CometCallbackHandler#
- class langchain_community.callbacks.comet_ml_callback.CometCallbackHandler(task_type: str | None = 'inference', workspace: str | None = None, project_name: str | None = None, tags: Sequence | None = None, name: str | None = None, visualizations: List[str] | None = None, complexity_metrics: bool = False, custom_metrics: Callable | None = None, stream_logs: bool = True)[source]#
Callback Handler that logs to Comet.
- Parameters:
job_type (str) β The type of comet_ml task such as βinferenceβ, βtestingβ or βqcβ
project_name (str) β The comet_ml project name
tags (list) β Tags to add to the task
task_name (str) β Name of the comet_ml task
visualize (bool) β Whether to visualize the run.
complexity_metrics (bool) β Whether to log complexity metrics
stream_logs (bool) β Whether to stream callback actions to Comet
task_type (str | None) β
workspace (str | None) β
name (str | None) β
visualizations (List[str] | None) β
custom_metrics (Callable | None) β
This handler will utilize the associated callback method and formats the input of each callback function with metadata regarding the state of LLM run, and adds the response to the list of records for both the {method}_records and action. It then logs the response to Comet.
Initialize callback handler.
Attributes
always_verboseWhether to call verbose callbacks even if verbose is False.
ignore_agentWhether to ignore agent callbacks.
ignore_chainWhether to ignore chain callbacks.
ignore_chat_modelWhether to ignore chat model callbacks.
ignore_custom_eventIgnore custom event.
ignore_llmWhether to ignore LLM callbacks.
ignore_retrieverWhether to ignore retriever callbacks.
ignore_retryWhether to ignore retry callbacks.
raise_errorWhether to raise an error if an exception occurs.
run_inlineWhether to run the callback inline.
Methods
__init__([task_type,Β workspace,Β ...])Initialize callback handler.
flush_tracker([langchain_asset,Β task_type,Β ...])Flush the tracker and setup the session.
on_agent_action(action,Β **kwargs)Run on agent action.
on_agent_finish(finish,Β **kwargs)Run when agent ends running.
on_chain_end(outputs,Β **kwargs)Run when chain ends running.
on_chain_error(error,Β **kwargs)Run when chain errors.
on_chain_start(serialized,Β inputs,Β **kwargs)Run when chain starts running.
on_chat_model_start(serialized,Β messages,Β *,Β ...)Run when a chat model starts running.
on_custom_event(name,Β data,Β *,Β run_id[,Β ...])Override to define a handler for a custom event.
on_llm_end(response,Β **kwargs)Run when LLM ends running.
on_llm_error(error,Β **kwargs)Run when LLM errors.
on_llm_new_token(token,Β **kwargs)Run when LLM generates a new token.
on_llm_start(serialized,Β prompts,Β **kwargs)Run when LLM starts.
on_retriever_end(documents,Β *,Β run_id[,Β ...])Run when Retriever ends running.
on_retriever_error(error,Β *,Β run_id[,Β ...])Run when Retriever errors.
on_retriever_start(serialized,Β query,Β *,Β run_id)Run when the Retriever starts running.
on_retry(retry_state,Β *,Β run_id[,Β parent_run_id])Run on a retry event.
on_text(text,Β **kwargs)Run when agent is ending.
on_tool_end(output,Β **kwargs)Run when tool ends running.
on_tool_error(error,Β **kwargs)Run when tool errors.
on_tool_start(serialized,Β input_str,Β **kwargs)Run when tool starts running.
Reset the callback metadata.
- __init__(task_type: str | None = 'inference', workspace: str | None = None, project_name: str | None = None, tags: Sequence | None = None, name: str | None = None, visualizations: List[str] | None = None, complexity_metrics: bool = False, custom_metrics: Callable | None = None, stream_logs: bool = True) None[source]#
Initialize callback handler.
- Parameters:
task_type (str | None) β
workspace (str | None) β
project_name (str | None) β
tags (Sequence | None) β
name (str | None) β
visualizations (List[str] | None) β
complexity_metrics (bool) β
custom_metrics (Callable | None) β
stream_logs (bool) β
- Return type:
None
- flush_tracker(langchain_asset: Any = None, task_type: str | None = 'inference', workspace: str | None = None, project_name: str | None = 'comet-langchain-demo', tags: Sequence | None = None, name: str | None = None, visualizations: List[str] | None = None, complexity_metrics: bool = False, custom_metrics: Callable | None = None, finish: bool = False, reset: bool = False) None[source]#
Flush the tracker and setup the session.
Everything after this will be a new table.
