Return VectorStoreRetriever initialized from this VectorStore.
as_retriever(
self,
search_type: str = 'similarity',
search_kwargs: Optional[Dict[str, Any]] = None,
tags: Optional[List[str]] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any = {}
) -> VectorStoreRetrieverExamples:
.. code-block:: python
# Retrieve more documents with higher diversity
# Useful if your dataset has many similar documents
docsearch.as_retriever(
search_type="mmr",
search_kwargs={'k': 6, 'lambda_mult': 0.25}
)
# Fetch more documents for the MMR algorithm to consider
# But only return the top 5
docsearch.as_retriever(
search_type="mmr",
search_kwargs={'k': 5, 'fetch_k': 50}
)
# Only retrieve documents that have a relevance score
# Above a certain threshold
docsearch.as_retriever(
search_type="similarity_score_threshold",
search_kwargs={'score_threshold': 0.8}
)
# Only get the single most similar document from the dataset
docsearch.as_retriever(search_kwargs={'k': 1})
# Use a filter to only retrieve documents from a specific paper
docsearch.as_retriever(
search_kwargs={'filter': {'paper_title':'GPT-4 Technical Report'}}
)
| Name | Type | Description |
|---|---|---|
search_type | str | Default: 'similarity'Defines the type of search that the Retriever should perform. Can be "similarity" (default), "mmr", or "similarity_score_threshold". |
search_kwargs | Optional[Dict[str, Any]] | Default: NoneKeyword arguments to pass to the search function. Can include things like: k: Amount of documents to return (Default: 4) score_threshold: Minimum relevance threshold for similarity_score_threshold fetch_k: Amount of documents to pass to MMR algorithm (Default: 20) lambda_mult: Diversity of results returned by MMR; 1 for minimum diversity and 0 for maximum. (Default: 0.5) filter: Filter by document metadata |
tags | Optional[List[str]] | Default: NoneList of tags associated with the retriever. |
metadata | Optional[Dict[str, Any]] | Default: NoneMetadata associated with the retriever. |
kwargs | Any | Default: {}Other arguments passed to the VectorStoreRetriever init. |