rw-integrate-image
Help users integrate Runway image generation APIs (text-to-image with reference images)
What this skill does
# Integrate Image Generation
> **PREREQUISITE:** Run `+rw-check-compatibility` first. Run `+rw-fetch-api-reference` to load the latest API reference before integrating. Requires `+rw-setup-api-key` for API credentials. Requires `+rw-integrate-uploads` when the user has local reference images.
Help users add Runway image generation to their server-side code.
## Available Models
| Model | Best For | Cost | Speed |
|-------|----------|------|-------|
| `gen4_image` | Highest quality | 5 credits (720p), 8 credits (1080p) | Standard |
| `gen4_image_turbo` | Fast generation | 2 credits | Fast |
| `gemini_2.5_flash` | Google Gemini model | 5 credits | Standard |
**Model selection guidance:**
- Default recommendation: **`gen4_image`** — best quality
- Budget/speed: **`gen4_image_turbo`** — cheapest and fastest
## Security
`referenceImages[].uri` is **fetched server-side by the Runway API** — treat it like any outbound fetch:
- **Prefer `runway://` URIs** from `+rw-integrate-uploads` — scoped to your account, no arbitrary web content.
- **If accepting URLs from clients**, validate first: require `https://`, allowlist trusted hosts, reject private addresses. See the Express.js example below.
- **Never forward `req.body.referenceImages`** straight into `textToImage.create`. The SDK snippets below use raw URLs for brevity — they aren't production templates.
- Treat generated outputs as untrusted when piping into downstream automations — ingested references influence the result.
## Endpoint: `POST /v1/text_to_image`
### Basic Text-to-Image
```javascript
// Node.js SDK
import RunwayML from '@runwayml/sdk';
const client = new RunwayML();
const task = await client.textToImage.create({
model: 'gen4_image',
promptText: 'A serene Japanese garden with cherry blossoms and a koi pond',
ratio: '1280:720'
}).waitForTaskOutput();
const imageUrl = task.output[0];
```
```python
# Python SDK
from runwayml import RunwayML
client = RunwayML()
task = client.text_to_image.create(
model='gen4_image',
prompt_text='A serene Japanese garden with cherry blossoms and a koi pond',
ratio='1280:720'
).wait_for_task_output()
image_url = task.output[0]
```
### With Reference Images
Reference images let you guide the generation with visual references. Use `@Tag` syntax in the prompt to reference specific images.
**Recommended:** upload via `+rw-integrate-uploads` and pass the returned `runway://` URI.
```javascript
import fs from 'fs';
const refUpload = await client.uploads.createEphemeral(
fs.createReadStream('/path/to/reference.jpg')
);
const task = await client.textToImage.create({
model: 'gen4_image',
promptText: 'A portrait in the style of @Reference',
referenceImages: [
{ uri: refUpload.runwayUri, tag: 'Reference' }
],
ratio: '1280:720'
}).waitForTaskOutput();
```
External URLs also work — only pass origins you control (see Security):
```javascript
const task = await client.textToImage.create({
model: 'gen4_image',
promptText: '@EiffelTower painted in the style of @StarryNight',
referenceImages: [
{ uri: 'https://cdn.yourapp.com/eiffel-tower.jpg', tag: 'EiffelTower' },
{ uri: 'https://cdn.yourapp.com/starry-night.jpg', tag: 'StarryNight' }
],
ratio: '1280:720'
}).waitForTaskOutput();
```
```python
task = client.text_to_image.create(
model='gen4_image',
prompt_text='@EiffelTower painted in the style of @StarryNight',
reference_images=[
{"uri": "https://cdn.yourapp.com/eiffel-tower.jpg", "tag": "EiffelTower"},
{"uri": "https://cdn.yourapp.com/starry-night.jpg", "tag": "StarryNight"}
],
ratio='1280:720'
).wait_for_task_output()
```
## Common Parameters
| Parameter | Type | Description |
|-----------|------|-------------|
| `model` | string | Model ID (required) |
| `promptText` | string | Text description of the image (required) |
| `ratio` | string | Aspect ratio, e.g. `'1280:720'`, `'720:1280'`, `'1080:1080'` |
| `referenceImages` | array | Optional. Array of `{ uri, tag }` objects for visual guidance |
## Integration Pattern
1. **Prefer uploads over URLs** — Default to `+rw-integrate-uploads` so inputs are `runway://` URIs. External URLs only from origins you control (see Security).
2. **Write the server-side handler** — Create an API route or server function.
3. **Handle the output** — Download and store the image, don't serve signed URLs to clients.
4. **Add error handling** — Wrap in try/catch.
### Example: Express.js API Route
```javascript
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 validateReferenceImages(refs) {
if (!Array.isArray(refs)) throw new Error('referenceImages must be an array');
return refs.map(({ uri, tag }) => {
if (typeof uri !== 'string' || typeof tag !== 'string') {
throw new Error('each reference needs a uri and tag');
}
if (uri.startsWith('runway://')) return { uri, tag };
const u = new URL(uri);
if (u.protocol !== 'https:') throw new Error('https required');
if (!ALLOWED_MEDIA_HOSTS.has(u.hostname)) throw new Error('untrusted media host');
return { uri: u.toString(), tag };
});
}
app.post('/api/generate-image', async (req, res) => {
try {
const { prompt, model = 'gen4_image', ratio = '1280:720', referenceImages } = req.body;
const task = await client.textToImage.create({
model,
promptText: prompt,
ratio,
...(referenceImages && { referenceImages: validateReferenceImages(referenceImages) })
}).waitForTaskOutput();
res.json({ imageUrl: task.output[0] });
} catch (error) {
console.error('Image generation failed:', error);
res.status(400).json({ error: error.message });
}
});
```
> For browser uploads: POST files to your server, upload via `+rw-integrate-uploads`, and pass the `runway://` URI. Don't accept raw URLs from the browser.
### Example: Next.js API Route
```typescript
// app/api/generate-image/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, referenceImages } = await request.json();
try {
const task = await client.textToImage.create({
model: 'gen4_image',
promptText: prompt,
ratio: '1280:720',
...(referenceImages && { referenceImages })
}).waitForTaskOutput();
return NextResponse.json({ imageUrl: task.output[0] });
} catch (error) {
return NextResponse.json(
{ error: error instanceof Error ? error.message : 'Generation failed' },
{ status: 500 }
);
}
}
```
### Example: FastAPI Route
```python
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from runwayml import RunwayML
app = FastAPI()
client = RunwayML()
class ImageRequest(BaseModel):
prompt: str
model: str = "gen4_image"
ratio: str = "1280:720"
reference_images: list[dict] | None = None
@app.post("/api/generate-image")
async def generate_image(req: ImageRequest):
try:
params = {
"model": req.model,
"prompt_text": req.prompt,
"ratio": req.ratio,
}
if req.reference_images:
params["reference_images"] = req.reference_images
task = client.text_to_image.create(**params).wait_for_task_output()
return {"image_url": task.output[0]}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
```
## Tips
- **Output URLs expire in 24-48 hours.** Download images to your own storage immediately.
- **Reference images use `@Tag` syntax** in the prompt — the tag must match the `tag` field in the `referenceImages` array.
- **For local files**, always uRelated in Image & Video
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