Files - Portkey Docs

To perform fine-tuning or batch inference with Vertex AI, you need to upload files to Google Cloud Storage. With Prisma AIRS AI Gateway, you can easily upload files to GCS and use them for fine-tuning or batch inference with Vertex AI models.

Uploading Files

REST
OpenAI NodeJS
OpenAI Python

curl -X POST --header 'Authorization: Bearer <portkey_api_key>' \
 --header 'x-portkey-provider: @your-vertex-provider' \
 --header 'x-portkey-vertex-storage-bucket-name: <bucket_name>' \
 --header 'x-portkey-provider-file-name: <file_name>.jsonl' \
 --header 'x-portkey-provider-model: <model_name>' \
 --form 'purpose="fine-tune"' \
 --form 'file=@dataset.jsonl' \
 'https://aigw.portkey.ai/v1/files'

import OpenAI from 'openai';
import * as fs from 'fs';

const openai = new OpenAI({
  apiKey: "PORTKEY_API_KEY",
  baseURL: "https://aigw.portkey.ai/v1",
  defaultHeaders: { "x-portkey-provider": "@VERTEX_PROVIDER", "x-portkey-vertex-storage-bucket-name": "your_bucket_name", "x-portkey-provider-file-name": "your_file_name.jsonl", "x-portkey-provider-model": "gemini-1.5-flash-001" }
});

const uploadFile = async () => {
  const file = await openai.files.create({
    purpose: "fine-tune", // Can be "fine-tune" or "batch"
    file: fs.createReadStream("dataset.jsonl")
  });

  console.log(file);
}

uploadFile();

from openai import OpenAI

openai = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url="https://aigw.portkey.ai/v1",
    default_headers={"x-portkey-provider": "@VERTEX_PROVIDER", "x-portkey-vertex-storage-bucket-name": "your_bucket_name", "x-portkey-provider-file-name": "your_file_name.jsonl", "x-portkey-provider-model": "gemini-1.5-flash-001"}
)

upload_file_response = openai.files.create(
  purpose="fine-tune", # Can be "fine-tune" or "batch"
  file=open("dataset.jsonl", "rb")
)

print(upload_file_response)

Get File

REST
OpenAI NodeJS
OpenAI Python

curl -X GET --header 'Authorization: Bearer <portkey_api_key>' \
--header 'x-portkey-provider: @your-vertex-provider' \
'https://aigw.portkey.ai/v1/files/<file_id>'

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: "PORTKEY_API_KEY",
  baseURL: "https://aigw.portkey.ai/v1",
  defaultHeaders: { "x-portkey-provider": "@VERTEX_PROVIDER" }
});

const getFile = async () => {
  const file = await openai.files.retrieve("file_id");

  console.log(file);
}

getFile();

from openai import OpenAI

openai = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url="https://aigw.portkey.ai/v1",
    default_headers={"x-portkey-provider": "@VERTEX_PROVIDER"}
)

file = openai.files.retrieve(file_id="file_id")

print(file)

Get File Content

REST
OpenAI NodeJS
OpenAI Python

curl -X GET --header 'Authorization: Bearer <portkey_api_key>' \
--header 'x-portkey-provider: @your-vertex-provider' \
'https://aigw.portkey.ai/v1/files/<file_id>/content'

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: "PORTKEY_API_KEY",
  baseURL: "https://aigw.portkey.ai/v1",
  defaultHeaders: { "x-portkey-provider": "@VERTEX_PROVIDER" }
});

const getFileContent = async () => {
  const fileContent = await openai.files.content("file_id");

  console.log(fileContent);
}

getFileContent();

from openai import OpenAI

openai = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url="https://aigw.portkey.ai/v1",
    default_headers={"x-portkey-provider": "@VERTEX_PROVIDER"}
)

file_content = openai.files.content(file_id="file_id")

print(file_content)

Note: The ListFiles endpoint is not supported for Vertex AI.

Last modified on September 15, 2026