Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/klingai-common-errors/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-common-errors. Copyright stays with the author (MIT).

Kling AI Common Errors

Overview

Complete error reference for the Kling AI API. Covers HTTP status codes, task-level failures, JWT issues, and generation-specific problems with tested solutions.

HTTP Error Codes

Task-Level Failures

When HTTP returns 200 but task_status is "failed":

JWT Authentication Errors

Problem: 401 on every request

# WRONG — missing headers parameter
token = jwt.encode(payload, sk, algorithm="HS256")

# CORRECT — include explicit headers
token = jwt.encode(payload, sk, algorithm="HS256",
                   headers={"alg": "HS256", "typ": "JWT"})

Problem: Token works then fails after 30 min

# WRONG — token generated once at import time
TOKEN = generate_token()

# CORRECT — refresh before expiry
class TokenManager:
    def __init__(self, ak, sk):
        self.ak, self.sk = ak, sk
        self._token = None
        self._exp = 0

    @property
    def token(self):
        if time.time() >= self._exp - 300:  # 5 min buffer
            payload = {"iss": self.ak, "exp": int(time.time()) + 1800,
                       "nbf": int(time.time()) - 5}
            self._token = jwt.encode(payload, self.sk, algorithm="HS256",
                                     headers={"alg": "HS256", "typ": "JWT"})
            self._exp = int(time.time()) + 1800
        return self._token

Rate Limit Handling

import time
import requests

def request_with_backoff(method, url, headers, json=None, max_retries=5):
    """Retry with exponential backoff on 429 and 5xx errors."""
    for attempt in range(max_retries):
        response = method(url, headers=headers, json=json)

        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
            print(f"Rate limited. Retrying in {retry_after}s...")
            time.sleep(retry_after)
            continue
        elif response.status_code >= 500:
            wait = 2 ** attempt
            print(f"Server error {response.status_code}. Retrying in {wait}s...")
            time.sleep(wait)
            continue

        response.raise_for_status()
        return response

    raise RuntimeError(f"Max retries ({max_retries}) exceeded")

Diagnostic Checklist

When a generation fails, check in order:

1. Auth valid? — Test with a simple GET request first
2. Credits available? — Check balance in developer console
3. Model valid? — Verify model_name matches catalog exactly
4. Parameters valid? — duration must be "5" or "10" (string, not int)
5. Prompt clean? — Remove special characters, keep under 2500 chars
6. Image accessible? — For I2V, verify image URL is publicly accessible
7. Feature exclusivity? — image_tail, dynamic_masks, and camera_control are mutually exclusive

Debug Logging

import logging

logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger("kling")

def debug_request(method, url, headers, json=None):
    """Log request/response for debugging."""
    logger.debug(f"→ {method.__name__.upper()} {url}")
    logger.debug(f"→ Body: {json}")
    r = method(url, headers=headers, json=json)
    logger.debug(f"← Status: {r.status_code}")
    logger.debug(f"← Body: {r.text[:500]}")
    return r

Prerequisites

• A sandbox workspace, synthetic or rights-cleared diagnostic brief, secret references, approved scope, redaction rules, draft-only destination, and incident owner.

Instructions

1. Reproduce errors with sandbox fixtures only; do not log authorization headers, prompts, source assets, response bodies, or generated asset URLs.
2. Capture aggregate status, error class, credit use, policy/rights outcome, and task state while verifying redaction and retention controls.
3. Halt the canary and remove temporary drafts on scope, policy, rights, budget, or retention drift; revoke temporary access where appropriate.
4. Store a redacted diagnostic receipt for the approved window and restore the known-good configuration before resuming work.

Output

Produce an error-triage receipt with environment, fixture classification, error class, aggregate status/credit signal, policy/rights/draft-only checks, incident owner, cleanup proof, and rollback reference. Exclude prompts, assets, identities, and credentials.

Error Handling

Examples

env=ci-sandbox; error=429; retries=backoff; budget=within-cap; policy=pass; destination=draft-only; cleanup=verified is a valid triage record.

Resources

• API Reference
• Content Policy
• Developer Portal