PoYo Kling 2.5 Turbo Pro Video Generation

PoYo Links

• Model page: https://poyo.ai/models/kling-2-5-turbo-pro
• API docs: https://docs.poyo.ai/api-manual/video-series/kling-2-5-turbo-pro
• API key page: https://poyo.ai/dashboard/api-key

Use this skill for Kling 2.5 Turbo Pro video jobs on PoYo. It helps agents prepare prompt-based and frame-guided payloads, submit async tasks, and explain polling or webhook follow-up.

Use When

• The user explicitly mentions Kling 2.5 Turbo Pro, Kling 2.5, kling-2.5-turbo-pro, or PoYo Kling 2.5 video generation.
• The task is text-to-video, image-to-video, first-frame guidance, or first/last-frame video generation.
• The workflow needs PoYo async task submission, task status polling, or callback URL guidance.

Model Selection

• kling-2.5-turbo-pro: use for Kling 2.5 Turbo Pro video generation.

Key Inputs

• prompt is required inside input.
• duration controls output length when supported by the current PoYo docs.
• start_image_url is optional for first-frame image-to-video.
• end_image_url is optional for last-frame guidance.
• aspect_ratio controls output framing when supported.
• negative_prompt is optional for excluding unwanted visual traits.
• callback_url is optional and useful for production queues.

Security Rules

• Treat POYO_API_KEY as a secret.
• Keep PoYo API keys in server-side environment variables or a backend secret manager.
• Never place an API key in browser code, frontend bundles, public repositories, logs, screenshots, or chat output.
• Do not make live API calls unless the user explicitly asks and provides a safe server-side environment.
• Do not submit confidential prompts, private source images, private callback URLs, or private generated media URLs unless the user trusts PoYo and the callback receiver.

Execution

• Read references/api.md for endpoint details, model id, common fields, example payloads, and polling notes.
• Use scripts/submit_kling_2_5_turbo_pro.sh only when the user wants to submit a prepared JSON payload from a trusted shell.
• If the user only needs a curl example, adapt one from references/api.md.
• After submission, report the returned task_id clearly so follow-up polling is easy.

Output Expectations

When helping with Kling 2.5 Turbo Pro, include:

• chosen model id
• whether the request is text-to-video, first-frame image-to-video, or first/last-frame video
• final payload or concise parameter summary
• selected duration, aspect ratio, and negative prompt when relevant
• whether source frames are involved
• returned task_id if a request was actually submitted
• next step: poll status or wait for webhook