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.

(https://context.ai).

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_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__`([token, verbose])
`on_agent_action`(action, *, run_id[, ...])	Run on agent action.
`on_agent_finish`(finish, *, run_id[, ...])	Run on the 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_custom_event`(name, data, *, run_id[, ...])	Override to define a handler for a custom event.
`on_llm_end`(response, **kwargs)	Run when LLM ends.
`on_llm_error`(error, *, run_id[, parent_run_id])	Run when LLM errors.
`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 the 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 an arbitrary text.
`on_tool_end`(output, *, run_id[, parent_run_id])	Run when the 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 the 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: UUID | None = None, **kwargs: Any) → Any#

Run on agent action.

Parameters:

action (AgentAction) – The agent action.
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_agent_finish(finish: AgentFinish, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) → Any#

Run on the agent end.

Parameters:

finish (AgentFinish) – The agent finish.
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_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: UUID | None = None, **kwargs: Any) → Any#

Run when chain 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_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_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 (list[str] | None) – The tags associated with the custom event (includes inherited tags).
metadata (dict[str, Any] | None) – 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]#

Run when LLM ends.

Parameters:

response (LLMResult)
kwargs (Any)

Return type:

None

on_llm_error(error: BaseException, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) → Any#

Run when LLM 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_llm_new_token(token: str, *, chunk: GenerationChunk | ChatGenerationChunk | None = None, run_id: UUID, parent_run_id: UUID | None = 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, containing content and other information.
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_llm_start(serialized: dict[str, Any], prompts: list[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 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]) – The serialized LLM.
prompts (List[str]) – The prompts.
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_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, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) → Any#

Run on an arbitrary text.

Parameters:

text (str) – The text.
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_tool_end(output: Any, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) → Any#

Run when the tool ends running.

Parameters:

output (Any) – The output of the tool.
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_tool_error(error: BaseException, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) → Any#

Run when tool 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_tool_start(serialized: dict[str, Any], input_str: str, *, run_id: UUID, parent_run_id: UUID | None = None, tags: list[str] | None = None, metadata: dict[str, Any] | None = None, inputs: dict[str, Any] | None = None, **kwargs: Any) → Any#

Run when the tool starts running.

Parameters:

serialized (Dict[str, Any]) – The serialized tool.
input_str (str) – The input string.
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.
inputs (Optional[Dict[str, Any]]) – The inputs.
kwargs (Any) – Additional keyword arguments.

Return type:

Any

Examples using ContextCallbackHandler

Context