> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/api-reference/completion-1/batch.md).

# Batch

Data models for batch operations

The `Batch` type represents a batch job returned by the [Batch API](/api-reference/batch.md) 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

```python
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}")
```

{% hint style="info" %}
The `Batch` and `BatchRequestCounts` types are direct re-exports from the OpenAI SDK. any-llm normalizes all provider batch responses into this format.
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.mozilla.ai/api-reference/completion-1/batch.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.