search
Function
Retrieves vectors in a database that are similar to the passed vectors.
Prototype
@abstractmethod def search(embeddings, k, filter_dict)
Parameters
Parameter |
Data Type |
Required/Optional |
Description |
|---|---|---|---|
embeddings |
Union[List[List[float], List[Dict[int, float]]] |
Required |
Vector object to be retrieved, which can be a dense vector or sparse vector. |
k |
Integer |
Optional |
Number of returned similar vectors. |
filter_dict |
Dict |
Optional |
Dictionary consisting of retrieval criteria. Currently, only document IDs can be filtered. The filtered document IDs are passed in a list. The length of the ID list cannot exceed 1000 × 1000. For example, if you need to filter the documents whose IDs are 1, 2, and 4, the input dictionary is {"document_id": [1, 2, 4]}. |
Parent topic: VectorStore