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Runwayml

该 Skill 提供使用 Runway API 生成 AI 视频、图像和音频的操作说明,涵盖文生视频、图生视频、视频转换、角色表演、文生图、语音合成、音效与配音等模型,包含 Node.js SDK 与 cURL 调用示例、可用模型与积分表、画面比例、时长限制、异步任务轮询和提示词建议。

slightly-unrelated
slightly-unrelated
热度 45.88
最近更新 2026-05-11 17:35:46
分类:创作依赖:代码执行 / 第三方 API / 读写文件应用场景:图像生成 / 视频编辑 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add runwayml
Metadata
name
runwayml
description
Generate AI videos, images, and audio with Runway API. Use when generating video from images, text-to-video, video-to-video, character performance, text-to-image, text-to-speech, sound effects, or voice processing with Runway.
license
MIT
compatibility
Requires internet access and a RunwayML API key stored as RUNWAYML_API_SECRET environment variable.
metadata
{"author":"slightly-unrelated","version":"1.0.0"}

Runway API Skill

Generate AI videos, images, and audio using Runway's API. Features Gen-4.5 — Runway's latest and most capable model — supporting both text-to-video and image-to-video generation, plus Gen-4 variants and third-party models from Google (Veo) and ElevenLabs.

Setup

  1. Get your API key from dev.runwayml.com
  2. Store it as RUNWAYML_API_SECRET in your environment
  3. Install the Node.js SDK: npm install @runwayml/sdk

Quick Start

Text-to-Video (gen4.5)

import RunwayML from "@runwayml/sdk";

const client = new RunwayML(); // reads RUNWAYML_API_SECRET automatically

const task = await client.textToVideo.create({
  model: "gen4.5",
  promptText: "A steaming bowl of noodles in a busy hawker centre, warm light, slow camera push-in",
  duration: 5,
  ratio: "1280:720"
}).waitForTaskOutput();

console.log("Video URL:", task.output[0]);

Image-to-Video (gen4.5)

import RunwayML from "@runwayml/sdk";
import fs from "fs";

const client = new RunwayML();

const imageData = fs.readFileSync("product.jpg");
const promptImage = `data:image/jpeg;base64,${imageData.toString("base64")}`;

const task = await client.imageToVideo.create({
  model: "gen4.5",
  promptImage,
  promptText: "Slow dolly-in toward the product jar, warm side lighting, sauce shimmer visible through glass",
  duration: 5,
  ratio: "1280:720"
}).waitForTaskOutput();

console.log("Video URL:", task.output[0]);

cURL (direct API)

# Text-to-video
curl -X POST "https://api.dev.runwayml.com/v1/image_to_video" \
  -H "Authorization: Bearer $RUNWAYML_API_SECRET" \
  -H "X-Runway-Version: 2024-11-06" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gen4.5",
    "promptText": "A serene mountain landscape at sunset",
    "ratio": "1280:720",
    "duration": 5
  }'

Available Models

Video Generation

Model Input Credits/sec Notes
gen4.5 ⭐ Text or Image 12 Newest & recommended
gen4_turbo Image only 5 Fast I2V iteration
veo3.1 Text or Image 40 Google Veo — includes audio
veo3.1_fast Text or Image 15 Veo — audio, cheaper
gen4_aleph Video + Text/Image 15 Video-to-video transformation
act_two Image or Video 5 Character performance/motion

Image Generation

Model Credits Notes
gen4_image 5–8/image High quality, supports style references
gen4_image_turbo 2/image Fast iteration (requires reference image)

Audio (ElevenLabs via Runway)

Model Output Credits
eleven_multilingual_v2 Text → Speech 1/50 chars
eleven_text_to_sound_v2 Text → Sound FX 1/6 sec
eleven_voice_dubbing Audio → Dubbed 1/2 sec

Valid Ratios

Ratio Format
1280:720 16:9 landscape (standard)
720:1280 9:16 portrait (Reels/Stories)
1584:672 21:9 ultra-wide
1104:832 4:3
832:1104 3:4
960:960 Square

Duration

  • gen4.5: 2–10 seconds
  • gen4_turbo: 5 or 10 seconds

Task Polling

All operations are async. The SDK's .waitForTaskOutput() handles polling automatically (10 min timeout).

Statuses: PENDING → THROTTLED → RUNNING → SUCCEEDED / FAILED

Manual poll:

curl "https://api.dev.runwayml.com/v1/tasks/{task_id}" \
  -H "Authorization: Bearer $RUNWAYML_API_SECRET" \
  -H "X-Runway-Version: 2024-11-06"

Prompting Tips

  • Describe single scenes (5–10 sec clips)
  • Use clear physical descriptions, not abstract concepts
  • For camera movement: "slow dolly-in", "tracking shot", "push toward subject"
  • Avoid negative phrasing — "no blur" produces unpredictable results
  • Keep prompts grounded and physically plausible

Official Docs