update: 优化剧情分析与章节规划算法,集成伏笔上下文追踪;完善章节删除时的级联清理逻辑

This commit is contained in:
xiamuceer-j
2026-01-19 17:23:50 +08:00
parent dc3dbaaf2c
commit 927072d16f
3 changed files with 308 additions and 31 deletions
+175 -10
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@@ -12,6 +12,7 @@ from app.models.outline import Outline
from app.models.character import Character
from app.models.career import Career, CharacterCareer
from app.models.memory import StoryMemory
from app.models.foreshadow import Foreshadow
from app.logger import get_logger
logger = get_logger(__name__)
@@ -25,12 +26,14 @@ class ChapterContext:
采用RTCO框架的分层设计:
- P0-核心(必须):大纲、衔接点、字数要求
- P1-重要(按需):角色、情感基调、风格
- P2-参考(条件触发):记忆、故事骨架、MCP资料
- P2-参考(条件触发):记忆、故事骨架、MCP资料、伏笔提醒
"""
# === P0-核心信息(必须包含)===
chapter_outline: str = "" # 本章大纲
continuation_point: Optional[str] = None # 衔接锚点(上一章结尾)
continuation_point: Optional[str] = None # 衔接锚点(增强版:含上一章摘要和结尾)
previous_chapter_summary: Optional[str] = None # 🔧 新增:上一章剧情摘要
previous_chapter_events: Optional[List[str]] = None # 🔧 新增:上一章关键事件
target_word_count: int = 3000 # 目标字数
min_word_count: int = 2500 # 最小字数
max_word_count: int = 4000 # 最大字数
@@ -54,6 +57,7 @@ class ChapterContext:
relevant_memories: Optional[str] = None # 相关记忆(精简版)
story_skeleton: Optional[str] = None # 故事骨架(50章+启用)
mcp_references: Optional[str] = None # MCP参考资料
foreshadow_reminders: Optional[str] = None # 伏笔提醒(新增)
# === 元信息 ===
context_stats: Dict[str, Any] = field(default_factory=dict) # 统计信息
@@ -62,7 +66,8 @@ class ChapterContext:
"""计算总上下文长度"""
total = 0
for field_name in ['chapter_outline', 'continuation_point', 'chapter_characters',
'relevant_memories', 'story_skeleton', 'style_instruction']:
'relevant_memories', 'story_skeleton', 'style_instruction',
'foreshadow_reminders', 'previous_chapter_summary']:
value = getattr(self, field_name, None)
if value:
total += len(value)
@@ -91,14 +96,16 @@ class ChapterContextBuilder:
STYLE_MAX_LENGTH = 200 # 风格描述最大长度
MAX_CONTEXT_LENGTH = 3000 # 总上下文最大字符数
def __init__(self, memory_service=None):
def __init__(self, memory_service=None, foreshadow_service=None):
"""
初始化构建器
Args:
memory_service: 记忆服务实例(可选,用于检索相关记忆)
foreshadow_service: 伏笔服务实例(可选,用于获取伏笔提醒)
"""
self.memory_service = memory_service
self.foreshadow_service = foreshadow_service
async def build(
self,
@@ -155,20 +162,28 @@ class ChapterContextBuilder:
chapter, outline, project.outline_mode
)
# === 衔接锚点(根据章节调整长度)===
# === 衔接锚点(根据章节调整长度,增强版含摘要和事件===
if chapter_number == 1:
context.continuation_point = None
context.previous_chapter_summary = None
context.previous_chapter_events = None
logger.info(" ✅ 第1章无需衔接锚点")
elif chapter_number <= 10:
context.continuation_point = await self._get_last_ending(
ending_info = await self._get_last_ending_enhanced(
chapter, db, self.ENDING_LENGTH_SHORT
)
logger.info(f" ✅ 衔接锚点(短): {len(context.continuation_point or '')}字符")
context.continuation_point = ending_info.get('ending_text')
context.previous_chapter_summary = ending_info.get('summary')
context.previous_chapter_events = ending_info.get('key_events')
logger.info(f" ✅ 衔接锚点(短): {len(context.continuation_point or '')}字符, 摘要: {len(context.previous_chapter_summary or '')}字符")
