refactor: 重构章节上下文构建系统，使用新的ChapterContextBuilder优化上下文生成
This commit is contained in:
xiamuceer
+92
-195
@@ -10,6 +10,7 @@ from datetime import datetime
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from asyncio import Queue, Lock
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from app.database import get_db
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from app.services.chapter_context_service import ChapterContextBuilder, FocusedMemoryRetriever
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from app.models.chapter import Chapter
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from app.models.project import Project
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from app.models.outline import Outline
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@@ -1314,86 +1315,23 @@ async def generate_chapter_content_stream(
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else:
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logger.info("未指定写作风格，使用原始提示词")
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# 🚀 使用智能上下文构建（支持海量章节）
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smart_context = await build_smart_chapter_context(
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db=db_session,
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project_id=project.id,
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current_chapter_number=current_chapter.chapter_number,
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user_id=current_user_id
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# 🚀 使用新的优化上下文构建器
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logger.info(f"🔧 使用优化的章节上下文构建器（V2）")
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context_builder = ChapterContextBuilder()
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chapter_context = await context_builder.build(
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chapter=current_chapter,
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project=project,
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outline=outline,
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user_id=current_user_id,
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db=db_session
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)
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# 组装上下文
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previous_content = ""
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if smart_context['story_skeleton']:
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previous_content += smart_context['story_skeleton'] + "\n\n"
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if smart_context['relevant_history']:
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previous_content += smart_context['relevant_history'] + "\n\n"
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if smart_context['recent_summary']:
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previous_content += smart_context['recent_summary'] + "\n\n"
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if smart_context['recent_full']:
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previous_content += smart_context['recent_full']
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# 🔧 修复1-n模式重复问题: 提取上一章结尾作为精确衔接点
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if current_chapter.chapter_number > 1:
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recent_chapters_parts = smart_context['recent_full'].split('===')
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if len(recent_chapters_parts) >= 2:
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# 提取最后一章(recent_full包含最近3章,最后一个是上一章)
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last_chapter_content = recent_chapters_parts[-1].strip()
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# 提取结尾500字
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last_chapter_ending = last_chapter_content[-600:] if len(last_chapter_content) > 600 else last_chapter_content
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previous_content += f"\n\n{'='*50}\n"
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previous_content += f"【⚠️ 上一章结尾内容(必读,用于衔接)】\n"
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previous_content += f"以下是上一章(第{current_chapter.chapter_number-1}章)的结尾部分:\n\n"
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previous_content += last_chapter_ending + "\n"
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previous_content += f"\n{'='*50}\n"
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previous_content += f"【本章({current_chapter.chapter_number}章)创作要求】\n"
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previous_content += f"1. 必须自然承接上述结尾的场景/情节/对话\n"
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previous_content += f"2. 不要重复叙述上一章已经发生的事件\n"
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previous_content += f"3. 从新的情节点、新的场景或新的时间点开始\n"
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previous_content += f"4. 角色状态要延续,不要重新介绍已出场角色\n"
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previous_content += f"{'='*50}\n"
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# 日志输出统计信息
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stats = smart_context['stats']
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logger.info(f"📊 智能上下文统计:")
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logger.info(f" - 前置章节总数: {stats.get('total_previous', 0)}")
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logger.info(f" - 故事骨架采样: {stats.get('skeleton_samples', 0)}章")
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logger.info(f" - 相关历史检索: {stats.get('relevant_history', 0)}章")
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logger.info(f" - 近期章节概要: {stats.get('recent_summaries', 0)}章")
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logger.info(f" - 最近完整内容: {stats.get('recent_full', 0)}章")
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logger.info(f" - 上下文总长度: {stats.get('total_length', 0)}字符")
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# 🧠 构建记忆增强上下文
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logger.info(f"🧠 开始构建记忆增强上下文...")
