SageMakerCallbackHandler#

class langchain_community.callbacks.sagemaker_callback.SageMakerCallbackHandler(run: Any)[source]#

Callback Handler that logs prompt artifacts and metrics to SageMaker Experiments.

Parameters:

run (sagemaker.experiments.run.Run) – Run object where the experiment is logged.

Initialize callback handler.

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_custom_event

Ignore custom event.

ignore_llm

Whether to ignore LLM callbacks.

ignore_retriever

Whether to ignore retriever callbacks.

ignore_retry

Whether to ignore retry callbacks.

raise_error

Whether to raise an error if an exception occurs.

run_inline

Whether to run the callback inline.

Methods

__init__(run)

Initialize callback handler.

flush_tracker()

Reset the steps and delete the temporary local directory.

jsonf(data, data_dir, filename[, is_output])

To log the input data as json file artifact.

on_agent_action(action, **kwargs)

Run on agent action.

on_agent_finish(finish, **kwargs)

Run when agent ends running.

on_chain_end(outputs, **kwargs)

Run when chain ends running.

on_chain_error(error, **kwargs)

Run when chain errors.

on_chain_start(serialized, inputs, **kwargs)

Run when chain starts running.

on_chat_model_start(serialized, messages, *, ...)

Run when a chat model starts running.

on_custom_event(name, data, *, run_id[, ...])

Override to define a handler for a custom event.

on_llm_end(response, **kwargs)

Run when LLM ends running.

on_llm_error(error, **kwargs)

Run when LLM errors.

on_llm_new_token(token, **kwargs)

Run when LLM generates a new token.

on_llm_start(serialized, prompts, **kwargs)

Run when LLM starts.

on_retriever_end(documents, *, run_id[, ...])

Run when Retriever ends running.

on_retriever_error(error, *, run_id[, ...])

Run when Retriever errors.

on_retriever_start(serialized, query, *, run_id)

Run when the Retriever starts running.

on_retry(retry_state, *, run_id[, parent_run_id])

Run on a retry event.

on_text(text, **kwargs)

Run when agent is ending.

on_tool_end(output, **kwargs)

Run when tool ends running.

on_tool_error(error, **kwargs)

Run when tool errors.

on_tool_start(serialized, input_str, **kwargs)

Run when tool starts running.
__init__(run: Any) → None[source]#

Initialize callback handler.

Parameters:

run (Any)

Return type:

None

flush_tracker() → None[source]#

Reset the steps and delete the temporary local directory.

Return type:

None

jsonf(
data: Dict[str, Any],
data_dir: str,
filename: str,
is_output: bool | None = True,
) → None[source]#

To log the input data as json file artifact.

Parameters:

  • data (Dict[str, Any])

  • data_dir (str)

  • filename (str)

  • is_output (bool | None)

Return type:

None

on_agent_action(
action: AgentAction,
**kwargs: Any,
) → Any[source]#

Run on agent action.

Parameters:
Return type:

Any

on_agent_finish(
finish: AgentFinish,
**kwargs: Any,
) → None[source]#

Run when agent ends running.

Parameters:
Return type:

None

on_chain_end(
outputs: Dict[str, Any],
**kwargs: Any,
) → None[source]#

Run when chain ends running.

Parameters:

  • outputs (Dict[str, Any])

  • kwargs (Any)

Return type:

None

on_chain_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Run when chain errors.

Parameters:

  • error (BaseException)

  • kwargs (Any)

Return type:

None

on_chain_start(
serialized: Dict[str, Any],
inputs: Dict[str, Any],
**kwargs: Any,
) → None[source]#

Run when chain starts running.

Parameters:

  • serialized (Dict[str, Any])

  • inputs (Dict[str, Any])

  • kwargs (Any)

Return type:

None

on_chat_model_start(
serialized: dict[str, Any],
messages: list[list[BaseMessage]],
*,
run_id: UUID,
parent_run_id: UUID | None = None,
tags: list[str] | None = None,
metadata: dict[str, Any] | None = None,
**kwargs: Any,
) → Any#

Run when a chat model starts running.

ATTENTION: This method is called for chat models. If you’re implementing

a handler for a non-chat model, you should use on_llm_start instead.

Parameters:

  • serialized (dict[str, Any]) – The serialized chat model.

  • messages (list[list[BaseMessage]]) – The messages.

  • run_id (UUID) – The run ID. This is the ID of the current run.

  • parent_run_id (UUID) – The parent run ID. This is the ID of the parent run.

  • tags (Optional[list[str]]) – The tags.

