Kling v1.6 Pro Effects

kling-v1-6-pro-effects

Kling v1.6 Pro Effects transforms images into videos by applying professional-grade effects, ensuring clean visuals and consistent video generation

Fast Inference

REST API

Try in Console API Docs Examples

Model Information

Response Time~270 sec

StatusActive

Version

0.0.1

Updatedabout 16 hours ago

API Reference

View Full Documentation

Prerequisites

Create an API Key from the Eachlabs Console
Install the required dependencies for your chosen language (e.g., requests for Python)

API Integration Steps

1. Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

import requests
import time

API_KEY = "YOUR_API_KEY"  # Replace with your API key
HEADERS = {
    "X-API-Key": API_KEY,
    "Content-Type": "application/json"
}

def create_prediction():
    response = requests.post(
        "https://api.eachlabs.ai/v1/prediction/",
        headers=HEADERS,
        json={
            "model": "kling-v1-6-pro-effects",
            "version": "0.0.1",
            "input": {
  "duration": 5,
  "template_slug": "kiss",
  "image_url_2": "your image url 2 here",
  "image_url_1": "your image url here"
},
            "webhook_url": ""
        }
    )
    prediction = response.json()
    
    if prediction["status"] != "success":
        raise Exception(f"Prediction failed: {prediction}")
    
    return prediction["predictionID"]

2. Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

def get_prediction(prediction_id):
    while True:
        result = requests.get(
            f"https://api.eachlabs.ai/v1/prediction/{prediction_id}",
            headers=HEADERS
        ).json()
        
        if result["status"] == "success":
            return result
        elif result["status"] == "error":
            raise Exception(f"Prediction failed: {result}")
        
        time.sleep(1)  # Wait before polling again

3. Complete Example

Here's a complete example that puts it all together, including error handling and result processing. This shows how to create a prediction and wait for the result in a production environment.

try:
    # Create prediction
    prediction_id = create_prediction()
    print(f"Prediction created: {prediction_id}")
    
    # Get result
    result = get_prediction(prediction_id)
    print(f"Output URL: {result['output']}")
    print(f"Processing time: {result['metrics']['predict_time']}s")
except Exception as e:
    print(f"Error: {e}")

Additional Information

The API uses a two-step process: create prediction and poll for results
Response time: ~270 seconds
Rate limit: 60 requests/minute
Concurrent requests: 10 maximum
Use long-polling to check prediction status until completion

Overview

Kling v1.6 Pro Effects generates stylized video animations by transforming one or two input images using a wide range of predefined animation templates. The output is a short video clip, typically 5 or 10 seconds in duration, with smooth motion effects applied to the visual elements of the provided image(s). Kling v1.6 Pro Effects supports both single-image and two-image templates, with a focus on expressive, character-based animations.

Technical Specifications

Kling v1.6 Standard Effects is designed to apply fixed motion effects to one or two images.

Output format is MP4 video.

The animation is rendered using internal keyframe interpolation combined with template-driven motion design.

Template logic defines both the camera movement and visual elements (e.g., hearts, particles, stretching).

Image resolution is auto-scaled to fit the output frame based on the selected template and aspect ratio.

Outputs are optimized for short emotional interactions (e.g., hugging, kissing gestures) or playful effects (e.g., squish, dizzy).

Key Considerations

image_url_2 is mandatory only for hug, kiss, and heart_gesture templates. Using these templates without this input will result in an error or broken output.

The input image(s) should not be overly cropped or too close-up. A full head-and-shoulders portrait works best.

Background removal is not automatic. If desired, use pre-processed images with transparent or clean backgrounds.

Lighting consistency between two input images (when required) helps achieve a more natural merge in dual-character animations.

Legal Information for Kling v1.6 Pro Effects

By using this Kling v1.6 Pro Effects, you agree to:

Kling Privacy
Kling SERVICE AGREEMENT

Tips & Tricks

image_url_1
- Ensure the face is clearly visible and centered.
- Avoid cluttered backgrounds.
image_url_2
- Required when using hug, kiss, or heart_gesture.
- Try to match head size, lighting, and pose with image_url_1 for best coherence.
- Background contrast between both images should be minimal to avoid flickering.
template_slug
Available options:
- hug
- kiss
- heart_gesture
- squish
- expansion
- fuzzyfuzzy
- bloombloom
- dizzydizzy
Tips:
- Use hug and kiss for warm, interactive animations.
- Use fuzzyfuzzy or bloombloom for cheerful, light-hearted effects.
- dizzydizzy works well for playful, motion-heavy animation.
duration
- Accepts 5 or 10 (in seconds).
- Use 10 for extended storytelling or dramatic effect.
- Use 5 for short loops or faster sharing formats.

Capabilities

Animate static portraits into emotionally expressive video sequences.

Combine two character portraits in a single animation.

Generate loopable short videos for entertainment, reaction content, or creative storytelling.

Preserve identity and facial structure while adding motion.

What can I use for?

Creating reaction videos from static images.

Generating emotional messages (e.g., hugs, kisses) from personal photos.

Enhancing avatars or character portraits with motion.

Producing lightweight video content for social platforms from still imagery.

Things to be aware of

Use two similar selfies from different people with hug or kiss templates to generate realistic, personal animations.

Test bloombloom with a smiling portrait for vibrant visual output.

Apply dizzydizzy to a surprised or wide-eyed image for humorous results.

Try both 5 and 10 duration options with the same inputs to compare pacing.

Limitations

Only supports portraits. Non-human subjects may produce distorted results.

Cannot generate custom animations beyond the provided templates.

Dual-character templates are limited to three predefined options.

Requires image URLs; direct file uploads are not supported.

Does not support background editing or audio.

Output Format: MP4

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