Batch Types

The Batch type represents a batch job returned by the Batch API functions.

`Batch`

Re-exported from openai.types.Batch.

Import: from any_llm.types.batch import Batch

Field	Type	Description
`id`	`str`	Unique batch identifier.
`object`	`str`	Always `"batch"`.
`endpoint`	`str`	The API endpoint used for all requests in the batch.
`input_file_id`	`str`	ID of the uploaded input file.
`completion_window`	`str`	Time frame for batch processing (e.g., `"24h"`).
`status`	`str`	Current status: `"validating"`, `"in_progress"`, `"finalizing"`, `"completed"`, `"failed"`, `"expired"`, `"cancelling"`, or `"cancelled"`.
`output_file_id`	`str \| None`	ID of the output file (available when status is `"completed"`).
`error_file_id`	`str \| None`	ID of the error file (if any requests failed).
`created_at`	`int`	Unix timestamp of batch creation.
`in_progress_at`	`int \| None`	Unix timestamp of when processing started.
`expires_at`	`int \| None`	Unix timestamp of when the batch expires.
`finalizing_at`	`int \| None`	Unix timestamp of when finalization started.
`completed_at`	`int \| None`	Unix timestamp of completion.
`failed_at`	`int \| None`	Unix timestamp of failure.
`expired_at`	`int \| None`	Unix timestamp of expiration.
`cancelling_at`	`int \| None`	Unix timestamp of cancellation request.
`cancelled_at`	`int \| None`	Unix timestamp of cancellation completion.
`request_counts`	`BatchRequestCounts \| None`	Counts of total, completed, and failed requests.
`metadata`	`dict[str, str] \| None`	Custom metadata attached to the batch.

`BatchRequestCounts`

Re-exported from openai.types.batch_request_counts.BatchRequestCounts.

Import: from any_llm.types.batch import BatchRequestCounts

Field	Type	Description
`total`	`int`	Total number of requests in the batch.
`completed`	`int`	Number of completed requests.
`failed`	`int`	Number of failed requests.

Usage

from any_llm import create_batch, retrieve_batch

batch = create_batch(
    provider="openai",
    input_file_path="requests.jsonl",
    endpoint="/v1/chat/completions",
)

print(f"Batch ID: {batch.id}")
print(f"Status: {batch.status}")

# Poll for completion
import time
while batch.status not in ("completed", "failed", "expired", "cancelled"):
    time.sleep(30)
    batch = retrieve_batch("openai", batch.id)
    print(f"Status: {batch.status}")
    if batch.request_counts:
        print(f"  Completed: {batch.request_counts.completed}/{batch.request_counts.total}")

if batch.status == "completed":
    print(f"Output file: {batch.output_file_id}")