feat: add NovelPage component with bookshelf, open book, and reading views
This commit is contained in:
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"""
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爽文事件规划（fiction.event_plan）— LLM 调用逻辑。
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按事件顺序生成，每完成一个事件即持久化并广播进度。
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"""
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from __future__ import annotations
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import json
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import logging
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import random
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import re
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from typing import Any, AsyncIterator, Dict, List, Optional
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from langchain_core.messages import HumanMessage, SystemMessage
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from models.fiction_models import (
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ChapterPlanItem,
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CoarseOutlineEvent,
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EventPlanEntry,
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FictionBookMetadata,
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FlowStepsPlan,
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)
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from services.fiction_event_plan_progress import emit as emit_progress
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from services.fiction_event_plan_progress import subscribe as subscribe_progress
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from services.fiction_metadata_service import fiction_metadata_service
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from services.fiction_prompt_utils import resolve_prompt
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from services.fiction_service import fiction_service
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from services.studio_step_respond import resolve_api_config
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from utils.llm_client import LLMClient
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logger = logging.getLogger(__name__)
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_llm_client = LLMClient()
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_JSON_FENCE = re.compile(r"```(?:json)?\s*([\s\S]*?)```", re.IGNORECASE)
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def _extract_json(raw: str) -> Dict[str, Any]:
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text = (raw or "").strip()
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if not text:
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raise ValueError("模型返回为空")
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fence = _JSON_FENCE.search(text)
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if fence:
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text = fence.group(1).strip()
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try:
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return json.loads(text)
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except json.JSONDecodeError:
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start = text.find("{")
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end = text.rfind("}")
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if start >= 0 and end > start:
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return json.loads(text[start : end + 1])
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raise ValueError("无法解析模型返回的 JSON")
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def _validate_api_config(api_config: Dict[str, str]) -> None:
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if not api_config.get("api_key"):
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raise ValueError("API Key 未配置，请先在 API 配置页面保存密钥")
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if not api_config.get("api_url"):
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raise ValueError("API 地址未配置，请先在 API 配置页面保存 mainLLM")
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def _format_guide_global_layers(layers: List[str]) -> str:
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entries = fiction_service.get_guide_global_entries().entries
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filtered = [e for e in entries if e.layer in layers]
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lines: List[str] = []
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for entry in filtered:
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lines.append(f"[{entry.layer}] {entry.title}\n{entry.content}")
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return "\n\n".join(lines) if lines else "（无全局指南）"
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def _format_book_guide(book_id: str) -> str:
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guide = fiction_service.get_book_guide(book_id)
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parts = [
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f"主角人设：{guide.persona}",
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f"核心爽点：{guide.highlight}",
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f"用户体验：{guide.experience}",
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f"创作禁区：{guide.forbiddenZones}",
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]
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return "\n".join(parts)
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def _get_flow_by_id(flow_id: str):
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catalog = fiction_service.get_emotion_catalog()
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for flow in catalog.flows:
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if flow.id == flow_id:
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return flow
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return None
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def _format_flow_steps(flow) -> str:
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lines = [f"情绪流：{flow.intro} (id: {flow.id})"]
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for step in flow.steps or []:
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lines.append(f" [{step.key}] {step.text}")
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return "\n".join(lines)
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def _build_event_plan_messages(
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book_id: str,
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event_id: str,
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event_title: str,
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event_summary: str,
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emotion_flow_id: str,
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) -> List[Any]:
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settings = fiction_service.get_book_settings(book_id)
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user_prompt = settings.prompts.eventPlan or fiction_service.get_default_settings().prompts.eventPlan
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system_prompt = resolve_prompt("eventPlan", user_prompt)
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guide_l2 = _format_guide_global_layers(["L2"])
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book_guide = _format_book_guide(book_id)
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flow = _get_flow_by_id(emotion_flow_id)
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flow_text = _format_flow_steps(flow) if flow else f"情绪流 id: {emotion_flow_id}"
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user_content = f"""## 全局创作指南（L2，仅用于事件规划）
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{guide_l2}
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## 本书 Guide 世界书
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{book_guide}
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## 当前粗纲事件
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- id: {event_id}
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- title: {event_title}
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- summary: {event_summary}
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## 为本事件随机选定的情绪流
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{flow_text}
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请输出 flowStepsPlan（起承转合）与 chapterPlan（章节级 brief）。
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输出 JSON 示例：
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{{
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"flowStepsPlan": {{
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"起": "本阶段规划…",
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"承": "…",
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"转": "…",
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"合": "…"
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}},
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"chapterPlan": [
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{{ "seq": 1, "phaseKey": "起", "phaseSlice": "全", "brief": "本章要点", "status": "planned" }}
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]
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}}"""
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return [
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SystemMessage(content=system_prompt),
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HumanMessage(content=user_content),
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]
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def _normalize_flow_steps_plan(raw: Any) -> FlowStepsPlan:
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data = raw if isinstance(raw, dict) else {}
