rw-integrate-uploads

from runwayml import RunwayML
from pathlib import Path
 
client = RunwayML()
 
# Upload from a file path
upload = client.uploads.create_ephemeral(
    Path('/path/to/image.jpg')
)
 
# Use the runway:// URI
task = client.image_to_video.create(
    model='gen4.5',
    prompt_image=upload.runway_uri,
    prompt_text='The scene comes to life',
    ratio='1280:720',
    duration=5
).wait_for_task_output()

const response = await fetch('https://api.dev.runwayml.com/v1/uploads', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.RUNWAYML_API_SECRET}`,
    'X-Runway-Version': '2024-11-06',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    filename: 'image.jpg',
    type: 'ephemeral'
  })
});
 
const { uploadUrl, fields, runwayUri } = await response.json();

const formData = new FormData();
 
// Add all presigned form fields first
for (const [key, value] of Object.entries(fields)) {
  formData.append(key, value);
}
 
// Add the file last
formData.append('file', fileBuffer, 'image.jpg');
 
await fetch(uploadUrl, {
  method: 'POST',
  body: formData
});

const task = await fetch('https://api.dev.runwayml.com/v1/image_to_video', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.RUNWAYML_API_SECRET}`,
    'X-Runway-Version': '2024-11-06',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gen4.5',
    promptImage: runwayUri,
    promptText: 'Animate this scene',
    ratio: '1280:720',
    duration: 5
  })
});

import RunwayML from '@runwayml/sdk';
import express from 'express';
import multer from 'multer';
 
const client = new RunwayML();
const app = express();
const upload = multer({ storage: multer.memoryStorage() });
 
app.post('/api/image-to-video', upload.single('image'), async (req, res) => {
  try {
    // Upload the user's file to Runway
    const runwayUpload = await client.uploads.createEphemeral(req.file.buffer);
 
    // Use the uploaded file for video generation
    const task = await client.imageToVideo.create({
      model: 'gen4.5',
      promptImage: runwayUpload.runwayUri,
      promptText: req.body.prompt || 'Animate this image',
      ratio: '1280:720',
      duration: 5
    }).waitForTaskOutput();
 
    res.json({ videoUrl: task.output[0] });
  } catch (error) {
    console.error('Generation failed:', error);
    res.status(500).json({ error: error.message });
  }
});

// app/api/image-to-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 formData = await request.formData();
  const imageFile = formData.get('image') as File;
  const prompt = formData.get('prompt') as string;
 
  try {
    // Upload file to Runway
    const upload = await client.uploads.createEphemeral(imageFile);
 
    // Generate video from the uploaded image
    const task = await client.imageToVideo.create({
      model: 'gen4.5',
      promptImage: upload.runwayUri,
      promptText: prompt || 'Animate this image',
      ratio: '1280:720',
      duration: 5
    }).waitForTaskOutput();
 
    return NextResponse.json({ videoUrl: task.output[0] });
  } catch (error) {
    return NextResponse.json(
      { error: error instanceof Error ? error.message : 'Failed' },
      { status: 500 }
    );
  }
}

from fastapi import FastAPI, UploadFile, Form, HTTPException
from runwayml import RunwayML
 
app = FastAPI()
client = RunwayML()
 
@app.post("/api/image-to-video")
async def image_to_video(image: UploadFile, prompt: str = Form("Animate this image")):
    try:
        # Upload to Runway
        content = await image.read()
        upload = client.uploads.create_ephemeral((image.filename, content))
 
        # Generate video
        task = client.image_to_video.create(
            model="gen4.5",
            prompt_image=upload.runway_uri,
            prompt_text=prompt,
            ratio="1280:720",
            duration=5
        ).wait_for_task_output()
 
        return {"video_url": task.output[0]}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))