langchain_community.callbacks.tracers.wandb.WandbTracer

class langchain_community.callbacks.tracers.wandb.WandbTracer(run_args: Optional[WandbRunArgs] = None, **kwargs: Any)

Callback Handler that logs to Weights and Biases.

This handler will log the model architecture and run traces to Weights and Biases. This will ensure that all LangChain activity is logged to W&B.

Initializes the WandbTracer.

Parameters

run_args – (dict, optional) Arguments to pass to wandb.init(). If not provided, wandb.init() will be called with no arguments. Please refer to the wandb.init for more details.

To use W&B to monitor all LangChain activity, add this tracer like any other LangChain callback: ``` from wandb.integration.langchain import WandbTracer

tracer = WandbTracer() chain = LLMChain(llm, callbacks=[tracer]) # …end of notebook / script: tracer.finish() ```

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__([run_args])	Initializes the WandbTracer.
finish()	Waits for all asynchronous processes to finish and data to upload.
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, *, ...)	Run when a chat model starts running.
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.

__init__(run_args: Optional[WandbRunArgs] = None, **kwargs: Any) → None

Initializes the WandbTracer.

Parameters

run_args – (dict, optional) Arguments to pass to wandb.init(). If not provided, wandb.init() will be called with no arguments. Please refer to the wandb.init for more details.

To use W&B to monitor all LangChain activity, add this tracer like any other LangChain callback: ``` from wandb.integration.langchain import WandbTracer

tracer = WandbTracer() chain = LLMChain(llm, callbacks=[tracer]) # …end of notebook / script: tracer.finish() ```

finish() → None

Waits for all asynchronous processes to finish and data to upload.

Proxy for wandb.finish().

on_agent_action(action: AgentAction, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on agent action.

on_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on agent end.

on_chain_end(outputs: Dict[str, Any], *, run_id: UUID, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Run

End a trace for a chain run.

on_chain_error(error: BaseException, *, inputs: Optional[Dict[str, Any]] = None, run_id: UUID, **kwargs: Any) → Run

Handle an error for a chain run.

on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], *, run_id: UUID, tags: Optional[List[str]] = None, parent_run_id: Optional[UUID] = None, metadata: Optional[Dict[str, Any]] = None, run_type: Optional[str] = None, name: Optional[str] = None, **kwargs: Any) → Run

Start a trace for a chain run.

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_end(response: LLMResult, *, run_id: UUID, **kwargs: Any) → Run

End a trace for an LLM run.

on_llm_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run

Handle an error for an LLM run.

on_llm_new_token(token: str, *, chunk: Optional[Union[GenerationChunk, ChatGenerationChunk]] = None, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Run

Run on new LLM token. Only available when streaming is enabled.

on_llm_start(serialized: Dict[str, Any], prompts: List[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, **kwargs: Any) → Run

Start a trace for an LLM run.

on_retriever_end(documents: Sequence[Document], *, run_id: UUID, **kwargs: Any) → Run

Run when Retriever ends running.

on_retriever_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run

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, name: Optional[str] = None, **kwargs: Any) → Run

Run when Retriever starts running.

on_retry(retry_state: RetryCallState, *, run_id: UUID, **kwargs: Any) → Run

Run on a retry event.

on_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on arbitrary text.

on_tool_end(output: str, *, run_id: UUID, **kwargs: Any) → Run

End a trace for a tool run.

on_tool_error(error: BaseException, *, run_id: UUID, **kwargs: Any) → Run

Handle an error for a tool 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, **kwargs: Any) → Run

Start a trace for a tool run.