Vector stores

Create a vector store file

POST /openai/v1/vector_stores/{vector_store_id}/files

Creates a vector store file from the supplied request.

Параметры пути

vector_store_id string обязательно

The ID of the vector store for which to create a File.

Текст запроса

The request body.

Content-Type: application/json

file_id string обязательно

A File ID that the vector store should use. Useful for tools like file_search that can access files. For multi-file ingestion, we recommend file_batches to minimize per-vector-store write requests.

chunking_strategy auto | static

The chunking strategy used to chunk the file(s). If not set, will use the auto strategy.

Один из следующих:

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 обязательно

Always auto.

auto

static OpenAI.StaticChunkingStrategyRequestParam

Customize your own chunking strategy by setting chunk size and chunk overlap.

type enum обязательно

Always static.

static

static OpenAI.StaticChunkingStrategy обязательно

max_chunk_size_tokens integer обязательно

chunk_overlap_tokens integer обязательно

attributes OpenAI.VectorStoreFileAttributes | 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, booleans, or numbers.

[key: string] string | OpenAI.numeric | boolean

Любое из следующих:

string

number

boolean

Ответы

The request has succeeded.

Текст

Content-Type: application/json

id string обязательно

The identifier, which can be referenced in API endpoints.

object enum обязательно

The object type, which is always vector_store.file.

vector_store.file

usage_bytes integer обязательно

created_at integer обязательно

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

vector_store_id string обязательно

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

status enum обязательно

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

in_progresscompletedcancelledfailed

last_error OpenAI.VectorStoreFileObjectLastError | null обязательно

code enum обязательно

server_errorunsupported_fileinvalid_file

message string обязательно

attributes OpenAI.VectorStoreFileAttributes | null

[key: string] string | OpenAI.numeric | boolean

Любое из следующих:

string

number

boolean

chunking_strategy static | other

The strategy used to chunk the file.

Один из следующих:

static OpenAI.StaticChunkingStrategyResponseParam

type enum обязательно

Always static.

static

static OpenAI.StaticChunkingStrategy обязательно

max_chunk_size_tokens integer обязательно

chunk_overlap_tokens integer обязательно

other OpenAI.OtherChunkingStrategyResponseParam

This is returned when the chunking strategy is unknown. Typically, this is because the file was indexed before the chunking_strategy concept was introduced in the API.

type enum обязательно

Always other.

other

Запрос

curl https://api.openai.com/v1/vector_stores/vs_abc123/files \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -H "Content-Type: application/json" \
    -H "OpenAI-Beta: assistants=v2" \
    -d '{
      "file_id": "file-abc123"
    }'

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 = client.vector_stores.files.create(
    vector_store_id="vs_abc123",
    file_id="file_id",
)
print(vector_store_file.id)

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

async function main() {
  const myVectorStoreFile = await openai.vectorStores.files.create(
    "vs_abc123",
    {
      file_id: "file-abc123"
    }
  );
  console.log(myVectorStoreFile);
}

main();

import OpenAI from 'openai';

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

const vectorStoreFile = await client.vectorStores.files.create('vs_abc123', { file_id: 'file_id' });

console.log(vectorStoreFile.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"),
    )
    vectorStoreFile, err := client.VectorStores.Files.New(
        context.TODO(),
        "vs_abc123",
        openai.VectorStoreFileNewParams{
            FileID: "file_id",
        },
    )
    if err != nil {
        panic(err.Error())
    }
    fmt.Printf("%+v
", vectorStoreFile.ID)
}

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.vectorstores.files.FileCreateParams;
import com.openai.models.vectorstores.files.VectorStoreFile;

public final class Main {
    private Main() {}

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

        FileCreateParams params = FileCreateParams.builder()
            .vectorStoreId("vs_abc123")
            .fileId("file_id")
            .build();
        VectorStoreFile vectorStoreFile = client.vectorStores().files().create(params);
    }
}

require "openai"

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

vector_store_file = openai.vector_stores.files.create("vs_abc123", file_id: "file_id")

puts(vector_store_file)

Response

{
  "id": "file-abc123",
  "object": "vector_store.file",
  "created_at": 1699061776,
  "usage_bytes": 1234,
  "vector_store_id": "vs_abcd",
  "status": "completed",
  "last_error": null
}