Skip to content
For the complete documentation index, see llms.txt. Markdown versions of documentation pages are available by appending .md to the page URL.
Primary navigation

Suggested
Overview Models Agents Tools Audio & voice Production API reference

Retrieve vector store

VectorStore vectorStores().retrieve(VectorStoreRetrieveParamsparams = VectorStoreRetrieveParams.none(), RequestOptionsrequestOptions = RequestOptions.none())
GET/vector_stores/{vector_store_id}

Retrieves a vector store.

ParametersExpand Collapse
VectorStoreRetrieveParams params
Optional<String> vectorStoreId
ReturnsExpand Collapse
class VectorStore:

A vector store is a collection of processed files can be used by the file_search tool.

String id

The identifier, which can be referenced in API endpoints.

long createdAt

The Unix timestamp (in seconds) for when the vector store was created.

formatunixtime
FileCounts fileCounts
Optional<Long> lastActiveAt

The Unix timestamp (in seconds) for when the vector store was last active.

formatunixtime
Optional<Metadata> metadata

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.

String name

The name of the vector store.

JsonValue; object_ "vector_store"constant"vector_store"constant

The object type, which is always vector_store.

Status status

The status of the vector store, which can be either expired, in_progress, or completed. A status of completed indicates that the vector store is ready for use.

long usageBytes

The total number of bytes used by the files in the vector store.

Optional<ExpiresAfter> expiresAfter

The expiration policy for a vector store.

Optional<Long> expiresAt

The Unix timestamp (in seconds) for when the vector store will expire.

formatunixtime

Retrieve vector store

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.VectorStore;
import com.openai.models.vectorstores.VectorStoreRetrieveParams;

public final class Main {
    private Main() {}

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

        VectorStore vectorStore = client.vectorStores().retrieve("vector_store_id");
    }
}
{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  },
  "usage_bytes": 139920,
  "status": "completed",
  "last_active_at": null,
  "metadata": {}
}
Returns Examples
{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  },
  "usage_bytes": 139920,
  "status": "completed",
  "last_active_at": null,
  "metadata": {}
}