Simplify AI memory pipeline

api/app/features/memoir/story_pipeline_sync.py

@@ -17,10 +17,7 @@ from sqlalchemy import func, select
 from sqlalchemy.orm import Session, joinedload
 
 from app.agents.memoir.narrative_agent import NarrativeAgent
-from app.agents.memoir.prompts import (
-    format_evidence_chunks_for_prompt,
-    format_narrative_user_content,
-)
+from app.agents.memoir.prompts import format_narrative_user_content
 from app.agents.memoir.story_route_agent import (
     APPEND_FIRST_CHAPTER_CATEGORIES,
     PLAN_BATCH_MAX_SEGMENTS,
@@ -59,6 +56,7 @@ from app.features.memoir.repo import (
     mark_chapter_dirty_sync,
     reorder_chapter_story_links_by_life_order_sync,
 )
+from app.features.memory.evidence_format import format_evidence_chunks_for_prompt
 from app.features.story.models import Story, StoryVersion
 from app.features.story.sync_write import (
     append_story_version_sync,
@@ -99,7 +97,7 @@ def _dialogue_lineage_dict_for_segment_ids(
 
 def _evidence_link_ids(
     evidence: dict,
-) -> tuple[list[str], list[str], list[str], list[str]]:
+) -> tuple[list[str], list[str], list[str]]:
     """从 MemoryService.retrieve 结果提取稳定 ID 列表。"""
     chunks: list[str] = []
     for c in evidence.get("relevant_chunks") or []:
@@ -109,15 +107,11 @@ def _evidence_link_ids(
     for f in evidence.get("relevant_facts") or []:
         if isinstance(f, dict) and f.get("id"):
             facts.append(str(f["id"]))
-    timelines: list[str] = []
-    for e in evidence.get("timeline_hints") or []:
-        if isinstance(e, dict) and e.get("id"):
-            timelines.append(str(e["id"]))
     summaries: list[str] = []
     for s in evidence.get("relevant_summaries") or []:
         if isinstance(s, dict) and s.get("id"):
             summaries.append(str(s["id"]))
-    return chunks, facts, timelines, summaries
+    return chunks, facts, summaries
 
 
 def _story_prompt_meta_for_lineage(
@@ -126,14 +120,13 @@ def _story_prompt_meta_for_lineage(
     memoir_correlation_id: str | None,
     top_k: int,
 ) -> dict:
-    c, f, t, s = _evidence_link_ids(evidence)
+    c, f, s = _evidence_link_ids(evidence)
     return {
         "memoir_retrieval": {
             "correlation_id": memoir_correlation_id,
             "top_k": top_k,
             "chunk_ids": c,
             "fact_ids": f,
-            "timeline_event_ids": t,
             "summary_ids": s,
         }
     }
@@ -150,13 +143,13 @@ def _persist_story_lineage_sync(
     dialogue_lineage: dict | None = None,
 ) -> None:
     """写入 StoryEvidenceLink + 本版本 prompt_meta（可审计检索闭包）。"""
-    c, f, t, s = _evidence_link_ids(evidence)
+    c, f, s = _evidence_link_ids(evidence)
     replace_story_evidence_links_sync(
         session,
         story_id=story_id,
         chunk_ids=c,
         fact_ids=f,
-        timeline_event_ids=t,
+        timeline_event_ids=[],
         summary_ids=s,
     )
     version.prompt_meta = _story_prompt_meta_for_lineage(
@@ -992,7 +985,6 @@ def run_story_pipeline_for_category_batch(
             "relevant_chunks": [],
             "relevant_summaries": [],
             "relevant_facts": [],
-            "timeline_hints": [],
             "relevant_stories": [],
         }
         ev_elapsed = time.perf_counter() - _t_ev