xiamuceer
1236 lines
50 KiB
Python
1236 lines
50 KiB
Python
"""章节管理API"""
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from fastapi import APIRouter, Depends, HTTPException, Request, Query, BackgroundTasks
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from fastapi.responses import StreamingResponse
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, func
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import json
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import asyncio
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from typing import Optional
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from datetime import datetime
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from app.database import get_db
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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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from app.models.character import Character
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from app.models.generation_history import GenerationHistory
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from app.models.writing_style import WritingStyle
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from app.models.analysis_task import AnalysisTask
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from app.models.memory import PlotAnalysis, StoryMemory
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from app.schemas.chapter import (
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ChapterCreate,
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ChapterUpdate,
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ChapterResponse,
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ChapterListResponse,
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ChapterGenerateRequest
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)
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from app.services.ai_service import AIService
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from app.services.prompt_service import prompt_service
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from app.services.plot_analyzer import PlotAnalyzer
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from app.services.memory_service import memory_service
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from app.logger import get_logger
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from app.api.settings import get_user_ai_service
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router = APIRouter(prefix="/chapters", tags=["章节管理"])
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logger = get_logger(__name__)
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@router.post("", response_model=ChapterResponse, summary="创建章节")
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async def create_chapter(
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chapter: ChapterCreate,
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db: AsyncSession = Depends(get_db)
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):
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"""创建新的章节"""
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# 验证项目是否存在
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result = await db.execute(
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select(Project).where(Project.id == chapter.project_id)
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)
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project = result.scalar_one_or_none()
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if not project:
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raise HTTPException(status_code=404, detail="项目不存在")
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# 计算字数
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word_count = len(chapter.content)
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db_chapter = Chapter(
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**chapter.model_dump(),
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word_count=word_count
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)
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db.add(db_chapter)
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# 更新项目的当前字数
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project.current_words = project.current_words + word_count
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await db.commit()
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await db.refresh(db_chapter)
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return db_chapter
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@router.get("/project/{project_id}", response_model=ChapterListResponse, summary="获取项目的所有章节")
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async def get_project_chapters(
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project_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""获取指定项目的所有章节（路径参数版本）"""
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# 获取总数
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count_result = await db.execute(
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select(func.count(Chapter.id)).where(Chapter.project_id == project_id)
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)
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total = count_result.scalar_one()
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# 获取章节列表
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result = await db.execute(
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select(Chapter)
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.where(Chapter.project_id == project_id)
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.order_by(Chapter.chapter_number)
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)
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chapters = result.scalars().all()
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return ChapterListResponse(total=total, items=chapters)
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@router.get("/{chapter_id}", response_model=ChapterResponse, summary="获取章节详情")
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async def get_chapter(
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chapter_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""根据ID获取章节详情"""
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result = await db.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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chapter = result.scalar_one_or_none()
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if not chapter:
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raise HTTPException(status_code=404, detail="章节不存在")
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return chapter
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@router.get("/{chapter_id}/navigation", summary="获取章节导航信息")
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async def get_chapter_navigation(
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chapter_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""
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获取章节的导航信息（上一章/下一章）
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用于章节阅读器的翻页功能
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"""
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# 获取当前章节
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result = await db.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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current_chapter = result.scalar_one_or_none()
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if not current_chapter:
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raise HTTPException(status_code=404, detail="章节不存在")
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# 获取上一章
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prev_result = await db.execute(
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select(Chapter)
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.where(Chapter.project_id == current_chapter.project_id)
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.where(Chapter.chapter_number < current_chapter.chapter_number)
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.order_by(Chapter.chapter_number.desc())
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.limit(1)
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)
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prev_chapter = prev_result.scalar_one_or_none()
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# 获取下一章
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next_result = await db.execute(
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select(Chapter)
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.where(Chapter.project_id == current_chapter.project_id)
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.where(Chapter.chapter_number > current_chapter.chapter_number)
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.order_by(Chapter.chapter_number.asc())
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.limit(1)
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)
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next_chapter = next_result.scalar_one_or_none()
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return {