  • metadata (Optional[dict[str, Any]]) – The metadata.

  • kwargs (Any) – Additional keyword arguments.

Return type:

Any

on_custom_event(
name: str,
data: Any,
*,
run_id: UUID,
tags: list[str] | None = None,
metadata: dict[str, Any] | None = None,
**kwargs: Any,
) → Any#

Override to define a handler for a custom event.

Parameters:

  • name (str) – The name of the custom event.

  • data (Any) – The data for the custom event. Format will match the format specified by the user.

  • run_id (UUID) – The ID of the run.

  • tags (Optional[list[str]]) – The tags associated with the custom event (includes inherited tags).

  • metadata (Optional[dict[str, Any]]) – The metadata associated with the custom event (includes inherited metadata).

  • kwargs (Any)

Return type:

Any

Added in version 0.2.15.

on_llm_end(
response: LLMResult,
**kwargs: Any,
) → None[source]#

Run when LLM ends running.

Parameters:
Return type:

None

on_llm_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Run when LLM errors.

Parameters:

  • error (BaseException)

  • kwargs (Any)

Return type:

None

on_llm_new_token(
token: str,
**kwargs: Any,
) → None[source]#

Run when LLM generates a new token.

Parameters:

  • token (str)

  • kwargs (Any)

Return type:

None

on_llm_start(
serialized: Dict[str, Any],
prompts: List[str],
**kwargs: Any,
) → None[source]#

Run when LLM starts.

Parameters:

  • serialized (Dict[str, Any])

  • prompts (List[str])

  • kwargs (Any)

Return type:

None

on_retriever_end(
documents: Sequence[Document],
*,
run_id: UUID,
parent_run_id: UUID | None = None,
**kwargs: Any,
) → Any#

Run when Retriever ends running.

Parameters:

  • documents (Sequence[Document]) – The documents retrieved.

  • run_id (UUID) – The run ID. This is the ID of the current run.

  • parent_run_id (UUID) – The parent run ID. This is the ID of the parent run.

  • kwargs (Any) – Additional keyword arguments.

Return type:

Any

on_retriever_error(
error: BaseException,
*,
run_id: UUID,
parent_run_id: UUID | None = None,
**kwargs: Any,
) → Any#

Run when Retriever errors.

Parameters:

  • error (BaseException) – The error that occurred.

  • run_id (UUID) – The run ID. This is the ID of the current run.

  • parent_run_id (UUID) – The parent run ID. This is the ID of the parent run.

  • kwargs (Any) – Additional keyword arguments.

Return type:

Any

on_retriever_start(
serialized: dict[str, Any],
query: str,
*,
run_id: UUID,
parent_run_id: UUID | None = None,
tags: list[str] | None = None,
metadata: dict[str, Any] | None = None,
**kwargs: Any,
) → Any#

Run when the Retriever starts running.

Parameters:

  • serialized (dict[str, Any]) – The serialized Retriever.

  • query (str) – The query.

  • run_id (UUID) – The run ID. This is the ID of the current run.

  • parent_run_id (UUID) – The parent run ID. This is the ID of the parent run.

  • tags (Optional[list[str]]) – The tags.

  • metadata (Optional[dict[str, Any]]) – The metadata.

  • kwargs (Any) – Additional keyword arguments.

Return type:

Any

on_retry(
retry_state: RetryCallState,
*,
run_id: UUID,
parent_run_id: UUID | None = None,
**kwargs: Any,
) → Any#

Run on a retry event.

Parameters:

  • retry_state (RetryCallState) – The retry state.

  • run_id (UUID) – The run ID. This is the ID of the current run.

  • parent_run_id (UUID) – The parent run ID. This is the ID of the parent run.

  • kwargs (Any) – Additional keyword arguments.

Return type:

Any

on_text(
text: str,
**kwargs: Any,
) → None[source]#

Run when agent is ending.

Parameters:

  • text (str)

  • kwargs (Any)

Return type:

None

on_tool_end(
output: Any,
**kwargs: Any,
) → None[source]#

Run when tool ends running.

Parameters:

  • output (Any)

  • kwargs (Any)

Return type:

None

on_tool_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Run when tool errors.

Parameters:

  • error (BaseException)

  • kwargs (Any)

Return type:

None

on_tool_start(
serialized: Dict[str, Any],
input_str: str,
**kwargs: Any,
) → None[source]#

Run when tool starts running.

Parameters:

  • serialized (Dict[str, Any])

  • input_str (str)

  • kwargs (Any)

Return type:

None

Examples using SageMakerCallbackHandler