RunTree#

class langsmith.run_trees.RunTree(
*,
id: UUID = None,
name: str,
start_time: datetime = None,
run_type: str = 'chain',
end_time: datetime | None = None,
extra: dict = None,
error: str | None = None,
serialized: dict | None = None,
events: list[dict] = 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,
attachments: dict[str, tuple[str, bytes] | Attachment | tuple[str, Path]] | dict[str, AttachmentInfo] = None,
parent_run: RunTree | None = None,
parent_dotted_order: str | None = None,
child_runs: list[RunTree] = None,
project_name: str = None,
project_id: UUID | None = None,
ls_client: Any | None = None,
dotted_order: str = '',
trace_id: UUID = '',
dangerously_allow_filesystem: bool | None = False,
)[source]#

Run Schema with back-references for posting runs.

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

client

Return the client.

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.

add_event(events)

Add an event to the list of events.

add_inputs(inputs)

Upsert the given outputs into the run.

add_metadata(metadata)

Add metadata to the run.

add_outputs(outputs)

Upsert the given outputs into the run.

add_tags(tags)

Add tags 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.

create_child(name[, run_type, run_id, ...])

Add a child run to the run tree.

dict(*[, include, exclude, by_alias, ...])

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

end(*[, outputs, error, end_time, events, ...])

Set the end time of the run and all child runs.

ensure_dotted_order(values)

Ensure the dotted order of the run.

from_dotted_order(dotted_order, **kwargs)

Create a new 'child' span from the provided dotted order.

from_headers(headers, **kwargs)

Create a new 'parent' span from the provided headers.

from_orm(obj)

from_runnable_config(config, **kwargs)

Create a new 'child' span from the provided runnable config.

get_url()

Return the URL of the run.

infer_defaults(values)

Assign name to the run.

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, ...])

patch()

Patch the run tree to the API in a background thread.

post([exclude_child_runs])

Post the run tree to the API asynchronously.

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

to_headers()

Return the RunTree as a dictionary of headers.

update_forward_refs(**localns)

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

validate(value)

wait()

Wait for all _futures to complete.
Parameters:

  • id (UUID)

  • name (str)

  • start_time (datetime)

  • run_type (str)

  • end_time (datetime | None)

  • extra (dict)

  • error (str | None)

  • serialized (dict | None)

  • events (list[dict])

  • inputs (dict)

  • outputs (dict | None)

  • reference_example_id (UUID | None)

  • parent_run_id (UUID | None)

  • tags (list[str] | None)

  • attachments (dict[str, tuple[str, bytes] | Attachment | tuple[str, Path]] | dict[str, AttachmentInfo])

  • parent_run (RunTree | None)

  • parent_dotted_order (str | None)

  • child_runs (list[RunTree])

  • project_name (str)

  • project_id (UUID | None)

  • ls_client (Any | None)

  • dotted_order (str)

  • trace_id (UUID)

  • dangerously_allow_filesystem (bool | None)

__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

add_event(
events: RunEvent | Sequence[RunEvent] | Sequence[dict] | dict | str,
) → None[source]#

Add an event to the list of events.

Parameters:

  • (Union[ls_schemas.RunEvent (events) – Sequence[dict], dict, str]): The event(s) to be added. It can be a single event, a sequence of events, a sequence of dictionaries, a dictionary, or a string.

  • Sequence[ls_schemas.RunEvent] – Sequence[dict], dict, str]): The event(s) to be added. It can be a single event, a sequence of events, a sequence of dictionaries, a dictionary, or a string.

  • events (RunEvent | Sequence[RunEvent] | Sequence[dict] | dict | str)

Return type:

None

:paramSequence[dict], dict, str]):

The event(s) to be added. It can be a single event, a sequence of events, a sequence of dictionaries, a dictionary, or a string.

Returns:

None

Parameters:

events (RunEvent | Sequence[RunEvent] | Sequence[dict] | dict | str)

Return type:

None

add_inputs(inputs: dict[str, Any]) → None[source]#

Upsert the given outputs into the run.

Parameters:

  • outputs (Dict[str, Any]) – A dictionary containing the outputs to be added.

  • inputs (dict[str, Any])

Returns:

None

Return type:

None

add_metadata(
metadata: dict[str, Any],
) → None[source]#

Add metadata to the run.