else:
context.continuation_point = await self._get_last_ending(
ending_info = await self._get_last_ending_enhanced(
chapter, db, self.ENDING_LENGTH_NORMAL
)
logger.info(f" ✅ 衔接锚点(标准): {len(context.continuation_point or '')}字符")
context.continuation_point = ending_info.get('ending_text')
context.previous_chapter_summary = ending_info.get('summary')
context.previous_chapter_events = ending_info.get('key_events')
logger.info(f" ✅ 衔接锚点(标准): {len(context.continuation_point or '')}字符, 摘要: {len(context.previous_chapter_summary or '')}字符")
# === P1-重要信息 ===
context.chapter_characters = await self._build_chapter_characters(
@@ -200,6 +215,14 @@ class ChapterContextBuilder:
)
logger.info(f" ✅ 故事骨架: {len(context.story_skeleton or '')}字符")
# === P2-伏笔提醒(新增)===
if self.foreshadow_service:
context.foreshadow_reminders = await self._get_foreshadow_reminders(
project.id, chapter_number, db
)
if context.foreshadow_reminders:
logger.info(f" ✅ 伏笔提醒: {len(context.foreshadow_reminders)}字符")
# === 统计信息 ===
context.context_stats = {
"chapter_number": chapter_number,
@@ -208,6 +231,7 @@ class ChapterContextBuilder:
"characters_length": len(context.chapter_characters),
"memories_length": len(context.relevant_memories or ""),
"skeleton_length": len(context.story_skeleton or ""),
"foreshadow_length": len(context.foreshadow_reminders or ""),
"total_length": context.get_total_context_length()
}
@@ -263,7 +287,7 @@ class ChapterContextBuilder:
max_length: int
) -> Optional[str]:
"""
获取上一章结尾内容作为衔接锚点
获取上一章结尾内容作为衔接锚点(旧版本,保留兼容性)
Args:
chapter: 当前章节
@@ -294,6 +318,105 @@ class ChapterContextBuilder:
return content[-max_length:]
async def _get_last_ending_enhanced(
self,
chapter: Chapter,
db: AsyncSession,
max_length: int
) -> Dict[str, Any]:
"""
获取增强版衔接锚点(含上一章摘要和关键事件)
🔧 新增功能:
1. 提取上一章结尾文本
2. 获取上一章剧情摘要(从记忆或expansion_plan
3. 提取上一章关键事件
Args:
chapter: 当前章节
db: 数据库会话
max_length: 最大长度
Returns:
包含 ending_text, summary, key_events 的字典
"""
result_info = {
'ending_text': None,
'summary': None,
'key_events': []
}
if chapter.chapter_number <= 1:
return result_info
# 查询上一章
result = await db.execute(
select(Chapter)
.where(Chapter.project_id == chapter.project_id)
.where(Chapter.chapter_number == chapter.chapter_number - 1)
)
prev_chapter = result.scalar_one_or_none()
if not prev_chapter:
return result_info
# 1. 提取结尾内容
if prev_chapter.content:
content = prev_chapter.content.strip()
if len(content) <= max_length:
result_info['ending_text'] = content
else:
result_info['ending_text'] = content[-max_length:]
# 2. 获取上一章摘要
# 优先从记忆中获取 chapter_summary
summary_result = await db.execute(
select(StoryMemory.content)
.where(StoryMemory.project_id == chapter.project_id)
.where(StoryMemory.chapter_id == prev_chapter.id)
.where(StoryMemory.memory_type == 'chapter_summary')
.limit(1)
)
summary_mem = summary_result.scalar_one_or_none()
if summary_mem:
result_info['summary'] = summary_mem[:300] # 限制长度
elif prev_chapter.summary:
# 回退到章节的summary字段
result_info['summary'] = prev_chapter.summary[:300]
elif prev_chapter.expansion_plan:
# 再回退到expansion_plan中的plot_summary
try:
plan = json.loads(prev_chapter.expansion_plan)
result_info['summary'] = plan.get('plot_summary', '')[:300]
