"""
Elasticsearch 连接管理器（向后兼容接口）

该文件提供与旧版 es_conn.py 兼容的接口，同时内部使用新的工程化模块。
"""
import re
import json
import time
from typing import Any, List, Dict, Optional, Union
from elasticsearch import Elasticsearch, helpers
from elasticsearch.helpers import bulk, BulkIndexError
from elastic_transport import ConnectionTimeout
from elasticsearch.exceptions import NotFoundError

from services.utils.es.base import ESConnection as _ESConnection
from services.utils.es.index import IndexManager
from services.utils.es.document import DocumentManager
from services.utils.es.search import SearchManager

# 单例装饰器
class singleton:
    def __init__(self, cls):
        self.cls = cls
        self._instance = None
    
    def __call__(self, *args, **kwargs):
        if self._instance is None:
            self._instance = self.cls(*args, **kwargs)
        return self._instance

@singleton
class ESConnection:
    """
    Elasticsearch 连接管理器（向后兼容）
    支持：
    - 单例模式
    - 连接池管理
    - CRUD操作
    - 向量相似度检索 + 全文检索的混合检索
    - 动态模板映射
    """
    
    def __init__(self, hosts: List[str] = None, **kwargs):
        """
        初始化 Elasticsearch 连接
        
        Args:
            hosts: Elasticsearch 主机列表，格式如 ["http://localhost:9200"]
            **kwargs: 其他 Elasticsearch 客户端配置参数
        """
        # 使用新的 ESConnection 作为底层连接
        self._es_conn = _ESConnection(hosts=hosts, **kwargs)
        
        # 初始化管理器
        self.index_manager = IndexManager(self._es_conn)
        self.document_manager = DocumentManager(self._es_conn)
        self.search_manager = SearchManager(self._es_conn)
        
        # 向后兼容属性
        self.es = self._es_conn.get_client()
        self.dynamic_templates = self._es_conn.dynamic_templates
    
    def _get_dynamic_templates(self) -> Dict[str, Any]:
        """
        获取动态模板映射配置（向后兼容方法）
        """
        return self.dynamic_templates
    
    def create_index(self, index_name: str, mappings: Dict[str, Any] = None, settings: Dict[str, Any] = None) -> bool:
        """
        创建索引
        """
        return self.index_manager.create_index(index_name, mappings, settings)
    
    def insert(self, index_name: str, document: Dict[str, Any], id: str = None, refresh: bool = False) -> bool:
        """
        插入单个文档
        """
        return self.document_manager.insert(index_name, document, id, refresh)
    
    def bulk_insert(self, index_name: str, documents: List[Dict[str, Any]], refresh: bool = False) -> Dict[str, Any]:
        """
        批量插入文档
        """
        return self.document_manager.bulk_insert(index_name, documents, refresh)
    
    def update(self, index_name: str, id: str, update_body: Dict[str, Any], refresh: bool = False) -> bool:
        """
        更新文档
        """
        return self.document_manager.update(index_name, id, update_body, refresh)
    
    def delete(self, index_name: str, id: str, refresh: bool = False) -> bool:
        """
        删除文档
        """
        return self.document_manager.delete(index_name, id, refresh)
    
    def delete_by_query(self, index_name: str, query: Dict[str, Any], refresh: bool = False) -> Dict[str, Any]:
        """
        按查询条件删除文档
        """
        return self.document_manager.delete_by_query(index_name, query, refresh)
    
    def get(self, index_name: str, id: str, fields: List[str] = None) -> Optional[Dict[str, Any]]:
        """
        获取单个文档
        """
        return self.document_manager.get(index_name, id, fields)
    
    def search(self, index_name: str, query: Dict[str, Any], size: int = 10, from_: int = 0, 
               fields: List[str] = None, highlight: Dict[str, Any] = None) -> Dict[str, Any]:
        """
        搜索文档
        """
        return self.search_manager.search(index_name, query, size, from_, fields, highlight)
    
    def hybrid_search(self, index_name: str, text_query: str, vector_field: str, vector: List[float], 
                     size: int = 10, from_: int = 0, fields: List[str] = None, 
                     text_weight: float = 0.5, vector_weight: float = 0.5) -> Dict[str, Any]:
        """
        混合检索：向量相似度检索 + 全文检索
        """
        return self.search_manager.hybrid_search(index_name, text_query, vector_field, vector, 
                                               size, from_, fields, text_weight, vector_weight)
    
    def knn_search(self, index_name: str, vector_field: str, vector: List[float], 
                  k: int = 10, filter_query: Dict[str, Any] = None) -> Dict[str, Any]:
        """
        向量相似度检索（k-NN）
        """
        return self.search_manager.knn_search(index_name, vector_field, vector, k, filter_query)
    
    def close(self):
        """
        关闭 Elasticsearch 连接
        """
        self._es_conn.close()