"""日志回调处理器模块"""

import logging
from typing import Any, Optional, Dict, List
from langchain_core.callbacks import BaseCallbackHandler
from langchain_core.messages import BaseMessage


class LoggingCallbackHandler(BaseCallbackHandler):
    """自定义的 CallbackHandler，使用项目的 logger 来记录日志"""

    def __init__(self, logger_name: str = 'app'):
        self.logger = logging.getLogger(logger_name)

    # def on_chat_model_start(
    #     self,
    #     serialized: Dict[str, Any],
    #     messages: List[List[BaseMessage]],
    #     **kwargs: Any,
    # ) -> None:
    #     """当 Chat 模型开始时调用"""
    #     self.logger.info("✅ Chat Model Start - Messages:")
    #     for msg_list in messages:
    #         for msg in msg_list:
    #             msg_type = msg.__class__.__name__
    #             content = msg.content if hasattr(msg, 'content') else str(msg)
    #             self.logger.info(f"[{msg_type}] {content}")

    # def on_llm_start(self, serialized: Dict[str, Any], prompts: Any, **kwargs: Any) -> None:
    #     """当 LLM 开始时调用（用于普通 LLM，非 Chat 模型）"""
    #     self.logger.info("✅ LLM Start - Input:")
    #     for prompt in prompts:
    #         self.logger.info(str(prompt))


    def on_llm_end(self, response, **kwargs: Any) -> None:
        """当 LLM 结束时调用"""
        self.logger.info("✅ LLM End - Output:")

        # 打印生成的文本
        if hasattr(response, 'generations') and response.generations:
            for gen_idx, generation_list in enumerate(response.generations):
                for msg_idx, generation in enumerate(generation_list):
                    # ChatGeneration: 使用 text 属性获取内容
                    if hasattr(generation, 'text') and generation.text:
                        for line in generation.text.split("\n"):
                            if line.strip():
                                self.logger.info(f"  {line}")
                    # 如果有 message 属性，输出额外信息（tool_calls 等）
                    if hasattr(generation, 'message') and generation.message:
                        msg = generation.message
                        content = msg.content if hasattr(msg, 'content') else ''
                        if not content or (isinstance(content, str) and not content.strip()):
                            self.logger.info(f"  [EMPTY content]")
                        tool_calls = msg.tool_calls if hasattr(msg, 'tool_calls') else []
                        if tool_calls:
                            self.logger.info(f"  [tool_calls: {[tc.get('name', '') for tc in tool_calls]}")

    def on_llm_error(
        self, error: Exception, **kwargs: Any
    ) -> None:
        """当 LLM 出错时调用"""
        self.logger.error(f"❌ LLM Error: {error}")

    def on_tool_start(
        self, serialized: Optional[Dict[str, Any]], input_str: str, **kwargs: Any
    ) -> None:
        """当工具开始调用时调用"""
        if serialized is None:
            tool_name = 'unknown_tool'
        else:
            tool_name = serialized.get('name', 'unknown_tool')
        self.logger.info(f"🔧 Tool Start - {tool_name} with input: {str(input_str)[:1000]}")

    def on_tool_end(self, output: str, **kwargs: Any) -> None:
        """当工具调用结束时调用"""
        self.logger.info(f"✅ Tool End Output: {output}")

    def on_tool_error(
        self, error: Exception, **kwargs: Any
    ) -> None:
        """当工具调用出错时调用"""
        self.logger.error(f"❌ Tool Error: {error}")