メインコンテンツまでスキップ

hybridSearch()

This operation conducts a hybrid search with an optional scalar filtering expression.

hybridSearch(data): Promise<SearchResults>

Request Syntax​

milvusClient.hybridSearch({
   db_name: string,
   collection_name: string,
   partition_names?: string[], 
   data: HybridSearchSingleReq[], 
   filter: string,
   limit?: number,
   offset?: number
   output_fields?: string | list[string],
   partition_names?: string | list[string],
   consistency_level?: string,
   ignore_growing?: boolean,
   rerank?: RerankerObj,
   timeout?: number,
 })

PARAMETERS:

  • db_name (string) -

    The name of the database that holds the target collection.

  • collection_name (string) -

    [REQUIRED]

    The name of the collection to search

  • consistency_level (ConsistencyLevelEnum) -

    The consistency level of the target collection. The value defaults to Bounded (1) with options of Strong (0), Bounded (1), Session (2), and Eventually (3).

  • data (HybridSearchSingleReq[]) -

    A list of search requests in the form of the HybridSearchSingleReq object.

    • data (VectorTypes[] | VectorTypes) -

      [REQUIRED]

      The query vectors. The following vector types are supported:

      • FloatVector (number[])

      • Float16Vector (number[] | Uint8Array)

      • BinaryVector (number[])

      • BFloat16Vector (number[] | Uint8Array)

      • SparseFloatVector (SparseVectorArray | SparseVectorDic | SparseVectorCSR | SparseVectorCOO)

        For details on how to generate a SparseFloatVector, refer to this code snippet.

    • limit (string) -

      The maximum number of results to return in the request. When performing a hybrid search with multiple ANN search requests, the top results defined by limit from each request will be combined and re-ranked before returning the final search results.

    • expr (string) -

      The expression to filter the results.

    • exprValues (keyValueObj) -

      If you choose to use placeholders in filter as stated in Filtering Templating, then you can specify the actual values for these placeholders as key-value pairs as the value of this parameter.

    • params (KeyValueObj) -

      The additional search parameters in key-value pairs.

      • radius (number) -

        Determines the threshold of least similarity. When setting metric_type to L2, ensure that this value is greater than that of range_filter. Otherwise, this value should be lower than that of range_filter.

      • range_filter (number) -

        Refines the search to vectors within a specific similarity range. When setting metric_type to IP or COSINE, ensure that this value is greater than that of radius. Otherwise, this value should be lower than that of radius.

      • level (number)

        Zilliz Cloud uses a unified parameter to simplify search parameter tuning instead of leaving you to work with a bunch of search parameters specific to various index algorithms.

        The value defaults to 1, and ranges from 1 to 10. Increasing the value results in a higher recall rate with degraded search performance. For details, refer to Tune Recall Rate.

      • page_retain_order (bool) -

        Whether to retain the order of the search result when offset is provided.

        This parameter applies only when you also set radius.

  • limit (number) -

    The total number of entities to return.

    You can use this parameter in combination with offset in param to enable pagination.

    The sum of this value and offset in param should be less than 16,384.

  • offset (number) -

    The number of records to skip in the search result.

    You can use this parameter in combination with limit to enable pagination.

    The sum of this value and limit should be less than 16,384.

  • output_fields (string[]) -

    A list of field names to include in each entity in return.

    The value defaults to None. If left unspecified, only the primary field is included.

  • partition_names (string[]) -

    A list of the names of the partitions to search.

  • reranker (RerankerObj) -

    A reranking strategy with its custom parameters.

    • strategy (string) -

      A re-ranking strategy. Possible values are:

      • RRF ("rrf")

        This strategy is recommended when there is no specific emphasis. The RRF can effectively balance the importance of each vector field.

      • WEIGHTED ("weighted")

        This strategy is recommended if you require the results to emphasize a particular vector field. The WeightedRanker allows you to assign higher weights to certain vector fields, emphasizing them more. For instance, in multimodal searches, textual descriptions of an image might be considered more important than the colors in this image.

    • params (keyValueObj) -

      The parameters are specific to reranking strategies.

      • When using the RRFRanker strategy, you need to input the parameter value k into the RRFRanker. The default value of k is 60. This parameter helps to determine how the ranks are combined from different ANN searches, aiming to balance and blend the importance across all searches.

      • When using the WeightedRanker strategy, you need to input weight values into the WeightedRanker function. The number of basic ANN searches in a Hybrid Search corresponds to the number of values that need to be inputted. The input values should be in the range [0,1], with values closer to 1 indicating greater importance.

  • timeout (number) -

    The timeout duration for this operation. Setting this to None indicates that this operation timeouts when any response arrives or any error occurs.

RETURNS Promise<SearchResults>

This method returns a promise that resolves to a SearchResults object.

{
    data: list[string],
    status: object
}

PARAMETERS:

  • results (object) -

    • id (string) -

      The ID of the search result

    • score(number) -

      The similarity score of the search result.

    • Plus output fields and their values.

  • status (object) -

    • code (number) -

      A code that indicates the operation result. It remains 0 if this operation succeeds.

    • error_code (string | number) -

      An error code that indicates an occurred error. It remains Success if this operation succeeds.

    • reason (string) -

      The reason that indicates the reason for the reported error. It remains an empty string if this operation succeeds.

Example​

const { MilvusClient, DataType } = require("@zilliz/milvus2-sdk-node")

res = await client.loadCollection({
    collection_name: "hybrid_search_collection"
})

import { MilvusClient, RRFRanker, WeightedRanker } from '@zilliz/milvus2-sdk-node';

const search = await client.search({
  collection_name: "hybrid_search_collection",
  data: [search_param_1, search_param_2],
  limit: 2,
  rerank: RRFRanker(100)
});