with_structured_output

Pydantic schema (include_raw=False)::

from langchain_aws.chat_models.bedrock import ChatBedrock
from pydantic import BaseModel

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

llm = ChatBedrock(
    model_id="anthropic.claude-3-sonnet-20240229-v1:0",
    model_kwargs={"temperature": 0.001},
)  # type: ignore[call-arg]
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.'
# )

Pydantic schema (include_raw=True)::

from langchain_aws.chat_models.bedrock import ChatBedrock
from pydantic import BaseModel

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

model = ChatBedrock(
    model_id="anthropic.claude-3-sonnet-20240229-v1:0",
    model_kwargs={"temperature": 0.001},
)  # type: ignore[call-arg]
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
# }

Dict schema (include_raw=False)::

from langchain_aws.chat_models.bedrock import ChatBedrock

schema = {
    "name": "AnswerWithJustification",
    "description": "An answer to the user question along with justification for the answer.",
    "input_schema": {
        "type": "object",
        "properties": {
            "answer": {"type": "string"},
            "justification": {"type": "string"},
        },
        "required": ["answer", "justification"]
    }
}
model = ChatBedrock(
    model_id="anthropic.claude-3-sonnet-20240229-v1:0",
    model_kwargs={"temperature": 0.001},
)  # type: ignore[call-arg]
structured_model = model.with_structured_output(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.'
# }