import random
import json
from typing import Optional, List, Dict, Any

from src.common.logger import get_logger
from src.config.config import global_config


logger = get_logger("learner_utils")


def _compute_weights(population: List[Dict]) -> List[float]:
    """
    根据表达的count计算权重，范围限定在1~5之间。
    count越高，权重越高，但最多为基础权重的5倍。
    """
    if not population:
        return []

    counts = []
    for item in population:
        count = item.get("count", 1)
        try:
            count_value = float(count)
        except (TypeError, ValueError):
            count_value = 1.0
        counts.append(max(count_value, 0.0))

    min_count = min(counts)
    max_count = max(counts)

    if max_count == min_count:
        weights = [1.0 for _ in counts]
    else:
        weights = []
        for count_value in counts:
            # 线性映射到[1,5]区间
            normalized = (count_value - min_count) / (max_count - min_count)
            weights.append(1.0 + normalized * 4.0)  # 1~5

    return weights


def weighted_sample(population: List[Dict], k: int) -> List[Dict]:
    """
    随机抽样函数

    Args:
        population: 总体数据列表
        k: 需要抽取的数量

    Returns:
        List[Dict]: 抽取的数据列表
    """
    if not population or k <= 0:
        return []

    if len(population) <= k:
        return population.copy()

    selected: List[Dict] = []
    population_copy = population.copy()

    for _ in range(min(k, len(population_copy))):
        weights = _compute_weights(population_copy)
        total_weight = sum(weights)
        if total_weight <= 0:
            # 回退到均匀随机
            idx = random.randint(0, len(population_copy) - 1)
            selected.append(population_copy.pop(idx))
            continue

        threshold = random.uniform(0, total_weight)
        cumulative = 0.0
        for idx, weight in enumerate(weights):
            cumulative += weight
            if threshold <= cumulative:
                selected.append(population_copy.pop(idx))
                break

    return selected


def parse_chat_id_list(chat_id_value: Any) -> List[List[Any]]:
    """
    解析chat_id字段，兼容旧格式（字符串）和新格式（JSON列表）

    Args:
        chat_id_value: 可能是字符串（旧格式）或JSON字符串（新格式）

    Returns:
        List[List[Any]]: 格式为 [[chat_id, count], ...] 的列表
    """
    if not chat_id_value:
        return []

    # 如果是字符串，尝试解析为JSON
    if isinstance(chat_id_value, str):
        # 尝试解析JSON
        try:
            parsed = json.loads(chat_id_value)
            if isinstance(parsed, list):
                # 新格式：已经是列表
                return parsed
            elif isinstance(parsed, str):
                # 解析后还是字符串，说明是旧格式
                return [[parsed, 1]]
            else:
                # 其他类型，当作旧格式处理
                return [[str(chat_id_value), 1]]
        except (json.JSONDecodeError, TypeError):
            # 解析失败，当作旧格式（纯字符串）
            return [[str(chat_id_value), 1]]
    elif isinstance(chat_id_value, list):
        # 已经是列表格式
        return chat_id_value
    else:
        # 其他类型，转换为旧格式
        return [[str(chat_id_value), 1]]


def update_chat_id_list(chat_id_list: List[List[Any]], target_chat_id: str, increment: int = 1) -> List[List[Any]]:
    """
    更新chat_id列表，如果target_chat_id已存在则增加计数，否则添加新条目

    Args:
        chat_id_list: 当前的chat_id列表，格式为 [[chat_id, count], ...]
        target_chat_id: 要更新或添加的chat_id
        increment: 增加的计数，默认为1

    Returns:
        List[List[Any]]: 更新后的chat_id列表
    """
    item = _find_chat_id_item(chat_id_list, target_chat_id)
    if item is not None:
        # 找到匹配的chat_id，增加计数
        if len(item) >= 2:
            item[1] = (item[1] if isinstance(item[1], (int, float)) else 0) + increment
        else:
            item.append(increment)
    else:
        # 未找到，添加新条目
        chat_id_list.append([target_chat_id, increment])

    return chat_id_list


def _find_chat_id_item(chat_id_list: List[List[Any]], target_chat_id: str) -> Optional[List[Any]]:
    """
    在chat_id列表中查找匹配的项（辅助函数）

    Args:
        chat_id_list: chat_id列表，格式为 [[chat_id, count], ...]
        target_chat_id: 要查找的chat_id

    Returns:
        如果找到则返回匹配的项，否则返回None
    """
    for item in chat_id_list:
        if isinstance(item, list) and len(item) >= 1 and str(item[0]) == str(target_chat_id):
            return item
    return None


def chat_id_list_contains(chat_id_list: List[List[Any]], target_chat_id: str) -> bool:
    """
    检查chat_id列表中是否包含指定的chat_id

