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life-echo/api/app/agents/memoir/chapter_composer_orchestrator.py

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重构回忆录为 story-first / markdown-first 架构并整合图片意图与前端 UI 修复 本次 squash merge 将 codex-story-first-image-intent 的整体改动合入 development,核心内容包括: 1. 后端数据与迁移:新增 stories、story_versions、story_image_intents、chapter_cover_intents、assets 等模型与 Alembic 迁移,建立 story-first、markdown-first、asset-first 的主数据链路。 2. 生成与任务链:引入 StoryBuilderOrchestrator、ChapterComposerOrchestrator、story_image_tasks、chapter_cover_tasks,图片生成从正文占位符改为结构化 intent -> asset -> markdown 回填。 3. 并发与一致性:为 story/chapter intent 增加 claim_token、claimed_at、attempt_count,采用数据库原子 claim 为主、Redis 锁为辅,避免重复生成、锁误删和 processing 卡死。 4. Memoir 读写路径:章节 canonical_markdown 成为正文真源,列表/详情接口补齐 markdown、cover_asset、word_count 等字段,PDF 与 asset 解析链路同步升级。 5. Memory / Retrieval:扩展 transcript ingest、chunking、evidence 检索与 story 聚合基础设施,为后续 story-first RAG 与多 agent 编排提供底座。 6. App 端体验:章节页继续走 MarkdownRenderer 阅读链,同时吸收 fix3-19 的跨平台 UI glitch 修复;更新对话页、首页、文案资源与章节列表映射逻辑。 7. 测试与文档:补充 asset resolver、story image task、章节封面派发、markdown 映射等回归测试,并加入图片占位符退役设计文档。
2026-03-20 10:30:07 +08:00
"""
ChapterComposerOrchestrator 读取 stories/evidence生成章节 markdown
Agent 只产出结构化结果不直接写 DB
"""
from __future__ import annotations
from typing import Any
from app.core.logging import get_logger
logger = get_logger(__name__)
class ChapterComposerOrchestrator:
"""
生成章节大纲和章节 markdown
仅返回 markdown不落库
"""
def compose_chapter_markdown(
self,
*,
title: str,
category: str,
evidence: dict,
existing_markdown: str = "",
user_profile: str = "",
birth_year: int | None = None,
llm: Any = None,
) -> str:
"""
evidence 生成章节 markdown
若有 existing_markdown 则追加/合并
返回 markdown 正文不写 DB
"""
from app.agents.memoir.narrative_agent import NarrativeAgent
chunks = evidence.get("relevant_chunks", [])
facts = evidence.get("relevant_facts", [])
new_content = self._format_evidence_for_prompt(chunks, facts)
agent = NarrativeAgent()
narrative = agent.generate_narrative(
stage=category,
slots={},
new_content=new_content,
existing_content=existing_markdown,
user_profile=user_profile,
birth_year=birth_year,
llm=llm,
)
return self._to_markdown(narrative)
def _format_evidence_for_prompt(self, chunks: list, facts: list) -> str:
"""将 evidence 格式化为 prompt 输入。"""
parts = []
for c in chunks[:10]:
content = (
c.get("content", "")
if isinstance(c, dict)
else getattr(c, "content", "")
)
if content:
parts.append(content.strip())
for f in facts[:5]:
if isinstance(f, dict):
subj = f.get("subject", "")
pred = f.get("predicate", "")
obj = f.get("object_json", "")
if subj or pred:
parts.append(f"{subj} {pred} {obj}")
else:
parts.append(
f"{getattr(f, 'subject', '')} {getattr(f, 'predicate', '')}"
)
return "\n\n".join(parts) if parts else ""
def _to_markdown(self, narrative: str) -> str:
"""将 narrativeJSON 或纯文本)转为 markdown。正文不含占位符。"""
if not narrative or not narrative.strip():
return ""
if narrative.strip().startswith("{") and "paragraphs" in narrative:
import json
try:
data = json.loads(narrative)
paras = data.get("paragraphs", [])
if isinstance(paras, list):
parts = []
for p in paras:
if isinstance(p, dict):
text = p.get("content", p.get("text", ""))
else:
text = str(p)
if text.strip():
parts.append(text.strip())
md = "\n\n".join(parts)
else:
md = narrative
except json.JSONDecodeError:
md = narrative
else:
md = narrative.strip()
return md