Tony20100/langchain_full huggingface dataset:
langchain_core.tracers.log_stream.RunLog¶
class langchain_core.tracers.log_stream.RunLog(*ops: Dict[str, Any], state: RunState)[source]¶
Run log.
Attributes
state
Current state of the log, obtained from applying all ops in sequence.
Methods
__init__(*ops, state)
Parameters
ops (List[Dict[str, Any]]) – 
state (RunState) – 
__init__(*ops: Dict[str, Any], state: RunState) → None[source]¶
Parameters
ops (Dict[str, Any]) – 
state (RunState) – 
Return type
None
langchain_core.tracers.log_stream.LogStreamCallbackHandler¶
class langchain_core.tracers.log_stream.LogStreamCallbackHandler(*, auto_close: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[str]] = None, exclude_types: Optional[Sequence[str]] = None, exclude_tags: Optional[Sequence[str]] = None, _schema_format: Literal['original', 'streaming_events'] = 'streaming_events')[source]¶
Tracer that streams run logs to a stream.
A tracer that streams run logs to a stream.
Parameters
auto_close (bool) – Whether to close the stream when the root run finishes.
include_names (Optional[Sequence[str]]) – Only include runs from Runnables with matching names.
include_types (Optional[Sequence[str]]) – Only include runs from Runnables with matching types.
include_tags (Optional[Sequence[str]]) – Only include runs from Runnables with matching tags.
exclude_names (Optional[Sequence[str]]) – Exclude runs from Runnables with matching names.
exclude_types (Optional[Sequence[str]]) – Exclude runs from Runnables with matching types.
exclude_tags (Optional[Sequence[str]]) – Exclude runs from Runnables with matching tags.
_schema_format (Literal['original', 'streaming_events']) – Primarily changes how the inputs and outputs are
handled.
For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
Attributes
ignore_agent
for streaming events.
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
raise_error
run_inline
Methods
__init__(*[, auto_close, include_names, ...])
A tracer that streams run logs to a stream.
include_run(run)
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
End a trace for a chain run.
on_chain_error(error, *[, inputs])
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)
Start a trace for a chain run.
on_chat_model_start(serialized, messages, *, ...)
Start a trace for an LLM run.
on_llm_end(response, *, run_id, **kwargs)
End a trace for an LLM run.
on_llm_error(error, *, run_id, **kwargs)
Handle an error for an LLM run.
on_llm_new_token(token, *[, chunk, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Start a trace for an LLM run.
on_retriever_end(documents, *, run_id, **kwargs)
Run when Retriever ends running.
Run when Retriever ends running.
on_retriever_error(error, *, run_id, **kwargs)
Run when Retriever errors.
on_retriever_start(serialized, query, *, run_id)
Run when Retriever starts running.
on_retry(retry_state, *, run_id, **kwargs)
Run on a retry event.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
End a trace for a tool run.
on_tool_error(error, *, run_id, **kwargs)
Handle an error for a tool run.
on_tool_start(serialized, input_str, *, run_id)
Start a trace for a tool run.
send(*ops)
Send a patch to the stream, return False if the stream is closed.
tap_output_aiter(run_id, output)
Tap an output async iterator to stream its values to the log.
tap_output_iter(run_id, output)
Tap an output async iterator to stream its values to the log.
__init__(*, auto_close: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[str]] = None, exclude_types: Optional[Sequence[str]] = None, exclude_tags: Optional[Sequence[str]] = None, _schema_format: Literal['original', 'streaming_events'] = 'streaming_events') → None[source]¶
A tracer that streams run logs to a stream.
Parameters
auto_close (bool) – Whether to close the stream when the root run finishes.
Parameters
auto_close (bool) – Whether to close the stream when the root run finishes.
include_names (Optional[Sequence[str]]) – Only include runs from Runnables with matching names.
include_types (Optional[Sequence[str]]) – Only include runs from Runnables with matching types.
include_tags (Optional[Sequence[str]]) – Only include runs from Runnables with matching tags.
exclude_names (Optional[Sequence[str]]) – Exclude runs from Runnables with matching names.
exclude_types (Optional[Sequence[str]]) – Exclude runs from Runnables with matching types.
exclude_tags (Optional[Sequence[str]]) – Exclude runs from Runnables with matching tags.
