> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zerogpu.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Supported Endpoints

> The only endpoint a batch line can target. Same request body, same response body, only the routing is asynchronous.

Every line in a batch input file must target `/v1/chat/completions` in the
`url` field, and the `endpoint` field on the create call must match. This
matches OpenAI's published batchable surface for this API version.

| `url`                  | Use case                      | Sync equivalent             |
| ---------------------- | ----------------------------- | --------------------------- |
| `/v1/chat/completions` | OpenAI-style chat completions | `POST /v1/chat/completions` |

The request body inside each JSONL line's `body` field is the **same** body
you would send synchronously. The response in the output JSONL's
`response.body` is the **same** response the synchronous endpoint would
return.

<Note>
  **Other ZeroGPU endpoints are sync-only**

  Internal routes like <code>/summary</code>, <code>/v1/responses</code>,
  <code>/usecase/classify/iab</code>, and <code>/gliner</code> remain
  reachable as synchronous calls but are <strong>not</strong> batchable.
  Submitting a JSONL line with one of these <code>url</code> values is
  rejected at create time with
  <code>"is not an allowed batch endpoint"</code>.
</Note>

***

## `/v1/chat/completions`

Standard OpenAI-style chat completions. Suitable for any model that supports
chat-completion semantics.

### Request body (inside JSONL `body`)

```json theme={null}
{
  "model": "<model-id>",
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    { "role": "user",   "content": "What is the capital of France?" }
  ]
}
```

| Field      | Required | Description                                                                                      |
| ---------- | -------- | ------------------------------------------------------------------------------------------------ |
| `model`    | Yes      | A model ID enabled for your project.                                                             |
| `messages` | Yes      | Array of `{role, content}`. `role` is one of `user`, `assistant`, `system`, `tool`, `developer`. |
| `stream`   | -        | **Must not be `true`.** Rejected at batch creation.                                              |

Per-model token limits apply (configured in model metadata). If input tokens
exceed the model's `max_tokens` setting, behavior depends on the model's
`error_on_max_token` flag: either the line fails with
`code: "context_length_exceeded"` (HTTP `400`), or the input is silently
truncated. Verify with your model's configuration.

### Response body (inside output JSONL `response.body`)

```json theme={null}
{
  "id":      "chatcmpl-...",
  "object":  "chat.completion",
  "created": 1736295000,
  "model":   "<model-id>",
  "choices": [
    {
      "index": 0,
      "message": {
        "role":        "assistant",
        "content":     "Paris.",
        "annotations": []
      },
      "finish_reason": "stop",
      "logprobs":      null
    }
  ],
  "usage": {
    "prompt_tokens":     12,
    "completion_tokens": 2,
    "total_tokens":      14,
    "prompt_tokens_details":     { "cached_tokens": 0, "audio_tokens": 0 },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "service_tier":       "default",
  "system_fingerprint": null
}
```

`system_fingerprint` is always `null` today. ZeroGPU does not yet expose
backend-determinism fingerprints. The field is present for SDK
compatibility (OpenAI's `ChatCompletion` type declares it as optional but
real OpenAI populates it on every response).

For **classification models** invoked via `/v1/chat/completions`,
`choices[0].message.content` is a JSON-stringified classification response
rather than free-form text. Parse it as JSON to extract the structured
result.

## Next steps

<CardGroup cols={2}>
  <Card title="JSONL format →" href="/docs/batch/jsonl-format">
    How to wrap each request body in a valid input JSONL line.
  </Card>

  <Card title="Objects & lifecycle →" href="/docs/batch/objects">
    The Batch object, status lifecycle, and every endpoint.
  </Card>

  <Card title="Quickstart →" href="/docs/batch/getting-started">
    End-to-end walkthrough in curl and Python.
  </Card>
</CardGroup>