klingai-text-to-video

# Kling AI Text-to-Video ## Overview Generate videos from text prompts using the `/v1/videos/text2video` endpoint. Supports models v1 through v2.6, standard/professional modes, camera control, negative prompts, and native audio (v2.6+). **Endpoint:** `POST https://api.klingai.com/v1/videos/text2video` ## Request Parameters | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `model_name` | string | Yes | Model version (see model catalog) | | `prompt` | string | Yes | Video description, max 2500 chars | | `negative_prompt` | string | No | What to exclude from generation | | `duration` | string | Yes | `"5"` or `"10"` seconds | | `aspect_ratio` | string | No | `"16:9"` (default), `"9:16"`, `"1:1"`, etc. | | `mode` | string | No | `"standard"` (default) or `"professional"` | | `cfg_scale` | float | No | Prompt adherence (0.0-1.0, default 0.5) | | `camera_control` | object | No | Camera movement config | | `callback_url` | string | No | Webhook URL for completion notification | ## Complete Example — Python ```python import jwt, time, os, requests BASE = "https://api.klingai.com/v1" def get_headers(): ak, sk = os.environ["KLING_ACCESS_KEY"], os.environ["KLING_SECRET_KEY"] token = jwt.encode( {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5}, sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"} ) return {"Authorization": f"Bearer {token}", "Content-Type": "application/j...