with_structured_output

from pydantic import BaseModel

class AnswerWithJustification(BaseModel):
    '''An answer to the user question along with justification for the answer.'''

    answer: str
    justification: str

model = ChatModel(model="model-name", temperature=0)
structured_model = model.with_structured_output(AnswerWithJustification)

structured_model.invoke(
    "What weighs more a pound of bricks or a pound of feathers"
)

# -> AnswerWithJustification(
#     answer='They weigh the same',
#     justification='Both a pound of bricks and a pound of feathers weigh one pound. The weight is the same, but the volume or density of the objects may differ.'
# )

from pydantic import BaseModel

class AnswerWithJustification(BaseModel):
    '''An answer to the user question along with justification for the answer.'''

    answer: str
    justification: str

model = ChatModel(model="model-name", temperature=0)
structured_model = model.with_structured_output(
    AnswerWithJustification, include_raw=True
)

structured_model.invoke(
    "What weighs more a pound of bricks or a pound of feathers"
)
# -> {
#     'raw': AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_Ao02pnFYXD6GN1yzc0uXPsvF', 'function': {'arguments': '{"answer":"They weigh the same.","justification":"Both a pound of bricks and a pound of feathers weigh one pound. The weight is the same, but the volume or density of the objects may differ."}', 'name': 'AnswerWithJustification'}, 'type': 'function'}]}),
#     'parsed': AnswerWithJustification(answer='They weigh the same.', justification='Both a pound of bricks and a pound of feathers weigh one pound. The weight is the same, but the volume or density of the objects may differ.'),
#     'parsing_error': None
# }

from pydantic import BaseModel
from langchain_core.utils.function_calling import convert_to_openai_tool

class AnswerWithJustification(BaseModel):
    '''An answer to the user question along with justification for the answer.'''

    answer: str
    justification: str

dict_schema = convert_to_openai_tool(AnswerWithJustification)
model = ChatModel(model="model-name", temperature=0)
structured_model = model.with_structured_output(dict_schema)

structured_model.invoke(
    "What weighs more a pound of bricks or a pound of feathers"
)
# -> {
#     'answer': 'They weigh the same',
#     'justification': 'Both a pound of bricks and a pound of feathers weigh one pound. The weight is the same, but the volume and density of the two substances differ.'
# }

Added support for TypedDict class.