import json
from typing import Dict, Any
from rich.traceback import install
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
from src.common.logger_manager import get_logger
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
from src.individuality.individuality import individuality
from src.chat.focus_chat.planners.action_manager import ActionManager
from src.chat.normal_chat.normal_prompt import prompt_builder
from src.chat.message_receive.message import MessageThinking
from json_repair import repair_json

logger = get_logger("normal_chat_planner")

install(extra_lines=3)


def init_prompt():
    Prompt(
        """
你的自我认知是：
{self_info_block}

注意，除了下面动作选项之外，你在聊天中不能做其他任何事情，这是你能力的边界，现在请你选择合适的action:

{action_options_text}

重要说明：
- "no_action" 表示只进行普通聊天回复，不执行任何额外动作
- 其他action表示在普通回复的基础上，执行相应的额外动作

你必须从上面列出的可用action中选择一个，并说明原因。
你的决策必须以严格的 JSON 格式输出，且仅包含 JSON 内容，不要有任何其他文字或解释。

{moderation_prompt}

当前聊天上下文：
{chat_context}

基于以上聊天上下文和用户的最新消息，选择最合适的action。

请你以下面格式输出你选择的action：
{{
    "action": "action_name",
    "reasoning": "说明你做出该action的原因",
    "参数1": "参数1的值",
    "参数2": "参数2的值",
    "参数3": "参数3的值",
    ...
}}

请输出你的决策 JSON：""",
        "normal_chat_planner_prompt",
    )

    Prompt(
        """
action_name: {action_name}
    描述：{action_description}
    参数：
{action_parameters}
    动作要求：
{action_require}""",
        "normal_chat_action_prompt",
    )


class NormalChatPlanner:
    def __init__(self, log_prefix: str, action_manager: ActionManager):
        self.log_prefix = log_prefix
        # LLM规划器配置
        self.planner_llm = LLMRequest(
            model=global_config.model.normal_chat_2,
            max_tokens=1000,
            request_type="normal_chat.planner",  # 用于normal_chat动作规划
        )

        self.action_manager = action_manager

    async def plan(self, message: MessageThinking, sender_name: str = "某人") -> Dict[str, Any]:
        """
        Normal Chat 规划器: 使用LLM根据上下文决定做出什么动作。

        参数:
            message: 思考消息对象
            sender_name: 发送者名称
        """

        action = "no_action"  # 默认动作改为no_action
        reasoning = "规划器初始化默认"
        action_data = {}

        try:
            # 设置默认值
            nickname_str = ""
            for nicknames in global_config.bot.alias_names:
                nickname_str += f"{nicknames},"
            name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"

            personality_block = individuality.get_personality_prompt(x_person=2, level=2)
            identity_block = individuality.get_identity_prompt(x_person=2, level=2)

            self_info = name_block + personality_block + identity_block

            # 获取当前可用的动作
            current_available_actions = self.action_manager.get_using_actions()

            # 如果没有可用动作或只有no_action动作，直接返回no_action
            if not current_available_actions or (
                len(current_available_actions) == 1 and "no_action" in current_available_actions
            ):
                logger.debug(f"{self.log_prefix}规划器: 没有可用动作或只有no_action动作，返回no_action")
                return {
                    "action_result": {"action_type": action, "action_data": action_data, "reasoning": reasoning},
                    "chat_context": "",
                    "action_prompt": "",
                }

            # 构建normal_chat的上下文 (使用与normal_chat相同的prompt构建方法)
            chat_context = await prompt_builder.build_prompt(
                message_txt=message.processed_plain_text,
                sender_name=sender_name,
                chat_stream=message.chat_stream,
            )

            # 构建planner的prompt
            prompt = await self.build_planner_prompt(
                self_info_block=self_info,
                chat_context=chat_context,
                current_available_actions=current_available_actions,
            )

            if not prompt:
                logger.warning(f"{self.log_prefix}规划器: 构建提示词失败")
                return {
                    "action_result": {"action_type": action, "action_data": action_data, "reasoning": reasoning},
                    "chat_context": chat_context,
                    "action_prompt": "",
                }

