langchain.retrievers.self_query.base.SelfQueryRetriever¶
class langchain.retrievers.self_query.base.SelfQueryRetriever[source]¶
Bases: BaseRetriever, BaseModel
Retriever that uses a vector store and an LLM to generate
the vector store queries.
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 llm_chain: langchain.chains.llm.LLMChain [Required]¶
The LLMChain for generating the vector store queries.
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 search_kwargs: dict [Optional]¶
Keyword arguments to pass in to the vector store search.
param search_type: str = 'similarity'¶
The search type to perform on the vector store.
param structured_query_translator: langchain.chains.query_constructor.ir.Visitor [Required]¶
Translator for turning internal query language into vectorstore search params.
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 use_original_query: bool = False¶
Use original query instead of the revised new query from LLM
param vectorstore: langchain.schema.vectorstore.VectorStore [Required]¶