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"current": {
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"id": current_chapter.id,
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"chapter_number": current_chapter.chapter_number,
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"title": current_chapter.title
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},
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"previous": {
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"id": prev_chapter.id,
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"chapter_number": prev_chapter.chapter_number,
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"title": prev_chapter.title
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} if prev_chapter else None,
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"next": {
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"id": next_chapter.id,
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"chapter_number": next_chapter.chapter_number,
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"title": next_chapter.title
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} if next_chapter else None
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}
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@router.put("/{chapter_id}", response_model=ChapterResponse, summary="更新章节")
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async def update_chapter(
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chapter_id: str,
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chapter_update: ChapterUpdate,
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db: AsyncSession = Depends(get_db)
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):
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"""更新章节信息"""
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result = await db.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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chapter = result.scalar_one_or_none()
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if not chapter:
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raise HTTPException(status_code=404, detail="章节不存在")
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# 记录旧字数
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old_word_count = chapter.word_count or 0
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# 更新字段
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update_data = chapter_update.model_dump(exclude_unset=True)
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for field, value in update_data.items():
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setattr(chapter, field, value)
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# 如果内容更新了，重新计算字数
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if "content" in update_data and chapter.content:
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new_word_count = len(chapter.content)
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chapter.word_count = new_word_count
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# 更新项目字数
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result = await db.execute(
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select(Project).where(Project.id == chapter.project_id)
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)
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project = result.scalar_one_or_none()
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if project:
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project.current_words = project.current_words - old_word_count + new_word_count
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await db.commit()
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await db.refresh(chapter)
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return chapter
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@router.delete("/{chapter_id}", summary="删除章节")
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async def delete_chapter(
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chapter_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""删除章节"""
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result = await db.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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chapter = result.scalar_one_or_none()
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if not chapter:
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raise HTTPException(status_code=404, detail="章节不存在")
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# 更新项目字数
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result = await db.execute(
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select(Project).where(Project.id == chapter.project_id)
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)
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project = result.scalar_one_or_none()
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if project:
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project.current_words = max(0, project.current_words - chapter.word_count)
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await db.delete(chapter)
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await db.commit()
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return {"message": "章节删除成功"}
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async def check_prerequisites(db: AsyncSession, chapter: Chapter) -> tuple[bool, str, list[Chapter]]:
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"""
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检查章节前置条件
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Args:
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db: 数据库会话
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chapter: 当前章节
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Returns:
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(可否生成, 错误信息, 前置章节列表)
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"""
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# 如果是第一章，无需检查前置
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if chapter.chapter_number == 1:
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return True, "", []
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# 查询所有前置章节（序号小于当前章节的）
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result = await db.execute(
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select(Chapter)
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.where(Chapter.project_id == chapter.project_id)
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.where(Chapter.chapter_number < chapter.chapter_number)
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.order_by(Chapter.chapter_number)
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)
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previous_chapters = result.scalars().all()
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# 检查是否所有前置章节都有内容
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incomplete_chapters = [
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ch for ch in previous_chapters
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if not ch.content or ch.content.strip() == ""
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]
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if incomplete_chapters:
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missing_numbers = [str(ch.chapter_number) for ch in incomplete_chapters]
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error_msg = f"需要先完成前置章节：第 {', '.join(missing_numbers)} 章"
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return False, error_msg, previous_chapters
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return True, "", previous_chapters
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@router.get("/{chapter_id}/can-generate", summary="检查章节是否可以生成")
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async def check_can_generate(
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chapter_id: str,
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db: AsyncSession = Depends(get_db)
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):
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"""
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检查章节是否满足生成条件
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返回可生成状态和前置章节信息
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"""
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# 获取章节
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result = await db.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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chapter = result.scalar_one_or_none()
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if not chapter:
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raise HTTPException(status_code=404, detail="章节不存在")
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# 检查前置条件
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can_generate, error_msg, previous_chapters = await check_prerequisites(db, chapter)
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# 构建前置章节信息
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previous_info = [
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{
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"id": ch.id,