_schema_format (Literal['original', 'streaming_events']) – Primarily changes how the inputs and outputs are
handled.
For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
Return type
None
include_run(run: Run) → bool[source]¶
Parameters
run (Run) – 
Return type
bool
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_tool_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run¶
Handle an error for a tool run.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Run¶
Start a trace for a tool run.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
Run
send(*ops: Dict[str, Any]) → bool[source]¶
Send a patch to the stream, return False if the stream is closed.
Parameters
ops (Dict[str, Any]) – 
Return type
bool
async tap_output_aiter(run_id: UUID, output: AsyncIterator[T]) → AsyncIterator[T][source]¶
Tap an output async iterator to stream its values to the log.
Parameters
run_id (UUID) – 
output (AsyncIterator[T]) – 
Return type
AsyncIterator[T]
langchain_core.tracers.schemas.TracerSessionV1Create¶
class langchain_core.tracers.schemas.TracerSessionV1Create[source]¶
Bases: TracerSessionV1Base
[Deprecated] Create class for TracerSessionV1.
Notes
Deprecated since version 0.1.0.
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.
param extra: Optional[Dict[str, Any]] = None¶
param name: Optional[str] = None¶
param start_time: datetime [Optional]¶
classmethod construct(_fields_set: Optional[SetStr] = 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 (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
langchain_core.tracers.evaluation.EvaluatorCallbackHandler¶
class langchain_core.tracers.evaluation.EvaluatorCallbackHandler(evaluators: Sequence[RunEvaluator], client: Optional[Client] = None, example_id: Optional[Union[str, UUID]] = None, skip_unfinished: bool = True, project_name: Optional[str] = 'evaluators', max_concurrency: Optional[int] = None, **kwargs: Any)[source]¶
Tracer that runs a run evaluator whenever a run is persisted.
Parameters
evaluators (Sequence[RunEvaluator]) – The run evaluators to apply to all top level runs.
client (LangSmith Client, optional) – The LangSmith client instance to use for evaluating the runs.
If not specified, a new instance will be created.
example_id (Union[UUID, str], optional) – The example ID to be associated with the runs.
project_name (str, optional) – The LangSmith project name to be organize eval chain runs under.
skip_unfinished (bool) – 
max_concurrency (Optional[int]) – 
kwargs (Any) – 
example_id¶
The example ID associated with the runs.
Type
Union[UUID, None]
client¶
The LangSmith client instance used for evaluating the runs.
Type
Client
evaluators¶
The sequence of run evaluators to be executed.
Type
Sequence[RunEvaluator]
executor¶
The thread pool executor used for running the evaluators.
Type
ThreadPoolExecutor
futures¶
The set of futures representing the running evaluators.
Type
Set[Future]
skip_unfinished¶
Whether to skip runs that are not finished or raised
an error.
Type
bool
project_name¶
The LangSmith project name to be organize eval chain runs under.
Type
Optional[str]
Initialize the tracer.
Parameters
Type
Optional[str]
Initialize the tracer.
Parameters
_schema_format – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs (Any) – Additional keyword arguments that will be passed to
the super class.
evaluators (Sequence[langsmith.RunEvaluator]) – 
client (Optional[langsmith.Client]) – 
example_id (Optional[Union[UUID, str]]) – 
skip_unfinished (bool) – 
project_name (Optional[str]) – 
max_concurrency (Optional[int]) – 
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
name
raise_error
run_inline
Methods
__init__(evaluators[, client, example_id, ...])
Initialize the tracer.
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
End a trace for a chain run.
End a trace for a chain run.
on_chain_error(error, *[, inputs])
Handle an error for a chain run.
on_chain_start(serialized, inputs, *, run_id)
Start a trace for a chain run.
on_chat_model_start(serialized, messages, *, ...)
