Batches

Perform batch inference with Azure OpenAI

With Portkey, you can perform Azure OpenAI Batch Inference operations. This is the most efficient way to

• Test your data with different foundation models
• Perform A/B testing with different foundation models
• Perform batch inference with different foundation models

Portkey supports two modes on Azure OpenAI:

• Provider Batch API (cheapest, completion_window: 24h, 48h, etc.)
• Portkey Batch API (fast, provider-agnostic, completion_window: immediate)

Using Azure OpenAI Batch API through Portkey

Create Batch Job

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

start_batch_response = portkey.batches.create(
  input_file_id="file_id", # file id of the input file
  endpoint="endpoint", # ex: /v1/chat/completions
  completion_window="completion_window", # ex: 24h
  metadata={} # metadata for the batch
)

print(start_batch_response)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const startBatch = async () => {
  const startBatchResponse = await portkey.batches.create({
    input_file_id: "file_id", // file id of the input file
    endpoint: "endpoint", // ex: /v1/chat/completions
    completion_window: "completion_window", // ex: 24h
    metadata: {} // metadata for the batch
  });

  console.log(startBatchResponse);
}

await startBatch();

curl --location 'https://api.portkey.ai/v1/batches' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider' \
--header 'Content-Type: application/json' \
--data '{
    "input_file_id": "<file_id>",
    "endpoint": "<endpoint>",
    "completion_window": "<completion_window>",
    "metadata": {}
}'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const startBatch = async () => {
  const startBatchResponse = await openai.batches.create({
    input_file_id: "file_id", // file id of the input file
    endpoint: "endpoint", // ex: /v1/chat/completions
    completion_window: "completion_window", // ex: 24h
    metadata: {} // metadata for the batch
  });

  console.log(startBatchResponse);
}

await startBatch();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

start_batch_response = openai.batches.create(
  input_file_id="file_id", # file id of the input file
  endpoint="endpoint", # ex: /v1/chat/completions
  completion_window="completion_window", # ex: 24h
  metadata={} # metadata for the batch
)

print(start_batch_response)

Create Batch Job with Blob Storage

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

start_batch_response = portkey.batches.create(
  endpoint="endpoint",  # ex: /v1/chat/completions
  completion_window="completion_window",  # ex: 24h
  metadata={},  # metadata for the batch
  input_blob="<blob_url>",
  output_folder={
    "url": "<output_blob_folder>" # both error file and output file will be saved in this folder
  }
)

print(start_batch_response)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const startBatch = async () => {
  const startBatchResponse = await portkey.batches.create({
    endpoint: "endpoint", // ex: /v1/chat/completions
    completion_window: "completion_window", // ex: 24h
    metadata: {}, // metadata for the batch
    input_blob: "<blob_url>",
    output_folder: {
      url: "<output_blob_folder>" // both error file and output file will be saved in this folder
    }
  });

  console.log(startBatchResponse);
}

await startBatch();

curl --location 'https://api.portkey.ai/v1/batches' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider' \
--header 'Content-Type: application/json' \
--data '{
    "endpoint": "<endpoint>",
    "completion_window": "<completion_window>",
    "metadata": {},
    "input_blob": "<blob_url>",
    "output_folder": {
      "url": "<output_blob_folder>" # both error file and output file will be saved in this folder
    }
}'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const startBatch = async () => {
  const startBatchResponse = await openai.batches.create({
    endpoint: "endpoint", // ex: /v1/chat/completions
    completion_window: "completion_window", // ex: 24h
    metadata: {}, // metadata for the batch
    extra_body: {
      input_blob: "<blob_url>",
      output_folder: {
        url: "<output_blob_folder>" // both error file and output file will be saved in this folder
      }
    }
  });

  console.log(startBatchResponse);
}

await startBatch();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

start_batch_response = openai.batches.create(
  endpoint="endpoint",  # ex: /v1/chat/completions
  completion_window="completion_window",  # ex: 24h
  metadata={},  # metadata for the batch
  extra_body={
    "input_blob": "<blob_url>",
    "output_folder": {
      "url": "<output_blob_folder>"  # both error file and output file will be saved in this folder
    }
  }
)

print(start_batch_response)

List Batch Jobs

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

batches = portkey.batches.list()

print(batches)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const listBatches = async () => {
  const batches = await portkey.batches.list();

  console.log(batches);
}

await listBatches();

curl --location 'https://api.portkey.ai/v1/batches' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const listBatches = async () => {
  const batches = await openai.batches.list();

  console.log(batches);
}

await listBatches();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

batches = openai.batches.list()

print(batches)

Get Batch Job Details

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

batch = portkey.batches.retrieve(batch_id="batch_id")

print(batch)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const getBatch = async () => {
  const batch = await portkey.batches.retrieve(batch_id="batch_id");

  console.log(batch);
}

await getBatch();

curl --location 'https://api.portkey.ai/v1/batches/<batch_id>' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const getBatch = async () => {
  const batch = await openai.batches.retrieve(batch_id="batch_id");

  console.log(batch);
}

await getBatch();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

batch = openai.batches.retrieve(batch_id="batch_id")

print(batch)

Get Batch Output

curl

curl --location 'https://api.portkey.ai/v1/batches/<batch_id>/output' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider'

List Batch Jobs

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

batches = portkey.batches.list()

print(batches)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const listBatchingJobs = async () => {
  const batching_jobs = await portkey.batches.list();

  console.log(batching_jobs);
}

await listBatchingJobs();

curl --location 'https://api.portkey.ai/v1/batches' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const listBatchingJobs = async () => {
  const batching_jobs = await openai.batches.list();

  console.log(batching_jobs);
}

await listBatchingJobs();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

batching_jobs = openai.batches.list()

print(batching_jobs)

Cancel Batch Job

Python

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    provider="@PROVIDER"   
)

cancel_batch_response = portkey.batches.cancel(batch_id="batch_id")

print(cancel_batch_response)

import { Portkey } from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    provider:"@PROVIDER"   
});

const cancelBatch = async () => {
  const cancel_batch_response = await portkey.batches.cancel(batch_id="batch_id");

  console.log(cancel_batch_response);
}

await cancelBatch();

curl --request POST --location 'https://api.portkey.ai/v1/batches/<batch_id>/cancel' \
--header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-provider: @provider'

import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

const cancelBatch = async () => {
  const cancel_batch_response = await openai.batches.cancel(batch_id="batch_id");

  console.log(cancel_batch_response);
}

await cancelBatch();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

cancel_batch_response = openai.batches.cancel(batch_id="batch_id")

print(cancel_batch_response)