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"chapter_number": ch.chapter_number,
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"title": ch.title,
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"has_content": bool(ch.content and ch.content.strip()),
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"word_count": ch.word_count or 0
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}
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for ch in previous_chapters
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]
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return {
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"can_generate": can_generate,
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"reason": error_msg if not can_generate else "",
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"previous_chapters": previous_info,
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"chapter_number": chapter.chapter_number
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}
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async def analyze_chapter_background(
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chapter_id: str,
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user_id: str,
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project_id: str,
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task_id: str,
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ai_service: AIService
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):
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"""
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后台异步分析章节
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Args:
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chapter_id: 章节ID
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user_id: 用户ID
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project_id: 项目ID
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task_id: 任务ID
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ai_service: AI服务实例
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"""
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db_session = None
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try:
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logger.info(f"🔍 开始后台分析章节: {chapter_id}")
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# 等待一小段时间，确保主会话的commit已经持久化到磁盘
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await asyncio.sleep(0.1)
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# 创建独立数据库会话
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from app.database import get_engine
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from sqlalchemy.ext.asyncio import async_sessionmaker, AsyncSession
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engine = await get_engine(user_id)
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AsyncSessionLocal = async_sessionmaker(
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engine,
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class_=AsyncSession,
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expire_on_commit=False
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)
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db_session = AsyncSessionLocal()
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# 1. 获取任务（添加重试逻辑）
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task = None
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for retry in range(3):
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task_result = await db_session.execute(
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select(AnalysisTask).where(AnalysisTask.id == task_id)
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)
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task = task_result.scalar_one_or_none()
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if task:
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break
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if retry < 2:
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logger.warning(f"⚠️ 第{retry+1}次未找到任务 {task_id}，等待后重试...")
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await asyncio.sleep(0.2)
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if not task:
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logger.error(f"❌ 任务不存在: {task_id}")
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return
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task.status = 'running'
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task.started_at = datetime.now()
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task.progress = 10
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await db_session.commit()
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# 2. 获取章节信息
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chapter_result = await db_session.execute(
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select(Chapter).where(Chapter.id == chapter_id)
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)
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chapter = chapter_result.scalar_one_or_none()
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if not chapter or not chapter.content:
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task.status = 'failed'
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task.error_message = '章节不存在或内容为空'
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task.completed_at = datetime.now()
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await db_session.commit()
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logger.error(f"❌ 章节不存在或内容为空: {chapter_id}")
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return
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task.progress = 20
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await db_session.commit()
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# 3. 使用PlotAnalyzer分析章节
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analyzer = PlotAnalyzer(ai_service)
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analysis_result = await analyzer.analyze_chapter(
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chapter_number=chapter.chapter_number,
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title=chapter.title,
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content=chapter.content,
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word_count=chapter.word_count or len(chapter.content)
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)
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if not analysis_result:
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task.status = 'failed'
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task.error_message = 'AI分析失败，请检查日志'
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task.completed_at = datetime.now()
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await db_session.commit()
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logger.error(f"❌ AI分析失败: {chapter_id}")
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return
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task.progress = 60
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await db_session.commit()
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# 4. 保存分析结果到数据库（先检查是否已存在）
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existing_analysis_result = await db_session.execute(
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select(PlotAnalysis).where(PlotAnalysis.chapter_id == chapter_id)
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)
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existing_analysis = existing_analysis_result.scalar_one_or_none()
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if existing_analysis:
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# 更新现有记录
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logger.info(f" 更新现有分析记录: {existing_analysis.id}")
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existing_analysis.plot_stage = analysis_result.get('plot_stage', '发展')
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existing_analysis.conflict_level = analysis_result.get('conflict', {}).get('level', 0)
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existing_analysis.conflict_types = analysis_result.get('conflict', {}).get('types', [])
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||
existing_analysis.emotional_tone = analysis_result.get('emotional_arc', {}).get('primary_emotion', '')
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existing_analysis.emotional_intensity = analysis_result.get('emotional_arc', {}).get('intensity', 0) / 10.0
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existing_analysis.hooks = analysis_result.get('hooks', [])
|
||
existing_analysis.hooks_count = len(analysis_result.get('hooks', []))
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existing_analysis.foreshadows = analysis_result.get('foreshadows', [])
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||
existing_analysis.foreshadows_planted = sum(1 for f in analysis_result.get('foreshadows', []) if f.get('type') == 'planted')
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existing_analysis.foreshadows_resolved = sum(1 for f in analysis_result.get('foreshadows', []) if f.get('type') == 'resolved')
