e4bf0710c7
数据库 - 新增迁移 0003：timeline_events.memory_source_id 外键 → memory_sources，便于按 ingest 源做时间线幂等 后端 - 记忆 - 新增 ingest 后 LLM 富化（摘要/事实/时间线），可配置开关与最大字符数 - 新增证据包组装：合并 chunk、摘要、事实、时间线、故事等检索结果；支持空 query 时是否仍带 rolling 等开关 - repo/retriever/service/router/schemas/summarizer/timeline/extractor 等扩展；文档 memory-retrieval.md 更新 后端 - 对话 WS - 增加 PING/PONG；分段 ASR 日志与空音频处理；转写失败与「无助手回复」错误提示更明确 - 助手多段回复持久化使用统一分隔符，与分段逻辑一致 后端 - Agent - reply_limits：按 [SPLIT] 与段落拆段，并保证非空 fallback，供 WS 与 TTS 多段下发 后端 - 回忆录任务 - transcript ingest 记录 source_id；任务成功结?
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
"""
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NarrativeAgent：生成创意标题和叙事改写。
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叙事正文走 `get_narrative_json_prompt` / `get_narrative_merge_json_prompt`（传记作家式书面语 + 事实边界）。
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"""
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from __future__ import annotations
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import json
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from typing import Any, Dict, Optional
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from app.agents.memoir.prompts import (
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get_creative_title_json_prompt,
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get_narrative_json_prompt,
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get_narrative_merge_json_prompt,
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)
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from app.core.langchain_llm import invoke_json_object
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from app.core.logging import get_logger
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from app.features.memoir.memoir_images.json_payload import extract_json_payload
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logger = get_logger(__name__)
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class NarrativeAgent:
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"""生成章节标题和叙事正文"""
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def generate_title(
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self,
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stage: str,
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emotion: str,
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slots: Dict[str, str],
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user_profile: str = "",
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birth_year: Optional[int] = None,
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llm: Any = None,
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) -> str:
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"""生成创意标题。若无 LLM 则返回默认标题"""
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if not llm:
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return f"{stage} 回忆"
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try:
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prompt = get_creative_title_json_prompt(
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stage=stage,
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emotion=emotion,
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slots=slots,
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user_profile=user_profile,
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birth_year=birth_year,
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)
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raw = invoke_json_object(
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llm,
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prompt,
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max_tokens=256,
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agent="NarrativeAgent.generate_title",
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)
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data = json.loads(extract_json_payload(raw))
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title = (data.get("title") or "").strip() if isinstance(data, dict) else ""
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if title:
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return title.strip('"')
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return f"{stage} 回忆"
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except Exception as e:
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logger.warning("NarrativeAgent 生成标题失败: {}", e)
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return f"{stage} 回忆"
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def generate_narrative(
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self,
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stage: str,
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slots: Dict[str, str],
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new_content: str,
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existing_content: str = "",
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user_profile: str = "",
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birth_year: Optional[int] = None,
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llm: Any = None,
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) -> str:
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"""将新对话改写为叙述。若无 LLM 则直接拼接。
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若 `existing_content` 非空（append 路径），使用整篇合并提示，输出覆盖全篇的有序段落。
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"""
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if not llm:
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if existing_content:
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return f"{existing_content}\n\n{new_content}"
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return new_content
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try:
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merge_mode = bool((existing_content or "").strip())
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if merge_mode:
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prompt = get_narrative_merge_json_prompt(
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stage=stage,
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slots=slots,
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new_content=new_content,
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existing_content=existing_content,
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user_profile=user_profile,
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birth_year=birth_year,
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)
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max_tokens = 8192
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agent_name = "NarrativeAgent.generate_narrative_merge"
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else:
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prompt = get_narrative_json_prompt(
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stage=stage,
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slots=slots,
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new_content=new_content,
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existing_content=existing_content,
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user_profile=user_profile,
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birth_year=birth_year,
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)
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max_tokens = 4096
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agent_name = "NarrativeAgent.generate_narrative"
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return invoke_json_object(
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llm,
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prompt,
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max_tokens=max_tokens,
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agent=agent_name,
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).strip()
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except Exception as e:
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logger.warning("NarrativeAgent 生成叙事失败: {}", e)
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if existing_content:
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return f"{existing_content}\n\n{new_content}"
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return new_content
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