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.

Padparameters

vector_store_id string vereist

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

batch_id string vereist

The ID of the file batch being retrieved.

Antwoorden

The request has succeeded.

Hoofdtekst

Content-Type: application/json

id string vereist

The identifier, which can be referenced in API endpoints.

object enum vereist

The object type, which is always vector_store.file_batch.

vector_store.file_batch

created_at integer vereist

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

vector_store_id string vereist

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

status enum vereist

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

in_progresscompletedcancelledfailed

file_counts OpenAI.VectorStoreFileBatchObjectFileCounts vereist

in_progress integer vereist

completed integer vereist

failed integer vereist

cancelled integer vereist

total integer vereist

Aanvraag

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)

Respons

{
  "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,
  }
}