Search vector store

VectorStoreSearchPage vectorStores().search(, )

POST/vector_stores/{vector_store_id}/search

Search a vector store for relevant chunks based on a query and file attributes filter.

ParametersExpand Collapse

VectorStoreSearchParams params

Optional<String> vectorStoreId

Query query

A query string for a search

String

List<String>

Optional<Filters> filters

A filter to apply based on file attributes.

class ComparisonFilter:

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

String key

The key to compare against the value.

Type type

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

EQ("eq")

NE("ne")

GT("gt")

GTE("gte")

LT("lt")

LTE("lte")

Value value

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

String

double

boolean

List<ComparisonFilterValueItem>

Accepts one of the following:

String

double

class CompoundFilter:

Combine multiple filters using and or or.

List<Filter> filters

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

Accepts one of the following:

class ComparisonFilter:

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

String key

The key to compare against the value.

Type type

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

EQ("eq")

NE("ne")

GT("gt")

GTE("gte")

LT("lt")

LTE("lte")

Value value

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

String

double

boolean

List<ComparisonFilterValueItem>

Accepts one of the following:

String

double

JsonValue

Type type

Type of operation: and or or.

Accepts one of the following:

AND("and")

OR("or")

Optional<Long> maxNumResults

The maximum number of results to return. This number should be between 1 and 50 inclusive.

minimum1

maximum50

Optional<RankingOptions> rankingOptions

Ranking options for search.

Optional<Ranker> ranker

Enable re-ranking; set to none to disable, which can help reduce latency.

Accepts one of the following:

NONE("none")

AUTO("auto")

DEFAULT_2024_11_15("default-2024-11-15")

Optional<Double> scoreThreshold

minimum0

maximum1

Optional<Boolean> rewriteQuery

Whether to rewrite the natural language query for vector search.

ReturnsExpand Collapse

class VectorStoreSearchResponse:

Optional<Attributes> attributes

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

Accepts one of the following:

String

double

boolean

List<Content> content

Content chunks from the file.

String text

The text content returned from search.

Type type

The type of content.

String fileId

The ID of the vector store file.

String filename

The name of the vector store file.

double score

The similarity score for the result.

minimum0

maximum1

Search vector store

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStoreSearchPage;
import com.openai.models.vectorstores.VectorStoreSearchParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        VectorStoreSearchParams params = VectorStoreSearchParams.builder()
            .vectorStoreId("vs_abc123")
            .query("string")
            .build();
        VectorStoreSearchPage page = client.vectorStores().search(params);
    }
}

{
  "object": "vector_store.search_results.page",
  "search_query": "What is the return policy?",
  "data": [
    {
      "file_id": "file_123",
      "filename": "document.pdf",
      "score": 0.95,
      "attributes": {
        "author": "John Doe",
        "date": "2023-01-01"
      },
      "content": [
        {
          "type": "text",
          "text": "Relevant chunk"
        }
      ]
    },
    {
      "file_id": "file_456",
      "filename": "notes.txt",
      "score": 0.89,
      "attributes": {
        "author": "Jane Smith",
        "date": "2023-01-02"
      },
      "content": [
        {
          "type": "text",
          "text": "Sample text content from the vector store."
        }
      ]
    }
  ],
  "has_more": false,
  "next_page": null
}

Returns Examples

{
  "object": "vector_store.search_results.page",
  "search_query": "What is the return policy?",
  "data": [
    {
      "file_id": "file_123",
      "filename": "document.pdf",
      "score": 0.95,
      "attributes": {
        "author": "John Doe",
        "date": "2023-01-01"
      },
      "content": [
        {
          "type": "text",
          "text": "Relevant chunk"
        }
      ]
    },
    {
      "file_id": "file_456",
      "filename": "notes.txt",
      "score": 0.89,
      "attributes": {
        "author": "Jane Smith",
        "date": "2023-01-02"
      },
      "content": [
        {
          "type": "text",
          "text": "Sample text content from the vector store."
        }
      ]
    }
  ],
  "has_more": false,
  "next_page": null
}