Batches

Perform batch inference with OpenAI

Portkey exposes OpenAI’s Batch API through one consistent endpoint, so you can run large, asynchronous evaluation jobs at 50 % lower cost.

Use batches when you need to run large jobs offline — e.g. nightly evals, A/B tests, or bulk embeddings.

Create Batch Job

Upload your .jsonl file first — see Files API for more details and then use the following code to create a 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="/v1/chat/completions",
  completion_window="24h",
  metadata={} # metadata for the batch
)

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)

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)

The status of a given Batch object can be any of the following:

Status	Description
validating	the input file is being validated before the batch can begin
failed	the input file has failed the validation process
in_progress	the input file was successfully validated and the batch is currently being run
finalizing	the batch has completed and the results are being prepared
completed	the batch has been completed and the results are ready
expired	the batch was not able to be completed within the 24-hour time window
cancelling	the batch is being cancelled (may take up to 10 minutes)
cancelled	the batch was cancelled

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'

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)