Start a trace for an LLM run.
on_llm_end(response, *, run_id, **kwargs)
End a trace for an LLM run.
on_llm_error(error, *, run_id, **kwargs)
Handle an error for an LLM run.
on_llm_new_token(token, *[, chunk, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Start a trace for an LLM run.
on_retriever_end(documents, *, run_id, **kwargs)
Run when Retriever ends running.
on_retriever_error(error, *, run_id, **kwargs)
Run when Retriever errors.
on_retriever_start(serialized, query, *, run_id)
Run when Retriever starts running.
on_retry(retry_state, *, run_id, **kwargs)
Run on a retry event.
on_text(text, *, run_id[, parent_run_id])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
End a trace for a tool run.
on_tool_error(error, *, run_id, **kwargs)
Handle an error for a tool run.
on_tool_start(serialized, input_str, *, run_id)
Start a trace for a tool run.
wait_for_futures()
Start a trace for a tool run.
wait_for_futures()
Wait for all futures to complete.
__init__(evaluators: Sequence[RunEvaluator], client: Optional[Client] = None, example_id: Optional[Union[str, UUID]] = None, skip_unfinished: bool = True, project_name: Optional[str] = 'evaluators', max_concurrency: Optional[int] = None, **kwargs: Any) → None[source]¶
Initialize the tracer.
Parameters
_schema_format – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs (Any) – Additional keyword arguments that will be passed to
the super class.
evaluators (Sequence[RunEvaluator]) – 
client (Optional[Client]) – 
example_id (Optional[Union[str, UUID]]) – 
skip_unfinished (bool) – 
project_name (Optional[str]) – 
max_concurrency (Optional[int]) – 
Return type
None
on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
Run when Retriever errors.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_retriever_start(serialized: Dict[str, Any], query: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, **kwargs: Any) → Run¶
Run when Retriever starts running.
Parameters
serialized (Dict[str, Any]) – 
query (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
kwargs (Any) – 
Return type
Run
on_retry(retry_state: RetryCallState, *, run_id: UUID, **kwargs: Any) → Run¶
Run on a retry event.
Parameters
retry_state (RetryCallState) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶
Run on arbitrary text.
Parameters
text (str) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
kwargs (Any) – 
Return type
Any
on_tool_end(output: Any, *, run_id: UUID, **kwargs: Any) → Run¶
End a trace for a tool run.
Parameters
output (Any) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_tool_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run¶
Handle an error for a tool run.
Parameters
error (BaseException) – 
run_id (UUID) – 
kwargs (Any) – 
Return type
Run
on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, name: Optional[str] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Run¶
Start a trace for a tool run.
Parameters
serialized (Dict[str, Any]) – 
input_str (str) – 
run_id (UUID) – 
tags (Optional[List[str]]) – 
parent_run_id (Optional[UUID]) – 
metadata (Optional[Dict[str, Any]]) – 
name (Optional[str]) – 
inputs (Optional[Dict[str, Any]]) – 
kwargs (Any) – 
Return type
Run
wait_for_futures() → None[source]¶
Wait for all futures to complete.
Return type
None
langchain_core.tracers.schemas.ToolRun¶
class langchain_core.tracers.schemas.ToolRun[source]¶
Bases: BaseRun
[Deprecated] Class for ToolRun.
Notes
Deprecated since version 0.1.0: Use Run instead.
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.
param action: str [Required]¶
param child_chain_runs: List[ChainRun] [Optional]¶
param child_execution_order: int [Required]¶
param child_llm_runs: List[LLMRun] [Optional]¶
param child_tool_runs: List[ToolRun] [Optional]¶
param end_time: datetime [Optional]¶
param error: Optional[str] = None¶
param execution_order: int [Required]¶
param extra: Optional[Dict[str, Any]] = None¶
param output: Optional[str] = None¶
param parent_uuid: Optional[str] = None¶
param serialized: Dict[str, Any] [Required]¶
param session_id: int [Required]¶
param start_time: datetime [Optional]¶
param tool_input: str [Required]¶
param uuid: str [Required]¶
classmethod construct(_fields_set: Optional[SetStr] = 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 (Optional[SetStr]) – 
values (Any) – 
Return type
Model
langchain_core.tracers.root_listeners.AsyncRootListenersTracer¶
class langchain_core.tracers.root_listeners.AsyncRootListenersTracer(*, config: RunnableConfig, on_start: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]], on_end: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]], on_error: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]])[source]¶
Async Tracer that calls listeners on run start, end, and error.
