`langchain_community.chains.ernie_functions.base`.create_structured_output_runnable¶

langchain_community.chains.ernie_functions.base.create_structured_output_runnable(output_schema: Union[Dict[str, Any], Type[BaseModel]], llm: Runnable, prompt: BasePromptTemplate, *, output_parser: Optional[Union[BaseOutputParser, BaseGenerationOutputParser]] = None, **kwargs: Any) → Runnable[源代码]¶

使用Ernie函数获取结构化输出的runnable。

参数

output_schema (Union[Dict[str, Any], Type[BaseModel]]) – 字典或pydantic.BaseModel类。如果传入字典，则假定它已经是有效的JsonSchema。为了获得最佳效果，pydantic.BaseModels应包含用于描述模式所代表的内容的文档字符串和参数的描述。
llm (Runnable) – 要使用的语言模型，假定其支持Ernie函数调用API。
prompt (BasePromptTemplate) – 要传递给模型的BasePromptTemplate。
output_parser (可选[Union[BaseOutputParser, BaseGenerationOutputParser]]) – 用于解析模型输出的BaseLLMOutputParser。默认情况下将从函数类型推断。如果传递了pydantic.BaseModels，则OutputParser将尝试使用它们解析输出。否则模型输出将简单地解析为JSON。
kwargs (任何类型) –

返回值

一个可运行的序列，当运行时将给定的函数传递给模型。

返回类型

可运行类型

示例

from typing import Optional

from langchain.chains.ernie_functions import create_structured_output_chain
from langchain_community.chat_models import ErnieBotChat
from langchain_core.prompts import ChatPromptTemplate
from langchain.pydantic_v1 import BaseModel, Field

class Dog(BaseModel):
    """Identifying information about a dog."""

    name: str = Field(..., description="The dog's name")
    color: str = Field(..., description="The dog's color")
    fav_food: Optional[str] = Field(None, description="The dog's favorite food")

llm = ErnieBotChat(model_name="ERNIE-Bot-4")
prompt = ChatPromptTemplate.from_messages(
    [
        ("user", "Use the given format to extract information from the following input: {input}"),
        ("assistant", "OK!"),
        ("user", "Tip: Make sure to answer in the correct format"),
    ]
)
chain = create_structured_output_chain(Dog, llm, prompt)
chain.invoke({"input": "Harry was a chubby brown beagle who loved chicken"})
# -> Dog(name="Harry", color="brown", fav_food="chicken")

langchain_community.chains.ernie_functions.base.create_structured_output_runnable¶

`langchain_community.chains.ernie_functions.base`.create_structured_output_runnable¶