- Parameters:
name (str | None) β Name of the performed session so far so it is identifiable
langchain_asset (Any) β The langchain asset to save.
finish (bool) β Whether to finish the run.
Returns β None
task_type (str | None) β
workspace (str | None) β
project_name (str | None) β
tags (Sequence | None) β
visualizations (List[str] | None) β
complexity_metrics (bool) β
custom_metrics (Callable | None) β
reset (bool) β
- Return type:
None
- get_custom_callback_meta() Dict[str, Any]#
- Return type:
Dict[str, Any]
- on_agent_action(action: AgentAction, **kwargs: Any) Any[source]#
Run on agent action.
- Parameters:
action (AgentAction) β
kwargs (Any) β
- Return type:
Any
- on_agent_finish(finish: AgentFinish, **kwargs: Any) None[source]#
Run when agent ends running.
- Parameters:
finish (AgentFinish) β
kwargs (Any) β
- Return type:
None
- on_chain_end(outputs: Dict[str, Any], **kwargs: Any) None[source]#
Run when chain ends running.
- Parameters:
outputs (Dict[str, Any]) β
kwargs (Any) β
- Return type:
None
- on_chain_error(error: BaseException, **kwargs: Any) None[source]#
Run when chain errors.
- Parameters:
error (BaseException) β
kwargs (Any) β
- 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]) β
inputs (Dict[str, Any]) β
kwargs (Any) β
- 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 youβre implementing
a handler for a non-chat model, you should use on_llm_start instead.
- Parameters:
serialized (Dict[str, Any]) β The serialized chat model.
messages (List[List[BaseMessage]]) β The messages.
run_id (UUID) β The run ID. This is the ID of the current run.
parent_run_id (UUID) β The parent run ID. This is the ID of the parent run.
tags (Optional[List[str]]) β The tags.
metadata (Optional[Dict[str, Any]]) β The metadata.
kwargs (Any) β 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) β The name of the custom event.
data (Any) β The data for the custom event. Format will match the format specified by the user.
run_id (UUID) β The ID of the run.
tags (List[str] | None) β The tags associated with the custom event (includes inherited tags).
metadata (Dict[str, Any] | None) β The metadata associated with the custom event (includes inherited metadata).
kwargs (Any) β
- Return type:
Any
New in version 0.2.15.
- on_llm_end(response: LLMResult, **kwargs: Any) None[source]#
Run when LLM ends running.
- Parameters:
response (LLMResult) β
kwargs (Any) β
- Return type:
None
- on_llm_error(error: BaseException, **kwargs: Any) None[source]#
Run when LLM errors.
- Parameters:
error (BaseException) β
kwargs (Any) β
- Return type:
None
- on_llm_new_token(token: str, **kwargs: Any) None[source]#
Run when LLM generates a new token.
- Parameters:
token (str) β
kwargs (Any) β
- 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]) β
prompts (List[str]) β
kwargs (Any) β
- 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]) β The documents retrieved.
run_id (UUID) β The run ID. This is the ID of the current run.
parent_run_id (UUID) β The parent run ID. This is the ID of the parent run.
kwargs (Any) β 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) β The error that occurred.
run_id (UUID) β The run ID. This is the ID of the current run.
parent_run_id (UUID) β The parent run ID. This is the ID of the parent run.
kwargs (Any) β 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]) β The serialized Retriever.
query (str) β The query.
run_id (UUID) β The run ID. This is the ID of the current run.
parent_run_id (UUID) β The parent run ID. This is the ID of the parent run.
tags (Optional[List[str]]) β The tags.
metadata (Optional[Dict[str, Any]]) β The metadata.
kwargs (Any) β 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) β The retry state.
run_id (UUID) β The run ID. This is the ID of the current run.
parent_run_id (UUID) β The parent run ID. This is the ID of the parent run.
kwargs (Any) β Additional keyword arguments.
- Return type:
Any
- on_text(text: str, **kwargs: Any) None[source]#
Run when agent is ending.
- Parameters:
text (str) β
kwargs (Any) β
- Return type:
None
- on_tool_end(output: Any, **kwargs: Any) None[source]#
Run when tool ends running.
- Parameters:
output (Any) β
kwargs (Any) β
- Return type:
None
- on_tool_error(error: BaseException, **kwargs: Any) None[source]#
Run when tool errors.
- Parameters:
error (BaseException) β
kwargs (Any) β
- 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]) β
input_str (str) β
kwargs (Any) β
- Return type:
None
- reset_callback_meta() None#
Reset the callback metadata.
- Return type:
None
Examples using CometCallbackHandler