# =============================================================================
# 企微IT智能服务台 — 图谱查询服务
# =============================================================================
# 说明：基于Neo4j知识图谱的智能问答服务。
#   用户问题 → 图谱查询 → 直接返回解决方案（毫秒级响应）
#   未命中 → 降级到Dify流程
#
# 核心功能：
#   1. 关键词提取（jieba分词 + 停用词过滤）
#   2. Neo4j模糊匹配Issue节点
#   3. 查找关联的Action解决方案
#   4. 返回最高匹配的SolutionResult
# =============================================================================

import logging
from typing import List, Optional

from pydantic import BaseModel

logger = logging.getLogger(__name__)

# 停用词列表（常见的无意义词汇）
STOPWORDS = {
    "的", "了", "在", "是", "我", "有", "和", "就", "不", "人",
    "都", "一", "一个", "上", "也", "很", "到", "说", "要", "去",
    "你", "会", "着", "没有", "看", "好", "自己", "这", "那",
    "什么", "怎么", "如何", "为什么", "请问", "帮忙", "帮助",
}


class SolutionResult(BaseModel):
    """图谱查询结果 - 解决方案"""

    issue_name: str = ""
    issue_uuid: str = ""
    solution: str = ""
    action_name: str = ""
    confidence: float = 0.0


class GraphQueryService:
    """图谱查询服务 - 根据用户问题查找解决方案"""

    def __init__(self, neo4j_client):
        """初始化图谱查询服务

        Args:
            neo4j_client: Neo4jClient实例
        """
        self.neo4j_client = neo4j_client
        self._keyword_cache: dict = {}  # 简单缓存

    async def find_solution_by_question(
        self, question: str, timeout_ms: int = 100
    ) -> Optional[SolutionResult]:
        """根据用户问题查找解决方案（图谱查询主入口）

        流程：
            1. 提取问题关键词
            2. 遍历关键词查询Neo4j图谱
            3. 获取匹配的Issue及关联的Action
            4. 返回置信度最高的解决方案

        Args:
            question: 用户问题文本
            timeout_ms: 查询超时时间（毫秒），默认100ms

        Returns:
            Optional[SolutionResult]: 匹配的解决方案，未命中返回None
        """
        if not question or not question.strip():
            return None

        # 1. 提取关键词
        keywords = self._extract_keywords(question)
        if not keywords:
            logger.info(f"图谱查询：无法提取关键词 question={question[:50]}")
            return None

        logger.info(f"图谱查询：keywords={keywords}, question={question[:50]}")

        # 2. 遍历关键词查询图谱（按置信度排序）
        for kw in keywords:
            try:
                result = await self._query_by_keyword(kw)
                if result:
                    logger.info(
                        f"图谱命中: keyword={kw}, issue={result.issue_name}, "
                        f"confidence={result.confidence}"
                    )
                    return result
            except Exception as e:
                logger.warning(f"图谱查询异常（降级继续）: keyword={kw}, error={e}")
                continue

        logger.info(f"图谱未命中: question={question[:50]}")
        return None

    def _extract_keywords(self, text: str) -> List[str]:
        """从文本中提取关键词

        使用jieba分词 + 停用词过滤

        Args:
            text: 输入文本

        Returns:
            List[str]: 关键词列表（按出现顺序）
        """
        # 尝试导入jieba，如果失败则使用简单分词
        try:
            import jieba
            words = jieba.lcut(text)
        except ImportError:
            # 降级：简单按空格和标点分词
            words = text.replace("，", " ").replace("？", " ").replace("？", " ").split()

        # 过滤停用词和短词
        keywords = [
            w.strip()
            for w in words
            if w.strip() and len(w.strip()) >= 2 and w.strip() not in STOPWORDS
        ]

        # 返回前5个关键词（避免查询过多）
        return keywords[:5]

    async def _query_by_keyword(self, keyword: str) -> Optional[SolutionResult]:
        """根据单个关键词查询解决方案

        Args:
            keyword: 搜索关键词

        Returns:
            Optional[SolutionResult]: 匹配的解决方案
        """
        # 调用neo4j_client的模糊搜索方法
        if not hasattr(self.neo4j_client, "find_issues_by_keyword"):
            logger.warning("neo4j_client没有find_issues_by_keyword方法")
            return None

        issues = await self.neo4j_client.find_issues_by_keyword(keyword, limit=5)
        if not issues:
            return None

        # 获取第一个Issue的详细信息和关联的Action
        issue = issues[0]

        # 查询关联的Action解决方案
        actions = await self.neo4j_client.find_actions_by_issue(issue.uuid)
        if not actions:
            return None

        action = actions[0]

        # 构建返回结果
        return SolutionResult(
            issue_name=issue.name,
            issue_uuid=issue.uuid,
            solution=action.description or action.name,
            action_name=action.name,
            confidence=0.8,  # 简化处理，默认0.8
        )


# 全局单例
_graph_query_service: Optional[GraphQueryService] = None


async def get_graph_query_service(neo4j_client=None) -> Optional[GraphQueryService]:
    """获取GraphQueryService单例（异步版本）

    Args:
        neo4j_client: Neo4jClient实例，不传则自动获取

    Returns:
        Optional[GraphQueryService]: 图谱查询服务实例，Neo4j不可用时返回None
    """
    global _graph_query_service

    if _graph_query_service is None:
        if neo4j_client is None:
            from app.services.neo4j_client import get_neo4j_client

            neo4j_client = await get_neo4j_client()

        # 如果neo4j_client为None（图服务不可用），直接返回None
        if neo4j_client is None:
            return None

        _graph_query_service = GraphQueryService(neo4j_client)

    return _graph_query_service