Vector stores
Create a vector store
Creates a vector store from the supplied request.
Request Body
The request body.
file_ids
string[]
A list of File IDs that the vector store should use. Useful for tools like file_search that can access files.
name
string
The name of the vector store.
description
string
A description for the vector store. Can be used to describe the vector store's purpose.
expires_after
OpenAI.VectorStoreExpirationAfter
The expiration policy for a vector store.
anchor
enum
required
Anchor timestamp after which the expiration policy applies. Supported anchors: last_active_at.
chunking_strategy
auto | static
The chunking strategy used to chunk the file(s). If not set, will use the auto strategy.
auto
OpenAI.AutoChunkingStrategyRequestParam
The default strategy. This strategy currently uses a max_chunk_size_tokens of 800 and chunk_overlap_tokens of 400.
type
enum
required
Always auto.
static
OpenAI.StaticChunkingStrategyRequestParam
Customize your own chunking strategy by setting chunk size and chunk overlap.
type
enum
required
Always static.
static
OpenAI.StaticChunkingStrategy
required
metadata
OpenAI.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.
Responses
The request has succeeded.
Body
id
string
required
The identifier, which can be referenced in API endpoints.
object
enum
required
The object type, which is always vector_store.
created_at
integer
required
The Unix timestamp (in seconds) for when the vector store was created.
name
string
required
The name of the vector store.
file_counts
OpenAI.VectorStoreObjectFileCounts
required
status
enum
required
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.
expires_after
OpenAI.VectorStoreExpirationAfter
The expiration policy for a vector store.
anchor
enum
required
Anchor timestamp after which the expiration policy applies. Supported anchors: last_active_at.
metadata
OpenAI.Metadata | null
required
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.
Request
curl https://api.openai.com/v1/vector_stores \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-H "OpenAI-Beta: assistants=v2" \
-d '{
"name": "Support FAQ"
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("OPENAI_API_KEY"), # This is the default and can be omitted
)
vector_store = client.vector_stores.create()
print(vector_store.id)import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const vectorStore = await openai.vectorStores.create({
name: "Support FAQ"
});
console.log(vectorStore);
}
main();import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});
const vectorStore = await client.vectorStores.create();
console.log(vectorStore.id);package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
vectorStore, err := client.VectorStores.New(context.TODO(), openai.VectorStoreNewParams{})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v
", vectorStore.ID)
}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.VectorStoreCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
VectorStore vectorStore = client.vectorStores().create();
}
}require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
vector_store = openai.vector_stores.create
puts(vector_store)Response
{
"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
}
}