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||
existing_analysis.plot_points = analysis_result.get('plot_points', [])
|
||
existing_analysis.plot_points_count = len(analysis_result.get('plot_points', []))
|
||
existing_analysis.character_states = analysis_result.get('character_states', [])
|
||
existing_analysis.scenes = analysis_result.get('scenes', [])
|
||
existing_analysis.pacing = analysis_result.get('pacing', 'moderate')
|
||
existing_analysis.overall_quality_score = analysis_result.get('scores', {}).get('overall', 0)
|
||
existing_analysis.pacing_score = analysis_result.get('scores', {}).get('pacing', 0)
|
||
existing_analysis.engagement_score = analysis_result.get('scores', {}).get('engagement', 0)
|
||
existing_analysis.coherence_score = analysis_result.get('scores', {}).get('coherence', 0)
|
||
existing_analysis.analysis_report = analyzer.generate_analysis_summary(analysis_result)
|
||
existing_analysis.suggestions = analysis_result.get('suggestions', [])
|
||
existing_analysis.dialogue_ratio = analysis_result.get('dialogue_ratio', 0)
|
||
existing_analysis.description_ratio = analysis_result.get('description_ratio', 0)
|
||
else:
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||
# 创建新记录
|
||
logger.info(f" 创建新的分析记录")
|
||
plot_analysis = PlotAnalysis(
|
||
chapter_id=chapter_id,
|
||
project_id=project_id,
|
||
plot_stage=analysis_result.get('plot_stage', '发展'),
|
||
conflict_level=analysis_result.get('conflict', {}).get('level', 0),
|
||
conflict_types=analysis_result.get('conflict', {}).get('types', []),
|
||
emotional_tone=analysis_result.get('emotional_arc', {}).get('primary_emotion', ''),
|
||
emotional_intensity=analysis_result.get('emotional_arc', {}).get('intensity', 0) / 10.0,
|
||
hooks=analysis_result.get('hooks', []),
|
||
hooks_count=len(analysis_result.get('hooks', [])),
|
||
foreshadows=analysis_result.get('foreshadows', []),
|
||
foreshadows_planted=sum(1 for f in analysis_result.get('foreshadows', []) if f.get('type') == 'planted'),
|
||
foreshadows_resolved=sum(1 for f in analysis_result.get('foreshadows', []) if f.get('type') == 'resolved'),
|
||
plot_points=analysis_result.get('plot_points', []),
|
||
plot_points_count=len(analysis_result.get('plot_points', [])),
|
||
character_states=analysis_result.get('character_states', []),
|
||
scenes=analysis_result.get('scenes', []),
|
||
pacing=analysis_result.get('pacing', 'moderate'),
|
||
overall_quality_score=analysis_result.get('scores', {}).get('overall', 0),
|
||
pacing_score=analysis_result.get('scores', {}).get('pacing', 0),
|
||
engagement_score=analysis_result.get('scores', {}).get('engagement', 0),
|
||
coherence_score=analysis_result.get('scores', {}).get('coherence', 0),
|
||
analysis_report=analyzer.generate_analysis_summary(analysis_result),
|
||
suggestions=analysis_result.get('suggestions', []),
|
||
dialogue_ratio=analysis_result.get('dialogue_ratio', 0),
|
||
description_ratio=analysis_result.get('description_ratio', 0)
|
||
)
|
||
db_session.add(plot_analysis)
|
||
|
||
await db_session.commit()
|
||
|
||
task.progress = 80
|
||
await db_session.commit()
|
||
|
||
# 5. 提取记忆并保存到向量数据库（传入章节内容用于计算位置）
|
||
memories = analyzer.extract_memories_from_analysis(
|
||
analysis=analysis_result,
|
||
chapter_id=chapter_id,
|
||
chapter_number=chapter.chapter_number,
|
||
chapter_content=chapter.content or ""
|
||
)
|
||
|
||
# 先删除该章节的旧记忆（支持重新分析）
|
||
old_memories_result = await db_session.execute(
|
||
select(StoryMemory).where(StoryMemory.chapter_id == chapter_id)
|
||
)
|
||
old_memories = old_memories_result.scalars().all()
|
||
for old_mem in old_memories:
|
||
await db_session.delete(old_mem)
|
||
logger.info(f" 删除旧记忆: {len(old_memories)}条")
|
||
|
||
# 准备批量添加的记忆数据
|
||
memory_records = []
|
||
for mem in memories:
|
||
memory_id = f"{chapter_id}_{mem['type']}_{len(memory_records)}"
|
||
memory_records.append({
|
||
'id': memory_id,
|
||
'content': mem['content'],
|
||
'type': mem['type'],
|
||
'metadata': mem['metadata']
|
||
})
|
||
|
||
# 从metadata中提取位置信息
|
||
text_position = mem['metadata'].get('text_position', -1)
|
||
text_length = mem['metadata'].get('text_length', 0)
|
||
|
||
# 同时保存到关系数据库
|
||
story_memory = StoryMemory(
|
||
id=memory_id,
|
||
project_id=project_id,
|
||
chapter_id=chapter_id,
|
||
memory_type=mem['type'],
|
||
content=mem['content'],
|
||
title=mem['title'],
|
||
importance_score=mem['metadata'].get('importance_score', 0.5),
|
||
tags=mem['metadata'].get('tags', []),
|
||
is_foreshadow=mem['metadata'].get('is_foreshadow', 0),
|
||
story_timeline=chapter.chapter_number, # 使用章节序号作为时间线
|
||
chapter_position=text_position, # 保存文本位置
|
||
text_length=text_length, # 保存文本长度
|
||
related_characters=mem['metadata'].get('related_characters', []),
|
||
related_locations=mem['metadata'].get('related_locations', [])
|
||
)
|
||
db_session.add(story_memory)
|
||
|
||
# 记录日志便于调试
|
||
if text_position >= 0:
|
||
logger.debug(f" 保存记忆 {memory_id}: position={text_position}, length={text_length}")
|
||
|
||
await db_session.commit()
|
||
|
||
# 批量添加到向量数据库
|
||
if memory_records:
|
||
added_count = await memory_service.batch_add_memories(
|
||
user_id=user_id,
|
||
project_id=project_id,
|
||
memories=memory_records
|
||
)
|
||
logger.info(f"✅ 添加{added_count}条记忆到向量库")
|
||
|
||
task.progress = 100
|
||
task.status = 'completed'
|
||
task.completed_at = datetime.now()
|
||
await db_session.commit()
|
||
|
||
logger.info(f"✅ 章节分析完成: {chapter_id}, 提取{len(memories)}条记忆")
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 后台分析异常: {str(e)}", exc_info=True)
|
||
# 确保任务状态被更新为failed，避免前端一直轮询
|
||
if db_session:
|
||
try:
|
||
# 重新获取任务以确保有最新状态
|
||
task_result = await db_session.execute(
|
||
select(AnalysisTask).where(AnalysisTask.id == task_id)
|
||
)
|
||
task = task_result.scalar_one_or_none()
|
||
if task:
|
||
task.status = 'failed'
|
||
task.error_message = str(e)[:500]
|
||
task.completed_at = datetime.now()
|
||
task.progress = 0 # 重置进度
|
||
await db_session.commit()
|
||
logger.info(f"✅ 任务状态已更新为failed: {task_id}")
|
||
else:
|
||
logger.error(f"❌ 无法找到任务进行状态更新: {task_id}")
|
||
except Exception as update_error:
|
||
logger.error(f"❌ 更新任务状态失败: {str(update_error)}")
|
||
finally:
|
||
if db_session:
|
||
await db_session.close()
|
||
|
||
|
||
@router.post("/{chapter_id}/generate-stream", summary="AI创作章节内容（流式）")
|
||
async def generate_chapter_content_stream(
|
||
chapter_id: str,
|
||
request: Request,
|
||
background_tasks: BackgroundTasks,
|
||
generate_request: ChapterGenerateRequest = ChapterGenerateRequest(),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
根据大纲、前置章节内容和项目信息AI创作章节完整内容（流式返回）
|
||
要求：必须按顺序生成，确保前置章节都已完成
|
||
|
||
请求体参数：
|
||
- style_id: 可选，指定使用的写作风格ID。不提供则不使用任何风格
|
||
- target_word_count: 可选，目标字数，默认3000字，范围500-10000字
|
||
|
||
注意：此函数不使用依赖注入的db，而是在生成器内部创建独立的数据库会话
|
||
以避免流式响应期间的连接泄漏问题
|
||
"""
|
||
style_id = generate_request.style_id
|
||
target_word_count = generate_request.target_word_count or 3000
|
||
# 预先验证章节存在性（使用临时会话）
|
||
async for temp_db in get_db(request):
|
||
try:
|
||
result = await temp_db.execute(
|
||
select(Chapter).where(Chapter.id == chapter_id)
|
||
)
|
||
chapter = result.scalar_one_or_none()
|
||
if not chapter:
|
||
raise HTTPException(status_code=404, detail="章节不存在")
|
||
|
||
# 检查前置条件
|
||
can_generate, error_msg, previous_chapters = await check_prerequisites(temp_db, chapter)
|
||
if not can_generate:
|
||
raise HTTPException(status_code=400, detail=error_msg)
|
||
|
||
# 保存前置章节数据供生成器使用
|
||
previous_chapters_data = [
|
||
{
|
||
'id': ch.id,
|
||
'chapter_number': ch.chapter_number,
|
||
'title': ch.title,
|
||
'content': ch.content
|
||
}
|
||
for ch in previous_chapters
|
||
]
|
||
finally:
|
||
await temp_db.close()
|
||
break
|
||
|
||
async def event_generator():
|
||
# 在生成器内部创建独立的数据库会话
|
||
db_session = None
|
||
db_committed = False
|
||
# 获取当前用户ID（在生成器外部就需要）
|
||
current_user_id = getattr(request.state, "user_id", "system")
|
||
|
||
try:
|
||
# 创建新的数据库会话
|
||
async for db_session in get_db(request):
|
||
# 重新获取章节信息
|
||
chapter_result = await db_session.execute(
|
||
select(Chapter).where(Chapter.id == chapter_id)
|
||
)
|
||
current_chapter = chapter_result.scalar_one_or_none()
|
||
if not current_chapter:
|
||
yield f"data: {json.dumps({'type': 'error', 'error': '章节不存在'}, ensure_ascii=False)}\n\n"
|
||
return
|
||
|
||
# 获取项目信息
|
||
project_result = await db_session.execute(
|
||
select(Project).where(Project.id == current_chapter.project_id)
|
||
)
|
||
project = project_result.scalar_one_or_none()
|
||
if not project:
|
||
yield f"data: {json.dumps({'type': 'error', 'error': '项目不存在'}, ensure_ascii=False)}\n\n"
|
||
return
|
||
|
||
# 获取对应的大纲
|
||
outline_result = await db_session.execute(
|
||
select(Outline)
|
||
.where(Outline.project_id == current_chapter.project_id)
|
||
.where(Outline.order_index == current_chapter.chapter_number)
|
||
.execution_options(populate_existing=True)
|
||
)
|
||
outline = outline_result.scalar_one_or_none()
|
||
|
||
# 获取所有大纲用于上下文
|
||
all_outlines_result = await db_session.execute(
|
||
select(Outline)
|
||
.where(Outline.project_id == current_chapter.project_id)
|
||
.order_by(Outline.order_index)
|
||
.execution_options(populate_existing=True)
|
||
)
|
||
all_outlines = all_outlines_result.scalars().all()
|
||
outlines_context = "\n".join([
|
||
f"第{o.order_index}章 {o.title}: {o.content[:100]}..."