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memory_context = await memory_service.build_context_for_generation(
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user_id=current_user_id,
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project_id=project.id,
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current_chapter=current_chapter.chapter_number,
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chapter_outline=outline.content if outline else current_chapter.summary or "",
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character_names=[c.name for c in characters] if characters else None
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)
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# 计算各部分的字符长度
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context_lengths = {
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'recent_context': len(memory_context.get('recent_context', '')),
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'relevant_memories': len(memory_context.get('relevant_memories', '')),
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'foreshadows': len(memory_context.get('foreshadows', '')),
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'character_states': len(memory_context.get('character_states', '')),
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'plot_points': len(memory_context.get('plot_points', ''))
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}
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total_memory_length = sum(context_lengths.values())
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logger.info(f"✅ 记忆上下文构建完成: {memory_context['stats']}")
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logger.info(f"📏 记忆上下文长度统计:")
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logger.info(f" - 最近章节记忆: {context_lengths['recent_context']} 字符")
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logger.info(f" - 语义相关记忆: {context_lengths['relevant_memories']} 字符")
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logger.info(f" - 未完结伏笔: {context_lengths['foreshadows']} 字符")
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logger.info(f" - 角色状态记忆: {context_lengths['character_states']} 字符")
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logger.info(f" - 重要情节点: {context_lengths['plot_points']} 字符")
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logger.info(f" - 记忆总长度: {total_memory_length} 字符")
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logger.info(f" - 前置章节上下文长度: {len(previous_content)} 字符")
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logger.info(f" - 总上下文长度(估算): {total_memory_length + len(previous_content) + 2000} 字符")
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logger.info(f"📊 优化上下文统计:")
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logger.info(f" - 章节序号: {current_chapter.chapter_number}")
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logger.info(f" - 衔接锚点长度: {len(chapter_context.continuation_point or '')} 字符")
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logger.info(f" - 相关记忆: {chapter_context.context_stats.get('memory_count', 0)} 条")
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logger.info(f" - 总上下文长度: {chapter_context.context_stats.get('total_length', 0)} 字符")
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# 发送开始事件
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yield f"data: {json.dumps({'type': 'start', 'message': '开始AI创作...'}, ensure_ascii=False)}\n\n"
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@@ -1520,74 +1458,55 @@ async def generate_chapter_content_stream(
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chapter_outline_content = outline.content if outline else current_chapter.summary or '暂无大纲'
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logger.warning(f"⚠️ 一对多模式但无expansion_plan，使用大纲内容")
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# 根据是否有前置内容选择不同的提示词，并应用写作风格、记忆增强和MCP参考资料（支持自定义）
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if previous_content:
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template = await PromptService.get_template("CHAPTER_GENERATION_WITH_CONTEXT", current_user_id, db_session)
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# 🚀 使用 V2 优化模板构建提示词
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if chapter_context.continuation_point:
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# 有前置内容，使用 WITH_CONTEXT 模板
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template = await PromptService.get_template("CHAPTER_GENERATION_V2_WITH_CONTEXT", current_user_id, db_session)
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base_prompt = PromptService.format_prompt(
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template,
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title=project.title,
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theme=project.theme or '',
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genre=project.genre or '',
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narrative_perspective=chapter_perspective,
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time_period=project.world_time_period or '未设定',
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location=project.world_location or '未设定',
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atmosphere=project.world_atmosphere or '未设定',
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rules=project.world_rules or '未设定',
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characters_info=characters_info or '暂无角色信息',
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outlines_context=outlines_context,
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previous_content=previous_content,
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# P0 核心参数
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project_title=project.title,
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chapter_number=current_chapter.chapter_number,
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chapter_title=current_chapter.title,
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chapter_outline=chapter_outline_content,
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target_word_count=target_word_count,
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max_word_count=target_word_count + 1000,
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memory_context=memory_context.get('recent_context', '') + "\n" + memory_context.get('relevant_memories', '') + "\n" + memory_context.get('foreshadows', '') + "\n" + memory_context.get('character_states', '') + "\n" + memory_context.get('plot_points', '') if memory_context else "暂无相关记忆"
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continuation_point=chapter_context.continuation_point,
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# P1 重要参数
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genre=project.genre or '未设定',
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narrative_perspective=chapter_perspective,
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characters_info=characters_info or '暂无角色信息',
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# P2 参考参数（动态裁剪后的）
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story_skeleton=chapter_context.story_skeleton or '',
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relevant_memories=chapter_context.relevant_memories or ''
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)
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# 插入模式说明和MCP参考
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mode_instruction = "\n\n【创作模式说明】\n本章采用细纲模式：本章是大纲节点的细化展开之一。请严格遵循上述详细规划（expansion_plan）中的剧情点、角色焦点、情感基调和叙事目标，确保与整体规划保持一致，同时自然衔接前文内容。\n" if outline_mode == 'one-to-many' else "\n\n【创作模式说明】\n本章采用一对一模式：一个大纲节点对应一个章节。请在承接前文的基础上，充分展开大纲中的情节，保持叙事的完整性。\n"
