// Node.js SDK
import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

const task = await client.textToVideo.create({
  model: 'gen4.5',
  promptText: 'A golden retriever running through a field of wildflowers at sunset',
  ratio: '1280:720',
  duration: 5
}).waitForTaskOutput();

// task.output is an array of signed URLs
const videoUrl = task.output[0];

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// Node.js SDK — preferred flow
import fs from 'fs';

const upload = await client.uploads.createEphemeral(
  fs.createReadStream('/path/to/image.jpg')
);

const task = await client.imageToVideo.create({
  model: 'gen4.5',
  promptImage: upload.runwayUri,
  promptText: 'The scene comes to life with gentle wind',
  ratio: '1280:720',
  duration: 5
}).waitForTaskOutput();

const task = await client.imageToVideo.create({
  model: 'gen4.5',
  promptImage: 'https://cdn.yourapp.com/landscape.jpg',
  promptText: 'Camera slowly pans right revealing a mountain range',
  ratio: '1280:720',
  duration: 5
}).waitForTaskOutput();

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// Node.js SDK — gen4_aleph
const task = await client.videoToVideo.create({
  model: 'gen4_aleph',
  videoUri: 'https://cdn.yourapp.com/source.mp4',
  promptText: 'Transform into an animated cartoon style',
}).waitForTaskOutput();

// Node.js SDK — seedance2 video-to-video (with optional image reference)
const task = await client.videoToVideo.create({
  model: 'seedance2',
  promptVideo: 'https://cdn.yourapp.com/input.mp4',
  promptText: 'Transform into a warm golden sunset scene',
  references: [{ type: 'image', uri: 'https://cdn.yourapp.com/style_ref.jpg' }]
}).waitForTaskOutput();

const task = await client.textToVideo.create({
  model: 'seedance2',
  promptText: 'A calm ocean wave gently crashing on a sandy beach at sunset',
  duration: 5,
  ratio: '1280:720'
}).waitForTaskOutput();

const task = await client.imageToVideo.create({
  model: 'seedance2',
  promptText: 'Smooth transition from day to night in a cozy mountain cabin',
  promptImage: [
    { uri: 'https://cdn.yourapp.com/image.jpg', position: 'first' },
    { uri: 'https://cdn.yourapp.com/image2.jpg', position: 'last' }
  ],
  duration: 4,
  ratio: '1280:720'
}).waitForTaskOutput();

const task = await client.imageToVideo.create({
  model: 'seedance2',
  promptText: 'Smooth transition from day to night in a cozy mountain cabin',
  promptImage: 'https://cdn.yourapp.com/image.jpg',
  references: [{ type: 'image', uri: 'https://cdn.yourapp.com/reference.jpg' }],
  duration: 4,
  ratio: '1280:720'
}).waitForTaskOutput();

task = client.video_to_video.create(
    model='seedance2',
    prompt_video='https://cdn.yourapp.com/input.mp4',
    prompt_text='Transform into a warm golden sunset scene',
    references=[{'type': 'image', 'uri': 'https://cdn.yourapp.com/style_ref.jpg'}]
).wait_for_task_output()

const task = await client.characterPerformance.create({
  model: 'act_two',
  promptImage: 'https://cdn.yourapp.com/character.jpg',
  promptPerformance: 'https://cdn.yourapp.com/performance.mp4',
  ratio: '1280:720',
  duration: 5
}).waitForTaskOutput();

import RunwayML from '@runwayml/sdk';
import express from 'express';

const client = new RunwayML();
const app = express();
app.use(express.json());

// `runway://` URIs bypass this check; external URLs must match the allowlist.
const ALLOWED_MEDIA_HOSTS = new Set(['cdn.yourapp.com', 'uploads.yourapp.com']);

function assertTrustedMediaUrl(raw) {
  const u = new URL(raw);
  if (u.protocol !== 'https:') throw new Error('https required');
  if (!ALLOWED_MEDIA_HOSTS.has(u.hostname)) throw new Error('untrusted media host');
  return u.toString();
}

app.post('/api/generate-video', async (req, res) => {
  try {
    const { prompt, imageUrl, model = 'gen4.5', duration = 5 } = req.body;

    const params = {
      model,
      promptText: prompt,
      ratio: '1280:720',
      duration
    };

    let task;
    if (imageUrl) {
      task = await client.imageToVideo.create({
        ...params,
        promptImage: assertTrustedMediaUrl(imageUrl)
      }).waitForTaskOutput();
    } else {
      task = await client.textToVideo.create(params).waitForTaskOutput();
    }

    res.json({ videoUrl: task.output[0] });
  } catch (error) {
    console.error('Video generation failed:', error);
    res.status(400).json({ error: error.message });
  }
});

// app/api/generate-video/route.ts
import RunwayML from '@runwayml/sdk';
import { NextRequest, NextResponse } from 'next/server';

const client = new RunwayML();

export async function POST(request: NextRequest) {
  const { prompt, imageUrl } = await request.json();

  try {
    const task = imageUrl
      ? await client.imageToVideo.create({
          model: 'gen4.5',
          promptImage: imageUrl,
          promptText: prompt,
          ratio: '1280:720',
          duration: 5
        }).waitForTaskOutput()
      : await client.textToVideo.create({
          model: 'gen4.5',
          promptText: prompt,
          ratio: '1280:720',
          duration: 5
        }).waitForTaskOutput();

    return NextResponse.json({ videoUrl: task.output[0] });
  } catch (error) {
    return NextResponse.json(
      { error: error instanceof Error ? error.message : 'Generation failed' },
      { status: 500 }
    );
  }
}

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from runwayml import RunwayML

app = FastAPI()
client = RunwayML()

class VideoRequest(BaseModel):
    prompt: str
    image_url: str | None = None
    model: str = "gen4.5"
    duration: int = 5

@app.post("/api/generate-video")
async def generate_video(req: VideoRequest):
    try:
        if req.image_url:
            task = client.image_to_video.create(
                model=req.model,
                prompt_image=req.image_url,
                prompt_text=req.prompt,
                ratio="1280:720",
                duration=req.duration
            ).wait_for_task_output()
        else:
            task = client.text_to_video.create(
                model=req.model,
                prompt_text=req.prompt,
                ratio="1280:720",
                duration=req.duration
            ).wait_for_task_output()

        return {"video_url": task.output[0]}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))