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 (List[str] | None) – The tags associated with the custom event (includes inherited tags).

  • metadata (Dict[str, Any] | None) – The metadata associated with the custom event (includes inherited metadata).

  • kwargs (Any) –

Return type:

Any

New 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

On this page