"""
回忆录整理 Agent：基于传记结构，将口语改写为书面语，归类到章节
支持异步调用
"""
import json
from app.core.logging import get_logger
from typing import Dict, List, Optional

from app.core.dependencies import get_llm_provider

from app.agents.prompts import (
    get_chapter_classification_prompt,
    get_text_rewrite_prompt,
    inject_image_placeholder_template,
    CHAPTER_CATEGORIES,
    STAGE_TO_ORDER,
)

logger = get_logger(__name__)


def _get_langchain_llm():
    try:
        provider = get_llm_provider()
        return getattr(provider, "langchain_llm", None)
    except Exception:
        return None


class MemoryAgent:
    """回忆录整理 Agent（支持异步）"""

    def __init__(self):
        self.llm = _get_langchain_llm()

    async def classify_chapter(self, segments_text: str) -> str:
        if not self.llm:
            return "childhood"
        try:
            prompt = get_chapter_classification_prompt(segments_text)
            response = await self.llm.ainvoke(prompt)
            content = response.content if hasattr(response, "content") else str(response)
            category = content.strip().lower()
            if category in CHAPTER_CATEGORIES:
                return category
        except Exception as e:
            logger.error("分类章节失败: %s", e)
        return "childhood"

    async def rewrite_to_literary(
        self,
        segments_text: str,
        chapter_category: str,
        existing_content: Optional[str] = None,
    ) -> Dict:
        if not self.llm:
            return {
                "title": CHAPTER_CATEGORIES.get(chapter_category, "章节"),
                "content": segments_text,
                "summary": "",
                "image_suggestions": [],
            }
        try:
            prompt = get_text_rewrite_prompt(
                segments_text, chapter_category, existing_content or ""
            )
            response = await self.llm.ainvoke(prompt)
            content = response.content if hasattr(response, "content") else str(response)
            content = content.strip()
            if content.startswith("```json"):
                content = content[7:]
            if content.startswith("```"):
                content = content[3:]
            if content.endswith("```"):
                content = content[:-3]
            content = content.strip()
            result = json.loads(content)
            result["content"] = inject_image_placeholder_template(
                result.get("content") or ""
            )
            return result
        except json.JSONDecodeError:
            raw = response.content if hasattr(response, "content") else str(response)
            return {
                "title": CHAPTER_CATEGORIES.get(chapter_category, "章节"),
                "content": inject_image_placeholder_template(raw),
                "summary": "",
                "image_suggestions": [],
            }
        except Exception as e:
            logger.error("改写文本失败: %s", e)
            return {
                "title": CHAPTER_CATEGORIES.get(chapter_category, "章节"),
                "content": segments_text,
                "summary": "",
                "image_suggestions": [],
            }

    async def process_segments(
        self,
        segments: List[Dict],
        existing_chapters: Optional[Dict[str, Dict]] = None,
    ) -> Dict[str, Dict]:
        if existing_chapters is None:
            existing_chapters = {}
        segments_by_category: Dict[str, List[str]] = {}
        for segment in segments:
            text = segment.get("transcript_text", "")
            if not text:
                continue
            category = await self.classify_chapter(text)
            if category not in segments_by_category:
                segments_by_category[category] = []
            segments_by_category[category].append(text)
        updated_chapters = existing_chapters.copy()
        for category, texts in segments_by_category.items():
            combined_text = "\n\n".join(texts)
            existing_content = existing_chapters.get(category, {}).get("content", "")
            result = await self.rewrite_to_literary(
                combined_text, category, existing_content
            )
            updated_chapters[category] = {
                "title": result.get("title", CHAPTER_CATEGORIES.get(category, "章节")),
                "content": result.get("content", ""),
                "summary": result.get("summary", ""),
                "image_suggestions": result.get("image_suggestions", []),
                "category": category,
                "order_index": STAGE_TO_ORDER.get(category, 999),
            }
        return updated_chapters