# Seedance 2.0 First and Last Frame

> Generate a video that starts on one image and ends on another — pin the opening and closing frames and let the prompt fill in the motion and the sound between them.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/bytedance/seedance-v2/first-last-frame`
- **Model ID**: `bytedance/seedance-v2/first-last-frame`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: video, image-to-video, first-last-frame, keyframe, transition, video generation, audio, bytedance, seedance

## Pricing

- **Price**: $0.227 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/seedance-v2/first-last-frame` 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/seedance-v2/first-last-frame/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/bytedance/seedance-v2/first-last-frame/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/bytedance/seedance-v2/first-last-frame/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

- **`image`** (`string`, _required_):
  Still image used as the FIRST frame of the clip. 300-6000 px on a side, under 30 MB, aspect ratio between 1:2.5 and 2.5:1.

- **`prompt`** (`string`, _required_):
  Describe what happens between the two frames: the action, the camera move, and the sound. English, Chinese, Japanese, Indonesian, Spanish and Portuguese prompts are all understood.

- **`duration`** (`integer`, _optional_):
  Clip length in seconds.
  - Default: `5`
  - Range: `4` to `15`

- **`end_image`** (`string`, _required_):
  Still image used as the LAST frame of the clip. May be the same image as the first frame, which produces a seamless loop. If its aspect ratio differs from the first frame's, the first frame wins and this image is cropped to fit.

- **`resolution`** (`resolution`, _optional_):
  Output resolution of the clip. Higher resolutions cost more per second of video.
  - Default: `"720p"`
  - Options: `"480p"`, `"720p"`, `"1080p"`

- **`aspect_ratio`** (`aspect_ratio`, _optional_):
  Frame shape of the clip. adaptive keeps the shape of the first frame; any other value re-frames it.
  - Default: `"adaptive"`
  - Options: `"16:9"`, `"4:3"`, `"1:1"`, `"3:4"`, `"9:16"`, `"21:9"`, `"adaptive"`

- **`generate_audio`** (`boolean`, _optional_):
  Generate a synchronized soundtrack (dialogue, ambience and sound effects) together with the picture. Set false for a silent clip; the price is the same either way.
  - Default: `true`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "image": "https://media.modelrunner.ai/4TBsiIAoeDvW4S4KbGsqw.jpeg",
  "prompt": "Dawn mist drifts slowly across the wet meadow grass while the pink light along the horizon gradually warms.",
  "duration": 5,
  "end_image": "https://media.modelrunner.ai/1w4oW0Joi6KWugXfSNWBP.jpeg",
  "resolution": "480p",
  "aspect_ratio": "16:9",
  "generate_audio": true
}
```

**Output**

```json
"https://media.modelrunner.ai/fRXBIRzEnHPdIgMRNynEq.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/seedance-v2/first-last-frame \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "image": "https://media.modelrunner.ai/4TBsiIAoeDvW4S4KbGsqw.jpeg",
  "prompt": "Dawn mist drifts slowly across the wet meadow grass while the pink light along the horizon gradually warms.",
  "duration": 5,
  "end_image": "https://media.modelrunner.ai/1w4oW0Joi6KWugXfSNWBP.jpeg",
  "resolution": "480p",
  "aspect_ratio": "16:9",
  "generate_audio": 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/seedance-v2/first-last-frame", {
  input: {
  "image": "https://media.modelrunner.ai/4TBsiIAoeDvW4S4KbGsqw.jpeg",
  "prompt": "Dawn mist drifts slowly across the wet meadow grass while the pink light along the horizon gradually warms.",
  "duration": 5,
  "end_image": "https://media.modelrunner.ai/1w4oW0Joi6KWugXfSNWBP.jpeg",
  "resolution": "480p",
  "aspect_ratio": "16:9",
  "generate_audio": true
}
});

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

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "bytedance/seedance-v2/first-last-frame",
        arguments={
  "image": "https://media.modelrunner.ai/4TBsiIAoeDvW4S4KbGsqw.jpeg",
  "prompt": "Dawn mist drifts slowly across the wet meadow grass while the pink light along the horizon gradually warms.",
  "duration": 5,
  "end_image": "https://media.modelrunner.ai/1w4oW0Joi6KWugXfSNWBP.jpeg",
  "resolution": "480p",
  "aspect_ratio": "16:9",
  "generate_audio": true
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/bytedance/seedance-v2/first-last-frame)
- [OpenAPI Schema](https://modelrunner.ai/models/bytedance/seedance-v2/first-last-frame/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/bytedance/seedance-v2/first-last-frame/llms.txt)