Parameters:

metadata (dict[str, Any])

Return type:

None

add_outputs(outputs: dict[str, Any]) → None[source]#

Upsert the given outputs into the run.

Parameters:

outputs (Dict[str, Any]) – A dictionary containing the outputs to be added.

Returns:

None

Return type:

None

add_tags(
tags: Sequence[str] | str,
) → None[source]#

Add tags to the run.

Parameters:

tags (Sequence[str] | str)

Return type:

None

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

copy(
*,
include: AbstractSetIntStr | MappingIntStrAny | None = None,
exclude: AbstractSetIntStr | MappingIntStrAny | None = None,
update: DictStrAny | None = None,
deep: bool = False,
) → 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

create_child(
name: str,
run_type: Literal['tool', 'chain', 'llm', 'retriever', 'embedding', 'prompt', 'parser'] = 'chain',
*,
run_id: UUID | str | None = None,
serialized: dict | None = None,
inputs: dict | None = None,
outputs: dict | None = None,
error: str | None = None,
reference_example_id: UUID | None = None,
start_time: datetime | None = None,
end_time: datetime | None = None,
tags: list[str] | None = None,
extra: dict | None = None,
attachments: dict[str, tuple[str, bytes] | Attachment | tuple[str, Path]] | None = None,
) → RunTree[source]#

Add a child run to the run tree.

Parameters:

  • name (str)

  • run_type (Literal['tool', 'chain', 'llm', 'retriever', 'embedding', 'prompt', 'parser'])

  • run_id (UUID | str | None)

  • serialized (dict | None)

  • inputs (dict | None)

  • outputs (dict | None)

  • error (str | None)

  • reference_example_id (UUID | None)

  • start_time (datetime | None)

  • end_time (datetime | None)

  • tags (list[str] | None)

  • extra (dict | None)

  • attachments (dict[str, tuple[str, bytes] | Attachment | tuple[str, Path]] | None)

Return type:

RunTree

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

end(
*,
outputs: dict | None = None,
error: str | None = None,
end_time: datetime | None = None,
events: Sequence[RunEvent] | None = None,
metadata: dict[str, Any] | None = None,
) → None[source]#

Set the end time of the run and all child runs.

Parameters:

  • outputs (dict | None)

  • error (str | None)

  • end_time (datetime | None)

  • events (Sequence[RunEvent] | None)

  • metadata (dict[str, Any] | None)

Return type:

None

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

Ensure the dotted order of the run.

Parameters:

values (dict)

Return type:

dict

classmethod from_dotted_order(
dotted_order: str,
**kwargs: Any,
) → RunTree[source]#

Create a new ‘child’ span from the provided dotted order.

Returns:

The new span.

Return type:

RunTree

Parameters:

  • dotted_order (str)

  • kwargs (Any)

classmethod from_headers(
headers: Mapping[str | bytes, str | bytes],
**kwargs: Any,
) → RunTree | None[source]#

Create a new ‘parent’ span from the provided headers.

Extracts parent span information from the headers and creates a new span. Metadata and tags are extracted from the baggage header. The dotted order and trace id are extracted from the trace header.

Returns:

The new span or None if

no parent span information is found.

Return type:

Optional[RunTree]

Parameters:

  • headers (Mapping[str | bytes, str | bytes])

  • kwargs (Any)

classmethod from_orm(obj: Any) → Model#
Parameters:

obj (Any)

Return type:

Model

classmethod from_runnable_config(
config: dict | None,
**kwargs: Any,
) → RunTree | None[source]#

Create a new ‘child’ span from the provided runnable config.

Requires langchain to be installed.

Returns:

The new span or None if

no parent span information is found.

Return type:

Optional[RunTree]

Parameters:

  • config (dict | None)

  • kwargs (Any)

get_url() → str[source]#

Return the URL of the run.

Return type:

str

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

Assign name to the run.

Parameters:

values (dict)

Return type:

dict

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

patch() → None[source]#

Patch the run tree to the API in a background thread.

Return type:

None

post(exclude_child_runs: bool = True) → None[source]#

Post the run tree to the API asynchronously.

Parameters:

exclude_child_runs (bool)

Return type:

None

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

to_headers() → dict[str, str][source]#

Return the RunTree as a dictionary of headers.

Return type:

dict[str, 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

wait() → None[source]#

Wait for all _futures to complete.

Return type:

None