|
||
for o in all_outlines
|
||
])
|
||
|
||
# 获取角色信息
|
||
characters_result = await db_session.execute(
|
||
select(Character).where(Character.project_id == current_chapter.project_id)
|
||
)
|
||
characters = characters_result.scalars().all()
|
||
characters_info = "\n".join([
|
||
f"- {c.name}({'组织' if c.is_organization else '角色'}, {c.role_type}): {c.personality[:100] if c.personality else ''}"
|
||
for c in characters
|
||
])
|
||
|
||
# 获取写作风格
|
||
style_content = ""
|
||
if style_id:
|
||
# 使用指定的风格
|
||
style_result = await db_session.execute(
|
||
select(WritingStyle).where(WritingStyle.id == style_id)
|
||
)
|
||
style = style_result.scalar_one_or_none()
|
||
if style:
|
||
# 验证风格是否可用：全局预设风格（project_id为NULL）或者当前项目的自定义风格
|
||
if style.project_id is None or style.project_id == current_chapter.project_id:
|
||
style_content = style.prompt_content or ""
|
||
style_type = "全局预设" if style.project_id is None else "项目自定义"
|
||
logger.info(f"使用指定风格: {style.name} ({style_type})")
|
||
else:
|
||
logger.warning(f"风格 {style_id} 不属于当前项目，无法使用")
|
||
else:
|
||
logger.warning(f"未找到风格 {style_id}")
|
||
else:
|
||
logger.info("未指定写作风格，使用原始提示词")
|
||
|
||
# 构建前置章节内容上下文（使用之前保存的数据）
|
||
previous_content = ""
|
||
if previous_chapters_data:
|
||
recent_chapters = previous_chapters_data[-3:] if len(previous_chapters_data) > 3 else previous_chapters_data
|
||
early_chapters = previous_chapters_data[:-3] if len(previous_chapters_data) > 3 else []
|
||
|
||
if early_chapters:
|
||
early_summary = "【前期剧情概要】\n" + "\n".join([
|
||
f"第{ch['chapter_number']}章《{ch['title']}》：{ch['content'][:200] if ch['content'] else ''}..."
|
||
for ch in early_chapters
|
||
])
|
||
previous_content += early_summary + "\n\n"
|
||
|
||
if recent_chapters:
|
||
recent_content = "【最近章节完整内容】\n" + "\n\n".join([
|
||
f"=== 第{ch['chapter_number']}章：{ch['title']} ===\n{ch['content']}"
|
||
for ch in recent_chapters
|
||
])
|
||
previous_content += recent_content
|
||
|
||
logger.info(f"构建前置上下文：{len(early_chapters)}章摘要 + {len(recent_chapters)}章完整内容")
|
||
|
||
# 🧠 构建记忆增强上下文
|
||
logger.info(f"🧠 开始构建记忆增强上下文...")
|
||
memory_context = await memory_service.build_context_for_generation(
|
||
user_id=current_user_id,
|
||
project_id=project.id,
|
||
current_chapter=current_chapter.chapter_number,
|
||
chapter_outline=outline.content if outline else current_chapter.summary or "",
|
||
character_names=[c.name for c in characters] if characters else None
|
||
)
|
||
|
||
# 计算各部分的字符长度
|
||
context_lengths = {
|
||
'recent_context': len(memory_context.get('recent_context', '')),
|
||
'relevant_memories': len(memory_context.get('relevant_memories', '')),
|
||
'foreshadows': len(memory_context.get('foreshadows', '')),
|
||
'character_states': len(memory_context.get('character_states', '')),
|
||
'plot_points': len(memory_context.get('plot_points', ''))
|
||
}
|
||
total_memory_length = sum(context_lengths.values())
|
||
|
||
logger.info(f"✅ 记忆上下文构建完成: {memory_context['stats']}")
|
||
logger.info(f"📏 记忆上下文长度统计:")
|
||
logger.info(f" - 最近章节记忆: {context_lengths['recent_context']} 字符")
|
||
logger.info(f" - 语义相关记忆: {context_lengths['relevant_memories']} 字符")
|
||
logger.info(f" - 未完结伏笔: {context_lengths['foreshadows']} 字符")
|
||
logger.info(f" - 角色状态记忆: {context_lengths['character_states']} 字符")
|
||
logger.info(f" - 重要情节点: {context_lengths['plot_points']} 字符")
|
||
logger.info(f" - 记忆总长度: {total_memory_length} 字符")
|
||
logger.info(f" - 前置章节上下文长度: {len(previous_content)} 字符")
|
||
logger.info(f" - 总上下文长度(估算): {total_memory_length + len(previous_content) + 2000} 字符")
|
||
|
||
# 发送开始事件
|
||
yield f"data: {json.dumps({'type': 'start', 'message': '开始AI创作...'}, ensure_ascii=False)}\n\n"
|
||
|
||
# 根据是否有前置内容选择不同的提示词，并应用写作风格和记忆增强
|
||
if previous_content:
|
||
prompt = prompt_service.get_chapter_generation_with_context_prompt(
|
||
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,
|
||
previous_content=previous_content,
|
||
chapter_number=current_chapter.chapter_number,
|
||
chapter_title=current_chapter.title,
|
||
chapter_outline=outline.content if outline else current_chapter.summary or '暂无大纲',
|
||
style_content=style_content,
|
||
target_word_count=target_word_count,
|
||
memory_context=memory_context
|
||
)
|
||
else:
|
||
prompt = prompt_service.get_chapter_generation_prompt(
|
||
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,