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mcp_text = ""
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if mcp_reference_materials:
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mcp_text = "\n【📚 MCP工具搜索 - 参考资料】\n以下是通过MCP工具搜索到的相关参考资料，可用于丰富情节和细节：\n\n" + mcp_reference_materials + "\n"
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base_prompt = base_prompt.replace("本章信息：", mcp_text + mode_instruction + "\n本章信息：")
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# 应用写作风格
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if style_content:
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prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
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else:
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prompt = base_prompt
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else:
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template = await PromptService.get_template("CHAPTER_GENERATION", current_user_id, db_session)
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# 第一章，使用无前置内容模板
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template = await PromptService.get_template("CHAPTER_GENERATION_V2", current_user_id, db_session)
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base_prompt = PromptService.format_prompt(
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template,
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title=project.title,
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theme=project.theme or '',
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genre=project.genre or '',
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narrative_perspective=chapter_perspective,
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time_period=project.world_time_period or '未设定',
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location=project.world_location or '未设定',
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atmosphere=project.world_atmosphere or '未设定',
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rules=project.world_rules or '未设定',
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characters_info=characters_info or '暂无角色信息',
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outlines_context=outlines_context,
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# P0 核心参数
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project_title=project.title,
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chapter_number=current_chapter.chapter_number,
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chapter_title=current_chapter.title,
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chapter_outline=chapter_outline_content,
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target_word_count=target_word_count,
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max_word_count=target_word_count + 1000
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# P1 重要参数
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genre=project.genre or '未设定',
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narrative_perspective=chapter_perspective,
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characters_info=characters_info or '暂无角色信息'
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)
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# 插入模式说明和记忆、MCP参考
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mode_instruction = "\n\n【创作模式说明】\n本章采用细纲模式：本章是大纲节点的细化展开之一。请严格遵循上述详细规划中的剧情点、角色焦点和情感基调，确保与整体规划保持一致。\n" if outline_mode == 'one-to-many' else "\n\n【创作模式说明】\n本章采用一对一模式：一个大纲节点对应一个章节。请充分展开大纲中的情节，注重叙事的完整性和丰满度。\n"
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memory_text = ""
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if memory_context:
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memory_text = "\n【🧠 智能记忆系统 - 重要参考】\n" + memory_context.get('recent_context', '') + "\n" + memory_context.get('relevant_memories', '') + "\n" + memory_context.get('foreshadows', '') + "\n" + memory_context.get('character_states', '') + "\n" + memory_context.get('plot_points', '')
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mcp_text = ""
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if mcp_reference_materials:
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mcp_text = "\n【📚 MCP工具搜索 - 参考资料】\n以下是通过MCP工具搜索到的相关参考资料，可用于丰富情节和细节：\n\n" + mcp_reference_materials + "\n"
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base_prompt = base_prompt.replace("本章信息：", memory_text + mcp_text + mode_instruction + "\n\n本章信息：")
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# 应用写作风格
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if style_content:
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prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
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else:
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prompt = base_prompt
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# 添加 MCP 参考资料（如果有）
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if mcp_reference_materials:
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mcp_section = f"\n\n<mcp_reference>\n{mcp_reference_materials}\n</mcp_reference>"
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base_prompt = base_prompt.replace("</task>", f"{mcp_section}\n</task>")
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logger.info(f"📖 已整合MCP参考资料（{len(mcp_reference_materials)}字符）")
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# 应用写作风格
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if style_content:
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prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
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else:
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prompt = base_prompt
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if mcp_reference_materials:
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logger.info(f"📖 已整合MCP参考资料（{len(mcp_reference_materials)}字符）到章节生成提示词")
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@@ -2774,34 +2693,24 @@ async def generate_single_chapter_for_batch(
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if style.user_id is None or style.user_id == user_id:
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style_content = style.prompt_content or ""
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# 构建智能上下文
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smart_context = await build_smart_chapter_context(
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db=db_session,
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project_id=project.id,
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current_chapter_number=chapter.chapter_number,
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user_id=user_id
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)
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# 组装上下文
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previous_content = ""
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if smart_context['story_skeleton']:
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previous_content += smart_context['story_skeleton'] + "\n\n"
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if smart_context['relevant_history']:
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previous_content += smart_context['relevant_history'] + "\n\n"
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if smart_context['recent_summary']:
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previous_content += smart_context['recent_summary'] + "\n\n"
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if smart_context['recent_full']:
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previous_content += smart_context['recent_full']
