Batch

Data models for batch operations

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}")

The Batch and BatchRequestCounts types are direct re-exports from the OpenAI SDK. any-llm normalizes all provider batch responses into this format.