LabelStudioCallbackHandler#

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

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

Parameters:

  • api_key (str | None) – Label Studio API key

  • url (str | None) – Label Studio URL

  • project_id (int | None) – Label Studio project ID

  • project_name (str) – Label Studio project name

  • project_config (str | None) – Label Studio project config (XML)

  • mode (str | LabelStudioMode) – 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.invoke('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_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__([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 a chain starts running.

on_chat_model_start(serialized, messages, *, ...)

Save the prompts in memory when an LLM starts.

on_custom_event(name, data, *, run_id[, ...])

Override to define a handler for a custom event.

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 the 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: str | None = None,
url: str | None = None,
project_id: int | None = None,
project_name: str = 'LangChain-%Y-%m-%d',
project_config: str | None = None,
mode: str | LabelStudioMode = LabelStudioMode.PROMPT,
)[source]#
Parameters:

  • api_key (str | None)

  • url (str | None)

  • project_id (int | None)

  • project_name (str)

  • project_config (str | None)

  • mode (str | LabelStudioMode)

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

  • run_id (str)

  • generations (List[List[Generation]])

Return type:

None

on_agent_action(
action: AgentAction,
**kwargs: Any,
) → Any[source]#

Do nothing when agent takes a specific action.

Parameters:
Return type:

Any

on_agent_finish(
finish: AgentFinish,
**kwargs: Any,
) → None[source]#

Do nothing

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]) – The outputs of the chain.

  • 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:

None

on_chain_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Do nothing when LLM chain outputs an error.

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 a chain starts running.

Parameters:

  • serialized (dict[str, Any]) – The serialized chain.

  • inputs (dict[str, Any]) – The inputs.

  • 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:

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[source]#

Save the prompts in memory when an LLM starts.

Parameters:

  • serialized (Dict[str, Any])

  • messages (List[List[BaseMessage]])

  • run_id (UUID)

  • parent_run_id (UUID | None)

  • tags (List[str] | None)

  • metadata (Dict[str, Any] | None)

  • kwargs (Any)

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 (Optional[list[str]]) – The tags associated with the custom event (includes inherited tags).

  • metadata (Optional[dict[str, Any]]) – The metadata associated with the custom event (includes inherited metadata).

  • kwargs (Any)

Return type:

Any

Added in version 0.2.15.

on_llm_end(
response: LLMResult,
**kwargs: Any,
) → None[source]#

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

Parameters:
Return type:

None

on_llm_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Do nothing when LLM outputs an error.

Parameters:

  • error (BaseException)

  • kwargs (Any)

Return type:

None

on_llm_new_token(
token: str,
**kwargs: Any,
) → None[source]#

Do nothing when a new token is generated.

Parameters:

  • token (str)

  • kwargs (Any)

Return type:

None

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

Save the prompts in memory when an 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]#

Do nothing

Parameters:

  • text (str)

  • kwargs (Any)

Return type:

None

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

Do nothing when tool ends.

Parameters:

  • output (str)

  • observation_prefix (str | None)

  • llm_prefix (str | None)

  • kwargs (Any)

Return type:

None

on_tool_error(
error: BaseException,
**kwargs: Any,
) → None[source]#

Do nothing when tool outputs an error.

Parameters:

  • error (BaseException)

  • kwargs (Any)

Return type:

None

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

Do nothing when tool starts.

Parameters:

  • serialized (Dict[str, Any])

  • input_str (str)

  • kwargs (Any)

Return type:

None

Examples using LabelStudioCallbackHandler