# Overview

TokLab serves image, video, audio and text models through one API and one API key. Image, video and audio models run as asynchronous tasks: you submit a request, receive a task ID and poll for the result. Text models answer directly, in the request format of the model's vendor.

## Base URL

```text
https://api.toklab.ai
```

Use HTTPS and send JSON request bodies. The audio endpoints take a `multipart/form-data` upload instead.

## Authentication

Send your key as a Bearer token on every request, including task queries:

```text
Authorization: Bearer YOUR_API_KEY
```

The Anthropic Messages endpoint also accepts the key in `x-api-key`, together with the `anthropic-version` header. See [Authentication](https://toklab.ai/docs/api/authentication).

## Media task endpoints

| Method | Path                       | Purpose                                                                                                         |
| ------ | -------------------------- | --------------------------------------------------------------------------------------------------------------- |
| POST   | `/v1/images/generations`   | Submit an image generation or editing task: GPT Image, Nano Banana and Midjourney.                              |
| POST   | `/v1/videos/generations`   | Submit a video task: Seedance 2.5 and 2.0 (ModelArk request body), Veo 3.1, Kling 3.0, MiniMax H3 and SD Video. |
| POST   | `/v1/audio/transcriptions` | Submit an audio file for transcription with Whisper-1.                                                          |
| POST   | `/v1/audio/translations`   | Submit an audio file for translation into English with Whisper-1.                                               |
| GET    | `/v1/tasks/{id}`           | Read the state and result of an image, video or audio task.                                                     |

Reference images, videos and audio are passed as URLs in the request body. An image request becomes an edit when it includes input images. Each model's reference lists its parameters.

## Text endpoints

| Method | Path                                           | Request format            |
| ------ | ---------------------------------------------- | ------------------------- |
| POST   | `/v1/chat/completions`                         | OpenAI Chat Completions   |
| POST   | `/v1/responses`                                | OpenAI Responses          |
| POST   | `/v1/messages`                                 | Anthropic Messages        |
| POST   | `/v1beta/models/{model}:generateContent`       | Google Gemini             |
| POST   | `/v1beta/models/{model}:streamGenerateContent` | Google Gemini, streamed   |
| GET    | `/v1/models`                                   | List the available models |

Not every text model supports every format. The model's API reference names the formats it accepts; for example, Claude Opus 5.5 accepts Chat Completions, Responses and Messages, while the Gemini text models use the `/v1beta` paths.

## Request lifecycle

### Media tasks

1. Submit the request. The response is a task, not the finished file: store its `id`.
2. Poll the task until it reaches a final state. Tasks on `/v1/tasks/{id}` report `processing`, then `completed` or `failed`.
3. Read the result. Images are in `output.data[].url`, videos in `output.video_url`, and Whisper output in `output.url`. Every result link points to TokLab's storage.

On failure, inspect `error.code` and `error.message`. Failed tasks are not charged. There is no completion webhook; poll the task instead, as described in [Webhooks](https://toklab.ai/docs/api/webhooks).

### Text requests

A text request returns the model's answer in the same response, in the vendor's official response shape. Set `stream` to `true`, or use `:streamGenerateContent` for Gemini, to receive server-sent events. Text models are billed per token.

## Next steps

* [Quickstart](https://toklab.ai/docs/api/quickstart)
* [Task states](https://toklab.ai/docs/api/tasks)
* [Errors](https://toklab.ai/docs/api/errors)