7fe0b70d5c
- 在 api/agents/conversation_agent.py 中添加 _detect_user_stage 方法，以通过关键词检测用户谈论的人生阶段。 - 在 api/agents/memory_agent.py 中更新章节排序逻辑，使用 STAGE_TO_ORDER 替代 CHAPTER_ORDER。 - 在 api/agents/state_schema.py 中添加方法以获取各阶段的填充情况。 - 在 api/agents/prompts/conversation_prompts.py 中更新对话提示，包含用户阶段检测和整体进度信息。 - 在 api/migrations/fix_chapter_order_index.sql 中添加 SQL 脚本以修复章节 order_index 的问题。 - 更新相关文档和提示以反映新功能。
394 lines
14 KiB
Python
394 lines
14 KiB
Python
"""
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回忆录处理 Celery 任务
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"""
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import json
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import logging
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import os
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import uuid
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from typing import Dict, List
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from datetime import datetime, timezone
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import redis
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from celery import shared_task
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from database.database import SessionLocal
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from database.models import Book, Chapter, Segment, MemoirState
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from services.llm_service import llm_service
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from agents.state_schema import MemoirStateSchema, SlotData, default_state
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from agents.prompts.memory_prompts import (
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get_creative_title_prompt,
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get_narrative_prompt,
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get_state_extraction_prompt,
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STAGE_TO_ORDER,
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)
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logger = logging.getLogger(__name__)
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def _update_task_status_sync(user_id: str, task_id: str, status: str, result: Dict = None):
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"""同步更新任务状态（在 Celery 任务中使用）"""
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try:
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redis_url = os.getenv("REDIS_URL", "redis://localhost:6379/0")
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r = redis.from_url(redis_url, decode_responses=True)
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key = f"task:user:{user_id}:tasks"
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# 获取现有任务信息
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data = r.hget(key, task_id)
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if data:
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task_info = json.loads(data)
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else:
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task_info = {"task_id": task_id}
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task_info["status"] = status
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task_info["updated_at"] = datetime.now(timezone.utc).isoformat()
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if result is not None:
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task_info["result"] = result
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r.hset(key, task_id, json.dumps(task_info))
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r.expire(key, 3600) # 1小时过期
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logger.info(f"任务状态已更新: task_id={task_id}, status={status}")
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except Exception as e:
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logger.error(f"更新任务状态失败: {e}")
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STAGE_KEYWORDS = {
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"childhood": ["童年", "小时候", "出生", "家乡", "小镇"],
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"education": ["上学", "学校", "老师", "同学", "教育", "大学"],
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"career": ["工作", "职业", "事业", "公司", "同事", "创业"],
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"family": ["伴侣", "孩子", "家庭", "家人", "结婚", "父母"],
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"belief": ["信念", "价值观", "座右铭", "坚持", "原则"],
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}
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def _detect_stage(user_message: str, fallback_stage: str) -> str:
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"""检测消息所属阶段"""
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message = user_message.lower()
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for stage, keywords in STAGE_KEYWORDS.items():
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if any(word in message for word in keywords):
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return stage
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return fallback_stage
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def _coerce_state(model: MemoirState) -> MemoirStateSchema:
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"""将数据库模型转换为 Schema"""
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return MemoirStateSchema.model_validate(
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{
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"stage_order": model.stage_order or default_state().stage_order,
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"current_stage": model.current_stage,
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"covered_stages": model.covered_stages or [],
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"slots": model.slots if isinstance(model.slots, dict) else default_state().slots,
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}
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)
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def _get_or_create_state_sync(user_id: str, db: Session) -> MemoirStateSchema:
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"""同步获取或创建状态"""
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stmt = select(MemoirState).where(MemoirState.user_id == user_id)
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result = db.execute(stmt)
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state = result.scalar_one_or_none()
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if state:
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return _coerce_state(state)
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default = default_state()
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state = MemoirState(
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id=str(uuid.uuid4()),
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user_id=user_id,
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stage_order=default.stage_order,
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current_stage=default.current_stage,
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covered_stages=default.covered_stages,
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slots={k: {sk: sv.model_dump() for sk, sv in v.items()} for k, v in default.slots.items()},
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)
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db.add(state)
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db.commit()
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db.refresh(state)
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return _coerce_state(state)
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def _update_slot_sync(
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user_id: str,
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stage: str,
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slot_name: str,
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snippet: str,
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segment_ids: List[str],
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db: Session,
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) -> MemoirStateSchema:
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"""同步更新 slot"""
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stmt = select(MemoirState).where(MemoirState.user_id == user_id)
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result = db.execute(stmt)
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state = result.scalar_one_or_none()
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if not state:
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_get_or_create_state_sync(user_id, db)
