bb16d3a5c9
访谈与阶段 - 新增 app/agents/stage_constants.py：集中 CHAT_STAGES、章节分类/顺序、阶段到默认 memoir 类别等，与 MemoirState 默认槽位顺序对齐；减少散落在 prompts 内的重复常量。 - 新增 app/agents/chat/prompt_context.py：以 ChatPromptContext 汇总 guided 系统提示所需字段（阶段、槽位、轮次、人设、记忆证据、回复长度模式、背景声线、职业等），统一走 get_guided_conversation_prompt。 - 大幅收敛 app/agents/chat/prompts_conversation.py；调整 prompts.py、stage_prompts.py、stage_detection.py；同步 interview_agent、profile_agent、helpers 与 state_schema，使对话侧构造提示的方式一致、可测。 回忆录流水线 - memoir/prompts.py 删除已迁至 stage_constants / 独立模板的大段常量与图片占位相关逻辑；classification / extraction / fidelity / narrative agents 与 orchest（全量历史仍可用于计数，注入模型时按轮次与字符上限截断）、image_prompt_fallback_disabled。 - dependencies 增加 get_llm_provider_fast（LRU 缓存，可与默认共用密钥与 base_url）。 任务与编排 - memoir_tasks：prepare_batches 注入 llm_fast；开启独立快档模型时打结构化日志。 - chapter_cover_tasks、story_image_tasks：与图片 prompt / JSON 工具路径或策略变更对齐（import 与行为一致）。 - story_pipeline_sync 等小处同步。 其它核心 - langchain_llm、text_normalize 随上述调用链微调。 开发者体验 - .cursor/settings.json：启用 redis-development、postman 插件。 测试 - 新增 test_image_prompt_policy：覆盖「禁止回退」等图片 prompt 策略。 - 更新 test_interview_prompts、test_interview_reply_length、test_experience_regressions、test_json_and_memory_utils，匹配新常量位置、json_utils 与对话/长度行为。
120 lines
4.0 KiB
Python
120 lines
4.0 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.core.json_utils 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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background_voice: str = "default",
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occupation: str = "",
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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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background_voice=background_voice,
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occupation=occupation,
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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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background_voice=background_voice,
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occupation=occupation,
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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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