langchain.retrievers.remote_retriever.RemoteLangChainRetriever

class langchain.retrievers.remote_retriever.RemoteLangChainRetriever(*, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, url: str, headers: Optional[dict] = None, input_key: str = 'message', response_key: str = 'response', page_content_key: str = 'page_content', metadata_key: str = 'metadata')[source]

Bases: BaseRetriever

Retriever for remote LangChain API.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param headers: Optional[dict] = None

Headers to use for the request.

param input_key: str = 'message'

Key to use for the input in the request.

param metadata: Optional[Dict[str, Any]] = None

Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a retriever with its use case.

param metadata_key: str = 'metadata'

Key to use for the metadata in the response.

param page_content_key: str = 'page_content'

Key to use for the page content in the response.

param response_key: str = 'response'

Key to use for the response in the request.

param tags: Optional[List[str]] = None

Optional list of tags associated with the retriever. Defaults to None These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a retriever with its use case.

param url: str [Required]

URL of the remote LangChain API.

async aget_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) List[Document]

Asynchronously get documents relevant to a query. :param query: string to find relevant documents for :param callbacks: Callback manager or list of callbacks :param tags: Optional list of tags associated with the retriever. Defaults to None

These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Parameters

metadata – Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Returns

List of relevant documents

async ainvoke(input: str, config: Optional[RunnableConfig] = None) List[Document]
get_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) List[Document]

Retrieve documents relevant to a query. :param query: string to find relevant documents for :param callbacks: Callback manager or list of callbacks :param tags: Optional list of tags associated with the retriever. Defaults to None

These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Parameters

metadata – Optional metadata associated with the retriever. Defaults to None This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in callbacks.

Returns

List of relevant documents

invoke(input: str, config: Optional[RunnableConfig] = None) List[Document]
to_json() Union[SerializedConstructor, SerializedNotImplemented]
to_json_not_implemented() SerializedNotImplemented
property lc_attributes: Dict

Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor.

property lc_namespace: List[str]

Return the namespace of the langchain object. eg. [“langchain”, “llms”, “openai”]

property lc_secrets: Dict[str, str]

Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”}

property lc_serializable: bool

Return whether or not the class is serializable.

model Config

Bases: object

Configuration for this pydantic object.

arbitrary_types_allowed = True