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result = db.execute(stmt)
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state = result.scalar_one()
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slots: Dict[str, Dict] = state.slots or {}
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stage_slots = slots.get(stage, {})
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existing = stage_slots.get(slot_name, {})
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merged_segment_ids = list({*(existing.get("segment_ids") or []), *segment_ids})
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stage_slots[slot_name] = SlotData(snippet=snippet, segment_ids=merged_segment_ids).model_dump()
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slots[stage] = stage_slots
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state.slots = slots
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state.current_stage = state.current_stage or stage
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db.commit()
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db.refresh(state)
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return _coerce_state(state)
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@shared_task(bind=True, max_retries=3, default_retry_delay=60)
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def process_memoir_segments(self, user_id: str, segment_ids: List[str]):
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"""
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处理回忆录段落的 Celery 任务
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Args:
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user_id: 用户 ID
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segment_ids: 段落 ID 列表
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"""
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task_id = self.request.id
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logger.info(f"开始处理回忆录段落: user_id={user_id}, task_id={task_id}, segments={len(segment_ids)}")
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# 更新任务状态为 running
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_update_task_status_sync(user_id, task_id, "running")
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try:
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db = SessionLocal()
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try:
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# 获取段落
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stmt = select(Segment).where(Segment.id.in_(segment_ids))
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result = db.execute(stmt)
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segments = result.scalars().all()
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if not segments:
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logger.warning(f"未找到段落: {segment_ids}")
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return {"status": "no_segments"}
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# 获取用户状态
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state = _get_or_create_state_sync(user_id, db)
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llm = llm_service.get_llm()
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# 按阶段分组处理
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stage_to_segments: Dict[str, List[Segment]] = {}
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for segment in segments:
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text = segment.transcript_text
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detected_stage = _detect_stage(text, state.current_stage)
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# 尝试使用 LLM 提取信息
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extracted_slots = {}
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if llm:
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try:
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prompt = get_state_extraction_prompt(
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user_message=text,
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current_stage=state.current_stage,
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stage_slots=state.slots.get(detected_stage, {}),
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)
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response = llm.invoke(prompt)
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content = response.content.strip()
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parsed = json.loads(content)
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detected_stage = parsed.get("detected_stage", detected_stage)
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extracted_slots = parsed.get("slots", {}) or {}
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except (json.JSONDecodeError, Exception) as e:
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logger.warning(f"LLM 解析失败: {e}")
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# 更新 slots
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for slot_name, snippet in extracted_slots.items():
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state = _update_slot_sync(
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user_id=user_id,
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stage=detected_stage,
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slot_name=slot_name,
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snippet=snippet,
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segment_ids=[segment.id],
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db=db,
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)
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stage_to_segments.setdefault(detected_stage, []).append(segment)
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# 生成章节内容
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for stage, stage_segments in stage_to_segments.items():
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segment_texts = [seg.transcript_text for seg in stage_segments]
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combined_text = "\n\n".join(segment_texts)
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source_ids = [seg.id for seg in stage_segments]
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# 查找或创建章节
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stmt_chapter = select(Chapter).where(
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Chapter.user_id == user_id,
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Chapter.category == stage,
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)
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result_chapter = db.execute(stmt_chapter)
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chapter = result_chapter.scalar_one_or_none()
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# 获取 slot snippets
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slot_snippets = {
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key: value.snippet
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for key, value in (state.slots.get(stage, {}) or {}).items()
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if value.snippet
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}
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# 生成标题和内容
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title = chapter.title if chapter else f"{stage} 回忆"
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existing_content = chapter.content if chapter else ""
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narrative = combined_text
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if llm:
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try:
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if not chapter:
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title_prompt = get_creative_title_prompt(
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stage=stage,
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emotion="neutral",
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slots=slot_snippets
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)
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title_response = llm.invoke(title_prompt)
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title = title_response.content.strip().strip('"')
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narrative_prompt = get_narrative_prompt(
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stage=stage,
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slots=slot_snippets,
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new_content=combined_text,
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existing_content=existing_content,
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)
