langchain.retrievers.llama_index.LlamaIndexGraphRetriever¶
class langchain.retrievers.llama_index.LlamaIndexGraphRetriever[source]¶
Bases: BaseRetriever
Retriever for question-answering with sources over an LlamaIndex
graph data structure.
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 graph: Any = None¶
LlamaIndex graph to query.
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 query_configs: List[Dict] [Optional]¶
List of query configs to pass to the query method.
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 abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶
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