except json.JSONDecodeError:
pass
# 3. 提取上一章关键事件
if prev_chapter.expansion_plan:
try:
plan = json.loads(prev_chapter.expansion_plan)
key_events = plan.get('key_events', [])
if key_events:
result_info['key_events'] = key_events[:5] # 最多5个事件
except json.JSONDecodeError:
pass
# 如果没有从expansion_plan获取到,尝试从记忆中获取
if not result_info['key_events']:
events_result = await db.execute(
select(StoryMemory.content)
.where(StoryMemory.project_id == chapter.project_id)
.where(StoryMemory.chapter_id == prev_chapter.id)
.where(StoryMemory.memory_type == 'plot_point')
.limit(5)
)
event_mems = events_result.scalars().all()
if event_mems:
result_info['key_events'] = [e[:100] for e in event_mems]
return result_info
async def _build_chapter_characters(
self,
chapter: Chapter,
@@ -564,6 +687,48 @@ class ChapterContextBuilder:
return "\n".join(lines) if lines else None
async def _get_foreshadow_reminders(
self,
project_id: str,
chapter_number: int,
db: AsyncSession
) -> Optional[str]:
"""
获取伏笔提醒信息用于章节生成
策略:
1. 获取计划在本章或之前回收但未回收的伏笔(超期提醒)
2. 获取已埋入且接近需要回收的伏笔(提前提醒)
3. 获取本章计划埋入的伏笔(埋入提醒)
Args:
project_id: 项目ID
chapter_number: 当前章节号
db: 数据库会话
Returns:
格式化的伏笔提醒文本
"""
if not self.foreshadow_service:
return None
try:
context_result = await self.foreshadow_service.build_chapter_context(
db=db,
project_id=project_id,
chapter_number=chapter_number,
include_pending=True,
include_overdue=True,
lookahead=5
)
context_text = context_result.get("context_text", "")
return context_text if context_text else None
except Exception as e:
logger.error(f"❌ 获取伏笔提醒失败: {str(e)}")
return None
async def _build_story_skeleton(
self,
project_id: str,
+58 -13
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@@ -163,7 +163,7 @@ class PlotExpansionService:
batch_size: int,
progress_callback: Optional[callable]
) -> List[Dict[str, Any]]:
"""分批生成章节规划"""
"""分批生成章节规划(增强差异化版本)"""
# 计算批次数
total_batches = (target_chapter_count + batch_size - 1) // batch_size
logger.info(f"分批生成计划: 总共{target_chapter_count}章,分{total_batches}批,每批{batch_size}")
@@ -184,6 +184,9 @@ class PlotExpansionService:
all_chapter_plans = []
# 🔧 收集所有已使用的关键事件,用于防止重复
used_key_events = set()
for batch_num in range(total_batches):
# 计算当前批次的章节数
remaining_chapters = target_chapter_count - len(all_chapter_plans)
@@ -196,20 +199,41 @@ class PlotExpansionService:
if progress_callback:
await progress_callback(batch_num + 1, total_batches, current_start_index, current_batch_size)
# 构建当前批次的提示词(包含已生成章节的上下文
# 🔧 增强的上下文构建(包含完整的差异化信息
previous_context = ""
if all_chapter_plans:
# 构建完整的已生成章节摘要(包含关键事件)
previous_summaries = []
for ch in all_chapter_plans[-3:]: # 显示最近3章
for ch in all_chapter_plans: # 显示所有已生成章节
key_events_str = "".join(ch.get('key_events', [])[:3]) if ch.get('key_events') else ""
previous_summaries.append(
f"{ch['sub_index']}节《{ch['title']}》: {ch['plot_summary'][:100]}..."
f"{ch['sub_index']}节《{ch['title']}》:\n"
f" - 剧情:{ch.get('plot_summary', '')[:150]}\n"
f" - 关键事件:{key_events_str}\n"
f" - 结尾方式:{ch.get('ending_type', '未知')}"
)
# 提取所有已使用的关键事件
all_used_events = []
for ch in all_chapter_plans:
all_used_events.extend(ch.get('key_events', []))
used_events_str = "".join(all_used_events[-20:]) if all_used_events else "暂无"