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return FlowStepsPlan(
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起=str(data.get("起") or data.get("qi") or ""),
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承=str(data.get("承") or data.get("cheng") or ""),
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转=str(data.get("转") or data.get("zhuan") or ""),
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合=str(data.get("合") or data.get("he") or ""),
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)
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def _normalize_chapter_plan(raw: Any) -> List[ChapterPlanItem]:
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if not isinstance(raw, list):
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return []
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items: List[ChapterPlanItem] = []
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for idx, item in enumerate(raw):
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if not isinstance(item, dict):
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continue
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seq = item.get("seq")
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if not isinstance(seq, int):
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seq = idx + 1
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status = str(item.get("status") or "planned")
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items.append(
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ChapterPlanItem(
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seq=seq,
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phaseKey=str(item.get("phaseKey") or item.get("phase_key") or "起"),
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phaseSlice=str(item.get("phaseSlice") or item.get("phase_slice") or ""),
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brief=str(item.get("brief") or ""),
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status=status,
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)
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)
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items.sort(key=lambda c: c.seq)
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return items
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def _parse_event_plan_response(data: Dict[str, Any], emotion_flow_id: str) -> EventPlanEntry:
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flow_steps = _normalize_flow_steps_plan(data.get("flowStepsPlan"))
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chapter_plan = _normalize_chapter_plan(data.get("chapterPlan"))
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if not chapter_plan:
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raise ValueError("chapterPlan 为空")
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return EventPlanEntry(
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emotionFlowId=emotion_flow_id,
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flowStepsPlan=flow_steps,
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chapterPlan=chapter_plan,
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)
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def _event_fully_planned(entry: EventPlanEntry) -> bool:
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return bool(entry.chapterPlan)
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def _resolve_targets(
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metadata: FictionBookMetadata,
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*,
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event_id: Optional[str] = None,
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) -> List[CoarseOutlineEvent]:
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coarse_events = metadata.coarseOutline.events
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if not coarse_events:
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raise ValueError("请先生成粗纲")
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events_map = dict(metadata.events or {})
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if event_id:
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targets = [e for e in coarse_events if e.id == event_id]
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if not targets:
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raise ValueError(f"粗纲中不存在事件: {event_id}")
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return targets
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return [
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e
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for e in coarse_events
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if e.id not in events_map or not _event_fully_planned(events_map[e.id])
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]
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def event_planned_payload(evt: CoarseOutlineEvent, entry: EventPlanEntry) -> Dict[str, Any]:
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phases: List[str] = []
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fsp = entry.flowStepsPlan
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for key in ("起", "承", "转", "合"):
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if getattr(fsp, key, ""):
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phases.append(key)
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return {
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"type": "event_planned",
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"eventId": evt.id,
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"title": evt.title,
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"chapterCount": len(entry.chapterPlan),
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"phases": phases,
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}
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def build_progress_snapshot(book_id: str) -> Dict[str, Any]:
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"""已规划事件的目录快照（不含 brief 剧透）。"""
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metadata = fiction_metadata_service.get_metadata(book_id)
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coarse_events = metadata.coarseOutline.events
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events_map = metadata.events or {}
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items: List[Dict[str, Any]] = []
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for evt in coarse_events:
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entry = events_map.get(evt.id)
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if entry and _event_fully_planned(entry):
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items.append(event_planned_payload(evt, entry))
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run = fiction_metadata_service.get_run(book_id)
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progress = run.progress or {}
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return {
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"type": "snapshot",
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"items": items,
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"done": progress.get("done", len(items)),
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"total": progress.get("total", len(coarse_events)),
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}
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async def _generate_one_event(
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book_id: str,
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evt: CoarseOutlineEvent,
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*,
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resolved: Dict[str, str],
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allowed: List[str],
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) -> EventPlanEntry:
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emotion_flow_id = random.choice(allowed)
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messages = _build_event_plan_messages(
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book_id,
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evt.id,
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evt.title,
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evt.summary,
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emotion_flow_id,
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)
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response = await _llm_client.chat_completion(
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messages=messages,
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api_url=resolved["api_url"],
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api_key=resolved["api_key"],
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model=resolved.get("model", "gpt-4o-mini"),
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temperature=0.7,
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max_tokens=8000,
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request_timeout=120,
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stream=False,
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)
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content = response["choices"][0]["message"]["content"]
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data = _extract_json(content)
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return _parse_event_plan_response(data, emotion_flow_id)
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async def iter_event_plan(
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book_id: str,
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*,
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profile_id: Optional[str] = None,
