API Reference

Vector Stores

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Modify vector store

client.vectorStores.update(stringvectorStoreID, VectorStoreUpdateParams { expires_after, metadata, name } body, RequestOptionsoptions?): VectorStore { id, created_at, file_counts, 8 more }

POST/vector_stores/{vector_store_id}

Modifies a vector store.

ParametersExpand Collapse

vectorStoreID: string

body: VectorStoreUpdateParams { expires_after, metadata, name }

ReturnsExpand Collapse

VectorStore { id, created_at, file_counts, 8 more }

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

id: string

The identifier, which can be referenced in API endpoints.

created_at: number

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

formatunixtime

file_counts: FileCounts { cancelled, completed, failed, 2 more }

last_active_at: number | null

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

formatunixtime

metadata: Metadata | null

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.

name: string

The name of the vector store.

object: "vector_store"

The object type, which is always vector_store.

status: "expired" | "in_progress" | "completed"

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.

usage_bytes: number

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

expires_after?: ExpiresAfter { anchor, days }

The expiration policy for a vector store.

expires_at?: number | null

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

formatunixtime

Modify vector store

TypeScript

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Java

CLI Tool

import OpenAI from "openai";
const openai = new OpenAI();

async function main() {
  const vectorStore = await openai.vectorStores.update(
    "vs_abc123",
    {
      name: "Support FAQ"
    }
  );
  console.log(vectorStore);
}

main();

{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "description": "Contains commonly asked questions and answers, organized by topic.",
  "bytes": 139920,
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  }
}

Returns Examples

{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "description": "Contains commonly asked questions and answers, organized by topic.",
  "bytes": 139920,
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  }
}