LangChain

入门指南#

本教程涵盖了如何开始使用聊天模型。该接口基于消息而不是原始文本。

from langchain.chat_models import ChatOpenAI
from langchain import PromptTemplate, LLMChain
from langchain.prompts.chat import (
    ChatPromptTemplate,
    SystemMessagePromptTemplate,
    AIMessagePromptTemplate,
    HumanMessagePromptTemplate,
)
from langchain.schema import (
    AIMessage,
    HumanMessage,
    SystemMessage
)

chat = ChatOpenAI(temperature=0)

通过向聊天模型传递一个或多个消息，您可以获得聊天完成。响应将是一条消息。LangChain目前支持的消息类型有AIMessage、HumanMessage、SystemMessage和ChatMessage - ChatMessage接受任意角色参数。大多数情况下，您只需处理HumanMessage、AIMessage和SystemMessage

chat([HumanMessage(content="Translate this sentence from English to French. I love programming.")])

AIMessage(content="J'aime programmer.", additional_kwargs={})

OpenAI的聊天模型支持多个消息作为输入。有关更多信息，请参见此处 (opens in a new tab)。下面是向聊天模型发送系统和用户消息的示例：

messages = [
    SystemMessage(content="You are a helpful assistant that translates English to French."),
    HumanMessage(content="I love programming.")
]
chat(messages)

AIMessage(content="J'aime programmer.", additional_kwargs={})

您可以进一步使用generate来生成多组消息的完成，这将返回一个带有额外message参数的LLMResult。

batch_messages = [
    [
        SystemMessage(content="You are a helpful assistant that translates English to French."),
        HumanMessage(content="I love programming.")
    ],
    [
        SystemMessage(content="You are a helpful assistant that translates English to French."),
        HumanMessage(content="I love artificial intelligence.")
    ],
]
result = chat.generate(batch_messages)
result

LLMResult(generations=[[ChatGeneration(text="J'aime programmer.", generation_info=None, message=AIMessage(content="J'aime programmer.", additional_kwargs={}))], [ChatGeneration(text="J'aime l'intelligence artificielle.", generation_info=None, message=AIMessage(content="J'aime l'intelligence artificielle.", additional_kwargs={}))]], llm_output={'token_usage': {'prompt_tokens': 57, 'completion_tokens': 20, 'total_tokens': 77}})

您可以从这个LLMResult中恢复诸如令牌使用情况之类的东西

result.llm_output

{'token_usage': {'prompt_tokens': 57,
  'completion_tokens': 20,
  'total_tokens': 77}}

PromptTemplates#

您可以通过使用MessagePromptTemplate来利用模板。您可以从一个或多个MessagePromptTemplates构建一个ChatPromptTemplate。您可以使用ChatPromptTemplate的format_prompt - 这将返回一个PromptValue，您可以将其转换为字符串或消息对象，具体取决于您是否想要将格式化值用作llm或chat模型的输入。

为了方便起见，模板上公开了一个from_template方法。如果您使用此模板，它将如下所示：

template="You are a helpful assistant that translates {input_language} to {output_language}."
system_message_prompt = SystemMessagePromptTemplate.from_template(template)
human_template="{text}"
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)

chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
 
# get a chat completion from the formatted messages
chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())

AIMessage(content="J'adore la programmation.", additional_kwargs={})

如果您想更直接地构建MessagePromptTemplate，可以在外部创建PromptTemplate，然后传入，例如：

prompt=PromptTemplate(
    template="You are a helpful assistant that translates {input_language} to {output_language}.",
    input_variables=["input_language", "output_language"],
)
system_message_prompt = SystemMessagePromptTemplate(prompt=prompt)

LLMChain#

您可以像以前一样使用现有的LLMChain-提供提示和模型。

chain = LLMChain(llm=chat, prompt=chat_prompt)

chain.run(input_language="English", output_language="French", text="I love programming.")

"J'adore la programmation."

流处理#

通过回调处理，ChatOpenAI支持流处理。

from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
chat = ChatOpenAI(streaming=True, callbacks=[StreamingStdOutCallbackHandler()], temperature=0)
resp = chat([HumanMessage(content="Write me a song about sparkling water.")])

Verse 1:
Bubbles rising to the top
A refreshing drink that never stops
Clear and crisp, it's pure delight
A taste that's sure to excite
 
Chorus:
Sparkling water, oh so fine
A drink that's always on my mind
With every sip, I feel alive
Sparkling water, you're my vibe
 
Verse 2:
No sugar, no calories, just pure bliss
A drink that's hard to resist
It's the perfect way to quench my thirst
A drink that always comes first
 
Chorus:
Sparkling water, oh so fine
A drink that's always on my mind
With every sip, I feel alive
Sparkling water, you're my vibe
 
Bridge:
From the mountains to the sea
Sparkling water, you're the key
To a healthy life, a happy soul
A drink that makes me feel whole
 
Chorus:
Sparkling water, oh so fine
A drink that's always on my mind
With every sip, I feel alive
Sparkling water, you're my vibe
 
Outro:
Sparkling water, you're the one
A drink that's always so much fun
I'll never let you go, my friend
Sparkling

流式处理（Streaming）操作指南（How-to Guides）