langchain.agents.openai_assistant.base.OpenAIAssistantFinishΒΆ

class langchain.agents.openai_assistant.base.OpenAIAssistantFinish[source]ΒΆ

Bases: AgentFinish

AgentFinish with run and thread metadata.

Override init to support instantiation by position for backward compat.

param log: str [Required]ΒΆ

Additional information to log about the return value. This is used to pass along the full LLM prediction, not just the parsed out return value. For example, if the full LLM prediction was Final Answer: 2 you may want to just return 2 as a return value, but pass along the full string as a log (for debugging or observability purposes).

param return_values: dict [Required]ΒΆ

Dictionary of return values.

param run_id: str [Required]ΒΆ
param thread_id: str [Required]ΒΆ
param type: Literal['AgentFinish'] = 'AgentFinish'ΒΆ
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) ModelΒΆ

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = β€˜allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) ModelΒΆ

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters
  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAnyΒΆ

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) ModelΒΆ
classmethod get_lc_namespace() List[str]ΒΆ

Get the namespace of the langchain object.

classmethod is_lc_serializable() bool[source]ΒΆ

Return whether or not the class is serializable.

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicodeΒΆ

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod lc_id() List[str]ΒΆ

A unique identifier for this class for serialization purposes.

The unique identifier is a list of strings that describes the path to the object.

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) ModelΒΆ
classmethod parse_obj(obj: Any) ModelΒΆ
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) ModelΒΆ
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAnyΒΆ
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicodeΒΆ
to_json() Union[SerializedConstructor, SerializedNotImplemented]ΒΆ
to_json_not_implemented() SerializedNotImplementedΒΆ
classmethod update_forward_refs(**localns: Any) NoneΒΆ

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) ModelΒΆ
property lc_attributes: DictΒΆ

List of attribute names that should be included in the serialized kwargs.

These attributes must be accepted by the constructor.

property lc_secrets: Dict[str, str]ΒΆ

A map of constructor argument names to secret ids.

For example,

{β€œopenai_api_key”: β€œOPENAI_API_KEY”}

property messages: Sequence[langchain_core.messages.base.BaseMessage]ΒΆ

Return the messages that correspond to this observation.