|
||
chapter_number=current_chapter.chapter_number,
|
||
chapter_title=current_chapter.title,
|
||
chapter_outline=outline.content if outline else current_chapter.summary or '暂无大纲',
|
||
style_content=style_content,
|
||
target_word_count=target_word_count,
|
||
memory_context=memory_context
|
||
)
|
||
|
||
logger.info(f"开始AI流式创作章节 {chapter_id}")
|
||
|
||
# 流式生成内容
|
||
full_content = ""
|
||
async for chunk in user_ai_service.generate_text_stream(prompt=prompt):
|
||
full_content += chunk
|
||
yield f"data: {json.dumps({'type': 'content', 'content': chunk}, ensure_ascii=False)}\n\n"
|
||
await asyncio.sleep(0) # 让出控制权
|
||
|
||
# 更新章节内容到数据库
|
||
old_word_count = current_chapter.word_count or 0
|
||
current_chapter.content = full_content
|
||
new_word_count = len(full_content)
|
||
current_chapter.word_count = new_word_count
|
||
current_chapter.status = "completed"
|
||
|
||
# 更新项目字数
|
||
project.current_words = project.current_words - old_word_count + new_word_count
|
||
|
||
# 记录生成历史
|
||
history = GenerationHistory(
|
||
project_id=current_chapter.project_id,
|
||
chapter_id=current_chapter.id,
|
||
prompt=f"创作章节: 第{current_chapter.chapter_number}章 {current_chapter.title}",
|
||
generated_content=full_content[:500] if len(full_content) > 500 else full_content,
|
||
model="default"
|
||
)
|
||
db_session.add(history)
|
||
|
||
await db_session.commit()
|
||
db_committed = True
|
||
await db_session.refresh(current_chapter)
|
||
|
||
logger.info(f"成功创作章节 {chapter_id}，共 {new_word_count} 字")
|
||
|
||
# 创建分析任务并启动后台分析
|
||
analysis_task = AnalysisTask(
|
||
chapter_id=chapter_id,
|
||
user_id=current_user_id,
|
||
project_id=project.id,
|
||
status='pending',
|
||
progress=0
|
||
)
|
||
db_session.add(analysis_task)
|
||
await db_session.commit()
|
||
# 不需要refresh，只需要获取ID
|
||
|
||
task_id = analysis_task.id
|
||
|
||
# 启动后台分析任务
|
||
background_tasks.add_task(
|
||
analyze_chapter_background,
|
||
chapter_id=chapter_id,
|
||
user_id=current_user_id,
|
||
project_id=project.id,
|
||
task_id=task_id,
|
||
ai_service=user_ai_service
|
||
)
|
||
|
||
logger.info(f"📋 已创建分析任务: {task_id}")
|
||
|
||
# 发送完成事件（包含分析任务ID）
|
||
completion_data = {
|
||
'type': 'done',
|
||
'message': '创作完成',
|
||
'word_count': new_word_count,
|
||
'analysis_task_id': task_id
|
||
}
|
||
yield f"data: {json.dumps(completion_data, ensure_ascii=False)}\n\n"
|
||
|
||
# 发送分析排队事件
|
||
analysis_queued_data = {
|
||
'type': 'analysis_queued',
|
||
'task_id': task_id,
|
||
'message': '章节分析已加入队列'
|
||
}
|
||
yield f"data: {json.dumps(analysis_queued_data, ensure_ascii=False)}\n\n"
|
||
|
||
break # 退出async for db_session循环
|
||
|
||
except GeneratorExit:
|
||
# SSE连接断开
|
||
logger.warning("章节生成器被提前关闭（SSE断开）")
|
||
if db_session and not db_committed:
|
||
try:
|
||
if db_session.in_transaction():
|
||
await db_session.rollback()
|
||
logger.info("章节生成事务已回滚（GeneratorExit）")
|
||
except Exception as e:
|
||
logger.error(f"GeneratorExit回滚失败: {str(e)}")
|
||
except Exception as e:
|
||
logger.error(f"流式创作章节失败: {str(e)}")
|
||
if db_session and not db_committed:
|
||
try:
|
||
if db_session.in_transaction():
|
||
await db_session.rollback()
|
||
logger.info("章节生成事务已回滚（异常）")
|
||
except Exception as rollback_error:
|
||
logger.error(f"回滚失败: {str(rollback_error)}")
|
||
yield f"data: {json.dumps({'type': 'error', 'error': str(e)}, ensure_ascii=False)}\n\n"
|
||
finally:
|
||
# 确保数据库会话被正确关闭
|
||
if db_session:
|
||
try:
|
||
# 最后检查：确保没有未提交的事务
|
||
if not db_committed and db_session.in_transaction():
|
||
await db_session.rollback()
|
||
logger.warning("在finally中发现未提交事务，已回滚")
|
||
|
||
await db_session.close()
|
||
logger.info("数据库会话已关闭")
|
||
except Exception as close_error:
|
||
logger.error(f"关闭数据库会话失败: {str(close_error)}")
|
||
# 强制关闭
|
||
try:
|
||
await db_session.close()
|
||
except:
|
||
pass
|
||
|
||
return StreamingResponse(
|
||
event_generator(),
|
||
media_type="text/event-stream",
|
||
headers={
|
||
"Cache-Control": "no-cache",
|
||
"Connection": "keep-alive",
|
||
"X-Accel-Buffering": "no"
|
||
}
|
||
)
|
||
|
||
|
||
@router.get("/{chapter_id}/analysis/status", summary="查询章节分析任务状态")
|
||
async def get_analysis_task_status(
|
||
chapter_id: str,
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
查询指定章节的最新分析任务状态
|
||
|
||
返回:
|
||
- task_id: 任务ID
|
||
- status: pending/running/completed/failed
