Kling 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.

maker
klingai
category
video
input → output
text → video, image → video, reference → video, video → video
runs via
api, javascript and python sdk, belt cli, mcp
updated
2026-08-07
price
$0.084-$0.168/sec, std: $0.084-$0.126, pro: $0.112-$0.168, +50% with video input

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.

get an api key

create one in settings → api keys. the examples read it from INFERENCE_API_KEY.

bash
1export INFERENCE_API_KEY="inf_your_key"

1. calling the api

install the client

nothing to install. any http client works; the examples use curl, and jq to read responses. every response wraps its result in a data field.

run and get result

send "wait": true to hold the connection until the task finishes. without it the call returns right away with the task still running.

bash
12# "wait": true holds the connection until the task finishes.3# the response is {"data": {"id", "status", "status_text", "output", ...}}4curl -X POST https://api.inference.sh/apps/run \5  -H "Authorization: Bearer $INFERENCE_API_KEY" \6  -H "Content-Type: application/json" \7  -d '{8    "app": "klingai/video-o1",9    "input": {10      "prompt": "A serene lake at sunset with birds flying overhead"11    },12    "wait": true13  }'

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks. send "stream": true and the response is a server-sent event stream that ends when the task does.

bash
12# "stream": true answers with server-sent events until the task finishes3curl -N -X POST https://api.inference.sh/apps/run \4  -H "Authorization: Bearer $INFERENCE_API_KEY" \5  -H "Content-Type: application/json" \6  -d '{7    "app": "klingai/video-o1",8    "input": {9      "prompt": "A serene lake at sunset with birds flying overhead"10    },11    "stream": true12  }'

run in the background

start the task and get its id back right away, then check on it later. for long tasks, or when you'd rather be called back, see webhooks.

bash
1# without "wait" the call returns the task right away (status 1, "received")2TASK_ID=$(curl -s -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "klingai/video-o1",7    "input": {8      "prompt": "A serene lake at sunset with birds flying overhead"9    }10  }' | jq -r '.data.id')1112# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)13curl -s https://api.inference.sh/tasks/$TASK_ID \14  -H "Authorization: Bearer $INFERENCE_API_KEY" | jq '.data | {status, status_text, 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

pass urls directly or use data uris for inline content.

bash
1# pass URLs or data URIs as input values2curl -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "klingai/video-o1",7    "input": {8      "image": "https://example.com/image.png",9      "audio": "data:audio/mp3;base64,..."10    },11    "wait": true12  }'

manual upload

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

bash
1# 1. create the file: the response has an upload_url and the file's uri2FILE=$(curl -s -X POST https://api.inference.sh/files \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{"files": [{"filename": "image.png", "content_type": "image/png"}]}')67# 2. PUT the bytes to upload_url8curl -X PUT "$(echo "$FILE" | jq -r '.data[0].upload_url')" \9  -H "Content-Type: image/png" \10  --data-binary @image.png1112# 3. pass the uri as an input value13echo "$FILE" | jq -r '.data[0].uri'

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.

bash
1curl -X POST https://api.inference.sh/apps/run \2  -H "Authorization: Bearer $INFERENCE_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "app": "klingai/video-o1",6    "input": {7        "prompt": "A serene lake at sunset with birds flying overhead"8    },9    "webhook": "https://your-server.com/webhook"10  }'

webhook payload

your endpoint receives a JSON POST with the task result:

json
1{2  "event": "task.completed",3  "timestamp": "2024-01-15T10:30:05Z",4  "data": {5    "id": "task_abc123",6    "short_id": "abc123",7    "status": 10,8    "status_text": "completed",9    "output": { ... },10    "created_at": "2024-01-15T10:30:00Z",11    "updated_at": "2024-01-15T10:30:05Z"12  }13}
eventstringtask.completed, task.failed or task.cancelled
timestampstringiso timestamp of the delivery
data.idstringtask id
data.short_idstringshort task id
data.statusnumberterminal status (10=completed, 11=failed, 12=cancelled, 13=rejected)
data.status_textstringthe status as a word: completed, failed or cancelled
data.outputobjecttask output (when completed)
data.errorstringerror message (when failed, omitted otherwise)
data.session_idstringsession id (when the task ran in a session, omitted otherwise)
data.created_atstringiso timestamp
data.updated_atstringiso timestamp

5. schema

input

promptstring*

text prompt describing the video. use @image_1, @element_name, @video_1 to reference inputs. max 2500 chars.

example: "A serene lake at sunset with birds flying overhead"
imagestring(file)

first-frame reference image.

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.

default: "feature"
resolutionstring

video resolution.

default: "1080p"
options:"720p""1080p"
aspect_ratiostring

video aspect ratio. required for text-to-video.

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

video duration in seconds. text-to-video: 5 or 10 only. with reference images: 3-10.

default: 5min:3max:10
watermarkboolean

add watermark to the output video.

default: false

output

videostring(file)*

the generated video file.

ready to run Kling Video O1?

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