KL

klingai-upgrade-migration

A guide for migrating between Kling AI model versions, including breaking changes and parameter updates.

Install

mkdir -p .claude/skills/klingai-upgrade-migration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8353" && unzip -o skill.zip -d .claude/skills/klingai-upgrade-migration && rm skill.zip

Installs to .claude/skills/klingai-upgrade-migration

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Migrate between Kling AI model versions safely. Use when upgrading from
71 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Migrate model configurations from v1.x to v2.x
  • Implement parallel A/B testing for model comparison
  • Configure feature flags for model version rollbacks
  • Adjust request parameters for native audio support
  • Identify breaking changes between model versions

How it works

The skill provides a structured approach to model migration by identifying breaking changes, such as model-specific constraints and parameter adjustments. It includes code examples for parallel testing and environment-based version control for safe rollbacks.

Inputs & outputs

You give it
Current model version and target model version
You get back
Updated request body and migration validation results

When to use klingai-upgrade-migration

  • Migrate from v1.x to v2.x models
  • Update Kling AI dependencies
  • Adjust parameter intensities for new models
  • Handle breaking changes in API requests

About this skill

Kling AI Upgrade & Migration

Overview

Guide for migrating between Kling AI model versions. Covers breaking changes, parameter differences, feature availability, and parallel testing strategies.

Version History

VersionReleaseKey Changes
v1.02024-06Initial T2V + I2V
v1.52024-091080p, motion brush, I2V-only model
v1.62024-11Lip sync, camera paths, effects API
v2.02025-03Quality leap, kling-v2-master
v2.12025-06Optimized I2V, kling-v2-1-master for T2V
v2.5 Turbo2025-0940% faster, best speed/quality ratio
v2.62025-12Native audio, 30-48 FPS, highest quality

Migration: v1.x to v2.x

# v1.x request
body = {
    "model_name": "kling-v1-6",
    "prompt": "A sunset over mountains",
    "duration": "5",
    "mode": "standard",
}

# v2.x -- only model_name changes
body["model_name"] = "kling-v2-master"

Breaking changes:

  • kling-v2-1 is I2V-only (no text-to-video support)
  • Camera control intensities produce different results at same values
  • Generation times differ (v2.x generally slower, higher quality)

Migration: v2.x to v2.6 with Audio

body["model_name"] = "kling-v2-6"
body["motion_has_audio"] = True  # NEW: synchronized audio

# Cost impact: audio multiplies credits 5x
# 5s standard: 10 -> 50 credits

Feature Availability Matrix

Featurev1.0v1.5v1.6v2.0v2.1v2.5Tv2.6
Text-to-videoYYYYI2V onlyYY
Image-to-videoYYYYYYY
Camera control--YYYYY
Motion brush-YYYYYY
Lip sync--YYYYY
Effects--YYYYY
Native audio------Y
1080p-YYYYYY

Parallel A/B Comparison

def compare_models(prompt, models):
    """Generate same prompt across models for comparison."""
    results = {}
    for model in models:
        r = requests.post(f"{BASE}/videos/text2video", headers=get_headers(), json={
            "model_name": model, "prompt": prompt, "duration": "5", "mode": "standard",
        }).json()
        results[model] = {"task_id": r["data"]["task_id"], "start": time.time()}

    # Poll all
    while any("url" not in r for r in results.values()):
        for model, info in results.items():
            if "url" in info or "error" in info:
                continue
            r = requests.get(
                f"{BASE}/videos/text2video/{info['task_id']}", headers=get_headers()
            ).json()
            if r["data"]["task_status"] == "succeed":
                info["url"] = r["data"]["task_result"]["videos"][0]["url"]
                info["time"] = round(time.time() - info["start"])
            elif r["data"]["task_status"] == "failed":
                info["error"] = r["data"].get("task_status_msg")
        time.sleep(10)

    for model, info in results.items():
        print(f"{model}: {info.get('url', info.get('error'))} ({info.get('time', '?')}s)")
    return results

Rollback Strategy

# Feature flag for instant rollback
KLING_MODEL = os.environ.get("KLING_MODEL_VERSION", "kling-v2-master")
body["model_name"] = KLING_MODEL

# To rollback: export KLING_MODEL_VERSION=kling-v1-6

Resources

When not to use it

  • When migrating data between different SaaS platforms
  • When updating non-Kling AI dependencies

Limitations

  • kling-v2-1 is I2V-only and does not support text-to-video
  • Generation times differ between versions

How it compares

This workflow automates the comparison of model outputs across versions, whereas manual migration often relies on ad-hoc testing.

Compared to similar skills

klingai-upgrade-migration side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
klingai-upgrade-migration (this skill)027dReviewIntermediate
flutter-development1,5555moNo flagsIntermediate
godot1,0445moReviewIntermediate
fastapi-templates5202moNo flagsIntermediate

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