会话缓冲区
这本笔记本展示了如何使用ConversationBufferMemory。这种记忆功能允许存储消息,然后以变量的形式提取消息。
我们首先可以将其作为字符串提取。
from langchain.memory import ConversationBufferMemory
memory = ConversationBufferMemory()
memory.save_context({"input": "hi"}, {"output": "whats up"})
memory.load_memory_variables({})
{'history': 'Human: hi\nAI: whats up'}
我们还可以获得消息列表形式的历史记录(如果您使用聊天模型,这将非常有用)。
memory = ConversationBufferMemory(return_messages=True)
memory.save_context({"input": "hi"}, {"output": "whats up"})
memory.load_memory_variables({})
{'history': [HumanMessage(content='hi', additional_kwargs={}),
AIMessage(content='whats up', additional_kwargs={})]}
在链中使用
最后,让我们看看如何在链中使用它(设置verbose=True
以便我们可以看到提示)。
from langchain_openai import OpenAI
from langchain.chains import ConversationChain
llm = OpenAI(temperature=0)
conversation = ConversationChain(
llm=llm,
verbose=True,
memory=ConversationBufferMemory()
)
conversation.predict(input="Hi there!")
> 进入新的ConversationChain链...
格式化后的提示:
以下是人类和AI之间友好的对话。AI健谈,并从其上下文中提供大量具体细节。如果AI不知道问题的答案,则如实表示不知道。
当前对话:
人类: Hi there!
AI:
> 完成链插入。
" Hi there! It's nice to meet you. How can I help you today?"
conversation.predict(input="I'm doing well! Just having a conversation with an AI.")
> 进入新的ConversationChain链...
格式化后的提示:
以下是人类和AI之间友好的对话。AI健谈,并从其上下文中提供大量具体细节。如果AI不知道问题的答案,则如实表示不知道。
当前对话:
人类: Hi there!
AI: Hi there! It's nice to meet you. How can I help you today?
人类: I'm doing well! Just having a conversation with an AI.
AI:
> 完成链插入。
" That's great! It's always nice to have a conversation with someone new. What would you like to talk about?"
conversation.predict(input="Tell me about yourself.")
> 进入新的ConversationChain链...
格式化后的提示:
以下是人类和AI之间友好的对话。AI健谈,并从其上下文中提供大量具体细节。如果AI不知道问题的答案,则如实表示不知道。
当前对话:
人类: Hi there!
AI: Hi there! It's nice to meet you. How can I help you today?
人类: I'm doing well! Just having a conversation with an AI.
AI: That's great! It's always nice to have a conversation with someone new. What would you like to talk about?
人类: Tell me about yourself.
AI:
> 完成链插入。
" Sure! I'm an AI created to help people with their everyday tasks. I'm programmed to understand natural language and provide helpful information. I'm also constantly learning and updating my knowledge base so I can provide more accurate and helpful answers."