    Args:
        chat_id_list: chat_id列表，格式为 [[chat_id, count], ...]
        target_chat_id: 要查找的chat_id

    Returns:
        bool: 如果包含则返回True
    """
    return _find_chat_id_item(chat_id_list, target_chat_id) is not None


def contains_bot_self_name(content: str) -> bool:
    """
    判断词条是否包含机器人的昵称或别名
    """
    if not content:
        return False

    bot_config = getattr(global_config, "bot", None)
    if not bot_config:
        return False

    target = content.strip().lower()
    nickname = str(getattr(bot_config, "nickname", "") or "").strip().lower()
    alias_names = [str(alias or "").strip().lower() for alias in getattr(bot_config, "alias_names", []) or []]

    candidates = [name for name in [nickname, *alias_names] if name]

    return any(name in target for name in candidates)


def is_bot_message(msg: Any) -> bool:
    """判断消息是否来自机器人自身。"""
    if msg is None:
        return False

    bot_config = getattr(global_config, "bot", None)
    if not bot_config:
        return False

    user_id = str(getattr(msg, "user_id", "") or getattr(getattr(msg, "user_info", None), "user_id", "") or "").strip()
    if not user_id:
        return False

    known_accounts = {
        str(getattr(bot_config, "qq_account", "") or "").strip(),
        str(getattr(bot_config, "telegram_account", "") or "").strip(),
    }

    for platform in getattr(bot_config, "platforms", []) or []:
        account = str(getattr(platform, "account", "") or getattr(platform, "id", "") or "").strip()
        if account:
            known_accounts.add(account)

    return user_id in {account for account in known_accounts if account}


# def build_context_paragraph(messages: List[Any], center_index: int) -> Optional[str]:
#     """
#     构建包含中心消息上下文的段落（前3条+后3条），使用标准的 readable builder 输出
#     """
#     if not messages or center_index < 0 or center_index >= len(messages):
#         return None

#     context_start = max(0, center_index - 3)
#     context_end = min(len(messages), center_index + 1 + 3)
#     context_messages = messages[context_start:context_end]

#     if not context_messages:
#         return None

#     try:
#         paragraph = build_readable_messages(
#             messages=context_messages,
#             replace_bot_name=True,
#             timestamp_mode="relative",
#             read_mark=0.0,
#             truncate=False,
#             show_actions=False,
#             show_pic=True,
#             message_id_list=None,
#             remove_emoji_stickers=False,
#             pic_single=True,
#         )
#     except Exception as e:
#         logger.warning(f"构建上下文段落失败: {e}")
#         return None

#     paragraph = paragraph.strip()
#     return paragraph or None


# def is_bot_message(msg: Any) -> bool:
#     """判断消息是否来自机器人自身"""
#     if msg is None:
#         return False

#     bot_config = getattr(global_config, "bot", None)
#     if not bot_config:
#         return False

#     platform = (
#         str(getattr(msg, "user_platform", "") or getattr(getattr(msg, "user_info", None), "platform", "") or "")
#         .strip()
#         .lower()
#     )
#     user_id = str(getattr(msg, "user_id", "") or getattr(getattr(msg, "user_info", None), "user_id", "") or "").strip()

#     if not platform or not user_id:
#         return False

#     platform_accounts = {}
#     try:
#         platform_accounts = parse_platform_accounts(getattr(bot_config, "platforms", []) or [])
#     except Exception:
#         platform_accounts = {}

#     bot_accounts: Dict[str, str] = {}
#     qq_account = str(getattr(bot_config, "qq_account", "") or "").strip()
#     if qq_account:
#         bot_accounts["qq"] = qq_account

#     telegram_account = str(getattr(bot_config, "telegram_account", "") or "").strip()
#     if telegram_account:
#         bot_accounts["telegram"] = telegram_account

#     for plat, account in platform_accounts.items():
#         if account and plat not in bot_accounts:
#             bot_accounts[plat] = account

#     bot_account = bot_accounts.get(platform)
#     return bool(bot_account and user_id == bot_account)


# def parse_expression_response(response: str) -> Tuple[List[Tuple[str, str, str]], List[Tuple[str, str]]]:
#     """
#     解析 LLM 返回的表达风格总结和黑话 JSON，提取两个列表。

#     期望的 JSON 结构：
#     [
#         {"situation": "AAAAA", "style": "BBBBB", "source_id": "3"},  // 表达方式
#         {"content": "词条", "source_id": "12"},  // 黑话
#         ...
#     ]

