Run#

class langchain_core.tracers.schemas.Run(*, id: UUID, name: str, start_time: datetime, run_type: str, end_time: datetime | None = None, extra: dict | None = None, error: str | None = None, serialized: dict | None = None, events: list[dict[str, Any]] = None, inputs: dict = None, outputs: dict | None = None, reference_example_id: UUID | None = None, parent_run_id: UUID | None = None, tags: list[str] | None = None, child_runs: list[Run] = None, trace_id: UUID | None = None, dotted_order: str | None = None)[source]#

Run schema for the V2 API in the Tracer.

Parameters:

child_runs (list[Run]) – The child runs.
tags (list[str] | None) – The tags. Default is an empty list.
events (list[dict[str, Any]]) – The events. Default is an empty list.
trace_id (UUID | None) – The trace ID. Default is None.
dotted_order (str | None) – The dotted order.
id (UUID)
name (str)
start_time (datetime)
run_type (str)
end_time (datetime | None)
extra (dict | None)
error (str | None)
serialized (dict | None)
inputs (dict)
outputs (dict | None)
reference_example_id (UUID | None)
parent_run_id (UUID | None)

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

Attributes

`metadata`	Retrieve the metadata (if any).
`revision_id`	Retrieve the revision ID (if any).

Methods

`__init__`(**data)	Create a new model by parsing and validating input data from keyword arguments.
`assign_name`(values)	Assign name to the run.
`construct`([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
`copy`(*[, include, exclude, update, deep])	Duplicate a model, optionally choose which fields to include, exclude and change.
`dict`(*[, include, exclude, by_alias, ...])	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
`from_orm`(obj)
`json`(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
`parse_file`(path, *[, content_type, ...])
`parse_obj`(obj)
`parse_raw`(b, *[, content_type, encoding, ...])
`schema`([by_alias, ref_template])
`schema_json`(*[, by_alias, ref_template])
`update_forward_refs`(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
`validate`(value)

__init__(**data: Any) → None#

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

Parameters:: data (Any)
Return type:: None

classmethod assign_name(values: dict) → dict[source]#

Assign name to the run.

Parameters:: values (dict)
Return type:: dict

classmethod construct(_fields_set: SetStr | None = None, **values: Any) → Model#

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 = ‘allow’ was set since it adds all passed values

Parameters:

_fields_set (SetStr | None)
values (Any)

Return type:

Model

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

Parameters:

include (AbstractSetIntStr | MappingIntStrAny | None) – fields to include in new model
exclude (AbstractSetIntStr | MappingIntStrAny | None) – fields to exclude from new model, as with values this takes precedence over include
update (DictStrAny | None) – 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 (bool) – set to True to make a deep copy of the model
self (Model)

Returns:

new model instance

Return type:

Model

dict(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#

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

Parameters:

include (AbstractSetIntStr | MappingIntStrAny | None)
exclude (AbstractSetIntStr | MappingIntStrAny | None)
by_alias (bool)
skip_defaults (bool | None)
exclude_unset (bool)
exclude_defaults (bool)
exclude_none (bool)

Return type:

DictStrAny

classmethod from_orm(obj: Any) → Model#

Parameters:: obj (Any)
Return type:: Model

json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = None, models_as_dict: bool = True, **dumps_kwargs: Any) → str#

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().

Parameters:

include (AbstractSetIntStr | MappingIntStrAny | None)
exclude (AbstractSetIntStr | MappingIntStrAny | None)
by_alias (bool)
skip_defaults (bool | None)
exclude_unset (bool)
exclude_defaults (bool)
exclude_none (bool)
encoder (Callable[[Any], Any] | None)
models_as_dict (bool)
dumps_kwargs (Any)

Return type:

str

classmethod parse_file(path: str | Path, *, content_type: str = None, encoding: str = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model#

Parameters:

path (str | Path)
content_type (str)
encoding (str)
proto (Protocol)
allow_pickle (bool)

Return type:

Model

classmethod parse_obj(obj: Any) → Model#

Parameters:: obj (Any)
Return type:: Model

classmethod parse_raw(b: str | bytes, *, content_type: str = None, encoding: str = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model#

Parameters:

b (str | bytes)
content_type (str)
encoding (str)
proto (Protocol)
allow_pickle (bool)

Return type:

Model

classmethod schema(by_alias: bool = True, ref_template: str = '#/definitions/{model}') → DictStrAny#

Parameters:

by_alias (bool)
ref_template (str)

Return type:

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: str = '#/definitions/{model}', **dumps_kwargs: Any) → str#

Parameters:

by_alias (bool)
ref_template (str)
dumps_kwargs (Any)

Return type:

str

classmethod update_forward_refs(**localns: Any) → None#

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

Parameters:: localns (Any)
Return type:: None

classmethod validate(value: Any) → Model#

Parameters:: value (Any)
Return type:: Model

Examples using Run

LangChain Expression Language Cheatsheet