配置Histroy(Python SDK)

History缓存，用于存储历史对话信息，辅助模型理解上下文信息，历史消息对有固定窗口、消息摘要等策略。

• 初始化：消息记录支持不同的存储方式， 如内存、DCS（Redis）和RDS（Sql）。

  from pangukitsappdev.memory.sql_message_history import SQLMessageHistory
  from pangukitsappdev.api.memory.cache.cache_config import ServerInfoSql, ServerInfoRedis
  from pangukitsappdev.api.memory.message_history_config import MessageHistoryConfig
  from pangukitsappdev.memory.redis_message_history import RedisMessageHistory
  from langchain.memory import ChatMessageHistory
  # 内存型:
  chat_message = ChatMessageHistory()
  
  # Redis:
  redis_chat_message = RedisMessageHistory(msg_history_config=MessageHistoryConfig(store_name="redis",
                                                                                   server_info=ServerInfoRedis(env_prefix="sdk.memory.dcs"),
                                                                                   session_tag="test-memory-0624"))
  # Sql:
  sql_chat_message = SQLMessageHistory(msg_history_config=MessageHistoryConfig(store_name="sql",
                                                                               server_info=ServerInfoSql(env_prefix="sdk.memory.rds"),
                                                                               session_tag="test-memory-0624"))

• 添加、查找、删除数据。

  # 更新数据
  chat_message.add_ai_message("i am ai.")
  chat_message.add_user_message("i am tester.")
  # 查找数据
  contents = [msg.content for msg in chat_message.messages]
  # 清理
  chat_message.clear()

• 消息策略（windows-size）：将固定轮次历史对话信息，作为历史上下文信息。

  from langchain.memory import ChatMessageHistory, ConversationBufferWindowMemory
  from pangukitsappdev.api.memory.cache.cache_config import ServerInfoRedis
  # 历史消息存储
  redis_chat_message = RedisMessageHistory(msg_history_config=MessageHistoryConfig(store_name="redis",
                                                                                   server_info=ServerInfoRedis(env_prefix="sdk.memory.dcs"),
                                                                                   session_tag="test-memory"))
  # 固定窗口策略: langchain.memory.buffer_window.ConversationBufferWindowMemory
  memory = ConversationBufferWindowMemory(k=3, chat_memory=redis_chat_message)
  
  memory.chat_memory.add_user_message("This is me, the human")
  memory.chat_memory.add_ai_message("This is me, the AI")
  print(memory.chat_memory.messages)
  memory.chat_memory.clear()

• 消息策略（信息摘要）
  将历史消息进行摘要后，作为历史上下文信息。

  from pangukitsappdev.memory.conversation_summory_memory import ConversationSummaryBufferMemory
  from pangukitsappdev.api.skill.base import SimpleSkill
  from pangukitsappdev.prompt.prompt_tmpl import PromptTemplates
  # 历史消息存储
  redis_chat_message = RedisMessageHistory(msg_history_config=MessageHistoryConfig(store_name="redis",
                                                                                   server_info=ServerInfoRedis(env_prefix="sdk.memory.dcs"),
                                                                                   session_tag="test-memory"))
  # 摘要策略
  memory = ConversationSummaryBufferMemory(summary_skill=SimpleSkill(PromptTemplates.get("memory_summary"), LLMs.of("pangu")),
                                           chat_memory=redis_chat_message)
  
  memory.chat_memory.add_user_message("This is me, the human")
  memory.chat_memory.add_ai_message("This is me, the AI")
  print(memory.chat_memory.messages)
  memory.chat_memory.clear()