apps/klingai/video-o1

video-o1

Kling Video O1 (Omni) - unified video generation with text, image references, start/end frames, element references, and video references for editing and style transfer. The most capable Kling model.

run in browser run via API

run with your agent

# install belt

$curl -fsSL https://cli.inference.sh | sh

# view schema & details

$belt app get klingai/video-o1

# run

$belt app run klingai/video-o1

api reference

about

kling video o1 (omni) - unified video generation with text, image references, start/end frames, element references, and video references for editing and style transfer. the most capable kling model.

1. calling the api

install the client

the client provides a convenient way to interact with the api.

bash

1pip install inferencesh

setup your api key

set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.

bash

1export INFERENCE_API_KEY="inf_your_key"

run and get result

submit a request and wait for the final result. best for batch processing or when you don't need progress updates.

python

1from inferencesh import inference23client = inference()456result = client.run({7        "app": "klingai/video-o1",8        "input": {}9    })1011print(result["output"])

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks.

python

1from inferencesh import inference23client = inference()456# stream=True yields updates as they arrive7for update in client.run({8        "app": "klingai/video-o1",9        "input": {}10    }, stream=True):11    if update.get("progress"):12        print(f"progress: {update['progress']}%")13    if update.get("output"):14        print(f"output: {update['output']}")

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

the python sdk automatically detects local file paths and uploads them. urls are passed through as-is.

python

1# local file paths are automatically uploaded2result = client.run({3    "app": "klingai/video-o1",4    "input": {5        "image": "/path/to/local/image.png",  # detected & uploaded6        "audio": "https://example.com/audio.mp3",  # url passed through7    }8})

manual upload

you can also upload files manually and use the returned url.

python

1# upload and get a hosted URL2file = client.files.upload("/path/to/file.png")3print(file.uri)  # https://cloud.inference.sh/...

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

python

1result = client.run({2    "app": "klingai/video-o1",3    "input": {},4    "webhook": "https://your-server.com/webhook"5}, wait=False)

webhook payload

your endpoint receives a JSON POST with the task result:

json

1{2  "id": "task_abc123",3  "status": 9,4  "output": { ... },5  "error": "",6  "session_id": null,7  "created_at": "2024-01-15T10:30:00Z",8  "updated_at": "2024-01-15T10:30:05Z"9}

idstring— task id

statusnumber— terminal status (9=completed, 10=failed, 11=cancelled)

outputobject— task output (when completed)

errorstring— error message (when failed)

session_idstring— session id (if using sessions)

created_atstring— iso timestamp

updated_atstring— iso timestamp

5. schema

input

promptstring*

text prompt describing the video. use <<<image_1>>>, <<<element_1>>>, <<<video_1>>> to reference inputs. max 2500 chars.

example: "A serene lake at sunset with birds flying overhead"

imagestring(file)

first-frame reference image. sets the opening frame of the video.

end_imagestring(file)

end-frame reference image. requires image (first frame) to be set.

reference_imagesarray

reference images for style, character, or scene consistency. referenced in prompt as <<<image_1>>>, <<<image_2>>>, etc. max 7 without video, max 4 with video.

default: []

reference_videostring(file)

reference video for camera style, motion, or editing. referenced in prompt as <<<video_1>>>.

reference_video_typestring

how to use reference video: 'feature' for style/motion reference, 'base' for direct editing/transformation.

default: "feature"

keep_original_soundboolean

keep original sound from reference video (only applies when reference_video is set).

default: true

modestring

generation quality. 'pro' for highest quality, 'std' for faster/cheaper.

default: "pro"

options:"std""pro"

aspect_ratiostring

video aspect ratio. required for text-to-video and reference generation (not needed when using first-frame image or video editing).

options:"16:9""9:16""1:1"

durationinteger

video duration in seconds (3-10). for video editing, output matches input video duration.

default: 5min:3max:10

watermarkboolean

add watermark to the output video.

default: false

output

videostring(file)*

the generated video file.

output_metaobject

structured metadata about inputs/outputs for pricing calculation

ready to run video-o1?

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