# OmniHuman 1.5

> Animate a still photo of a person to speak and move in sync with an audio track, producing a natural talking-head video.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/bytedance/omnihuman/v1.5`
- **Model ID**: `bytedance/omnihuman/v1.5`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: bytedance, omnihuman, image-to-video, talking-head, audio, lip-sync

## Pricing

- **Price**: $0.16 per output second

## Request Lifecycle

This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps:

1. **Submit** — `POST https://queue.modelrunner.run/bytedance/omnihuman/v1.5` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>` (exact key=value matches, AND-ed). The response carries request handles only (no output yet):

```json
{
  "status": "IN_QUEUE",
  "request_id": "<21-char id>",
  "status_url": "https://queue.modelrunner.run/bytedance/omnihuman/v1.5/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/bytedance/omnihuman/v1.5/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/bytedance/omnihuman/v1.5/requests/<request_id>/cancel"
}
```

2. **Poll status** — `GET <status_url>` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field.

3. **Read result** — `GET <response_url>`. Returns the finished request, including the generated `output`:

```json
{ "id": "<request_id>", "status": "COMPLETED", "output": ..., "input": ... }
```

The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow.

### Input Schema

- **`prompt`** (`string | null`, _optional_):
  Optional text prompt guiding the motion, gestures, and performance. Leave empty to let the audio drive the animation.

- **`mask_url`** (`string | null`, _optional_):
  Optional mask image. When the photo has more than one person, only the person inside the white region of the mask will be animated to speak.

- **`audio_url`** (`string`, _required_):
  URL of the audio track the person should speak or sing. Keep audio under 30s at 1080p, under 60s at 720p.

- **`image_url`** (`string`, _required_):
  URL of the source photo of the person to animate.

- **`resolution`** (`resolution`, _optional_):
  Output resolution. 1080p limits input audio to 30s; 720p allows up to 60s.
  - Default: `"1080p"`
  - Options: `"720p"`, `"1080p"`

- **`turbo_mode`** (`boolean`, _optional_):
  Generate faster with a slight quality trade-off. No price impact.
  - Default: `false`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "prompt": "natural presenter delivering the line, subtle head movement",
  "audio_url": "https://media.modelrunner.ai/v293WP0BkvLcoXC3MJLud.mp3",
  "image_url": "https://media.modelrunner.ai/ho4HXHjCrHjv7MZs-omnihuman_v15_input_image.png",
  "resolution": "720p",
  "turbo_mode": true
}
```

**Output**

```json
"https://media.modelrunner.ai/9NpBN3azH3hU5r9nNm5dj.mp4"
```
## Usage Examples

### cURL

The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`.

```bash
# 1. Submit the request (returns request handles, not the output)
SUBMIT=$(curl --silent --request POST \
  --url https://queue.modelrunner.run/bytedance/omnihuman/v1.5 \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "prompt": "natural presenter delivering the line, subtle head movement",
  "audio_url": "https://media.modelrunner.ai/v293WP0BkvLcoXC3MJLud.mp3",
  "image_url": "https://media.modelrunner.ai/ho4HXHjCrHjv7MZs-omnihuman_v15_input_image.png",
  "resolution": "720p",
  "turbo_mode": true
}')

STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url')
RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url')

# 2. Poll until the request leaves the queue / in-progress state
while true; do
  STATUS=$(curl --silent --url "$STATUS_URL" \
    --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  case "$STATUS" in
    COMPLETED) break ;;
    FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;;
  esac
  sleep 1
done

# 3. Read the finished request, including the generated output
curl --silent --url "$RESPONSE_URL" \
  --header "Authorization: Key $MODEL_RUNNER_KEY"
```

### JavaScript

```javascript
import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("bytedance/omnihuman/v1.5", {
  input: {
  "prompt": "natural presenter delivering the line, subtle head movement",
  "audio_url": "https://media.modelrunner.ai/v293WP0BkvLcoXC3MJLud.mp3",
  "image_url": "https://media.modelrunner.ai/ho4HXHjCrHjv7MZs-omnihuman_v15_input_image.png",
  "resolution": "720p",
  "turbo_mode": true
}
});

console.log(result.data);
```

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "bytedance/omnihuman/v1.5",
        arguments={
  "prompt": "natural presenter delivering the line, subtle head movement",
  "audio_url": "https://media.modelrunner.ai/v293WP0BkvLcoXC3MJLud.mp3",
  "image_url": "https://media.modelrunner.ai/ho4HXHjCrHjv7MZs-omnihuman_v15_input_image.png",
  "resolution": "720p",
  "turbo_mode": true
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/bytedance/omnihuman/v1.5)
- [OpenAPI Schema](https://modelrunner.ai/models/bytedance/omnihuman/v1.5/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/bytedance/omnihuman/v1.5/llms.txt)