|
||
- progress: 0-100
|
||
- error_message: 错误信息(如果失败)
|
||
- created_at: 创建时间
|
||
- completed_at: 完成时间
|
||
"""
|
||
# 获取该章节最新的分析任务
|
||
result = await db.execute(
|
||
select(AnalysisTask)
|
||
.where(AnalysisTask.chapter_id == chapter_id)
|
||
.order_by(AnalysisTask.created_at.desc())
|
||
.limit(1)
|
||
)
|
||
task = result.scalar_one_or_none()
|
||
|
||
if not task:
|
||
raise HTTPException(status_code=404, detail="未找到分析任务")
|
||
|
||
return {
|
||
"task_id": task.id,
|
||
"chapter_id": task.chapter_id,
|
||
"status": task.status,
|
||
"progress": task.progress,
|
||
"error_message": task.error_message,
|
||
"created_at": task.created_at.isoformat() if task.created_at else None,
|
||
"started_at": task.started_at.isoformat() if task.started_at else None,
|
||
"completed_at": task.completed_at.isoformat() if task.completed_at else None
|
||
}
|
||
|
||
|
||
@router.get("/{chapter_id}/analysis", summary="获取章节分析结果")
|
||
async def get_chapter_analysis(
|
||
chapter_id: str,
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
获取章节的完整分析结果
|
||
|
||
返回:
|
||
- analysis_data: 完整的分析数据(JSON)
|
||
- summary: 分析摘要文本
|
||
- memories: 提取的记忆列表
|
||
- created_at: 分析时间
|
||
"""
|
||
# 获取分析结果
|
||
analysis_result = await db.execute(
|
||
select(PlotAnalysis)
|
||
.where(PlotAnalysis.chapter_id == chapter_id)
|
||
.order_by(PlotAnalysis.created_at.desc())
|
||
.limit(1)
|
||
)
|
||
analysis = analysis_result.scalar_one_or_none()
|
||
|
||
if not analysis:
|
||
raise HTTPException(status_code=404, detail="该章节暂无分析结果")
|
||
|
||
# 获取相关记忆
|
||
memories_result = await db.execute(
|
||
select(StoryMemory)
|
||
.where(StoryMemory.chapter_id == chapter_id)
|
||
.order_by(StoryMemory.importance_score.desc())
|
||
)
|
||
memories = memories_result.scalars().all()
|
||
|
||
return {
|
||
"chapter_id": chapter_id,
|
||
"analysis": analysis.to_dict(), # 使用to_dict()方法
|
||
"memories": [
|
||
{
|
||
"id": mem.id,
|
||
"type": mem.memory_type,
|
||
"title": mem.title,
|
||
"content": mem.content,
|
||
"importance": mem.importance_score,
|
||
"tags": mem.tags,
|
||
"is_foreshadow": mem.is_foreshadow,
|
||
"position": mem.chapter_position,
|
||
"related_characters": mem.related_characters
|
||
}
|
||
for mem in memories
|
||
],
|
||
"created_at": analysis.created_at.isoformat() if analysis.created_at else None
|
||
}
|
||
|
||
|
||
@router.get("/{chapter_id}/annotations", summary="获取章节标注数据")
|
||
async def get_chapter_annotations(
|
||
chapter_id: str,
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
获取章节的标注数据（用于前端展示标注）
|
||
|
||
返回格式化的标注列表，包含精确位置信息
|
||
适用于章节内容的可视化标注展示
|
||
"""
|
||
# 获取章节
|
||
chapter_result = await db.execute(
|
||
select(Chapter).where(Chapter.id == chapter_id)
|
||
)
|
||
chapter = chapter_result.scalar_one_or_none()
|
||
|
||
if not chapter:
|
||
raise HTTPException(status_code=404, detail="章节不存在")
|
||
|
||
# 获取分析结果
|
||
analysis_result = await db.execute(
|
||
select(PlotAnalysis)
|
||
.where(PlotAnalysis.chapter_id == chapter_id)
|
||
.order_by(PlotAnalysis.created_at.desc())
|
||
.limit(1)
|
||
)
|
||
analysis = analysis_result.scalar_one_or_none()
|
||
|
||
# 获取记忆
|
||
memories_result = await db.execute(
|
||
select(StoryMemory)
|
||
.where(StoryMemory.chapter_id == chapter_id)
|
||
.order_by(StoryMemory.importance_score.desc())
|
||
)
|
||
memories = memories_result.scalars().all()
|
||
|
||
# 构建标注数据
|
||
annotations = []
|
||
|
||
for mem in memories:
|
||
# 优先从数据库读取位置信息
|
||
position = mem.chapter_position if mem.chapter_position is not None else -1
|
||
length = mem.text_length if hasattr(mem, 'text_length') and mem.text_length is not None else 0
|
||
metadata_extra = {}
|
||
|
||
# 如果数据库中没有位置信息，尝试从分析数据中重新计算
|
||
if position == -1 and analysis and chapter.content:
|
||
# 根据记忆类型从分析数据中查找对应项
|
||
if mem.memory_type == 'hook' and analysis.hooks:
|
||
for hook in analysis.hooks:
|
||
# 通过标题或内容匹配
|
||
if mem.title and hook.get('type') in mem.title:
|
||
keyword = hook.get('keyword', '')
|
||
if keyword:
|
||
pos = chapter.content.find(keyword)
|
||
if pos != -1:
|
||
position = pos
|
||
length = len(keyword)
|
||
metadata_extra["strength"] = hook.get('strength', 5)
|
||
metadata_extra["position_desc"] = hook.get('position', '')
|
||
break
|
||
|
||
elif mem.memory_type == 'foreshadow' and analysis.foreshadows:
|
||
for foreshadow in analysis.foreshadows:
|
||
