AI Agents with LangGraph
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Structured Output Demo
You’ll use the ChatOpenAI model for this demo, so make sure you have your API key in your .env file in the root of your project:
OPENAI_API_KEY=<your-api-key>
from dotenv import load_dotenv
load_dotenv()
import os
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
api_key=os.getenv("OPENAI_API_KEY"),
temperature=1.0
)
from langchain_core.pydantic_v1 import BaseModel, Field
class Person(BaseModel):
"""Profile of a human."""
name: str = Field(description="The person's name")
age: int = Field(description="The person's age, between 1 and 100")
structured_llm = llm.with_structured_output(Person)
structured_llm.invoke("Create a random character for a story")
from typing_extensions import Annotated, TypedDict
class Person(TypedDict):
"""Profile of a human."""
name: Annotated[str, ..., "The person's name"]
age: Annotated[int, ..., "The person's age"]