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narrative_response = llm.invoke(narrative_prompt)
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narrative = narrative_response.content.strip()
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except Exception as e:
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logger.warning(f"LLM 生成失败: {e}")
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if existing_content:
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narrative = f"{existing_content}\n\n{combined_text}"
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# 更新或创建章节
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if chapter:
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chapter.content = narrative
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chapter.title = title
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chapter.is_new = True
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chapter.source_segments = list({*(chapter.source_segments or []), *source_ids})
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else:
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# 根据 stage 计算正确的排序索引
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calculated_order_index = STAGE_TO_ORDER.get(stage, 999)
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chapter = Chapter(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title=title,
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content=narrative,
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order_index=calculated_order_index,
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status="completed",
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category=stage,
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images=[],
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is_new=True,
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source_segments=source_ids,
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)
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db.add(chapter)
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db.flush()
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# 更新 Book
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stmt_book = select(Book).where(Book.user_id == user_id).order_by(Book.updated_at.desc())
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result_book = db.execute(stmt_book)
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book = result_book.scalar_one_or_none()
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if not book:
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book = Book(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title="我的回忆录",
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total_pages=0,
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total_words=0,
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cover_image_url=None,
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)
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db.add(book)
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book.has_update = True
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book.last_update_chapter_id = chapter.id
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# 标记段落为已处理
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for seg in segments:
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seg.processed = True
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db.commit()
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logger.info(f"回忆录处理完成: user_id={user_id}, task_id={task_id}")
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# 更新任务状态为成功
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_update_task_status_sync(user_id, task_id, "success", {"processed": len(segments)})
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return {"status": "success", "processed": len(segments)}
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finally:
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db.close()
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except Exception as e:
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logger.error(f"回忆录处理失败: {e}")
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# 更新任务状态为失败
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_update_task_status_sync(user_id, task_id, "failure", {"error": str(e)})
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# 重试
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raise self.retry(exc=e)
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@shared_task(bind=True, max_retries=3, default_retry_delay=30)
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def generate_chapter_content(self, user_id: str, stage: str, new_content: str):
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"""
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单独生成章节内容的任务（用于实时更新）
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Args:
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user_id: 用户 ID
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stage: 阶段
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new_content: 新内容
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"""
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logger.info(f"生成章节内容: user_id={user_id}, stage={stage}")
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try:
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db = SessionLocal()
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try:
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llm = llm_service.get_llm()
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# 查找章节
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stmt = select(Chapter).where(
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Chapter.user_id == user_id,
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Chapter.category == stage,
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)
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result = db.execute(stmt)
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chapter = result.scalar_one_or_none()
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existing_content = chapter.content if chapter else ""
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if llm:
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prompt = get_narrative_prompt(
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stage=stage,
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slots={},
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new_content=new_content,
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existing_content=existing_content,
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)
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response = llm.invoke(prompt)
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narrative = response.content.strip()
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else:
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narrative = f"{existing_content}\n\n{new_content}" if existing_content else new_content
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if chapter:
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chapter.content = narrative
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chapter.is_new = True
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else:
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# 根据 stage 计算正确的排序索引
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calculated_order_index = STAGE_TO_ORDER.get(stage, 999)
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chapter = Chapter(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title=f"{stage} 回忆",
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content=narrative,
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order_index=calculated_order_index,
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status="completed",
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category=stage,
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images=[],
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is_new=True,
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source_segments=[],
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)
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db.add(chapter)
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db.commit()
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return {"status": "success"}
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finally:
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db.close()
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except Exception as e:
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logger.error(f"章节生成失败: {e}")
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raise self.retry(exc=e)
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