Batch

Process multiple requests asynchronously at lower cost

The Batch API is experimental and may change in future releases. Provider support is limited - check the providers page for availability.

The Batch API lets you submit multiple requests as a single job for asynchronous processing, typically at lower cost than real-time requests.

How It Works

1. Prepare a JSONL file where each line is a batch request object.

2. Call create_batch() with the file path and target endpoint.

3. any-llm uploads the file to the provider and creates the batch job.

4. Poll with retrieve_batch() to check status.

5. When complete, download results from the provider.

Input File Format

The input file must be a JSONL file where each line follows this structure:

{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-4.1-mini", "messages": [{"role": "user", "content": "Hello"}]}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-4.1-mini", "messages": [{"role": "user", "content": "World"}]}}

any_llm.create_batch()

Create a batch job by uploading a local JSONL file.

def create_batch(
    provider: str | LLMProvider,
    input_file_path: str,
    endpoint: str,
    *,
    completion_window: str = "24h",
    metadata: dict[str, str] | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> Batch

any_llm.acreate_batch()

Async variant with the same parameters.

Parameters (create)

Parameter	Type	Default	Description
provider	str | LLMProvider	required	Provider name to use for the request (e.g., 'openai', 'mistral')
input_file_path	str	required	Path to a local file containing batch requests in JSONL format.
endpoint	str	required	The endpoint to be used for all requests (e.g., '/v1/chat/completions')
completion_window	str	"24h"	The time frame within which the batch should be processed (default: '24h')
metadata	dict[str, str] | None	None	Optional custom metadata for the batch
api_key	str | None	None	API key for the provider
api_base	str | None	None	Base URL for the provider API
client_args	dict[str, Any] | None	None	Additional provider-specific arguments for client instantiation
**kwargs	Any	required	Additional provider-specific arguments

Returns: A Batch object.

any_llm.retrieve_batch()

Retrieve the current status and details of a batch job.

def retrieve_batch(
    provider: str | LLMProvider,
    batch_id: str,
    *,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> Batch

any_llm.aretrieve_batch()

Async variant with the same parameters.

Parameters (retrieve)

Parameter	Type	Default	Description
provider	str | LLMProvider	required	Provider name to use for the request (e.g., 'openai', 'mistral')
batch_id	str	required	The ID of the batch to retrieve
api_key	str | None	None	API key for the provider
api_base	str | None	None	Base URL for the provider API
client_args	dict[str, Any] | None	None	Additional provider-specific arguments for client instantiation
**kwargs	Any	required	Additional provider-specific arguments

Returns: A Batch object.

any_llm.cancel_batch()

Cancel an in-progress batch job.

def cancel_batch(
    provider: str | LLMProvider,
    batch_id: str,
    *,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> Batch

any_llm.acancel_batch()

Async variant with the same parameters.

Returns: The cancelled Batch object.

any_llm.list_batches()

List batch jobs for a provider.

def list_batches(
    provider: str | LLMProvider,
    *,
    after: str | None = None,
    limit: int | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> Sequence[Batch]

any_llm.alist_batches()

Async variant with the same parameters.

Parameters (list)

Parameter	Type	Default	Description
provider	str | LLMProvider	required	Provider name to use for the request (e.g., 'openai', 'mistral')
after	str | None	None	A cursor for pagination. Returns batches after this batch ID.
limit	int | None	None	Maximum number of batches to return (default: 20)
api_key	str | None	None	API key for the provider
api_base	str | None	None	Base URL for the provider API
client_args	dict[str, Any] | None	None	Additional provider-specific arguments for client instantiation
**kwargs	Any	required	Additional provider-specific arguments

Returns: A Sequence of Batch objects.

Usage

from any_llm import create_batch, retrieve_batch, list_batches

# Create a batch job
batch = create_batch(
    provider="openai",
    input_file_path="requests.jsonl",
    endpoint="/v1/chat/completions",
)
print(f"Batch created: {batch.id}, status: {batch.status}")

# Check status
batch = retrieve_batch("openai", batch.id)
print(f"Status: {batch.status}")

# List all batches
batches = list_batches("openai")
for b in batches:
    print(f"{b.id}: {b.status}")