Initialize the tracer.
Parameters
_schema_format – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs – Additional keyword arguments that will be passed to
the super class.
config (RunnableConfig) – 
on_start (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
on_end (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
on_error (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
Attributes
Attributes
ignore_agent
Whether to ignore agent callbacks.
ignore_chain
Whether to ignore chain callbacks.
ignore_chat_model
Whether to ignore chat model callbacks.
ignore_llm
Whether to ignore LLM callbacks.
ignore_retriever
Whether to ignore retriever callbacks.
ignore_retry
Whether to ignore retry callbacks.
raise_error
run_inline
Methods
__init__(*, config, on_start, on_end, on_error)
Initialize the tracer.
on_agent_action(action, *, run_id[, ...])
Run on agent action.
on_agent_finish(finish, *, run_id[, ...])
Run on agent end.
on_chain_end(outputs, *, run_id[, inputs])
Run when chain ends running.
on_chain_error(error, *[, inputs])
Run when chain errors.
on_chain_start(serialized, inputs, *, run_id)
Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)
Run when a chat model starts running.
on_llm_end(response, *, run_id[, ...])
Run when LLM ends running.
on_llm_error(error, *, run_id[, ...])
Run when LLM errors.
on_llm_new_token(token, *[, chunk, ...])
Run on new LLM token.
on_llm_start(serialized, prompts, *, run_id)
Run when LLM starts running.
on_retriever_end(documents, *, run_id[, ...])
Run on retriever end.
on_retriever_error(error, *, run_id[, ...])
Run on retriever error.
on_retriever_start(serialized, query, *, run_id)
on_retriever_start(serialized, query, *, run_id)
Run on retriever start.
on_retry(retry_state, *, run_id, **kwargs)
Run on a retry event.
on_text(text, *, run_id[, parent_run_id, tags])
Run on arbitrary text.
on_tool_end(output, *, run_id, **kwargs)
Run when tool ends running.
on_tool_error(error, *, run_id[, ...])
Run when tool errors.
on_tool_start(serialized, input_str, *, run_id)
Run when tool starts running.
__init__(*, config: RunnableConfig, on_start: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]], on_end: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]], on_error: Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) → None[source]¶
Initialize the tracer.
Parameters
_schema_format – Primarily changes how the inputs and outputs are
handled. For internal use only. This API will change.
- ‘original’ is the format used by all current tracers.
This format is slightly inconsistent with respect to inputs
and outputs.
’streaming_events’ is used for supporting streaming events,for internal usage. It will likely change in the future, or
be deprecated entirely in favor of a dedicated async tracer
for streaming events.
’original+chat’ is a format that is the same as ‘original’except it does NOT raise an attribute error on_chat_model_start
kwargs – Additional keyword arguments that will be passed to
the super class.
kwargs – Additional keyword arguments that will be passed to
the super class.
config (RunnableConfig) – 
on_start (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
on_end (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
on_error (Optional[Union[Callable[[Run], Awaitable[None]], Callable[[Run, RunnableConfig], Awaitable[None]]]]) – 
Return type
None
async on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent action.
Parameters
action (AgentAction) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, **kwargs: Any) → None¶
Run on agent end.
Parameters
finish (AgentFinish) – 
run_id (UUID) – 
parent_run_id (Optional[UUID]) – 
tags (Optional[List[str]]) – 
kwargs (Any) – 
Return type
None
async on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → None¶
Run when chain ends running.
Parameters
outputs (Dict[str, Any]) – 
run_id (UUID) –