langchain_community.callbacks.labelstudio_callback.LabelStudioCallbackHandler

class langchain_community.callbacks.labelstudio_callback.LabelStudioCallbackHandler(api_key: Optional[str] = None, url: Optional[str] = None, project_id: Optional[int] = None, project_name: str = 'LangChain-%Y-%m-%d', project_config: Optional[str] = None, mode: Union[str, LabelStudioMode] = LabelStudioMode.PROMPT)

Label Studio callback handler. Provides the ability to send predictions to Label Studio for human evaluation, feedback and annotation.

Parameters

• api_key – Label Studio API key

• url – Label Studio URL

• project_id – Label Studio project ID

• project_name – Label Studio project name

• project_config – Label Studio project config (XML)

• mode – Label Studio mode (“prompt” or “chat”)

Examples

>>> from langchain_community.llms import OpenAI
>>> from langchain_community.callbacks import LabelStudioCallbackHandler
>>> handler = LabelStudioCallbackHandler(
...             api_key='<your_key_here>',
...             url='http://localhost:8080',
...             project_name='LangChain-%Y-%m-%d',
...             mode='prompt'
... )
>>> llm = OpenAI(callbacks=[handler])
>>> llm.predict('Tell me a story about a dog.')

Attributes

DEFAULT_PROJECT_NAME
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__([api_key, url, project_id, ...])
add_prompts_generations(run_id, generations)
on_agent_action(action, **kwargs)	Do nothing when agent takes a specific action.
on_agent_finish(finish, **kwargs)	Do nothing
on_chain_end(outputs, **kwargs)	Run when chain ends running.
on_chain_error(error, **kwargs)	Do nothing when LLM chain outputs an error.
on_chain_start(serialized, inputs, **kwargs)	Run when chain starts running.
on_chat_model_start(serialized, messages, *, ...)	Save the prompts in memory when an LLM starts.
on_llm_end(response, **kwargs)	Create a new Label Studio task for each prompt and generation.
on_llm_error(error, **kwargs)	Do nothing when LLM outputs an error.
on_llm_new_token(token, **kwargs)	Do nothing when a new token is generated.
on_llm_start(serialized, prompts, **kwargs)	Save the prompts in memory when an 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_retry(retry_state, *, run_id[, parent_run_id])	Run on a retry event.
on_text(text, **kwargs)	Do nothing
on_tool_end(output[, observation_prefix, ...])	Do nothing when tool ends.
on_tool_error(error, **kwargs)	Do nothing when tool outputs an error.
on_tool_start(serialized, input_str, **kwargs)	Do nothing when tool starts.

__init__(api_key: Optional[str] = None, url: Optional[str] = None, project_id: Optional[int] = None, project_name: str = 'LangChain-%Y-%m-%d', project_config: Optional[str] = None, mode: Union[str, LabelStudioMode] = LabelStudioMode.PROMPT)

add_prompts_generations(run_id: str, generations: List[List[Generation]]) → None

on_agent_action(action: AgentAction, **kwargs: Any) → Any

Do nothing when agent takes a specific action.

on_agent_finish(finish: AgentFinish, **kwargs: Any) → None

Do nothing

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

Run when chain ends running.

on_chain_error(error: BaseException, **kwargs: Any) → None

Do nothing when LLM chain outputs an error.

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

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

Save the prompts in memory when an LLM starts.

on_llm_end(response: LLMResult, **kwargs: Any) → None

Create a new Label Studio task for each prompt and generation.

on_llm_error(error: BaseException, **kwargs: Any) → None

Do nothing when LLM outputs an error.

on_llm_new_token(token: str, **kwargs: Any) → None

Do nothing when a new token is generated.

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

Save the prompts in memory when an 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: BaseException, *, 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_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on a retry event.

on_text(text: str, **kwargs: Any) → None

Do nothing

on_tool_end(output: str, observation_prefix: Optional[str] = None, llm_prefix: Optional[str] = None, **kwargs: Any) → None

Do nothing when tool ends.

on_tool_error(error: BaseException, **kwargs: Any) → None

Do nothing when tool outputs an error.

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

Do nothing when tool starts.

Examples using LabelStudioCallbackHandler

• Label Studio