Vector stores

Get a vector store file batch

GET /openai/v1/vector_stores/{vector_store_id}/file_batches/{batch_id}

Retrieves a vector store file batch by its identifier.

Paramètres de chemin d’accès

vector_store_id string obligatoire

The ID of the vector store that the file batch belongs to.

batch_id string obligatoire

The ID of the file batch being retrieved.

Réponses

The request has succeeded.

Corps

Content-Type: application/json

id string obligatoire

The identifier, which can be referenced in API endpoints.

object enum obligatoire

The object type, which is always vector_store.file_batch.

vector_store.file_batch

created_at integer obligatoire

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

vector_store_id string obligatoire

The ID of the vector store that the File is attached to.

status enum obligatoire

The status of the vector store files batch, which can be either in_progress, completed, cancelled or failed.

in_progresscompletedcancelledfailed

file_counts OpenAI.VectorStoreFileBatchObjectFileCounts obligatoire

in_progress integer obligatoire

completed integer obligatoire

failed integer obligatoire

cancelled integer obligatoire

total integer obligatoire

Requête

curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches/vsfb_abc123 \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -H "OpenAI-Beta: assistants=v2"

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_file_batch = client.vector_stores.file_batches.retrieve(
    batch_id="vsfb_abc123",
    vector_store_id="vs_abc123",
)
print(vector_store_file_batch.id)

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

async function main() {
  const vectorStoreFileBatch = await openai.vectorStores.fileBatches.retrieve(
    "vsfb_abc123",
    { vector_store_id: "vs_abc123" }
  );
  console.log(vectorStoreFileBatch);
}

main();

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});

const vectorStoreFileBatch = await client.vectorStores.fileBatches.retrieve('vsfb_abc123', {
  vector_store_id: 'vs_abc123',
});

console.log(vectorStoreFileBatch.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"),
    )
    vectorStoreFileBatch, err := client.VectorStores.FileBatches.Get(
        context.TODO(),
        "vs_abc123",
        "vsfb_abc123",
    )
    if err != nil {
        panic(err.Error())
    }
    fmt.Printf("%+v
", vectorStoreFileBatch.ID)
}

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams;
import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;

public final class Main {
    private Main() {}

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

        FileBatchRetrieveParams params = FileBatchRetrieveParams.builder()
            .vectorStoreId("vs_abc123")
            .batchId("vsfb_abc123")
            .build();
        VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params);
    }
}

require "openai"

openai = OpenAI::Client.new(api_key: "My API Key")

vector_store_file_batch = openai.vector_stores.file_batches.retrieve("vsfb_abc123", vector_store_id: "vs_abc123")

puts(vector_store_file_batch)

Response

{
  "id": "vsfb_abc123",
  "object": "vector_store.file_batch",
  "created_at": 1699061776,
  "vector_store_id": "vs_abc123",
  "status": "in_progress",
  "file_counts": {
    "in_progress": 1,
    "completed": 1,
    "failed": 0,
    "cancelled": 0,
    "total": 0,
  }
}