previous_context = f"""
【已生成章节概要】(接续生成,注意衔接)
{chr(10).join(previous_summaries)}
⚠️ 当前是第{current_start_index}-{current_start_index + current_batch_size - 1}节(共{target_chapter_count}节中的一部分)
"""
【🔴 已生成章节完整信息(必须参考以确保差异化)】
{chr(10).join(previous_summaries)}
【🔴 已使用的关键事件(本批次不可重复使用)】
{used_events_str}
【🔴 差异化强制要求】
⚠️ 当前是第{current_start_index}-{current_start_index + current_batch_size - 1}节(共{target_chapter_count}节中的第{batch_num + 1}批)
⚠️ 每个新章节必须有完全不同的:
1. 开场场景(不同地点/时间/人物状态)
2. 核心事件(不与已生成章节的关键事件重复)
3. 结尾悬念(不同类型的钩子)
⚠️ 新章节的key_events不得与上面【已使用的关键事件】中的任何事件相同或相似
"""
# 获取自定义提示词模板
template = await PromptService.get_template("OUTLINE_EXPAND_MULTI", project.user_id, db)
# 格式化提示词
@@ -501,7 +525,7 @@ class PlotExpansionService:
ai_response: str,
outline_id: str
) -> List[Dict[str, Any]]:
"""解析AI的展开响应(使用统一的JSON清洗方法)"""
"""解析AI的展开响应(使用统一的JSON清洗方法,增强差异化字段"""
try:
# 使用统一的JSON清洗方法
cleaned_text = self.ai_service._clean_json_response(ai_response)
@@ -513,11 +537,30 @@ class PlotExpansionService:
if not isinstance(chapter_plans, list):
chapter_plans = [chapter_plans]
# 为每个章节规划添加outline_id
for plan in chapter_plans:
# 为每个章节规划添加outline_id和差异化标识
for idx, plan in enumerate(chapter_plans):
plan["outline_id"] = outline_id
# 🔧 确保有 ending_type 字段(用于差异化追踪)
if "ending_type" not in plan:
# 根据叙事目标推断结尾类型
narrative_goal = plan.get("narrative_goal", "")
if "悬念" in narrative_goal or "疑问" in narrative_goal:
plan["ending_type"] = "悬念"
elif "冲突" in narrative_goal or "对抗" in narrative_goal:
plan["ending_type"] = "冲突升级"
elif "转折" in narrative_goal:
plan["ending_type"] = "情节转折"
elif "情感" in narrative_goal or "情绪" in narrative_goal:
plan["ending_type"] = "情感收尾"
else:
plan["ending_type"] = f"自然过渡-{idx + 1}"
# 🔧 确保 key_events 是列表且非空
if not plan.get("key_events"):
plan["key_events"] = [f"章节{idx + 1}核心事件"]
logger.info(f"✅ 成功解析 {len(chapter_plans)} 个章节规划")
logger.info(f"✅ 成功解析 {len(chapter_plans)} 个章节规划(含差异化标识)")
return chapter_plans
except json.JSONDecodeError as e:
@@ -533,6 +576,7 @@ class PlotExpansionService:
"emotional_tone": "未知",
"narrative_goal": "需要重新生成",
"conflict_type": "未知",
"ending_type": "未知",
"estimated_words": 3000
}]
except Exception as e:
@@ -547,6 +591,7 @@ class PlotExpansionService:
"emotional_tone": "未知",
"narrative_goal": "需要重新生成",
"conflict_type": "未知",
"ending_type": "未知",
"estimated_words": 3000
}]
+75 -8
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@@ -561,7 +561,14 @@ class PromptService:
上一章结尾:
{continuation_point}
⚠️ 要求:从此处自然续写,不得重复上述内容
【🔴 上一章已完成剧情(禁止重复!)】
{previous_chapter_summary}
⚠️ 严重警告:
1. 上述"已完成剧情""衔接锚点"是**已经写过的**内容
2. 本章必须推进到**新的情节点**,绝对不能重新叙述已经发生的事件
3. 如果锚点是对话结束,请描写对话后的动作或场景转换,不要重复对话
4. 如果锚点是场景描写,请直接开始人物行动,不要重复描写环境
</continuation>
<characters priority="P1">
@@ -569,6 +576,11 @@ class PromptService:
{characters_info}
</characters>
<foreshadow_reminders priority="P1">
【🎯 伏笔提醒 - 需关注】
{foreshadow_reminders}
</foreshadow_reminders>
<memory priority="P2">
【相关记忆 - 参考】
{relevant_memories}
@@ -585,13 +597,20 @@ class PromptService:
✅ 自然承接上一章结尾,不重复已发生事件
✅ 保持角色性格、说话方式一致
✅ 字数控制在目标范围内
✅ 如有伏笔提醒,请在本章中适当埋入或回收相应伏笔
【🔴 反重复特别指令】
✅ 检查本章开篇是否与"衔接锚点"内容重复
✅ 检查本章情节是否与"上一章已完成剧情"重复
✅ 确保本章推进到了大纲中规划的新事件
【禁止事项】
❌ 输出章节标题、序号等元信息
❌ 使用"总之""综上所述"等AI常见总结语
