pyrit.models.PromptResponse

class PromptResponse(*, completion: str, prompt: str = '', id: str = '', completion_tokens: int = 0, prompt_tokens: int = 0, total_tokens: int = 0, model: str = '', object: str = '', created_at: int = 0, logprobs: bool | None = False, index: int = 0, finish_reason: str = '', api_request_time_to_complete_ns: int = 0, metadata: dict = {})

Bases: BaseModel

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
load_from_file(file_path)	Load the Prompt Response from disk
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(_BaseModel__context)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
save_to_file(directory_path)	Save the Prompt Response to disk and return the path of the new file.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
to_json()
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
completion
prompt
id
completion_tokens
prompt_tokens
total_tokens
model
object
created_at
logprobs
index
finish_reason
api_request_time_to_complete_ns
metadata

api_request_time_to_complete_ns: int

completion: str

completion_tokens: int

created_at: int

finish_reason: str

id: str

index: int

static load_from_file(file_path: Path) → PromptResponse

Load the Prompt Response from disk

Parameters:

file_path – The path to load the file from

Returns:

The loaded embedding response

logprobs: bool | None

metadata: dict

model: str

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

object: str

prompt: str

prompt_tokens: int

save_to_file(directory_path: Path) → str

Save the Prompt Response to disk and return the path of the new file.

Parameters:

directory_path – The path to save the file to

Returns:

The full path to the file that was saved

to_json() → str

total_tokens: int