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api_config: Optional[Dict[str, str]] = None,
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event_id: Optional[str] = None,
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) -> AsyncIterator[Dict[str, Any]]:
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"""按事件逐个生成，每完成一个即保存并 yield 进度事件。"""
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resolved = resolve_api_config(profile_id, api_config)
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_validate_api_config(resolved)
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metadata = fiction_metadata_service.get_metadata(book_id)
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meta = fiction_service.get_book_meta(book_id)
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allowed = list(meta.allowedFlowIds or [])
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if not allowed:
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raise ValueError("本书未配置 allowedFlowIds")
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targets = _resolve_targets(metadata, event_id=event_id)
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coarse_events = metadata.coarseOutline.events
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coarse_total = len(coarse_events)
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if not targets:
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logger.info("Event plans already exist for book %s, skipping generation", book_id)
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fiction_metadata_service.set_pipeline_stage(
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book_id, status="idle", pipeline_stage="event_plan_done"
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)
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fiction_metadata_service.clear_pipeline_progress(book_id)
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done_evt: Dict[str, Any] = {"type": "done", "done": coarse_total, "total": coarse_total}
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emit_progress(book_id, done_evt)
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yield done_evt
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return
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run = fiction_metadata_service.get_run(book_id)
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if run.status == "error":
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fiction_metadata_service.clear_pipeline_error(book_id)
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fiction_metadata_service.set_pipeline_stage(
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book_id, status="running", pipeline_stage="event_plan"
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)
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events_map = dict(metadata.events or {})
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def _planned_count() -> int:
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return sum(
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1
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for e in coarse_events
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if e.id in events_map and _event_fully_planned(events_map[e.id])
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)
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initial_done = _planned_count()
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fiction_metadata_service.set_pipeline_progress(
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book_id, done=initial_done, total=coarse_total
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)
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started: Dict[str, Any] = {
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"type": "started",
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"done": initial_done,
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"total": coarse_total,
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"pending": len(targets),
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}
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emit_progress(book_id, started)
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yield started
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try:
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for evt in targets:
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entry = await _generate_one_event(
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book_id, evt, resolved=resolved, allowed=allowed
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)
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events_map[evt.id] = entry
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metadata.events = events_map
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fiction_metadata_service.save_metadata(book_id, metadata)
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done_count = _planned_count()
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fiction_metadata_service.set_pipeline_progress(
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book_id, done=done_count, total=coarse_total
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)
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payload = event_planned_payload(evt, entry)
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emit_progress(book_id, payload)
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yield payload
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fiction_metadata_service.set_pipeline_stage(
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book_id, status="idle", pipeline_stage="event_plan_done"
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)
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fiction_metadata_service.clear_pipeline_progress(book_id)
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done_evt = {"type": "done", "done": _planned_count(), "total": coarse_total}
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emit_progress(book_id, done_evt)
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yield done_evt
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except Exception as exc:
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completed = [
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eid for eid, ent in events_map.items() if _event_fully_planned(ent)
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]
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err_evt: Dict[str, Any] = {
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"type": "error",
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"message": str(exc),
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"completedEvents": completed,
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"done": _planned_count(),
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"total": coarse_total,
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}
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emit_progress(book_id, err_evt)
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fiction_metadata_service.set_pipeline_stage(
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book_id, status="error", pipeline_stage="event_plan"
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)
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yield err_evt
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raise
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async def run_event_plan(
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book_id: str,
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*,
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profile_id: Optional[str] = None,
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api_config: Optional[Dict[str, str]] = None,
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event_id: Optional[str] = None,
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) -> FictionBookMetadata:
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async for _event in iter_event_plan(
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book_id,
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profile_id=profile_id,
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api_config=api_config,
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event_id=event_id,
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):
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pass
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return fiction_metadata_service.get_metadata(book_id)
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async def stream_event_plan_subscribe(book_id: str) -> AsyncIterator[Dict[str, Any]]:
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"""订阅进行中的事件纲要进度（先快照，再实时）。"""
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snapshot = build_progress_snapshot(book_id)
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yield snapshot
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run = fiction_metadata_service.get_run(book_id)
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if run.status == "running" and run.pipelineStage == "event_plan":
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async for event in subscribe_progress(book_id):
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if event.get("type") == "snapshot":
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continue
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yield event
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elif snapshot["items"] or snapshot.get("done", 0) > 0:
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yield {
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"type": "done",
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"done": snapshot["done"],
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"total": snapshot["total"],
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}
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