❌ 在结尾处使用开放式反问
❌ 添加作者注释或创作说明
❌ 重复叙述上一章已发生的事件
❌ 重复叙述上一章已发生的事件(包括环境描写、心理活动)
❌ 在开篇使用"接上回""书接上文"等套话
</constraints>
<output>
@@ -783,7 +802,7 @@ class PromptService:
❌ 空泛的描述
</constraints>"""
# 情节分析提示词 V2(RTCO框架)
# 情节分析提示词 V2RTCO框架 + 伏笔ID追踪
PLOT_ANALYSIS = """<system>
你是专业的小说编辑和剧情分析师,擅长深度剖析章节内容。
</system>
@@ -791,6 +810,12 @@ class PromptService:
<task>
【分析任务】
全面分析第{chapter_number}章《{title}》的剧情要素、钩子、伏笔、冲突和角色发展。
【🔴 伏笔追踪任务(重要)】
系统已提供【已埋入伏笔列表】,当你识别到章节中有回收伏笔时:
1. 必须从列表中找出对应的伏笔ID
2. 在 foreshadows 数组中使用 reference_foreshadow_id 字段关联
3. 如果无法确定是哪个伏笔,reference_foreshadow_id 填 null
</task>
<chapter priority="P0">
@@ -803,6 +828,13 @@ class PromptService:
{content}
</chapter>
<existing_foreshadows priority="P1">
【已埋入伏笔列表 - 用于回收匹配】
以下是本项目中已埋入但尚未回收的伏笔,分析时如发现章节内容回收了某个伏笔,请使用对应的ID:
{existing_foreshadows}
</existing_foreshadows>
<analysis_framework priority="P0">
【分析维度】
@@ -820,12 +852,26 @@ class PromptService:
- 出现位置(开头/中段/结尾)
- **关键词**:【必填】从原文逐字复制8-25字的文本片段,用于精确定位
**2. 伏笔分析 (Foreshadowing)**
**2. 伏笔分析 (Foreshadowing) - 🔴 支持ID追踪**
- 埋下的新伏笔:内容、预期作用、隐藏程度(1-10)
- 回收的旧伏笔:呼应哪一章、回收效果
- 回收的旧伏笔:【必须】从已埋入伏笔列表中匹配ID
- 伏笔质量:巧妙性和合理性
- **关键词**:【必填】从原文逐字复制8-25字
每个伏笔需要:
- **title**:简洁标题(10-20字,概括伏笔核心)
- **content**:详细描述伏笔内容和预期作用
- **type**planted(埋下)或 resolved(回收)
- **strength**:强度1-10(对读者的吸引力)
- **subtlety**:隐藏度1-10(越高越隐蔽)
- **reference_chapter**:回收时引用的原埋入章节号,埋下时为null
- **reference_foreshadow_id**:【回收时必填】被回收伏笔的ID(从已埋入伏笔列表中选择),埋下时为null
- **keyword**:【必填】从原文逐字复制8-25字的定位文本
- **category**:分类(identity=身世/mystery=悬念/item=物品/relationship=关系/event=事件/ability=能力/prophecy=预言)
- **is_long_term**:是否长线伏笔(跨10章以上回收为true)
- **related_characters**:涉及的角色名列表
- **estimated_resolve_chapter**:预估回收章节号(埋下时预估,回收时为当前章节)
**3. 冲突分析 (Conflict)**
- 冲突类型:人与人/人与己/人与环境/人与社会
- 冲突各方及立场
@@ -921,12 +967,32 @@ class PromptService:
],
"foreshadows": [
{{
"content": "伏笔内容",
"title": "伏笔简洁标题",
"content": "伏笔详细内容和预期作用",
"type": "planted",
"strength": 7,
"subtlety": 8,
"reference_chapter": null,
"keyword": "从原文逐字复制的8-25字文本"
"reference_foreshadow_id": null,
"keyword": "从原文逐字复制的8-25字文本",
"category": "mystery",
"is_long_term": false,
"related_characters": ["角色A", "角色B"],
"estimated_resolve_chapter": 15
}},
{{
"title": "回收的伏笔标题",
"content": "伏笔如何被回收的描述",
"type": "resolved",
"strength": 8,
"subtlety": 6,
"reference_chapter": 5,
"reference_foreshadow_id": "abc123-已埋入伏笔的ID",
"keyword": "从原文逐字复制的8-25字文本",
"category": "mystery",
"is_long_term": false,
"related_characters": ["角色A"],
"estimated_resolve_chapter": 10
}}
],
"conflict": {{
@@ -998,6 +1064,7 @@ class PromptService:
✅ 逐字复制:keyword必须从原文复制,长度8-25字
✅ 精确定位:keyword能在原文中精确找到
✅ 职业变化可选:仅当章节明确描述时填写
✅ 【伏笔ID追踪】回收伏笔时,必须从【已埋入伏笔列表】中查找匹配的ID填入 reference_foreshadow_id
【评分约束 - 严格执行】
✅ 严格按评分标准打分,支持小数(如6.5、7.2、8.3)
@@ -2336,7 +2403,7 @@ class PromptService:
"description": "基于前置章节内容创作新章节(用于第2章及以后)",
"parameters": ["project_title", "genre", "chapter_number", "chapter_title", "chapter_outline",
"target_word_count", "narrative_perspective", "characters_info", "continuation_point",
"relevant_memories", "story_skeleton"]
"foreshadow_reminders", "relevant_memories", "story_skeleton", "previous_chapter_summary"]
},
"CHAPTER_REGENERATION_SYSTEM": {
"name": "章节重写系统提示",