"""
NarrativeAgent：生成创意标题和叙事改写。
对应现有逻辑：get_creative_title_prompt、get_narrative_prompt
"""
from __future__ import annotations

from typing import Any, Dict, Optional

from app.core.logging import get_logger

from app.agents.memoir.prompts import (
    get_creative_title_prompt,
    get_narrative_json_prompt,
)

logger = get_logger(__name__)


class NarrativeAgent:
    """生成章节标题和叙事正文"""

    def generate_title(
        self,
        stage: str,
        emotion: str,
        slots: Dict[str, str],
        user_profile: str = "",
        birth_year: Optional[int] = None,
        llm: Any = None,
    ) -> str:
        """生成创意标题。若无 LLM 则返回默认标题"""
        if not llm:
            return f"{stage} 回忆"
        try:
            prompt = get_creative_title_prompt(
                stage=stage,
                emotion=emotion,
                slots=slots,
                user_profile=user_profile,
                birth_year=birth_year,
            )
            response = llm.invoke(prompt)
            return (response.content or "").strip().strip('"')
        except Exception as e:
            logger.warning("NarrativeAgent 生成标题失败: %s", e)
            return f"{stage} 回忆"

    def generate_narrative(
        self,
        stage: str,
        slots: Dict[str, str],
        new_content: str,
        existing_content: str = "",
        user_profile: str = "",
        birth_year: Optional[int] = None,
        llm: Any = None,
    ) -> str:
        """将新对话改写为叙述。若无 LLM 则直接拼接"""
        if not llm:
            if existing_content:
                return f"{existing_content}\n\n{new_content}"
            return new_content
        try:
            prompt = get_narrative_json_prompt(
                stage=stage,
                slots=slots,
                new_content=new_content,
                existing_content=existing_content,
                user_profile=user_profile,
                birth_year=birth_year,
            )
            json_llm = llm.bind(
                model_kwargs={"response_format": {"type": "json_object"}},
                max_tokens=4096,
            )
            response = json_llm.invoke(prompt)
            return (response.content or "").strip()
        except Exception as e:
            logger.warning("NarrativeAgent 生成叙事失败: %s", e)
            if existing_content:
                return f"{existing_content}\n\n{new_content}"
            return new_content