#     Returns:
#         Tuple[List[Tuple[str, str, str]], List[Tuple[str, str]]]:
#             第一个列表是表达方式 (situation, style, source_id)
#             第二个列表是黑话 (content, source_id)
#     """
#     if not response:
#         return [], []

#     raw = response.strip()

#     # 尝试提取 ```json 代码块
#     json_block_pattern = r"```json\s*(.*?)\s*```"
#     match = re.search(json_block_pattern, raw, re.DOTALL)
#     if match:
#         raw = match.group(1).strip()
#     else:
#         # 去掉可能存在的通用 ``` 包裹
#         raw = re.sub(r"^```\s*", "", raw, flags=re.MULTILINE)
#         raw = re.sub(r"```\s*$", "", raw, flags=re.MULTILINE)
#         raw = raw.strip()

#     parsed = None
#     expressions: List[Tuple[str, str, str]] = []  # (situation, style, source_id)
#     jargon_entries: List[Tuple[str, str]] = []  # (content, source_id)

#     try:
#         # 优先尝试直接解析
#         if raw.startswith("[") and raw.endswith("]"):
#             parsed = json.loads(raw)
#         else:
#             repaired = repair_json(raw)
#             if isinstance(repaired, str):
#                 parsed = json.loads(repaired)
#             else:
#                 parsed = repaired
#     except Exception as parse_error:
#         # 如果解析失败，尝试修复中文引号问题
#         # 使用状态机方法，在 JSON 字符串值内部将中文引号替换为转义的英文引号
#         try:

#             def fix_chinese_quotes_in_json(text):
#                 """使用状态机修复 JSON 字符串值中的中文引号"""
#                 result = []
#                 i = 0
#                 in_string = False
#                 escape_next = False

#                 while i < len(text):
#                     char = text[i]

#                     if escape_next:
#                         # 当前字符是转义字符后的字符，直接添加
#                         result.append(char)
#                         escape_next = False
#                         i += 1
#                         continue

#                     if char == "\\":
#                         # 转义字符
#                         result.append(char)
#                         escape_next = True
#                         i += 1
#                         continue

#                     if char == '"' and not escape_next:
#                         # 遇到英文引号，切换字符串状态
#                         in_string = not in_string
#                         result.append(char)
#                         i += 1
#                         continue

#                     if in_string:
#                         # 在字符串值内部，将中文引号替换为转义的英文引号
#                         if char == '"':  # 中文左引号 U+201C
#                             result.append('\\"')
#                         elif char == '"':  # 中文右引号 U+201D
#                             result.append('\\"')
#                         else:
#                             result.append(char)
#                     else:
#                         # 不在字符串内，直接添加
#                         result.append(char)

#                     i += 1

#                 return "".join(result)

#             fixed_raw = fix_chinese_quotes_in_json(raw)

#             # 再次尝试解析
#             if fixed_raw.startswith("[") and fixed_raw.endswith("]"):
#                 parsed = json.loads(fixed_raw)
#             else:
#                 repaired = repair_json(fixed_raw)
#                 if isinstance(repaired, str):
#                     parsed = json.loads(repaired)
#                 else:
#                     parsed = repaired
#         except Exception as fix_error:
#             logger.error(f"解析表达风格 JSON 失败，初始错误: {type(parse_error).__name__}: {str(parse_error)}")
#             logger.error(f"修复中文引号后仍失败，错误: {type(fix_error).__name__}: {str(fix_error)}")
#             logger.error(f"解析表达风格 JSON 失败，原始响应：{response}")
#             logger.error(f"处理后的 JSON 字符串（前500字符）：{raw[:500]}")
#             return [], []

#     if isinstance(parsed, dict):
#         parsed_list = [parsed]
#     elif isinstance(parsed, list):
#         parsed_list = parsed
#     else:
#         logger.error(f"表达风格解析结果类型异常: {type(parsed)}, 内容: {parsed}")
#         return [], []

#     for item in parsed_list:
#         if not isinstance(item, dict):
#             continue

#         # 检查是否是表达方式条目（有 situation 和 style）
#         situation = str(item.get("situation", "")).strip()
#         style = str(item.get("style", "")).strip()
#         source_id = str(item.get("source_id", "")).strip()

#         if situation and style and source_id:
#             # 表达方式条目
#             expressions.append((situation, style, source_id))
#         elif item.get("content"):
#             # 黑话条目（有 content 字段）
#             content = str(item.get("content", "")).strip()
#             source_id = str(item.get("source_id", "")).strip()
#             if content and source_id:
#                 jargon_entries.append((content, source_id))

#     return expressions, jargon_entries