vectorstore=vectorstore,
docstore=store,
child_splitter=child_splitter,
parent_splitter=parent_splitter,
)
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 child_splitter: langchain.text_splitter.TextSplitter [Required]¶
The text splitter to use to create child documents.
param docstore: langchain.schema.storage.BaseStore[str, langchain.schema.document.Document] [Required]¶
The storage layer for the parent documents
param id_key: str = 'doc_id'¶
The key to use to track the parent id. This will be stored in the
metadata of child documents.
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 parent_splitter: Optional[langchain.text_splitter.TextSplitter] = None¶
The text splitter to use to create parent documents.
If none, then the parent documents will be the raw documents passed in.
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 vectorstore: langchain.vectorstores.base.VectorStore [Required]¶
The underlying vectorstore to use to store small chunks
and their embedding vectors