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如何合并相同类型的连续消息

某些模型不支持传入相同类型的连续消息（也称为相同消息类型的“运行”）。

merge_message_runs 工具使得合并相同类型的连续消息变得容易。

设置​

%pip install -qU langchain-core langchain-anthropic

基本用法​

from langchain_core.messages import (
    AIMessage,
    HumanMessage,
    SystemMessage,
    merge_message_runs,
)

messages = [
    SystemMessage("you're a good assistant."),
    SystemMessage("you always respond with a joke."),
    HumanMessage([{"type": "text", "text": "i wonder why it's called langchain"}]),
    HumanMessage("and who is harrison chasing anyways"),
    AIMessage(
        'Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!'
    ),
    AIMessage("Why, he's probably chasing after the last cup of coffee in the office!"),
]

merged = merge_message_runs(messages)
print("\n\n".join([repr(x) for x in merged]))
SystemMessage(content="you're a good assistant.\nyou always respond with a joke.", additional_kwargs={}, response_metadata={})

HumanMessage(content=[{'type': 'text', 'text': "i wonder why it's called langchain"}, 'and who is harrison chasing anyways'], additional_kwargs={}, response_metadata={})

AIMessage(content='Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!\nWhy, he\'s probably chasing after the last cup of coffee in the office!', additional_kwargs={}, response_metadata={})

请注意，如果要合并的消息之一是内容块列表，则合并后的消息将具有内容块列表。如果要合并的两个消息都有字符串内容，则这些内容将用换行符连接。

链式操作​

merge_message_runs 可以以命令式（如上所示）或声明式的方式使用，使其易于与链中的其他组件组合：

from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(model="claude-3-sonnet-20240229", temperature=0)
# Notice we don't pass in messages. This creates
# a RunnableLambda that takes messages as input
merger = merge_message_runs()
chain = merger | llm
chain.invoke(messages)
API Reference:ChatAnthropic
Note: you may need to restart the kernel to use updated packages.
AIMessage(content=[], additional_kwargs={}, response_metadata={'id': 'msg_01KNGUMTuzBVfwNouLDpUMwf', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 84, 'output_tokens': 3}}, id='run-b908b198-9c24-450b-9749-9d4a8182937b-0', usage_metadata={'input_tokens': 84, 'output_tokens': 3, 'total_tokens': 87})

查看LangSmith跟踪，我们可以看到在消息传递给模型之前，它们被合并了：https://smith.langchain.com/public/ab558677-cac9-4c59-9066-1ecce5bcd87c/r

仅从合并来看，我们可以看到它是一个Runnable对象，可以像所有Runnables一样被调用：

merger.invoke(messages)
[SystemMessage(content="you're a good assistant.\nyou always respond with a joke.", additional_kwargs={}, response_metadata={}),
 HumanMessage(content=[{'type': 'text', 'text': "i wonder why it's called langchain"}, 'and who is harrison chasing anyways'], additional_kwargs={}, response_metadata={}),
 AIMessage(content='Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!\nWhy, he\'s probably chasing after the last cup of coffee in the office!', additional_kwargs={}, response_metadata={})]

merge_message_runs 也可以放在提示之后：

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        ("system", "You're great a {skill}"),
        ("system", "You're also great at explaining things"),
        ("human", "{query}"),
    ]
)
chain = prompt | merger | llm
chain.invoke({"skill": "math", "query": "what's the definition of a convergent series"})
API Reference:ChatPromptTemplate
AIMessage(content='A convergent series is an infinite series whose partial sums approach a finite value as more terms are added. In other words, the sequence of partial sums has a limit.\n\nMore formally, an infinite series Σ an (where an are the terms of the series) is said to be convergent if the sequence of partial sums:\n\nS1 = a1\nS2 = a1 + a2  \nS3 = a1 + a2 + a3\n...\nSn = a1 + a2 + a3 + ... + an\n...\n\nconverges to some finite number S as n goes to infinity. We write:\n\nlim n→∞ Sn = S\n\nThe finite number S is called the sum of the convergent infinite series.\n\nIf the sequence of partial sums does not approach any finite limit, the infinite series is said to be divergent.\n\nSome key properties:\n- A series converges if and only if the sequence of its partial sums is a Cauchy sequence.\n- Absolute/conditional convergence criteria help determine if a given series converges.\n- Convergent series have many important applications in mathematics, physics, engineering etc.', additional_kwargs={}, response_metadata={'id': 'msg_01MfV6y2hep7ZNvDz24A36U4', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 29, 'output_tokens': 267}}, id='run-9d925f58-021e-4bd0-94fc-f8f5e91010a4-0', usage_metadata={'input_tokens': 29, 'output_tokens': 267, 'total_tokens': 296})

LangSmith 跟踪: https://smith.langchain.com/public/432150b6-9909-40a7-8ae7-944b7e657438/r/f4ad5fb2-4d38-42a6-b780-25f62617d53f

API 参考​

有关所有参数的完整描述，请参阅API参考：https://python.langchain.com/api_reference/core/messages/langchain_core.messages.utils.merge_message_runs.html

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