            # 使用LLM生成动作决策
            try:
                content, reasoning_content, model_name = await self.planner_llm.generate_response(prompt)
                logger.debug(f"{self.log_prefix}规划器原始响应: {content}")

                # 解析JSON响应
                try:
                    # 尝试修复JSON
                    fixed_json = repair_json(content)
                    action_result = json.loads(fixed_json)

                    action = action_result.get("action", "no_action")
                    reasoning = action_result.get("reasoning", "未提供原因")

                    # 提取其他参数作为action_data
                    action_data = {k: v for k, v in action_result.items() if k not in ["action", "reasoning"]}

                    # 验证动作是否在可用动作列表中
                    if action not in current_available_actions:
                        logger.warning(f"{self.log_prefix}规划器选择了不可用的动作: {action}, 回退到no_action")
                        action = "no_action"
                        reasoning = f"选择的动作{action}不在可用列表中，回退到no_action"
                        action_data = {}

                except json.JSONDecodeError as e:
                    logger.warning(f"{self.log_prefix}规划器JSON解析失败: {e}, 内容: {content}")
                    action = "no_action"
                    reasoning = "JSON解析失败，使用默认动作"
                    action_data = {}

            except Exception as e:
                logger.error(f"{self.log_prefix}规划器LLM调用失败: {e}")
                action = "no_action"
                reasoning = "LLM调用失败，使用默认动作"
                action_data = {}

        except Exception as outer_e:
            logger.error(f"{self.log_prefix}规划器异常: {outer_e}")
            chat_context = "无法获取聊天上下文"  # 设置默认值
            prompt = ""  # 设置默认值
            action = "no_action"
            reasoning = "规划器出现异常，使用默认动作"
            action_data = {}

        logger.debug(f"{self.log_prefix}规划器决策动作:{action}, 动作信息: '{action_data}', 理由: {reasoning}")

        # 恢复到默认动作集
        self.action_manager.restore_actions()
        logger.debug(
            f"{self.log_prefix}规划后恢复到默认动作集, 当前可用: {list(self.action_manager.get_using_actions().keys())}"
        )

        action_result = {"action_type": action, "action_data": action_data, "reasoning": reasoning}

        plan_result = {
            "action_result": action_result,
            "chat_context": chat_context,
            "action_prompt": prompt,
        }

        return plan_result

    async def build_planner_prompt(
        self,
        self_info_block: str,
        chat_context: str,
        current_available_actions: Dict[str, Any],
    ) -> str:
        """构建 Normal Chat Planner LLM 的提示词"""
        try:
            # 构建动作选项文本
            action_options_text = ""
            for action_name, action_info in current_available_actions.items():
                action_description = action_info.get("description", "")
                action_parameters = action_info.get("parameters", {})
                action_require = action_info.get("require", [])

                # 格式化参数
                parameters_text = ""
                for param_name, param_desc in action_parameters.items():
                    parameters_text += f"    - {param_name}: {param_desc}\n"

                # 格式化要求
                require_text = ""
                for req in action_require:
                    require_text += f"    - {req}\n"

                # 构建单个动作的提示
                action_prompt = await global_prompt_manager.format_prompt(
                    "normal_chat_action_prompt",
                    action_name=action_name,
                    action_description=action_description,
                    action_parameters=parameters_text,
                    action_require=require_text,
                )
                action_options_text += action_prompt + "\n\n"

            # 审核提示
            moderation_prompt = "请确保你的回复符合平台规则，避免不当内容。"

            # 使用模板构建最终提示词
            prompt = await global_prompt_manager.format_prompt(
                "normal_chat_planner_prompt",
                self_info_block=self_info_block,
                action_options_text=action_options_text,
                moderation_prompt=moderation_prompt,
                chat_context=chat_context,
            )

            return prompt

        except Exception as e:
            logger.error(f"{self.log_prefix}构建Planner提示词失败: {e}")
            return ""


init_prompt()