langchain.callbacks.wandb_callback.WandbCallbackHandler¶
- class langchain.callbacks.wandb_callback.WandbCallbackHandler(job_type: Optional[str] = None, project: Optional[str] = 'langchain_callback_demo', entity: Optional[str] = None, tags: Optional[Sequence] = None, group: Optional[str] = None, name: Optional[str] = None, notes: Optional[str] = None, visualize: bool = False, complexity_metrics: bool = False, stream_logs: bool = False)[source]¶
Bases:
BaseMetadataCallbackHandler,BaseCallbackHandlerCallback Handler that logs to Weights and Biases.
- Parameters
job_type (str) – The type of job.
project (str) – The project to log to.
entity (str) – The entity to log to.
tags (list) – The tags to log.
group (str) – The group to log to.
name (str) – The name of the run.
notes (str) – The notes to log.
visualize (bool) – Whether to visualize the run.
complexity_metrics (bool) – Whether to log complexity metrics.
stream_logs (bool) – Whether to stream callback actions to W&B
This handler will utilize the associated callback method called 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 using the run.log() method to Weights and Biases.
Initialize callback handler.
Methods
__init__([job_type, project, entity, tags, ...])Initialize callback handler.
flush_tracker([langchain_asset, reset, ...])Flush the tracker and reset the session.
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_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 Retriever starts running.
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.
Reset the callback metadata.
Attributes
Whether to call verbose callbacks even if verbose is False.
Whether to ignore agent callbacks.
Whether to ignore chain callbacks.
Whether to ignore chat model callbacks.
Whether to ignore LLM callbacks.
Whether to ignore retriever callbacks.
Whether to ignore retry callbacks.
- flush_tracker(langchain_asset: Any = None, reset: bool = True, finish: bool = False, job_type: Optional[str] = None, project: Optional[str] = None, entity: Optional[str] = None, tags: Optional[Sequence] = None, group: Optional[str] = None, name: Optional[str] = None, notes: Optional[str] = None, visualize: Optional[bool] = None, complexity_metrics: Optional[bool] = None) None[source]¶
Flush the tracker and reset the session.
- Parameters
langchain_asset – The langchain asset to save.
reset – Whether to reset the session.
finish – Whether to finish the run.
job_type – The job type.
project – The project.
entity – The entity.
tags – The tags.
group – The group.
name – The name.
notes – The notes.
visualize – Whether to visualize.
complexity_metrics – Whether to compute complexity metrics.
Returns – None
- get_custom_callback_meta() Dict[str, Any]¶
- on_agent_finish(finish: AgentFinish, **kwargs: Any) None[source]¶
Run when agent ends running.
- on_chain_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) None[source]¶
Run when chain errors.
- on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) None[source]¶
Run when chain starts running.
- on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) Any¶
Run when a chat model starts running.
- on_llm_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) None[source]¶
Run when LLM errors.
- on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) None[source]¶
Run when LLM starts.
- on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) Any¶
Run when Retriever ends running.
- on_retriever_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) Any¶
Run when Retriever errors.
- 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, **kwargs: Any) Any¶
Run when Retriever starts running.
- on_tool_error(error: Union[Exception, KeyboardInterrupt], **kwargs: Any) None[source]¶
Run when tool errors.
- on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) None[source]¶
Run when tool starts running.
- reset_callback_meta() None¶
Reset the callback metadata.
- property always_verbose: bool¶
Whether to call verbose callbacks even if verbose is False.
- property ignore_agent: bool¶
Whether to ignore agent callbacks.
- property ignore_chain: bool¶
Whether to ignore chain callbacks.
- property ignore_chat_model: bool¶
Whether to ignore chat model callbacks.
- property ignore_llm: bool¶
Whether to ignore LLM callbacks.
- property ignore_retriever: bool¶
Whether to ignore retriever callbacks.
- property ignore_retry: bool¶
Whether to ignore retry callbacks.
- raise_error: bool = False¶
- run_inline: bool = False¶