# runway-act-two-v2v

> Take an existing character video and sync it with the motion from a reference video. This lets you update facial expressions, head turns, and speech gestures while keeping the original look and style. It’s perfect for reshooting performances, dubbing, or animating characters without re-rendering visuals.

## Overview

- **Endpoint**: `POST https://api.muapi.ai/api/v1/runway-act-two-v2v`
- **Model ID**: `runway-act-two-v2v`
- **Category**: video to video
- **Variant**: Act 2 Video to Video
- **Family**: runway
- **Cost**: 0.3 credits per call (some models compute cost dynamically based on params)

## API Usage

MuApi uses a **submit-then-poll** pattern: submit a job, get a `request_id`, then poll the predictions endpoint until `status` is `completed`. Optionally pass `?webhook=YOUR_URL` on the submit call to receive a POST callback when the job finishes (skip polling).

**Authentication**: send your MuApi key in the `x-api-key` header. Get one at https://muapi.ai/access-keys.

### 1. Submit a job

```http
POST https://api.muapi.ai/api/v1/runway-act-two-v2v
Content-Type: application/json
x-api-key: YOUR_API_KEY
```

**Minimum (required only):**

```json
{
  "video_url": "https://example.com/your-video_url",
  "reference_video_url": "https://example.com/your-reference_video_url"
}
```

**Full example (all params):**

```json
{
  "video_url": "https://example.com/your-video_url",
  "reference_video_url": "https://example.com/your-reference_video_url",
  "aspect_ratio": "16:9"
}
```

**Response:**

```json
{
  "request_id": "abc123",
  "status": "processing"
}
```

### 2. Poll for the result

```http
GET https://api.muapi.ai/api/v1/predictions/{request_id}/result
x-api-key: YOUR_API_KEY
```

Possible `status` values: `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`. Poll every 2-5 seconds until terminal. When `completed`, the result URLs are in the `outputs` array.

**Example response when `completed`:**

```json
{
  "id": "abc123",
  "status": "completed",
  "outputs": [
    "https://cdn.muapi.ai/.../output.png"
  ],
  "urls": {
    "get": "https://api.muapi.ai/api/v1/predictions/abc123/result"
  },
  "created_at": "2026-05-08T12:34:56Z",
  "has_nsfw_contents": []
}
```

### cURL

```bash
# 1. Submit
REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/runway-act-two-v2v \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"video_url":"https://example.com/your-video_url","reference_video_url":"https://example.com/your-reference_video_url"}' | jq -r .request_id)

# 2. Poll until completed
while :; do
  RESP=$(curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY")
  STATUS=$(echo "$RESP" | jq -r .status)
  [ "$STATUS" = "completed" ] && echo "$RESP" | jq .outputs && break
  [ "$STATUS" = "failed" ] && echo "$RESP" && exit 1
  sleep 3
done
```

### Python

```python
import os, time, requests

API = "https://api.muapi.ai/api/v1"
headers = {"x-api-key": os.environ["MUAPI_API_KEY"]}

r = requests.post(f"{API}/runway-act-two-v2v", headers=headers, json={"video_url":"https://example.com/your-video_url","reference_video_url":"https://example.com/your-reference_video_url"})
request_id = r.json()["request_id"]

while True:
    res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json()
    if res["status"] == "completed":
        print(res["outputs"]); break
    if res["status"] == "failed":
        raise RuntimeError(res.get("error")); 
    time.sleep(3)
```

## Input Schema

The API accepts the following input parameters:

- **`video_url`** (`string`, _required_):
  URL of the input video. An video of your character. In the output, the character will use the reference video performance in its original static environment.

- **`reference_video_url`** (`string`, _required_):
  A video URL pointing to a video of a person performing in the manner that you would like your character to perform.

- **`aspect_ratio`** (`string`, _optional_):
  Aspect ratio of the output video.
  - Default: `"16:9"`
  - Options: `"16:9"`, `"9:16"`, `"1:1"`, `"4:3"`, `"3:4"`, `"21:9"`

## Output Schema

The polling endpoint returns the following fields:

- **`id`** (`string`): The request ID.
- **`status`** (`string`): One of `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`.
- **`outputs`** (`array`): URLs to generated images/videos/audio. Empty until `status` is `completed`.
- **`urls.get`** (`string`): Self-link to re-fetch this prediction.
- **`error`** (`string` | `null`): Error message if `status` is `failed`.
- **`created_at`** (`string`): ISO-8601 timestamp of when the request was created.
- **`has_nsfw_contents`** (`array of boolean`): Per-output NSFW detection flags.

## Webhooks (optional)

Append `?webhook=https://your-server/path` to the submit URL. When the job reaches a terminal state, MuApi will POST the same shape as the polling response to your URL — no polling needed.

## Agent Integration

MuApi ships an MCP server and CLI so agents (Claude Code, Cursor, custom) can call this endpoint without writing HTTP code:

```bash
# Install the CLI
npm install -g muapi-cli

# Authenticate once
muapi auth login

# Expose all MuApi models as MCP tools to your agent
muapi mcp serve
```

The MCP server exposes tools that wrap submit + poll for every model, including `runway-act-two-v2v`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.).

## Related Models
- [Aleph Video to Video](https://muapi.ai/playground/runway-aleph-v2v)
- [Text to Video](https://muapi.ai/playground/runway-text-to-video)
- [Act 2 Image to Video](https://muapi.ai/playground/runway-act-two-i2v)
- [Image to Video](https://muapi.ai/playground/runway-image-to-video)
- [Act 2 Video to Video](https://muapi.ai/playground/runway-act-two-v2v)

## Resources
- [Playground Page](https://muapi.ai/playground/runway-act-two-v2v)
- [API Reference](https://muapi.ai/playground/runway-act-two-v2v?tab=2)
- [Global llms.txt](https://muapi.ai/llms.txt)