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src/summeryanyfile/generators/chains.py
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220
src/summeryanyfile/generators/chains.py
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"""
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处理链管理器 - 管理LangChain处理链
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"""
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from typing import Dict, Any
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import logging
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from langchain_core.language_models.chat_models import BaseChatModel
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import Runnable
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from ..config.prompts import PromptTemplates
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from ..utils.logger import LoggerMixin
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logger = logging.getLogger(__name__)
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class ChainManager(LoggerMixin):
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"""处理链管理器"""
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def __init__(self, llm: BaseChatModel):
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self.llm = llm
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self.prompt_templates = PromptTemplates()
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self._chains: Dict[str, Runnable] = {}
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self._setup_chains()
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def _setup_chains(self):
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"""设置所有处理链"""
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self.logger.debug("正在设置处理链...")
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# 文档结构分析链
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self._chains["structure_analysis"] = (
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self.prompt_templates.get_structure_analysis_prompt()
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| self.llm
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| StrOutputParser()
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)
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# 初始PPT框架生成链
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self._chains["initial_outline"] = (
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self.prompt_templates.get_initial_outline_prompt()
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| self.llm
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| StrOutputParser()
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)
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# 内容细化链
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self._chains["refine_outline"] = (
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self.prompt_templates.get_refine_outline_prompt()
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| self.llm
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| StrOutputParser()
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)
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# 错误恢复链
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self._chains["error_recovery"] = (
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self.prompt_templates.get_error_recovery_prompt()
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| self.llm
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| StrOutputParser()
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)
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self.logger.debug(f"已设置 {len(self._chains)} 个处理链")
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def get_chain(self, chain_name: str) -> Runnable:
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"""
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获取指定的处理链
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Args:
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chain_name: 链名称
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Returns:
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处理链实例
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Raises:
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KeyError: 链不存在
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"""
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if chain_name not in self._chains:
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raise KeyError(f"处理链不存在: {chain_name}")
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return self._chains[chain_name]
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async def invoke_chain(
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self,
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chain_name: str,
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inputs: Dict[str, Any],
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config: Dict[str, Any] = None
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) -> str:
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"""
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调用指定的处理链
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Args:
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chain_name: 链名称
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inputs: 输入参数
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config: 运行配置
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Returns:
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处理结果
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"""
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chain = self.get_chain(chain_name)
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try:
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self.logger.debug(f"调用处理链: {chain_name}")
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result = await chain.ainvoke(inputs, config or {})
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self.logger.debug(f"处理链 {chain_name} 执行成功")
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return result
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except Exception as e:
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self.logger.error(f"处理链 {chain_name} 执行失败: {e}")
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raise
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def list_chains(self) -> list:
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"""列出所有可用的处理链"""
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return list(self._chains.keys())
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def update_llm(self, llm: BaseChatModel):
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"""更新LLM并重新设置处理链"""
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self.logger.info("更新LLM并重新设置处理链")
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self.llm = llm
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self._setup_chains()
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def add_custom_chain(self, name: str, chain: Runnable):
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"""
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添加自定义处理链
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Args:
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name: 链名称
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chain: 处理链实例
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"""
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self._chains[name] = chain
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self.logger.info(f"已添加自定义处理链: {name}")
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def remove_chain(self, name: str):
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"""
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移除处理链
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Args:
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name: 链名称
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"""
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if name in self._chains:
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del self._chains[name]
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self.logger.info(f"已移除处理链: {name}")
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else:
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self.logger.warning(f"尝试移除不存在的处理链: {name}")
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class ChainExecutor:
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"""处理链执行器，提供重试和错误处理功能"""
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def __init__(self, chain_manager: ChainManager, max_retries: int = 3):
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self.chain_manager = chain_manager
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self.max_retries = max_retries
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self.logger = logging.getLogger(self.__class__.__name__)
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async def execute_with_retry(
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self,
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chain_name: str,
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inputs: Dict[str, Any],
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config: Dict[str, Any] = None
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) -> str:
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"""
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带重试的链执行
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Args:
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chain_name: 链名称
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inputs: 输入参数
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config: 运行配置
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Returns:
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处理结果
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Raises:
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Exception: 所有重试都失败后抛出最后一个异常
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"""
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last_exception = None
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for attempt in range(self.max_retries):
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try:
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result = await self.chain_manager.invoke_chain(chain_name, inputs, config)
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if attempt > 0:
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self.logger.info(f"处理链 {chain_name} 在第 {attempt + 1} 次尝试后成功")
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return result
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except Exception as e:
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last_exception = e
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self.logger.warning(f"处理链 {chain_name} 第 {attempt + 1} 次尝试失败: {e}")
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if attempt < self.max_retries - 1:
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# 可以在这里添加退避策略
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import asyncio
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await asyncio.sleep(1 * (attempt + 1)) # 简单的线性退避
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self.logger.error(f"处理链 {chain_name} 在 {self.max_retries} 次尝试后仍然失败")
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raise last_exception
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async def execute_with_fallback(
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self,
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primary_chain: str,
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fallback_chain: str,
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inputs: Dict[str, Any],
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fallback_inputs: Dict[str, Any] = None,
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config: Dict[str, Any] = None
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) -> str:
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"""
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带回退的链执行
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Args:
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primary_chain: 主要处理链
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fallback_chain: 回退处理链
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inputs: 主要链的输入参数
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fallback_inputs: 回退链的输入参数
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config: 运行配置
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Returns:
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处理结果
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"""
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try:
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return await self.execute_with_retry(primary_chain, inputs, config)
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except Exception as e:
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self.logger.warning(f"主要处理链 {primary_chain} 失败，尝试回退链 {fallback_chain}: {e}")
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fallback_inputs = fallback_inputs or inputs
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try:
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return await self.execute_with_retry(fallback_chain, fallback_inputs, config)
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except Exception as fallback_e:
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self.logger.error(f"回退处理链 {fallback_chain} 也失败了: {fallback_e}")
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raise fallback_e
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