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a< Extract and save the relevant entities mentioned in the following passage together with their properties.
Only extract the properties mentioned in the 'information_extraction' function.
If a property is not present and is not required in the function parameters, do not include it in the output.
Passage:
{input}
z0.1.14a LangChain has introduced a method called `with_structured_output` thatis available on ChatModels capable of tool calling.You can read more about the method here: . Please follow our extraction use case documentation for more guidelineson how to do information extraction with LLMs.. If you notice other issues, please provide feedback here:z1.0a)
from pydantic import BaseModel, Field
from langchain_anthropic import ChatAnthropic
class Joke(BaseModel):
setup: str = Field(description="The setup of the joke")
punchline: str = Field(description="The punchline to the joke")
# Or any other chat model that supports tools.
# Please reference to to the documentation of structured_output
# to see an up to date list of which models support
# with_structured_output.
model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0)
structured_llm = model.with_structured_output(Joke)
structured_llm.invoke("Tell me a joke about cats.
Make sure to call the Joke function.")
)sincemessageremoval alternativeNschemallmprompttagsverbosec [ U 5 nU=( d [ R " [ 5 n[ SS9n[ U5 n[
UUUUUUS9$ )a Creates a chain that extracts information from a passage.
Args:
schema: The schema of the entities to extract.
llm: The language model to use.
prompt: The prompt to use for extraction.
verbose: Whether to run in verbose mode. In verbose mode, some intermediate
logs will be printed to the console. Defaults to the global `verbose` value,
accessible via `langchain.globals.get_verbose()`.
Returns:
Chain that can be used to extract information from a passage.
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U5 nU=( d [ R " [ 5 n[ USS9n[ U5 n [ UUU UUS9$ )a Creates a chain that extracts information from a passage using pydantic schema.
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pydantic_schema: The pydantic schema of the entities to extract.
llm: The language model to use.
prompt: The prompt to use for extraction.
verbose: Whether to run in verbose mode. In verbose mode, some intermediate
logs will be printed to the console. Defaults to the global `verbose` value,
accessible via `langchain.globals.get_verbose()`
Returns:
Chain that can be used to extract information from a passage.
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