langchain_community.callbacks.context_callback.ContextCallbackHandler¶

class langchain_community.callbacks.context_callback.ContextCallbackHandler(token: str = '', verbose: bool = False, **kwargs: Any)[source]¶

Callback Handler that records transcripts to the Context service.

Keyword Arguments

token (optional) – The token with which to authenticate requests to Context. Visit https://with.context.ai/settings to generate a token. If not provided, the value of the CONTEXT_TOKEN environment variable will be used.

Raises

ImportError – if the context-python package is not installed.

Parameters

  • token (str) –

  • verbose (bool) –

  • kwargs (Any) –

Chat Example:
>>> from langchain_community.llms import ChatOpenAI
>>> from langchain_community.callbacks import ContextCallbackHandler
>>> context_callback = ContextCallbackHandler(
...     token="<CONTEXT_TOKEN_HERE>",
... )
>>> chat = ChatOpenAI(
...     temperature=0,
...     headers={"user_id": "123"},
...     callbacks=[context_callback],
...     openai_api_key="API_KEY_HERE",
... )
>>> messages = [
...     SystemMessage(content="You translate English to French."),
...     HumanMessage(content="I love programming with LangChain."),
... ]
>>> chat.invoke(messages)
Chain Example:
>>> from langchain.chains import LLMChain
>>> from langchain_community.chat_models import ChatOpenAI
>>> from langchain_community.callbacks import ContextCallbackHandler
>>> context_callback = ContextCallbackHandler(
...     token="<CONTEXT_TOKEN_HERE>",
... )
>>> human_message_prompt = HumanMessagePromptTemplate(
...     prompt=PromptTemplate(
...         template="What is a good name for a company that makes {product}?",
...         input_variables=["product"],
...    ),
... )
>>> chat_prompt_template = ChatPromptTemplate.from_messages(
...   [human_message_prompt]
... )
>>> callback = ContextCallbackHandler(token)
>>> # Note: the same callback object must be shared between the
...   LLM and the chain.
>>> chat = ChatOpenAI(temperature=0.9, callbacks=[callback])
>>> chain = LLMChain(
...   llm=chat,
...   prompt=chat_prompt_template,
...   callbacks=[callback]
... )
>>> chain.run("colorful socks")

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__([token, verbose])

on_agent_action(action, *, run_id[, ...])

Run on agent action.

on_agent_finish(finish, *, run_id[, ...])

Run on agent end.

on_chain_end(outputs, **kwargs)

Run when chain ends.

on_chain_error(error, *, run_id[, parent_run_id])

Run when chain errors.

on_chain_start(serialized, inputs, **kwargs)

Run when chain starts.

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

Run when the chat model is started.

on_llm_end(response, **kwargs)

Run when LLM ends.

on_llm_error(error, *, run_id[, parent_run_id])

Run when LLM errors. :param error: The error that occurred. :type error: BaseException :param kwargs: Additional keyword arguments. - response (LLMResult): The response which was generated before the error occurred. :type kwargs: Any.

on_llm_new_token(token, *[, chunk, ...])

Run on new LLM token.

on_llm_start(serialized, prompts, *, run_id)

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, *, run_id[, parent_run_id])

Run on arbitrary text.

on_tool_end(output, *, run_id[, parent_run_id])

Run when tool ends running.

on_tool_error(error, *, run_id[, parent_run_id])

Run when tool errors.

on_tool_start(serialized, input_str, *, run_id)

Run when tool starts running.
__init__(token: str = '', verbose: bool = False, **kwargs: Any) → None[source]¶
Parameters

  • token (str) –

  • verbose (bool) –

  • kwargs (Any) –

Return type

None

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

Run on agent action.

Parameters

  • action (AgentAction) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

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

Run on agent end.

Parameters

  • finish (AgentFinish) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

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

Run when chain ends.

Parameters

  • outputs (Dict[str, Any]) –

  • kwargs (Any) –

Return type

None

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

Run when chain errors.

Parameters

  • error (BaseException) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

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

Run when chain starts.

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]], *, run_id: UUID, **kwargs: Any) → Any[source]¶

Run when the chat model is started.

Parameters

  • serialized (Dict[str, Any]) –

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

  • run_id (UUID) –

  • kwargs (Any) –

Return type

Any

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

Run when LLM ends.

Parameters

  • response (LLMResult) –

  • kwargs (Any) –

Return type

None

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

Run when LLM errors. :param error: The error that occurred. :type error: BaseException :param kwargs: Additional keyword arguments.

  • response (LLMResult): The response which was generated before

    the error occurred.

Parameters

  • error (BaseException) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

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

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

Parameters

  • token (str) – The new token.

  • chunk (GenerationChunk | ChatGenerationChunk) – The new generated chunk,

  • information. (containing content and other) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

on_llm_start(serialized: Dict[str, Any], prompts: List[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 LLM starts running.

ATTENTION: This method is called for non-chat models (regular LLMs). If

you’re implementing a handler for a chat model, you should use on_chat_model_start instead.

Parameters

  • serialized (Dict[str, Any]) –

  • prompts (List[str]) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • tags (Optional[List[str]]) –

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

  • kwargs (Any) –

Return type

Any

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

Run on arbitrary text.

Parameters

  • text (str) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

on_tool_end(output: Any, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any¶

Run when tool ends running.

Parameters

  • output (Any) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

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

Run when tool errors.

Parameters

  • error (BaseException) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • kwargs (Any) –

Return type

Any

on_tool_start(serialized: Dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶

Run when tool starts running.

Parameters

  • serialized (Dict[str, Any]) –

  • input_str (str) –

  • run_id (UUID) –

  • parent_run_id (Optional[UUID]) –

  • tags (Optional[List[str]]) –

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

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

  • kwargs (Any) –

Return type

Any

Examples using ContextCallbackHandler¶