try:
-        evidence = retrieve_evidence_sync(session, user_id, combined_text, top_k=top_k)
+        evidence = retrieve_evidence_sync(
+            session,
+            user_id,
+            combined_text,
+            top_k=top_k,
+            embedding_provider=emb,
+        )
     except Exception as e:
         logger.warning("Evidence 检索跳过: {}", e)
         evidence = {
@@ -726,6 +735,16 @@ def run_story_pipeline_for_category_batch(
             "relevant_stories": [],
         }
 
+    logger.info(
+        "memoir_evidence_retrieved user_id={} chunks={} facts={} summaries={} stories={} vector_ok={}",
+        user_id,
+        len(evidence.get("relevant_chunks") or []),
+        len(evidence.get("relevant_facts") or []),
+        len(evidence.get("relevant_summaries") or []),
+        len(evidence.get("relevant_stories") or []),
+        embedding_available,
+    )
+
     evidence_text = format_evidence_chunks_for_prompt(evidence)
     oral_for_memoir = normalize_oral_for_memoir(combined_text, llm=llm)
     ct_raw = (combined_text or "").strip()