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# 构建记忆增强上下文
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memory_context = await memory_service.build_context_for_generation(
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# 🚀 使用新的优化上下文构建器
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logger.info(f"🔧 批量生成 - 使用优化的章节上下文构建器（V2）")
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context_builder = ChapterContextBuilder()
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chapter_context = await context_builder.build(
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chapter=chapter,
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project=project,
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outline=outline,
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user_id=user_id,
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project_id=project.id,
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current_chapter=chapter.chapter_number,
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chapter_outline=outline.content if outline else chapter.summary or "",
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character_names=[c.name for c in characters] if characters else None
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db=db_session
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)
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# 日志输出统计信息
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logger.info(f"📊 批量生成 - 优化上下文统计:")
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logger.info(f" - 章节序号: {chapter.chapter_number}")
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logger.info(f" - 衔接锚点长度: {len(chapter_context.continuation_point or '')} 字符")
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logger.info(f" - 相关记忆: {chapter_context.context_stats.get('memory_count', 0)} 条")
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logger.info(f" - 总上下文长度: {chapter_context.context_stats.get('total_length', 0)} 字符")
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# 📋 根据大纲模式构建差异化的章节大纲上下文
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chapter_outline_content = ""
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if outline_mode == 'one-to-one':
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@@ -2844,61 +2753,49 @@ async def generate_single_chapter_for_batch(
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chapter_outline_content = outline.content if outline else chapter.summary or '暂无大纲'
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logger.warning(f"⚠️ 批量生成 - 一对多模式但无expansion_plan，使用大纲内容")
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# 生成提示词（支持自定义）
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if previous_content:
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# 获取自定义提示词模板
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template = await PromptService.get_template("CHAPTER_GENERATION_WITH_CONTEXT", user_id, db_session)
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# 🚀 使用 V2 优化模板构建提示词（批量生成）
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if chapter_context.continuation_point:
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# 有前置内容，使用 WITH_CONTEXT 模板
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template = await PromptService.get_template("CHAPTER_GENERATION_V2_WITH_CONTEXT", user_id, db_session)
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base_prompt = PromptService.format_prompt(
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template,
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title=project.title,
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theme=project.theme or '',
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genre=project.genre or '',
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narrative_perspective=project.narrative_perspective or '第三人称',
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time_period=project.world_time_period or '未设定',
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location=project.world_location or '未设定',
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atmosphere=project.world_atmosphere or '未设定',
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rules=project.world_rules or '未设定',
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characters_info=characters_info or '暂无角色信息',
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outlines_context=outlines_context,
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previous_content=previous_content,
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# P0 核心参数
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project_title=project.title,
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chapter_number=chapter.chapter_number,
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chapter_title=chapter.title,
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chapter_outline=chapter_outline_content,
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target_word_count=target_word_count,
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max_word_count=target_word_count + 1000,
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memory_context=memory_context.get('recent_context', '') + "\n" + memory_context.get('relevant_memories', '') + "\n" + memory_context.get('foreshadows', '') + "\n" + memory_context.get('character_states', '') + "\n" + memory_context.get('plot_points', '') if memory_context else "暂无相关记忆"
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continuation_point=chapter_context.continuation_point,
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# P1 重要参数
|
||||
genre=project.genre or '未设定',
|
||||
narrative_perspective=project.narrative_perspective or '第三人称',
|
||||
characters_info=characters_info or '暂无角色信息',
|
||||
# P2 参考参数（动态裁剪后的）
|
||||
story_skeleton=chapter_context.story_skeleton or '',
|
||||
relevant_memories=chapter_context.relevant_memories or ''
|
||||
)
|
||||
# 应用写作风格
|
||||
if style_content:
|
||||
prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
|
||||
else:
|
||||
prompt = base_prompt
|
||||
else:
|
||||
# 获取自定义提示词模板
|
||||
template = await PromptService.get_template("CHAPTER_GENERATION", user_id, db_session)
|
||||
# 第一章，使用无前置内容模板
|
||||
template = await PromptService.get_template("CHAPTER_GENERATION_V2", user_id, db_session)
|
||||
base_prompt = PromptService.format_prompt(
|
||||
template,
|
||||
title=project.title,
|
||||
theme=project.theme or '',
|
||||
genre=project.genre or '',
|
||||
narrative_perspective=project.narrative_perspective or '第三人称',
|
||||
time_period=project.world_time_period or '未设定',
|
||||
location=project.world_location or '未设定',
|
||||
atmosphere=project.world_atmosphere or '未设定',
|
||||
rules=project.world_rules or '未设定',
|
||||
characters_info=characters_info or '暂无角色信息',
|
||||
outlines_context=outlines_context,
|
||||
# P0 核心参数
|
||||
project_title=project.title,
|
||||
chapter_number=chapter.chapter_number,
|
||||
chapter_title=chapter.title,
|
||||
chapter_outline=chapter_outline_content,
|
||||
target_word_count=target_word_count,
|
||||
max_word_count=target_word_count + 1000
|
||||
# P1 重要参数
|
||||
genre=project.genre or '未设定',
|
||||
narrative_perspective=project.narrative_perspective or '第三人称',
|
||||
characters_info=characters_info or '暂无角色信息'
|
||||
)
|
||||
# 应用写作风格
|
||||
if style_content:
|
||||
prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
|
||||
else:
|
||||
prompt = base_prompt
|
||||
|
||||
# 应用写作风格
|
||||
if style_content:
|
||||
prompt = WritingStyleManager.apply_style_to_prompt(base_prompt, style_content)
|
||||
else:
|
||||
prompt = base_prompt
|
||||
|
||||
# 🎨 方案一：将写作风格注入到系统提示词（批量生成）
|
||||
system_prompt_with_style = None
|
||||
|
||||
Reference in New Issue
Block a user