with_structured_output

Example: schema=Pydantic class, method="function_calling", include_raw=False:

from typing import Optional

from langchain_fireworks import ChatFireworks
from pydantic import BaseModel, Field

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

    answer: str
    # If we provide default values and/or descriptions for fields, these will be passed
    # to the model. This is an important part of improving a model's ability to
    # correctly return structured outputs.
    justification: str | None = Field(
        default=None, description="A justification for the answer."
    )

model = ChatFireworks(
    model="accounts/fireworks/models/gpt-oss-120b",
    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.'
# )

Example: schema=Pydantic class, method="function_calling", include_raw=True:

from langchain_fireworks import ChatFireworks
from pydantic import BaseModel

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

    answer: str
    justification: str

model = ChatFireworks(
    model="accounts/fireworks/models/gpt-oss-120b",
    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
# }

Example: schema=TypedDict class, method="function_calling", include_raw=False:

from typing_extensions import Annotated, TypedDict

from langchain_fireworks import ChatFireworks

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

    answer: str
    justification: Annotated[
        str | None, None, "A justification for the answer."
    ]

model = ChatFireworks(
    model="accounts/fireworks/models/gpt-oss-120b",
    temperature=0,
)
structured_model = model.with_structured_output(AnswerWithJustification)

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.'
# }

Example: schema=OpenAI function schema, method="function_calling", include_raw=False:

from langchain_fireworks import ChatFireworks

oai_schema = {
    "name": "AnswerWithJustification",
    "description": "An answer to the user question along with justification for the answer.",
    "parameters": {
        "type": "object",
        "properties": {
            "answer": {"type": "string"},
            "justification": {
                "description": "A justification for the answer.",
                "type": "string",
            },
        },
        "required": ["answer"],
    },
}

model = ChatFireworks(
    model="accounts/fireworks/models/gpt-oss-120b",
    temperature=0,
)
structured_model = model.with_structured_output(oai_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.'
# }

Example: schema=Pydantic class, method="json_mode", include_raw=True:

from langchain_fireworks import ChatFireworks
from pydantic import BaseModel

class AnswerWithJustification(BaseModel):
    answer: str
    justification: str

model = ChatFireworks(
    model="accounts/fireworks/models/gpt-oss-120b", temperature=0
)
structured_model = model.with_structured_output(
    AnswerWithJustification, method="json_mode", include_raw=True
)

structured_model.invoke(
    "Answer the following question. "
    "Make sure to return a JSON blob with keys 'answer' and 'justification'. "
    "What's heavier a pound of bricks or a pound of feathers?"
)
# -> {
#     'raw': AIMessage(content='{"answer": "They are both the same weight.", "justification": "Both a pound of bricks and a pound of feathers weigh one pound. The difference lies in the volume and density of the materials, not the weight."}'),
#     'parsed': AnswerWithJustification(answer='They are both the same weight.', justification='Both a pound of bricks and a pound of feathers weigh one pound. The difference lies in the volume and density of the materials, not the weight.'),
#     'parsing_error': None
# }

Example: schema=None, method="json_mode", include_raw=True:

structured_model = model.with_structured_output(
    method="json_mode", include_raw=True
)

structured_model.invoke(
    "Answer the following question. "
    "Make sure to return a JSON blob with keys 'answer' and 'justification'. "
    "What's heavier a pound of bricks or a pound of feathers?"
)
# -> {
#     'raw': AIMessage(content='{"answer": "They are both the same weight.", "justification": "Both a pound of bricks and a pound of feathers weigh one pound. The difference lies in the volume and density of the materials, not the weight."}'),
#     'parsed': {
#         'answer': 'They are both the same weight.',
#         'justification': 'Both a pound of bricks and a pound of feathers weigh one pound. The difference lies in the volume and density of the materials, not the weight.'
#     },
#     'parsing_error': None
# }