> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/openai/openai-python/llms.txt
> Use this file to discover all available pages before exploring further.

# Remix Video

Create a remix of a completed video using a refreshed prompt.

## Method Signature

```python theme={null}
client.videos.remix(
    video_id="video_abc123",
    prompt="Same scene but at night with stars in the sky"
)
```

## Parameters

<ParamField path="video_id" type="string" required>
  The ID of the completed video to remix.
</ParamField>

<ParamField path="prompt" type="string" required>
  Updated text prompt that directs the remix generation.
</ParamField>

## Returns

Returns a new `Video` object representing the remix generation job.

<ResponseField name="id" type="string">
  Unique identifier for the remix video job.
</ResponseField>

<ResponseField name="status" type="string">
  Current lifecycle status of the remix job:

  * `queued` - waiting to start
  * `in_progress` - currently generating
  * `completed` - successfully finished
  * `failed` - generation failed
</ResponseField>

<ResponseField name="remixed_from_video_id" type="string">
  Identifier of the source video that was remixed.
</ResponseField>

<ResponseField name="created_at" type="integer">
  Unix timestamp (seconds) for when the remix job was created.
</ResponseField>

<ResponseField name="completed_at" type="integer">
  Unix timestamp (seconds) for when the job completed, if finished.
</ResponseField>

<ResponseField name="expires_at" type="integer">
  Unix timestamp (seconds) for when the downloadable assets expire, if set.
</ResponseField>

<ResponseField name="model" type="string">
  The video generation model that produced the remix.
</ResponseField>

<ResponseField name="prompt" type="string">
  The remix prompt that was used to generate the video.
</ResponseField>

<ResponseField name="seconds" type="integer">
  Duration of the generated clip in seconds (inherited from source video).
</ResponseField>

<ResponseField name="size" type="string">
  The resolution of the generated video (inherited from source video).
</ResponseField>

<ResponseField name="progress" type="integer">
  Approximate completion percentage for the generation task (0-100).
</ResponseField>

<ResponseField name="error" type="object">
  Error payload that explains why generation failed, if applicable.
</ResponseField>

## Examples

### Basic video remix

```python theme={null}
from openai import OpenAI
client = OpenAI()

# First, create an original video
original = client.videos.create_and_poll(
    prompt="A peaceful lake surrounded by mountains",
    model="sora-2",
    seconds=8
)

if original.status == "completed":
    # Now remix it with a different prompt
    remix = client.videos.remix(
        video_id=original.id,
        prompt="Same scene but during a dramatic thunderstorm"
    )
    
    print(f"Remix job started: {remix.id}")
    print(f"Remixed from: {remix.remixed_from_video_id}")
    print(f"Status: {remix.status}")
```

### Remix and poll for completion

```python theme={null}
from openai import OpenAI
client = OpenAI()

original_video_id = "video_abc123"

# Create the remix
remix = client.videos.remix(
    video_id=original_video_id,
    prompt="Transform this into a cyberpunk aesthetic with neon lights"
)

# Wait for completion
remix = client.videos.poll(remix.id)

if remix.status == "completed":
    print("Remix completed successfully!")
    print(f"Original video: {remix.remixed_from_video_id}")
    print(f"Remix video: {remix.id}")
else:
    print(f"Remix failed: {remix.error}")
```

### Create multiple variations

```python theme={null}
from openai import OpenAI
client = OpenAI()

# Start with an original video
original = client.videos.create_and_poll(
    prompt="A busy city intersection during the day",
    model="sora-2",
    seconds=8,
    size="1280x720"
)

if original.status == "completed":
    # Create multiple remixes with different prompts
    remix_prompts = [
        "Same intersection at sunset with golden lighting",
        "Same intersection at night with car headlights",
        "Same intersection in the rain with reflections"
    ]
    
    remixes = []
    for prompt in remix_prompts:
        remix = client.videos.remix(
            video_id=original.id,
            prompt=prompt
        )
        remixes.append(remix)
        print(f"Started remix: {remix.id}")
    
    # Poll all remixes
    completed_remixes = []
    for remix in remixes:
        completed = client.videos.poll(remix.id)
        if completed.status == "completed":
            completed_remixes.append(completed)
            print(f"Remix {completed.id} completed")
```

### Iterative refinement

```python theme={null}
from openai import OpenAI
client = OpenAI()

# Create original
video = client.videos.create_and_poll(
    prompt="A garden with blooming flowers",
    model="sora-2",
    seconds=8
)

# First refinement
video_v2 = client.videos.remix(
    video_id=video.id,
    prompt="Same garden but add butterflies flying around"
)
video_v2 = client.videos.poll(video_v2.id)

# Second refinement based on first remix
if video_v2.status == "completed":
    video_v3 = client.videos.remix(
        video_id=video_v2.id,
        prompt="Same scene but at golden hour with warm lighting"
    )
    video_v3 = client.videos.poll(video_v3.id)
    
    print(f"Final version: {video_v3.id}")
    print(f"Evolution: {video.id} -> {video_v2.id} -> {video_v3.id}")
```

### Remix with download

```python theme={null}
from openai import OpenAI
client = OpenAI()

original_id = "video_abc123"

# Create and wait for remix
remix = client.videos.remix(
    video_id=original_id,
    prompt="Make it look like a vintage 1980s film"
)

remix = client.videos.poll(remix.id)

if remix.status == "completed":
    # Download the remixed video
    content = client.videos.download_content(remix.id)
    with open(f"remix_{remix.id}.mp4", "wb") as f:
        f.write(content.read())
    print(f"Remix downloaded: remix_{remix.id}.mp4")
```