if foreshadow.get('content') in mem.content:
|
||
keyword = foreshadow.get('keyword', '')
|
||
if keyword:
|
||
pos = chapter.content.find(keyword)
|
||
if pos != -1:
|
||
position = pos
|
||
length = len(keyword)
|
||
metadata_extra["foreshadow_type"] = foreshadow.get('type', 'planted')
|
||
metadata_extra["strength"] = foreshadow.get('strength', 5)
|
||
break
|
||
|
||
elif mem.memory_type == 'plot_point' and analysis.plot_points:
|
||
for plot_point in analysis.plot_points:
|
||
if plot_point.get('content') in mem.content:
|
||
keyword = plot_point.get('keyword', '')
|
||
if keyword:
|
||
pos = chapter.content.find(keyword)
|
||
if pos != -1:
|
||
position = pos
|
||
length = len(keyword)
|
||
break
|
||
else:
|
||
# 如果数据库有位置，也从分析数据中提取额外的元数据
|
||
if analysis:
|
||
if mem.memory_type == 'hook' and analysis.hooks:
|
||
for hook in analysis.hooks:
|
||
if mem.title and hook.get('type') in mem.title:
|
||
metadata_extra["strength"] = hook.get('strength', 5)
|
||
metadata_extra["position_desc"] = hook.get('position', '')
|
||
break
|
||
|
||
elif mem.memory_type == 'foreshadow' and analysis.foreshadows:
|
||
for foreshadow in analysis.foreshadows:
|
||
if foreshadow.get('content') in mem.content:
|
||
metadata_extra["foreshadow_type"] = foreshadow.get('type', 'planted')
|
||
metadata_extra["strength"] = foreshadow.get('strength', 5)
|
||
break
|
||
|
||
annotation = {
|
||
"id": mem.id,
|
||
"type": mem.memory_type,
|
||
"title": mem.title,
|
||
"content": mem.content,
|
||
"importance": mem.importance_score or 0.5,
|
||
"position": position,
|
||
"length": length,
|
||
"tags": mem.tags or [],
|
||
"metadata": {
|
||
"is_foreshadow": mem.is_foreshadow,
|
||
"related_characters": mem.related_characters or [],
|
||
"related_locations": mem.related_locations or [],
|
||
**metadata_extra
|
||
}
|
||
}
|
||
|
||
annotations.append(annotation)
|
||
|
||
return {
|
||
"chapter_id": chapter_id,
|
||
"chapter_number": chapter.chapter_number,
|
||
"title": chapter.title,
|
||
"word_count": chapter.word_count or 0,
|
||
"annotations": annotations,
|
||
"has_analysis": analysis is not None,
|
||
"summary": {
|
||
"total_annotations": len(annotations),
|
||
"hooks": len([a for a in annotations if a["type"] == "hook"]),
|
||
"foreshadows": len([a for a in annotations if a["type"] == "foreshadow"]),
|
||
"plot_points": len([a for a in annotations if a["type"] == "plot_point"]),
|
||
"character_events": len([a for a in annotations if a["type"] == "character_event"])
|
||
}
|
||
}
|
||
|
||
|
||
@router.post("/{chapter_id}/analyze", summary="手动触发章节分析")
|
||
async def trigger_chapter_analysis(
|
||
chapter_id: str,
|
||
request: Request,
|
||
background_tasks: BackgroundTasks,
|
||
db: AsyncSession = Depends(get_db),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
手动触发章节分析(用于重新分析或分析旧章节)
|
||
"""
|
||
# 从请求中获取用户ID
|
||
user_id = getattr(request.state, "user_id", None)
|
||
if not user_id:
|
||
raise HTTPException(status_code=401, detail="未登录")
|
||
|
||
# 验证章节存在
|
||
chapter_result = await db.execute(
|
||
select(Chapter).where(Chapter.id == chapter_id)
|
||
)
|
||
chapter = chapter_result.scalar_one_or_none()
|
||
|
||
if not chapter:
|
||
raise HTTPException(status_code=404, detail="章节不存在")
|
||
|
||
if not chapter.content or chapter.content.strip() == "":
|
||
raise HTTPException(status_code=400, detail="章节内容为空，无法分析")
|
||
|
||
# 获取项目信息
|
||
project_result = await db.execute(
|
||
select(Project).where(Project.id == chapter.project_id)
|
||
)
|
||
project = project_result.scalar_one_or_none()
|
||
|
||
if not project:
|
||
raise HTTPException(status_code=404, detail="项目不存在")
|
||
|
||
# 创建分析任务
|
||
analysis_task = AnalysisTask(
|
||
chapter_id=chapter_id,
|
||
user_id=user_id,
|
||
project_id=project.id,
|
||
status='pending',
|
||
progress=0
|
||
)
|
||
db.add(analysis_task)
|
||
await db.commit()
|
||
# 注意：不需要refresh，因为我们只需要id，而id在commit后已经生成
|
||
|
||
task_id = analysis_task.id
|
||
|
||
# 启动后台分析任务
|
||
background_tasks.add_task(
|
||
analyze_chapter_background,
|
||
chapter_id=chapter_id,
|
||
user_id=user_id,
|
||
project_id=project.id,
|
||
task_id=task_id,
|
||
ai_service=user_ai_service
|
||
)
|
||
|
||
logger.info(f"📋 手动触发分析任务: {task_id}")
|
||
|
||
return {
|
||
"task_id": task_id,
|
||
"chapter_id": chapter_id,
|
||
"status": "pending",
|
||
"message": "分析任务已创建并加入队列"
|
||
}
|