langchain.retrievers.vespa_retriever.VespaRetriever¶

class langchain.retrievers.vespa_retriever.VespaRetriever(*, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, app: Vespa, body: Dict, content_field: str, metadata_fields: Sequence[str])[source]¶

Bases: BaseRetriever

Retriever that uses Vespa.

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 app: Vespa [Required]¶

Vespa application to query.

param body: Dict [Required]¶

Body of the query.

param content_field: str [Required]¶

Name of the content field.

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_fields: Sequence[str] [Required]¶

Names of the metadata fields.

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.

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]¶
classmethod from_params(url: str, content_field: str, *, k: Optional[int] = None, metadata_fields: Union[Sequence[str], Literal['*']] = (), sources: Optional[Union[Sequence[str], Literal['*']]] = None, _filter: Optional[str] = None, yql: Optional[str] = None, **kwargs: Any) → VespaRetriever[source]¶

Instantiate retriever from params.

Parameters

  • url (str) – Vespa app URL.

  • content_field (str) – Field in results to return as Document page_content.

  • k (Optional[int]) – Number of Documents to return. Defaults to None.

  • metadata_fields (Sequence[str] or "*") – Fields in results to include in document metadata. Defaults to empty tuple ().

  • sources (Sequence[str] or "*" or None) – Sources to retrieve from. Defaults to None.

  • _filter (Optional[str]) – Document filter condition expressed in YQL. Defaults to None.

  • yql (Optional[str]) – Full YQL query to be used. Should not be specified if _filter or sources are specified. Defaults to None.

  • kwargs (Any) – Keyword arguments added to query body.

Returns

Instantiated VespaRetriever.

Return type

VespaRetriever

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

get_relevant_documents_with_filter(query: str, *, _filter: Optional[str] = None) → List[Document][source]¶
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¶

Examples using VespaRetriever¶