search()

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

search(data): Promise<ResStatus>

Request Syntax

milvusClient.search({
   collection_name: string,
   partition_names?: string[], 
   data: number[] | number[][], 
   filter: string,
   limit?: number,
   offset?: number
   output_fields?: string | list[string],
   partition_names?: string | list[string],
   consistency_level?: string,
   ignore_growing?: boolean,
   group_by_field?: string,
   group_size?: number,
   strict_group_size?: boolean,
   timeout?: number,
 })

PARAMETERS:

• 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 (number[] | number[][]) -

  A list of vector embeddings.

  Milvus searches for the most similar vector embeddings to the specified ones.

• filter (string) -

  A scalar filtering condition to filter matching entities.

  The value defaults to an empty string, indicating that no condition applies.

  You can set this parameter to an empty string to skip scalar filtering. To build a scalar filtering condition, refer to Boolean Expression Rules.

• ignore_growing (boolean) -

  A boolean value indicating whether to skip the search in growing segments.

• 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.

  In a grouping search, however, limit specifies the maximum number of groups to return, rather than individual entities. Each group is formed based on the specified group_by_field.

• 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.

• 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.

  • max_empty_result_buckets (number)

    This param is only used for range search for IVF-serial indexes, including BIN_IVF_FLAT, IVF_FLAT, IVF_SQ8, IVF_PQ, and SCANN. The value defaults to 1 and ranges from 1 to 65536.

    During range search, the search process terminates early if the number of buckets with no valid range search results reaches the specified value. Increasing this parameter improves range search recall.

  • 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.

  • 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.

• 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.

• group_by_field (string) -

  Groups search results by a specified field to ensure diversity and avoid returning multiple results from the same group.

• group_size (number) -

  The target number of entities to return within each group in a grouping search. For example, setting group_size=2 instructs the system to return up to 2 of the most similar entities (e.g., document passages or vector representations) within each group. Without setting group_size, the system defaults to returning only 1 entity per group.

• strict_group_size (boolean) -

  This Boolean parameter dictates whether group_size should be strictly enforced. When group_size=true, the system will attempt to fill each group with exactly group_size results, as long as sufficient data exists within each group. If there is an insufficient number of entities in a group, it will return only the available entities, ensuring that groups with adequate data meet the specified group_size.

• 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