klingai-debug-bundle

# Kling AI Debug Bundle ## Overview Structured logging, request tracing, and diagnostic tools for Kling AI API integrations. Captures request/response pairs, task lifecycle events, and timing metrics for every call to `https://api.klingai.com/v1`. ## Debug-Enabled Client ```python import jwt, time, os, requests, logging, json from datetime import datetime logging.basicConfig( level=logging.DEBUG, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s" ) logger = logging.getLogger("kling.debug") class KlingDebugClient: """Kling AI client with full request/response logging.""" BASE = "https://api.klingai.com/v1" def __init__(self): self.ak = os.environ["KLING_ACCESS_KEY"] self.sk = os.environ["KLING_SECRET_KEY"] self._request_log = [] def _get_headers(self): token = jwt.encode( {"iss": self.ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5}, self.sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"} ) return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"} def _traced_request(self, method, path, body=None): """Execute request with full tracing.""" url = f"{self.BASE}{path}" start = time.monotonic() trace = { "timestamp": datetime.utcnow().isoformat(), "method": method, "path": path, "request_body": body, } try: if ...