Search()

Searches vector fields and returns ranked hits for each query vector.

pub async fn search(&self, request: SearchRequest) -> Result<SearchResponse>

Request Syntax

let request = SearchRequest::builder()
    .collection_name("books")
    .vector_field("embedding")
    .vectors(SearchVectors::Float(vec![vec![0.1, 0.2, 0.3, 0.4]]))
    .output_fields(["id", "title"])
    .limit(5)
    .build()?;

REQUEST FIELDS:

• database_name: Option<String>

  Name of the target database; uses the default database when empty.

• collection_name: String

  Name of the collection to search. Required.

• ids: Ids

  Primary keys whose stored vectors are used as search targets. Mutually exclusive with vectors.

• vector_field: String

  Name of the vector field to search (the ANN field).

• vectors: SearchVectors

  Query vectors, one per query. Supports dense float, binary, float16, bfloat16, sparse, int8, embedded-text, and struct embedding-list inputs.

• partition_names: Vec<String>

  Partition names to restrict the search to; searches the whole collection when empty.

• filter: String

  Scalar filter expression applied before the vector search.

• filter_templates: HashMap<String, Value>

  Placeholder values referenced by the filter expression.

• output_fields: Vec<String>

  Names of the scalar fields returned for each hit.

• limit: i64

  Number of hits returned per query vector. Defaults to 10.

• offset: i64

  Number of leading hits to skip per query vector. Defaults to 0.

• round_decimal: i64

  Number of decimal places for the returned scores; -1 disables rounding. Defaults to -1.

• ignore_growing: bool

  Whether to ignore growing segments during the search. Defaults to false.

• group_by_field: String

  Scalar field used to group the search results.

• group_size: i64

  Number of results to return per group. Defaults to 1.

• strict_group_size: bool

  Whether each group must return exactly group_size results. Defaults to false.

• radius: Option<f64>

  Range-search radius that filters the returned distances.

• range_filter: Option<f64>

  Lower or upper distance bound used together with radius.

• metric_type: Option<MetricType>

  Distance or similarity metric for the search; the server default is used when unset.

• extra_params: HashMap<String, String>

  Additional search parameters, such as nprobe or ef.

• rerank: Option<FunctionScore>

  Reranking configuration for single-vector search.

• timezone: String

  Timezone applied when searching or filtering Timestamptz fields.

• highlighter: Option<Highlighter>

  Text-highlighting configuration for full-text search.

• consistency_level: Option<ConsistencyLevel>

  Consistency guarantee for the search; the collection default is used when unset.

RETURNS:

Result

SearchResponse exposes results() returning a SearchResults, which holds one SingleResult per query vector; each SingleResult carries the hit IDs, scores, and requested output fields. The response also reports the session timestamp and execution cost statistics. Returns Error on failure.

Example

let request = SearchRequest::builder()
    .collection_name("books")
    .vector_field("embedding")
    .vectors(SearchVectors::Float(vec![vec![0.1, 0.2, 0.3, 0.4]]))
    .output_fields(["id", "title"])
    .limit(5)
    .build()?;
let resp = client.search(request).await?;