langchain.callbacks.context_callback.ContextCallbackHandler

class langchain.callbacks.context_callback.ContextCallbackHandler(token: str = '', verbose: bool = False, **kwargs: Any)

Bases: BaseCallbackHandler

Callback Handler that records transcripts to the Context service.

(https://getcontext.ai).

Keyword Arguments

token (optional) – The token with which to authenticate requests to Context. Visit https://go.getcontext.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.

Chat Example:

>>> from langchain.llms import ChatOpenAI
>>> from langchain.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(messages)

Chain Example:

>>> from langchain import LLMChain
>>> from langchain.llms import ChatOpenAI
>>> from langchain.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")

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.
on_llm_new_token(token, *, run_id[, ...])	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_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.

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

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

Run on agent action.

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

Run on agent end.

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

Run when chain ends.

on_chain_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run when chain errors.

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

Run when chain starts.

on_chat_model_start(serialized: Dict[str, Any], messages: List[List[BaseMessage]], *, run_id: UUID, **kwargs: Any) → Any

Run when the chat model is started.

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

Run when LLM ends.

on_llm_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run when LLM errors.

on_llm_new_token(token: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

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

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.

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: Union[Exception, KeyboardInterrupt], *, 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_text(text: str, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run on arbitrary text.

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

Run when tool ends running.

on_tool_error(error: Union[Exception, KeyboardInterrupt], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

Run when tool errors.

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, **kwargs: Any) → Any

Run when tool starts running.

property ignore_agent: bool

Whether to ignore agent callbacks.

property ignore_chain: bool

Whether to ignore chain callbacks.

property ignore_chat_model: bool

Whether to ignore chat model callbacks.

property ignore_llm: bool

Whether to ignore LLM callbacks.

property ignore_retriever: bool

Whether to ignore retriever callbacks.

property ignore_retry: bool

Whether to ignore retry callbacks.

raise_error: bool = False

run_inline: bool = False

Examples using ContextCallbackHandler

• Context