langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler

class langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler

Callback handler for streaming. Only works with LLMs that support streaming.

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__()
on_agent_action(action, **kwargs)	Run on agent action.
on_agent_finish(finish, **kwargs)	Run on agent end.
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 LLM 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 on new LLM token.
on_llm_start(serialized, prompts, **kwargs)	Run when LLM starts running.
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)	Run on arbitrary text.
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.

__init__()

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

Run on agent action.

Parameters

• action (AgentAction) –

• kwargs (Any) –

Return type

Any

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

Run on agent end.

Parameters

• finish (AgentFinish) –

• kwargs (Any) –

Return type

None

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

Run when chain ends running.

Parameters

• outputs (Dict[str, Any]) –

• kwargs (Any) –

Return type

None

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

Run when chain errors.

Parameters

• error (BaseException) –

• kwargs (Any) –

Return type

None

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

Run when chain starts running.

Parameters

• serialized (Dict[str, Any]) –

• inputs (Dict[str, Any]) –

• kwargs (Any) –

Return type

None

on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], **kwargs: Any) → None

Run when LLM starts running.

Parameters

• serialized (Dict[str, Any]) –

• messages (List[List[BaseMessage]]) –

• kwargs (Any) –

Return type

None

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

Run when LLM ends running.

Parameters

• response (LLMResult) –

• kwargs (Any) –

Return type

None

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

Run when LLM errors.

Parameters

• error (BaseException) –

• kwargs (Any) –

Return type

None

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

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

Parameters

• token (str) –

• kwargs (Any) –

Return type

None

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

Run when LLM starts running.

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: Optional[UUID] = None, **kwargs: Any) → Any

Run when Retriever ends running.

Parameters

• documents (Sequence[Document]) –

• run_id (UUID) –

• parent_run_id (Optional[UUID]) –

• kwargs (Any) –

Return type

Any

on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run when Retriever errors.

Parameters

• error (BaseException) –

• run_id (UUID) –

• parent_run_id (Optional[UUID]) –

• kwargs (Any) –

Return type

Any

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.

Parameters

• serialized (Dict[str, Any]) –

• query (str) –

• run_id (UUID) –

• parent_run_id (Optional[UUID]) –

• tags (Optional[List[str]]) –

• metadata (Optional[Dict[str, Any]]) –

• kwargs (Any) –

Return type

Any

on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on a retry event.

Parameters

• retry_state (RetryCallState) –

• run_id (UUID) –

• parent_run_id (Optional[UUID]) –

• kwargs (Any) –

Return type

Any

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

Run on arbitrary text.

Parameters

• text (str) –

• kwargs (Any) –

Return type

None

on_tool_end(output: Any, **kwargs: Any) → None

Run when tool ends running.

Parameters

• output (Any) –

• kwargs (Any) –

Return type

None

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

Run when tool errors.

Parameters

• error (BaseException) –

• kwargs (Any) –

Return type

None

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

Run when tool starts running.

Parameters

• serialized (Dict[str, Any]) –

• input_str (str) –

• kwargs (Any) –

Return type

None

Examples using StreamingStdOutCallbackHandler

• Callbacks support token-wise streaming

• Download a llamafile from HuggingFace

• GPT4All

• Guardrails for Amazon Bedrock with trace

• Let’s try out LLAMA model offered on EverlyAI Hosted Endpoints {#lets-try-out-llama-model-offered-on-everlyai-hosted-endpoints}

• Note importing TitanTakeoffPro instead of TitanTakeoff will work as well both use same object under the hood

• Run the chain specifying only the input variable for the first chain.

• Setup {#setup}

• arthur_tracking.md

• ctransformers.md

• get a new token: https://deepinfra.com/login?from=%2Fdash

• get a token: https://huggingface.co/docs/api-inference/quicktour#get-your-api-token

• gpt_router.md

• litellm.md

• litellm_router.md

• magics to auto-reload external modules in case you are making changes to langchain while working on this notebook

• textgen.md

• yuan2.md

• zhipuai.md